## FailureResponse The failure response object. The error that caused the failure. The error object. The error code. The error message. ## Error The error object. The error code. The error message. ## Account The Account object. The Account's unique identifier. ## Environment The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. ## EnvironmentResponse The result of a mutation which creates or modifies an Environment. The Environment which was created or modified. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. ## PageInfo The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## Application The Application object. Propel Applications represent the web or mobile app you are building. They provide the API credentials that allow your client- or server-side app to access the Propel API. The Application's Propeller determines the speed and cost of your Metric Queries. The Application's unique identifier. The Application's unique name. The Application's description. The Application's Account. The Account object. The Account's unique identifier. The Application's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. The Application's creation date and time in UTC. The Application's last modification date and time in UTC. The Application's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Application's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Application's OAuth 2.0 client identifier. The Application's OAuth 2.0 client secret. The Application's Propeller. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Application's OAuth 2.0 scopes. The API operations an Application is authorized to perform. * `ADMIN`: Grant read/write access to Data Sources, Data Pools, Metrics and Policies. * `APPLICATION_ADMIN`: Grant read/write access to Applications. * `DATA_POOL_QUERY`: Grant read access to query Data Pools. * `DATA_POOL_READ`: Grant read access to read Data Pools. * `DATA_POOL_STATS`: Grant read access to fetch column statistics from Data Pools. * `ENVIRONMENT_ADMIN`: Grant read/write access to Environments. * `METRIC_QUERY`: Grant read access to query Metrics. * `METRIC_STATS`: Grant read access to fetch Dimension statistics from Metrics. * `METRIC_READ`: Grant read access to Metrics. This does not allow querying Metrics. For that, see `METRIC_QUERY`. A paginated list of Data Pool Access Policies associated with the Application. ### Arguments See DataPoolAccessPolicyConnection A paginated list of Policies associated with the Application. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection ## ApplicationResponse The result of a mutation which creates or modifies an Application. The Application which was created or modified. The Application object. Propel Applications represent the web or mobile app you are building. They provide the API credentials that allow your client- or server-side app to access the Propel API. The Application's Propeller determines the speed and cost of your Metric Queries. The Application's unique identifier. The Application's unique name. The Application's description. The Application's Account. The Account object. The Account's unique identifier. The Application's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Application's creation date and time in UTC. The Application's last modification date and time in UTC. The Application's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Application's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Application's OAuth 2.0 client identifier. The Application's OAuth 2.0 client secret. The Application's Propeller. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Application's OAuth 2.0 scopes. The API operations an Application is authorized to perform. * `ADMIN`: Grant read/write access to Data Sources, Data Pools, Metrics and Policies. * `APPLICATION_ADMIN`: Grant read/write access to Applications. * `DATA_POOL_QUERY`: Grant read access to query Data Pools. * `DATA_POOL_READ`: Grant read access to read Data Pools. * `DATA_POOL_STATS`: Grant read access to fetch column statistics from Data Pools. * `ENVIRONMENT_ADMIN`: Grant read/write access to Environments. * `METRIC_QUERY`: Grant read access to query Metrics. * `METRIC_STATS`: Grant read access to fetch Dimension statistics from Metrics. * `METRIC_READ`: Grant read access to Metrics. This does not allow querying Metrics. For that, see `METRIC_QUERY`. A paginated list of Data Pool Access Policies associated with the Application. ### Arguments See DataPoolAccessPolicyConnection A paginated list of Policies associated with the Application. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection ## DataSource The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. The Account object. The Account's unique identifier. The Data Source's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. The types of Data Sources. * `WEBHOOK`: Indicates a Webhook Data Source. * `TWILIO_SEGMENT`: Indicates a Twilio Segment Data Source. * `S3`: Indicates an Amazon S3 Data Source. * `Redshift`: Indicates a Redshift Data Source. * `POSTGRESQL`: Indicates a PostgreSQL Data Source. * `KAFKA`: Indicates a Kafka Data Source. * `Http`: Indicates an Http Data Source. * `CLICKHOUSE`: Indicates a ClickHouse Data Source. * `AMAZON_DYNAMODB`: Indicates an Amazon DynamoDB Data Source. * `AMAZON_DATA_FIREHOSE`: Indicates an Amazon Data Firehose Data Source. * `Snowflake`: Indicates a Snowflake Data Source. * `INTERNAL`: Indicates an internal Data Source. The Data Source's status. The status of a Data Source. * `CREATED`: The Data Source has been created, but it is not connected yet. * `CONNECTING`: Propel is attempting to connect the Data Source. * `CONNECTED`: The Data Source is connected. * `BROKEN`: The Data Source failed to connect. * `DELETING`: Propel is deleting the Data Source. The Data Source's connection settings. The Snowflake Data Source connection settings. The Snowflake account. This is the part before the "snowflakecomputing.com" part of your Snowflake URL. The Snowflake database name. The Snowflake warehouse name. It should be "PROPELLING" if you used the default name in the setup script. The Snowflake schema. The Snowflake username. It should be "PROPEL" if you used the default name in the setup script. The Snowflake role. It should be "PROPELLER" if you used the default name in the setup script. The Amazon Data Firehose Data Source's connection settings. Enables or disables access control for the Data Pool. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. HTTP basic access authentication credentials. You must configure these same credentials to be included in the `X-Amz-Firehose-Access-Key` header when Amazon Data Firehose issues requests to its custom HTTP endpoint. See HttpBasicAuthSettings Additional columns for the table in Propel. See AmazonDataFirehoseDataSourceColumn Copy this value into the URL field when configuring your Amazon Data Firehose to deliver to a custom HTTP endpoint. Override the Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse, and a default will be chosen based on the Data Pool's `timestamp` value, if any. You can override these defaults in order to specify a custom table engine, custom ORDER BY, etc. See TableSettings The primary timestamp column, if any. Copy this value into the `X-Amz-Firehose-Access-Key` header when configuring your Amazon Data Firehose to deliver to a custom HTTP endpoint. The Amazon DynamoDB Data Source's connection settings. Enables or disables access control for the Data Pool. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. HTTP basic access authentication credentials. You must configure these same credentials to be included in the `X-Amz-Firehose-Access-Key` header when Amazon Data Firehose transmits records from your DynamoDB table to its custom HTTP endpoint. See HttpBasicAuthSettings Additional columns for the table in Propel. See AmazonDynamoDBDataSourceColumn Copy this value into the URL field when configuring your Amazon Data Firehose to transmit records from your DynamoDB table to a custom HTTP endpoint. Override the Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse, and a default will be chosen based on the Data Pool's `timestamp` value, if any. You can override these defaults in order to specify a custom table engine, custom ORDER BY, etc. See TableSettings The primary timestamp column, if any. Copy this value into the `X-Amz-Firehose-Access-Key` header when configuring your Amazon Data Firehose to transmit records from your DynamoDB table to its custom HTTP endpoint. The ClickHouse Data Source connection settings. Which database to connect to The password for the provided user Whether the user has readonly permissions or not for querying ClickHouse The URL where the ClickHouse host is listening to HTTP\[S] connections The user for authenticating against the ClickHouse host The HTTP Data Source connection settings. The HTTP Basic authentication settings for uploading new data. If this parameter is not provided, anyone with the URL to your tables will be able to upload data. While it's OK to test without HTTP Basic authentication, we recommend enabling it. See HttpBasicAuthSettings The HTTP Data Source's tables. See HttpDataSourceTable The Kafka Data Source connection settings. The type of authentication to use. Can be SCRAM-SHA-256, SCRAM-SHA-512, PLAIN or NONE The bootstrap server(s) to connect to The password for the provided user Whether the the connection to the Kafka servers is encrypted or not The user for authenticating against the Kafka servers The PostgreSQL Data Source connection settings. Which database to connect to The host where PostgreSQL is listening The port where PostgreSQL is listening (usually 5432) Which schema to use The user for authenticating against PostgreSQL The connection settings for an Amazon S3 Data Source. These include the Amazon S3 bucket name, the AWS access key ID, and the tables (along with their paths). We do not allow fetching the AWS secret access key after it has been set. The AWS access key ID for an IAM user with sufficient access to the Amazon S3 bucket. The name of the Amazon S3 bucket. The Amazon S3 Data Source's tables. See S3DataSourceTable The Twilio Segment Data Source connection settings. Enables or disables access control for the Data Pool. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. The HTTP basic authentication settings for the Twilio Segment Data Source URL. If this parameter is not provided, anyone with the webhook URL will be able to send events. While it's OK to test without HTTP Basic authentication, we recommend enabling it. See HttpBasicAuthSettings The additional columns for the table in Propel. See TwilioSegmentDataSourceColumn Override the Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse, and a default will be chosen based on the Data Pool's `timestamp` and `uniqueId` values, if any. You can override these defaults in order to specify a custom table engine, custom ORDER BY, etc. See TableSettings The primary timestamp column, if any. The webhook URL that Twilio Segment should POST events to. The Webhook Data Source connection settings. Enables or disables access control for the Data Pool. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. The HTTP basic authentication settings for the Webhook Data Source URL. If this parameter is not provided, anyone with the webhook URL will be able to send events. While it's OK to test without HTTP Basic authentication, we recommend enabling it. See HttpBasicAuthSettings The additional columns for the table in Propel. See WebhookDataSourceColumn Override the Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse, and a default will be chosen based on the Data Pool's `timestamp` and `uniqueId` values, if any. You can override these defaults in order to specify a custom table engine, custom ORDER BY, etc. See TableSettings The primary timestamp column, if any. The Webhook URL for posting JSON events The tenant ID column, if any. deprecated: Will be removed; use Data Pool Access Policies instead. The unique ID column, if any. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated. deprecated: Will be removed; use Table Settings to define the primary key. The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. The Data Source Check object. Data Source Checks are executed when setting up your Data Source. They check that Propel will be able to receive data and setup Data Pools. The exact Checks to perform vary by Data Source. For example, Snowflake-backed Data Sources will have their own specific Checks. The name of the Data Source Check to be performed. A description of the Data Source Check to be performed. The status of the Data Source Check (all checks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). The status of a Data Source Check. * `NOT_STARTED`: The Check has not started. * `SUCCEEDED`: The Check succeeded. * `FAILED`: The Check failed. If the Data Source Check failed, this field includes a descriptive error message. The error object. The error code. The error message. The time at which the Data Source Check was performed. If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead The error object. The error code. The error message. ## DataSourceCheck The Data Source Check object. Data Source Checks are executed when setting up your Data Source. They check that Propel will be able to receive data and setup Data Pools. The exact Checks to perform vary by Data Source. For example, Snowflake-backed Data Sources will have their own specific Checks. The name of the Data Source Check to be performed. A description of the Data Source Check to be performed. The status of the Data Source Check (all checks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). The status of a Data Source Check. * `NOT_STARTED`: The Check has not started. * `SUCCEEDED`: The Check succeeded. * `FAILED`: The Check failed. If the Data Source Check failed, this field includes a descriptive error message. The error object. The error code. The error message. The time at which the Data Source Check was performed. ## TableIntrospection The table introspection object. When setting up a Data Source, Propel may need to introspect tables in order to determine what tables and columns are available to create Data Pools from. The table introspection represents the lifecycle of this operation (whether it's in-progress, succeeded, or failed) and the resulting tables and columns. These will be captured as table and column objects, respectively. The Data Source the table introspection was performed for. See DataSource The status of the table introspection. The status of a table introspection. * `NOT_STARTED`: The table introspection has not started. * `STARTED`: The table introspection has started. * `SUCCEEDED`: The table introspection succeeded. * `FAILED`: The table introspection failed. The table introspection's creation date and time in UTC. The table introspection's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The table introspection's last modification date and time in UTC. The table introspection's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The number of tables introspected. The tables introspected. ### Arguments See TableConnection ## Table The table object. Once a table introspection succeeds, it creates a new table object for every table it introspected. The table's ID. The table's name. The Data Source to which the table belongs. See DataSource The number of rows contained within the table at the time of introspection. Check the table's `cachedAt` time, since this info can become out of date. The size of the table (in bytes) at the time of introspection. Check the table's `cachedAt` time, since this info can become out of date. The time at which the table was cached (i.e., the time at which it was introspected). The time at which the table was created. This is the same as its `cachedAt` time. The table's creator. This corresponds to the initiator of the table Introspection. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The table's columns. ### Arguments The column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The time at which the columns were cached (i.e., the time at which they were introspected). The column connection's edges. The column edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See Column The column connection's nodes. The column object. Once a table introspection succeeds, it creates a new table object for every table it introspected. Within each table object, it also creates a column object for every column it introspected. The column's name. The column's type. Whether the column is nullable, meaning whether it accepts a null value. The time at which the column was cached (i.e., the time at which it was introspected). The time at which the column was created. This is the same as its `cachedAt` time. The column's creator. This corresponds to the initiator of the table introspection. It can be either a User ID, an Application ID, or "system" if it was created by Propel. This is the suggested Data Pool column type to use when converting this Data Source column to a Data Pool column. Propel makes this suggestion based on the Data Source column type. If the Data Source column type is unsupported, this field returns `null`. Sometimes, you know better which Data Pool column type to convert to. In these cases, you can refer to `supportedDataPoolColumnTypes` for the full set of supported conversions. See ColumnType This is the set of supported Data Pool column types you can use when converting this Data Source column to a Data Pool column. If the Data Source column type is unsupported, this field returns an empty array. For example, a numeric Data Source column type could be converted to a narrower or wider numeric Data Pool column type; a string-valued Data Source column type could be mapped to a date or timestamp Data Pool column type. See ColumnType Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed The column connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. The table's columns which can be used as a timestamp for a Data Pool. ### Arguments The column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The time at which the columns were cached (i.e., the time at which they were introspected). The column connection's edges. The column edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See Column The column connection's nodes. The column object. Once a table introspection succeeds, it creates a new table object for every table it introspected. Within each table object, it also creates a column object for every column it introspected. The column's name. The column's type. Whether the column is nullable, meaning whether it accepts a null value. The time at which the column was cached (i.e., the time at which it was introspected). The time at which the column was created. This is the same as its `cachedAt` time. The column's creator. This corresponds to the initiator of the table introspection. It can be either a User ID, an Application ID, or "system" if it was created by Propel. This is the suggested Data Pool column type to use when converting this Data Source column to a Data Pool column. Propel makes this suggestion based on the Data Source column type. If the Data Source column type is unsupported, this field returns `null`. Sometimes, you know better which Data Pool column type to convert to. In these cases, you can refer to `supportedDataPoolColumnTypes` for the full set of supported conversions. See ColumnType This is the set of supported Data Pool column types you can use when converting this Data Source column to a Data Pool column. If the Data Source column type is unsupported, this field returns an empty array. For example, a numeric Data Source column type could be converted to a narrower or wider numeric Data Pool column type; a string-valued Data Source column type could be mapped to a date or timestamp Data Pool column type. See ColumnType Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed The column connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. The table's columns which can be used as a measure for a Metric. ### Arguments The column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The time at which the columns were cached (i.e., the time at which they were introspected). The column connection's edges. The column edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See Column The column connection's nodes. The column object. Once a table introspection succeeds, it creates a new table object for every table it introspected. Within each table object, it also creates a column object for every column it introspected. The column's name. The column's type. Whether the column is nullable, meaning whether it accepts a null value. The time at which the column was cached (i.e., the time at which it was introspected). The time at which the column was created. This is the same as its `cachedAt` time. The column's creator. This corresponds to the initiator of the table introspection. It can be either a User ID, an Application ID, or "system" if it was created by Propel. This is the suggested Data Pool column type to use when converting this Data Source column to a Data Pool column. Propel makes this suggestion based on the Data Source column type. If the Data Source column type is unsupported, this field returns `null`. Sometimes, you know better which Data Pool column type to convert to. In these cases, you can refer to `supportedDataPoolColumnTypes` for the full set of supported conversions. See ColumnType This is the set of supported Data Pool column types you can use when converting this Data Source column to a Data Pool column. If the Data Source column type is unsupported, this field returns an empty array. For example, a numeric Data Source column type could be converted to a narrower or wider numeric Data Pool column type; a string-valued Data Source column type could be mapped to a date or timestamp Data Pool column type. See ColumnType Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed The column connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed ## Column The column object. Once a table introspection succeeds, it creates a new table object for every table it introspected. Within each table object, it also creates a column object for every column it introspected. The column's name. The column's type. Whether the column is nullable, meaning whether it accepts a null value. The time at which the column was cached (i.e., the time at which it was introspected). The time at which the column was created. This is the same as its `cachedAt` time. The column's creator. This corresponds to the initiator of the table introspection. It can be either a User ID, an Application ID, or "system" if it was created by Propel. This is the suggested Data Pool column type to use when converting this Data Source column to a Data Pool column. Propel makes this suggestion based on the Data Source column type. If the Data Source column type is unsupported, this field returns `null`. Sometimes, you know better which Data Pool column type to convert to. In these cases, you can refer to `supportedDataPoolColumnTypes` for the full set of supported conversions. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. This is the set of supported Data Pool column types you can use when converting this Data Source column to a Data Pool column. If the Data Source column type is unsupported, this field returns an empty array. For example, a numeric Data Source column type could be converted to a narrower or wider numeric Data Pool column type; a string-valued Data Source column type could be mapped to a date or timestamp Data Pool column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed ## InternalConnectionSettings ## SnowflakeConnectionSettings The Snowflake Data Source connection settings. The Snowflake account. This is the part before the "snowflakecomputing.com" part of your Snowflake URL. The Snowflake database name. The Snowflake warehouse name. It should be "PROPELLING" if you used the default name in the setup script. The Snowflake schema. The Snowflake username. It should be "PROPEL" if you used the default name in the setup script. The Snowflake role. It should be "PROPELLER" if you used the default name in the setup script. ## HttpBasicAuthSettings The HTTP Basic authentication settings. Username for HTTP Basic authentication that must be included in the Authorization header when uploading new data. Password for HTTP Basic authentication that must be included in the Authorization header when uploading new data. ## HttpDataSourceTable An HTTP Data Source's table. The ID of the table The name of the table All the columns present in the table A column in an HTTP Data Source's table. The column name. It has to be unique within a table. The column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. The ClickHouse type to use when `type` is set to `CLICKHOUSE`. Whether the column's type is nullable or not. ## HttpDataSourceColumn A column in an HTTP Data Source's table. The column name. It has to be unique within a table. The column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. The ClickHouse type to use when `type` is set to `CLICKHOUSE`. Whether the column's type is nullable or not. ## S3DataSourceTable An Amazon S3 Data Source's table. The ID of the table The name of the table The path to the table's files in Amazon S3. All the columns present in the table A column in an Amazon S3 Data Source's table. The column name. The column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Whether the column's type is nullable or not. ## S3DataSourceColumn A column in an Amazon S3 Data Source's table. The column name. The column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Whether the column's type is nullable or not. ## AmazonDataFirehoseDataSourceColumn A column in an Amazon Data Firehose Data Source's table. The column name. The JSON property that the column will be derived from. For example, if you send a JSON event like this: ```json theme={"system"} { "greeting": { "message": "hello, world" } } ``` Then you can use the JSON property "greeting.message" to extract "hello, world" to a column. The column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Whether the column's type is nullable or not. ## AmazonDynamoDBDataSourceColumn A column in an Amazon DynamoDB Data Source's table. The column name. The JSON property that the column will be derived from. For example, if you send a JSON event like this: ```json theme={"system"} { "greeting": { "message": "hello, world" } } ``` Then you can use the JSON property "greeting.message" to extract "hello, world" to a column. The column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Whether the column's type is nullable or not. ## TwilioSegmentDataSourceColumn A column in a Twilio Segment Data Source's table. The column name. The JSON property that the column will be derived from. For example, if you POST a JSON event like this: ```json theme={"system"} { "greeting": { "message": "hello, world" } } ``` Then you can use the JSON property "greeting.message" to extract "hello, world" to a column. The column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Whether the column's type is nullable or not. ## WebhookDataSourceColumn A column in a Webhook Data Source's table. The column name. The JSON property that the column will be derived from. For example, if you POST a JSON event like this: ```json theme={"system"} { "greeting": { "message": "hello, world" } } ``` Then you can use the JSON property "greeting.message" to extract "hello, world" to a column. The column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Whether the column's type is nullable or not. ## DataSourceResponse The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. The Account object. The Account's unique identifier. The Data Source's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. The types of Data Sources. * `WEBHOOK`: Indicates a Webhook Data Source. * `TWILIO_SEGMENT`: Indicates a Twilio Segment Data Source. * `S3`: Indicates an Amazon S3 Data Source. * `Redshift`: Indicates a Redshift Data Source. * `POSTGRESQL`: Indicates a PostgreSQL Data Source. * `KAFKA`: Indicates a Kafka Data Source. * `Http`: Indicates an Http Data Source. * `CLICKHOUSE`: Indicates a ClickHouse Data Source. * `AMAZON_DYNAMODB`: Indicates an Amazon DynamoDB Data Source. * `AMAZON_DATA_FIREHOSE`: Indicates an Amazon Data Firehose Data Source. * `Snowflake`: Indicates a Snowflake Data Source. * `INTERNAL`: Indicates an internal Data Source. The Data Source's status. The status of a Data Source. * `CREATED`: The Data Source has been created, but it is not connected yet. * `CONNECTING`: Propel is attempting to connect the Data Source. * `CONNECTED`: The Data Source is connected. * `BROKEN`: The Data Source failed to connect. * `DELETING`: Propel is deleting the Data Source. The Data Source's connection settings. See SnowflakeConnectionSettings See InternalConnectionSettings See AmazonDataFirehoseConnectionSettings See AmazonDynamoDBConnectionSettings See ClickHouseConnectionSettings See HttpConnectionSettings See KafkaConnectionSettings See PostgreSqlConnectionSettings See S3ConnectionSettings See TwilioSegmentConnectionSettings See WebhookConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. The Data Source Check object. Data Source Checks are executed when setting up your Data Source. They check that Propel will be able to receive data and setup Data Pools. The exact Checks to perform vary by Data Source. For example, Snowflake-backed Data Sources will have their own specific Checks. The name of the Data Source Check to be performed. A description of the Data Source Check to be performed. The status of the Data Source Check (all checks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataSourceCheckStatus If the Data Source Check failed, this field includes a descriptive error message. See Error The time at which the Data Source Check was performed. If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead The error object. The error code. The error message. ## DataPool The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. The Account object. The Account's unique identifier. The Data Pool's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. The status of a Data Pool. * `CREATED`: The Data Pool has been created and will be set up soon. * `PENDING`: Propel is attempting to set up the Data Pool. * `LIVE`: The Data Pool is set up and serving data. Check its Syncs to monitor data ingestion. * `SETUP_FAILED`: The Data Pool setup failed. Check its Setup Tasks before re-attempting setup. * `CONNECTING` * `CONNECTED` * `BROKEN` * `PAUSING` * `PAUSED` * `DELETING`: Propel is deleting the Data Pool and all of its associated data. The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. A Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. The primary timestamp column's type. The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. The Data Pool column edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See DataPoolColumn The Data Pool column connection's nodes. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool column connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. The list of measures (numeric columns) in the Data Pool. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. The Data Pool column edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See DataPoolColumn The Data Pool column connection's nodes. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool column connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. A list of setup tasks performed on the Data Pool during its most recent setup attempt. The Data Pool Setup Task object. Data Pool Setup Tasks are executed when setting up your Data Pool. They ensure Propel will be able to sync records from your Data Source to your Data Pool. The exact Setup Tasks to perform vary by Data Source. For example, Data Pools pointing to a Snowflake-backed Data Sources will have their own specific Setup Tasks. The name of the Data Pool Setup Task to be performed. A description of the Data Pool Setup Task to be performed. The status of the Data Pool Setup Task (all setup tasks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). The status of a Data Pool Setup Task. * `NOT_STARTED`: The Data Pool Setup Task has not been started yet. * `SUCCEEDED`: The Data Pool Setup Task has completed successfully. * `FAILED`: The Data Pool Setup Task has failed. If the Data Pool Setup Task failed, this field includes a descriptive error message. The error object. The error code. The error message. The time at which the Data Pool Setup Task was completed. Settings related to Data Pool syncing. Settings related to Data Pool syncing. Indicates whether syncing is enabled or disabled. The Data Pool Sync Status. It indicates whether a Data Pool is syncing data or not. * `ENABLED`: Syncing is enabled for the Data Pool. * `DISABLING`: Propel is disabling syncing for the Data Pool. * `DISABLED`: Syncing is disabled for the Data Pool. The syncing interval. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. The available Data Pool sync intervals. Specify unit of time between attempts to sync data from your data warehouse. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. * `EVERY_1_MINUTE` * `EVERY_5_MINUTES` * `EVERY_15_MINUTES` * `EVERY_30_MINUTES` * `EVERY_1_HOUR` * `EVERY_4_HOURS` * `EVERY_12_HOURS` * `EVERY_24_HOURS` The date and time of the most recent Sync in UTC. The list of Syncs of the Data Pool. ### Arguments The filter to apply when listing the Syncs for a Data Pool. * `EMPTY`: Returns only Syncs with empty records. * `NOT_EMPTY`: Returns only Syncs that contain one or more records. * `ALL`: Returns all Syncs, regardless of whether they contain records or not. See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments Response returned by the validateExpression query for validating expressions in Custom Metrics. Returns whether the expression is valid or not with a reason explaining why. True if the expression is valid, false otherwise. The reason for why the expression is not valid in case it isn't, null otherwise. The Data Pool's table settings. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. A Data Pool's table engine. See MergeTreeTableEngine See ReplacingMergeTreeTableEngine See SummingMergeTreeTableEngine See AggregatingMergeTreeTableEngine See PostgreSqlTableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The Data Pool's columns that participate in its PARTITION BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its PRIMARY KEY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its ORDER BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead deprecated: Refer to `setupTasks` instead The error object. The error code. The error message. The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead A Data Pool's tenant ID column. The tenant ID column is used to control access to your data with access policies. The name of the column that represents the tenant ID. The tenant ID column's type. The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. A Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. The name of the column that represents the unique ID. ## TableSettings A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. A Data Pool's table engine. Parameters for the MergeTree table engine. The type is always `MERGE_TREE`. See TableEngineType Parameters for the ReplacingMergeTree table engine. The type is always `REPLACING_MERGE_TREE`. See TableEngineType The `ver` parameter to the ReplacingMergeTree engine. Parameters for the SummingMergeTree table engine. The type is always `SUMMING_MERGE_TREE`. See TableEngineType The columns argument for the SummingMergeTree table engine Parameters for the AggregatingMergeTree table engine. The type is always `AGGREGATING_MERGE_TREE`. See TableEngineType Parameters for the PostgreSQL table engine. The type is always `POSTGRESQL`. See TableEngineType The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. ## MergeTreeTableEngine Parameters for the MergeTree table engine. The type is always `MERGE_TREE`. ClickHouse table engine types. * `MERGE_TREE`: The MergeTree table engine. * `REPLACING_MERGE_TREE`: The ReplacingMergeTree table engine. * `SUMMING_MERGE_TREE`: The SummingMergeTree table engine. * `AGGREGATING_MERGE_TREE`: The AggregatingMergeTree table engine. * `POSTGRESQL`: The PostgreSQL table engine. ## ReplacingMergeTreeTableEngine Parameters for the ReplacingMergeTree table engine. The type is always `REPLACING_MERGE_TREE`. ClickHouse table engine types. * `MERGE_TREE`: The MergeTree table engine. * `REPLACING_MERGE_TREE`: The ReplacingMergeTree table engine. * `SUMMING_MERGE_TREE`: The SummingMergeTree table engine. * `AGGREGATING_MERGE_TREE`: The AggregatingMergeTree table engine. * `POSTGRESQL`: The PostgreSQL table engine. The `ver` parameter to the ReplacingMergeTree engine. ## SummingMergeTreeTableEngine Parameters for the SummingMergeTree table engine. The type is always `SUMMING_MERGE_TREE`. ClickHouse table engine types. * `MERGE_TREE`: The MergeTree table engine. * `REPLACING_MERGE_TREE`: The ReplacingMergeTree table engine. * `SUMMING_MERGE_TREE`: The SummingMergeTree table engine. * `AGGREGATING_MERGE_TREE`: The AggregatingMergeTree table engine. * `POSTGRESQL`: The PostgreSQL table engine. The columns argument for the SummingMergeTree table engine ## AggregatingMergeTreeTableEngine Parameters for the AggregatingMergeTree table engine. The type is always `AGGREGATING_MERGE_TREE`. ClickHouse table engine types. * `MERGE_TREE`: The MergeTree table engine. * `REPLACING_MERGE_TREE`: The ReplacingMergeTree table engine. * `SUMMING_MERGE_TREE`: The SummingMergeTree table engine. * `AGGREGATING_MERGE_TREE`: The AggregatingMergeTree table engine. * `POSTGRESQL`: The PostgreSQL table engine. ## PostgreSqlTableEngine Parameters for the PostgreSQL table engine. The type is always `POSTGRESQL`. ClickHouse table engine types. * `MERGE_TREE`: The MergeTree table engine. * `REPLACING_MERGE_TREE`: The ReplacingMergeTree table engine. * `SUMMING_MERGE_TREE`: The SummingMergeTree table engine. * `AGGREGATING_MERGE_TREE`: The AggregatingMergeTree table engine. * `POSTGRESQL`: The PostgreSQL table engine. ## DataPoolSetupTask The Data Pool Setup Task object. Data Pool Setup Tasks are executed when setting up your Data Pool. They ensure Propel will be able to sync records from your Data Source to your Data Pool. The exact Setup Tasks to perform vary by Data Source. For example, Data Pools pointing to a Snowflake-backed Data Sources will have their own specific Setup Tasks. The name of the Data Pool Setup Task to be performed. A description of the Data Pool Setup Task to be performed. The status of the Data Pool Setup Task (all setup tasks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). The status of a Data Pool Setup Task. * `NOT_STARTED`: The Data Pool Setup Task has not been started yet. * `SUCCEEDED`: The Data Pool Setup Task has completed successfully. * `FAILED`: The Data Pool Setup Task has failed. If the Data Pool Setup Task failed, this field includes a descriptive error message. The error object. The error code. The error message. The time at which the Data Pool Setup Task was completed. ## Dimension The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats Statistics about a particular Dimension. An array of unique values for the Dimension, up to 1,000. Empty if the Dimension contains more than 1,000 unique values. Fetching unique values incurs query costs. ### Arguments The minimum value of the Dimension. The maximum value of the Dimension. The average value of the Dimension. Empty for non-numeric Dimensions. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. See Propeller The Query status. See QueryStatus The Query type. See QueryType The Query subtype. See QuerySubtype The SQL the query executed. ## DimensionStatistics Statistics about a particular Dimension. An array of unique values for the Dimension, up to 1,000. Empty if the Dimension contains more than 1,000 unique values. Fetching unique values incurs query costs. ### Arguments The minimum value of the Dimension. The maximum value of the Dimension. The average value of the Dimension. Empty for non-numeric Dimensions. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Query status. The Query status. * `COMPLETED`: The Query was completed succesfully. * `ERROR`: The Query experienced an error. * `TIMED_OUT`: The Query timed out. The Query type. The Query type. * `METRIC`: Indicates a Metric Query. * `STATS`: Indicates a Dimension Stats Query. * `REPORT`: Indicates a Report Query. * `RECORDS`: Indicates a Record Table Query. * `RECORDS_BY_UNIQUE_ID`: Indicates records queried by unique ID. * `SQL`: Indicates a SQL Query. * `TOP_VALUES`: Indicates a Top Values Query. The Query subtype. The Query subtype. * `COUNTER`: Indicates a Metric counter Query. * `TIME_SERIES`: Indicates a Metric time series Query. * `LEADERBOARD`: Indicates a Metric leaderboard Query. The SQL the query executed. ## MaterializedView The Materialized View's unique identifier. The Materialized View's unique name. The Materialized View's description. The Materialized View's Account. The Account object. The Account's unique identifier. The Materialized View's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. The Materialized View's creation date and time in UTC. The Materialized View's last modification date and time in UTC. The Materialized View's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Materialized View's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The SQL that the Materialized View executes. The Materialized View's destination (AKA "target") Data Pool. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. The Account object. The Account's unique identifier. The Data Pool's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. The status of a Data Pool. * `CREATED`: The Data Pool has been created and will be set up soon. * `PENDING`: Propel is attempting to set up the Data Pool. * `LIVE`: The Data Pool is set up and serving data. Check its Syncs to monitor data ingestion. * `SETUP_FAILED`: The Data Pool setup failed. Check its Setup Tasks before re-attempting setup. * `CONNECTING` * `CONNECTED` * `BROKEN` * `PAUSING` * `PAUSED` * `DELETING`: Propel is deleting the Data Pool and all of its associated data. The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. A Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. The primary timestamp column's type. The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo The list of measures (numeric columns) in the Data Pool. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo A list of setup tasks performed on the Data Pool during its most recent setup attempt. The Data Pool Setup Task object. Data Pool Setup Tasks are executed when setting up your Data Pool. They ensure Propel will be able to sync records from your Data Source to your Data Pool. The exact Setup Tasks to perform vary by Data Source. For example, Data Pools pointing to a Snowflake-backed Data Sources will have their own specific Setup Tasks. The name of the Data Pool Setup Task to be performed. A description of the Data Pool Setup Task to be performed. The status of the Data Pool Setup Task (all setup tasks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataPoolSetupTaskStatus If the Data Pool Setup Task failed, this field includes a descriptive error message. See Error The time at which the Data Pool Setup Task was completed. Settings related to Data Pool syncing. Settings related to Data Pool syncing. Indicates whether syncing is enabled or disabled. See DataPoolSyncStatus The syncing interval. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. See DataPoolSyncInterval The date and time of the most recent Sync in UTC. The list of Syncs of the Data Pool. ### Arguments The filter to apply when listing the Syncs for a Data Pool. * `EMPTY`: Returns only Syncs with empty records. * `NOT_EMPTY`: Returns only Syncs that contain one or more records. * `ALL`: Returns all Syncs, regardless of whether they contain records or not. See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments Response returned by the validateExpression query for validating expressions in Custom Metrics. Returns whether the expression is valid or not with a reason explaining why. True if the expression is valid, false otherwise. The reason for why the expression is not valid in case it isn't, null otherwise. The Data Pool's table settings. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. See TableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The Data Pool's columns that participate in its PARTITION BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its PRIMARY KEY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its ORDER BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead deprecated: Refer to `setupTasks` instead The error object. The error code. The error message. The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead A Data Pool's tenant ID column. The tenant ID column is used to control access to your data with access policies. The name of the column that represents the tenant ID. The tenant ID column's type. The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. A Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. The name of the column that represents the unique ID. The Materialized View's source Data Pool. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. The Account object. The Account's unique identifier. The Data Pool's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. The status of a Data Pool. * `CREATED`: The Data Pool has been created and will be set up soon. * `PENDING`: Propel is attempting to set up the Data Pool. * `LIVE`: The Data Pool is set up and serving data. Check its Syncs to monitor data ingestion. * `SETUP_FAILED`: The Data Pool setup failed. Check its Setup Tasks before re-attempting setup. * `CONNECTING` * `CONNECTED` * `BROKEN` * `PAUSING` * `PAUSED` * `DELETING`: Propel is deleting the Data Pool and all of its associated data. The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. A Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. The primary timestamp column's type. The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo The list of measures (numeric columns) in the Data Pool. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo A list of setup tasks performed on the Data Pool during its most recent setup attempt. The Data Pool Setup Task object. Data Pool Setup Tasks are executed when setting up your Data Pool. They ensure Propel will be able to sync records from your Data Source to your Data Pool. The exact Setup Tasks to perform vary by Data Source. For example, Data Pools pointing to a Snowflake-backed Data Sources will have their own specific Setup Tasks. The name of the Data Pool Setup Task to be performed. A description of the Data Pool Setup Task to be performed. The status of the Data Pool Setup Task (all setup tasks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataPoolSetupTaskStatus If the Data Pool Setup Task failed, this field includes a descriptive error message. See Error The time at which the Data Pool Setup Task was completed. Settings related to Data Pool syncing. Settings related to Data Pool syncing. Indicates whether syncing is enabled or disabled. See DataPoolSyncStatus The syncing interval. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. See DataPoolSyncInterval The date and time of the most recent Sync in UTC. The list of Syncs of the Data Pool. ### Arguments The filter to apply when listing the Syncs for a Data Pool. * `EMPTY`: Returns only Syncs with empty records. * `NOT_EMPTY`: Returns only Syncs that contain one or more records. * `ALL`: Returns all Syncs, regardless of whether they contain records or not. See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments Response returned by the validateExpression query for validating expressions in Custom Metrics. Returns whether the expression is valid or not with a reason explaining why. True if the expression is valid, false otherwise. The reason for why the expression is not valid in case it isn't, null otherwise. The Data Pool's table settings. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. See TableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The Data Pool's columns that participate in its PARTITION BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its PRIMARY KEY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its ORDER BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead deprecated: Refer to `setupTasks` instead The error object. The error code. The error message. The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead A Data Pool's tenant ID column. The tenant ID column is used to control access to your data with access policies. The name of the column that represents the tenant ID. The tenant ID column's type. The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. A Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. The name of the column that represents the unique ID. Other Data Pools queried by the Materialized View. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. The Account object. The Account's unique identifier. The Data Pool's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. The status of a Data Pool. * `CREATED`: The Data Pool has been created and will be set up soon. * `PENDING`: Propel is attempting to set up the Data Pool. * `LIVE`: The Data Pool is set up and serving data. Check its Syncs to monitor data ingestion. * `SETUP_FAILED`: The Data Pool setup failed. Check its Setup Tasks before re-attempting setup. * `CONNECTING` * `CONNECTED` * `BROKEN` * `PAUSING` * `PAUSED` * `DELETING`: Propel is deleting the Data Pool and all of its associated data. The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. A Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. The primary timestamp column's type. The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo The list of measures (numeric columns) in the Data Pool. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo A list of setup tasks performed on the Data Pool during its most recent setup attempt. The Data Pool Setup Task object. Data Pool Setup Tasks are executed when setting up your Data Pool. They ensure Propel will be able to sync records from your Data Source to your Data Pool. The exact Setup Tasks to perform vary by Data Source. For example, Data Pools pointing to a Snowflake-backed Data Sources will have their own specific Setup Tasks. The name of the Data Pool Setup Task to be performed. A description of the Data Pool Setup Task to be performed. The status of the Data Pool Setup Task (all setup tasks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataPoolSetupTaskStatus If the Data Pool Setup Task failed, this field includes a descriptive error message. See Error The time at which the Data Pool Setup Task was completed. Settings related to Data Pool syncing. Settings related to Data Pool syncing. Indicates whether syncing is enabled or disabled. See DataPoolSyncStatus The syncing interval. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. See DataPoolSyncInterval The date and time of the most recent Sync in UTC. The list of Syncs of the Data Pool. ### Arguments The filter to apply when listing the Syncs for a Data Pool. * `EMPTY`: Returns only Syncs with empty records. * `NOT_EMPTY`: Returns only Syncs that contain one or more records. * `ALL`: Returns all Syncs, regardless of whether they contain records or not. See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments Response returned by the validateExpression query for validating expressions in Custom Metrics. Returns whether the expression is valid or not with a reason explaining why. True if the expression is valid, false otherwise. The reason for why the expression is not valid in case it isn't, null otherwise. The Data Pool's table settings. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. See TableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The Data Pool's columns that participate in its PARTITION BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its PRIMARY KEY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its ORDER BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead deprecated: Refer to `setupTasks` instead The error object. The error code. The error message. The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead A Data Pool's tenant ID column. The tenant ID column is used to control access to your data with access policies. The name of the column that represents the tenant ID. The tenant ID column's type. The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. A Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. The name of the column that represents the unique ID. ## MaterializedViewResponse The result of a mutation which creates or modifies a Materialized View. The Materialized View which was created or modified. The Materialized View's unique identifier. The Materialized View's unique name. The Materialized View's description. The Materialized View's Account. The Account object. The Account's unique identifier. The Materialized View's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Materialized View's creation date and time in UTC. The Materialized View's last modification date and time in UTC. The Materialized View's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Materialized View's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The SQL that the Materialized View executes. The Materialized View's destination (AKA "target") Data Pool. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId The Materialized View's source Data Pool. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId Other Data Pools queried by the Materialized View. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId ## Filter The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. The available Filter operators. * `EQUALS`: Selects values that are equal to the specified value. * `NOT_EQUALS`: Selects values that are not equal to the specified value. * `GREATER_THAN`: Selects values that are greater than the specified value. * `GREATER_THAN_OR_EQUAL_TO`: Selects values that are greater or equal to the specified value. * `LESS_THAN`: Selects values that are less than the specified value. * `LESS_THAN_OR_EQUAL_TO`: Selects values that are less or equal to the specified value. * `IS_NULL`: Selects values that are null. This operator does not accept a value. * `IS_NOT_NULL`: Selects values that are not null. This operator does not accept a value. * `LIKE`: Selects values that match the specified pattern. * `NOT_LIKE`: "Selects values that do not match the specified pattern. The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. ## UpdateDataPoolRecordsJobSetColumn The fields for creating an Update Data Pool Records Job. ``` { "column": "status", "expression": "'completed'" } { "column": "counter", "expression": "counter + 1" } { "column": "full_name", "expression": "concat(first_name, ' ', last_name)" } ``` The name of the column to update. The value to which the column will be updated. Once evaluated, it should be of the same data type as the column. ## Timestamp A Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. The primary timestamp column's type. ## Tenant A Data Pool's tenant ID column. The tenant ID column is used to control access to your data with access policies. The name of the column that represents the tenant ID. The tenant ID column's type. ## UniqueId A Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. The name of the column that represents the unique ID. ## DataPoolColumn The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead ## DataPoolResponse The result of a mutation which creates or modifies a Data Pool. The Data Pool which was created or modified. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. The Account object. The Account's unique identifier. The Data Pool's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. The status of a Data Pool. * `CREATED`: The Data Pool has been created and will be set up soon. * `PENDING`: Propel is attempting to set up the Data Pool. * `LIVE`: The Data Pool is set up and serving data. Check its Syncs to monitor data ingestion. * `SETUP_FAILED`: The Data Pool setup failed. Check its Setup Tasks before re-attempting setup. * `CONNECTING` * `CONNECTED` * `BROKEN` * `PAUSING` * `PAUSED` * `DELETING`: Propel is deleting the Data Pool and all of its associated data. The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. A Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. The primary timestamp column's type. The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo The list of measures (numeric columns) in the Data Pool. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo A list of setup tasks performed on the Data Pool during its most recent setup attempt. The Data Pool Setup Task object. Data Pool Setup Tasks are executed when setting up your Data Pool. They ensure Propel will be able to sync records from your Data Source to your Data Pool. The exact Setup Tasks to perform vary by Data Source. For example, Data Pools pointing to a Snowflake-backed Data Sources will have their own specific Setup Tasks. The name of the Data Pool Setup Task to be performed. A description of the Data Pool Setup Task to be performed. The status of the Data Pool Setup Task (all setup tasks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataPoolSetupTaskStatus If the Data Pool Setup Task failed, this field includes a descriptive error message. See Error The time at which the Data Pool Setup Task was completed. Settings related to Data Pool syncing. Settings related to Data Pool syncing. Indicates whether syncing is enabled or disabled. See DataPoolSyncStatus The syncing interval. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. See DataPoolSyncInterval The date and time of the most recent Sync in UTC. The list of Syncs of the Data Pool. ### Arguments The filter to apply when listing the Syncs for a Data Pool. * `EMPTY`: Returns only Syncs with empty records. * `NOT_EMPTY`: Returns only Syncs that contain one or more records. * `ALL`: Returns all Syncs, regardless of whether they contain records or not. See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments Response returned by the validateExpression query for validating expressions in Custom Metrics. Returns whether the expression is valid or not with a reason explaining why. True if the expression is valid, false otherwise. The reason for why the expression is not valid in case it isn't, null otherwise. The Data Pool's table settings. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. See TableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The Data Pool's columns that participate in its PARTITION BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its PRIMARY KEY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its ORDER BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead deprecated: Refer to `setupTasks` instead The error object. The error code. The error message. The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead A Data Pool's tenant ID column. The tenant ID column is used to control access to your data with access policies. The name of the column that represents the tenant ID. The tenant ID column's type. The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. A Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. The name of the column that represents the unique ID. ## DataPoolSyncing Settings related to Data Pool syncing. Indicates whether syncing is enabled or disabled. The Data Pool Sync Status. It indicates whether a Data Pool is syncing data or not. * `ENABLED`: Syncing is enabled for the Data Pool. * `DISABLING`: Propel is disabling syncing for the Data Pool. * `DISABLED`: Syncing is disabled for the Data Pool. The syncing interval. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. The available Data Pool sync intervals. Specify unit of time between attempts to sync data from your data warehouse. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. * `EVERY_1_MINUTE` * `EVERY_5_MINUTES` * `EVERY_15_MINUTES` * `EVERY_30_MINUTES` * `EVERY_1_HOUR` * `EVERY_4_HOURS` * `EVERY_12_HOURS` * `EVERY_24_HOURS` The date and time of the most recent Sync in UTC. ## Sync The Sync object. This represents the process of syncing data from your Data Source (for example, a Snowflake data warehouse) to your Data Pool. The Sync's unique identifier. The Sync's Account. The Account object. The Account's unique identifier. The Sync's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. The Sync's creation date and time in UTC. The Sync's last modification date and time in UTC. The Sync's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Sync's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Sync's Data Pool. See DataPool The Sync's Data Pool's Data Source. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. The Account object. The Account's unique identifier. The Data Source's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. The types of Data Sources. * `WEBHOOK`: Indicates a Webhook Data Source. * `TWILIO_SEGMENT`: Indicates a Twilio Segment Data Source. * `S3`: Indicates an Amazon S3 Data Source. * `Redshift`: Indicates a Redshift Data Source. * `POSTGRESQL`: Indicates a PostgreSQL Data Source. * `KAFKA`: Indicates a Kafka Data Source. * `Http`: Indicates an Http Data Source. * `CLICKHOUSE`: Indicates a ClickHouse Data Source. * `AMAZON_DYNAMODB`: Indicates an Amazon DynamoDB Data Source. * `AMAZON_DATA_FIREHOSE`: Indicates an Amazon Data Firehose Data Source. * `Snowflake`: Indicates a Snowflake Data Source. * `INTERNAL`: Indicates an internal Data Source. The Data Source's status. The status of a Data Source. * `CREATED`: The Data Source has been created, but it is not connected yet. * `CONNECTING`: Propel is attempting to connect the Data Source. * `CONNECTED`: The Data Source is connected. * `BROKEN`: The Data Source failed to connect. * `DELETING`: Propel is deleting the Data Source. The Data Source's connection settings. See SnowflakeConnectionSettings See InternalConnectionSettings See AmazonDataFirehoseConnectionSettings See AmazonDynamoDBConnectionSettings See ClickHouseConnectionSettings See HttpConnectionSettings See KafkaConnectionSettings See PostgreSqlConnectionSettings See S3ConnectionSettings See TwilioSegmentConnectionSettings See WebhookConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. The Data Source Check object. Data Source Checks are executed when setting up your Data Source. They check that Propel will be able to receive data and setup Data Pools. The exact Checks to perform vary by Data Source. For example, Snowflake-backed Data Sources will have their own specific Checks. The name of the Data Source Check to be performed. A description of the Data Source Check to be performed. The status of the Data Source Check (all checks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataSourceCheckStatus If the Data Source Check failed, this field includes a descriptive error message. See Error The time at which the Data Source Check was performed. If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead The error object. The error code. The error message. The number of new, updated, and deleted records contained within the Sync, if known. This excludes filtered records. The (compressed) size of the Sync, in bytes, if known. The status of the Sync (all Syncs begin as SYNCING before transitioning to SUCCEEDED or FAILED). The status of a Sync. * `SYNCING`: Propel is actively syncing records contained within the Sync. * `SUCCEEDED`: The Sync succeeded. Propel successfully synced all records contained within the Sync. * `FAILED`: The Sync failed. Propel failed to sync some or all records contained within the Sync. * `DELETING`: Propel is deleting the Sync. The time at which the Sync started. The time at which the Sync succeeded. The time at which the Sync failed. If the Sync failed, this represents the reason the Sync failed. The error object. The error code. The error message. The number of new records contained within the Sync, if known. This excludes filtered records. deprecated: All records are considered to be processed; see `processedRecords` instead The number of updated records contained within the Sync, if known. This excludes filtered records. deprecated: All records are considered to be processed; see `processedRecords` instead The number of deleted records contained within the Sync, if known. This excludes filtered records. deprecated: All records are considered to be processed; see `processedRecords` instead The number of filtered records contained within the Sync, due to issues such as a missing timestamp Dimension, if any are known to be invalid. deprecated: All records are considered to be processed; see `processedRecords` instead ## MetricReportConnection The Metric Report connection object. It includes `headers` and `rows` for a single page of a report. It also allows paging forward and backward to other pages of the report. The report connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. The report connection's edges. The Metric Report edge object. The edge's node. The Metric Report node object. This type represents a single row of a report. An ordered array of display names for your dimensions and Metrics, as defined in the report input. Use this to display your table's header. An ordered array of columns. Each column contains the dimension and Metric values for a single row, as defined in the report input. Use this to display a single row within your table. The edge's cursor. The report connection's nodes. The Metric Report node object. This type represents a single row of a report. An ordered array of display names for your dimensions and Metrics, as defined in the report input. Use this to display your table's header. An ordered array of columns. Each column contains the dimension and Metric values for a single row, as defined in the report input. Use this to display a single row within your table. An ordered array of display names for your dimensions and Metrics, as defined in the report input. Use this to display your table's header. An ordered array of rows. Each row contains dimension and Metric values, as defined in the report input. Use these to display the rows of your table. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Query status. The Query status. * `COMPLETED`: The Query was completed succesfully. * `ERROR`: The Query experienced an error. * `TIMED_OUT`: The Query timed out. The Query type. The Query type. * `METRIC`: Indicates a Metric Query. * `STATS`: Indicates a Dimension Stats Query. * `REPORT`: Indicates a Report Query. * `RECORDS`: Indicates a Record Table Query. * `RECORDS_BY_UNIQUE_ID`: Indicates records queried by unique ID. * `SQL`: Indicates a SQL Query. * `TOP_VALUES`: Indicates a Top Values Query. The Query subtype. The Query subtype. * `COUNTER`: Indicates a Metric counter Query. * `TIME_SERIES`: Indicates a Metric time series Query. * `LEADERBOARD`: Indicates a Metric leaderboard Query. The SQL the query executed. ## MetricReportEdge The Metric Report edge object. The edge's node. The Metric Report node object. This type represents a single row of a report. An ordered array of display names for your dimensions and Metrics, as defined in the report input. Use this to display your table's header. An ordered array of columns. Each column contains the dimension and Metric values for a single row, as defined in the report input. Use this to display a single row within your table. The edge's cursor. ## MetricReportNode The Metric Report node object. This type represents a single row of a report. An ordered array of display names for your dimensions and Metrics, as defined in the report input. Use this to display your table's header. An ordered array of columns. Each column contains the dimension and Metric values for a single row, as defined in the report input. Use this to display a single row within your table. ## Metric The Metric object. A Metric is a business indicator measured over time. The Metric's unique identifier. The Metric's unique name. The Metric's description. The Metric's Account. The Account object. The Account's unique identifier. The Metric's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. The Metric's creation date and time in UTC. The Metric's last modification date and time in UTC. The Metric's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Metric's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool that powers this Metric. See DataPool The Metric's Dimensions. These Dimensions are available to Query Filters. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats Statistics about a particular Dimension. An array of unique values for the Dimension, up to 1,000. Empty if the Dimension contains more than 1,000 unique values. Fetching unique values incurs query costs. ### Arguments The minimum value of the Dimension. The maximum value of the Dimension. The average value of the Dimension. Empty for non-numeric Dimensions. The Query statistics and metadata. See QueryInfo The Metric's timestamp, if any. This is the same as its Data Pool's timestamp, if any. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats Statistics about a particular Dimension. An array of unique values for the Dimension, up to 1,000. Empty if the Dimension contains more than 1,000 unique values. Fetching unique values incurs query costs. ### Arguments The minimum value of the Dimension. The maximum value of the Dimension. The average value of the Dimension. Empty for non-numeric Dimensions. The Query statistics and metadata. See QueryInfo List the Boosters associated to the Metric. ### Arguments See BoosterConnection The Metric's type. The different Metric types determine how the values are calculated. The available Metric types. * `COUNT`: Counts the number of records that matches the Metric Filters. For time series, it will count the values for each time granularity. * `SUM`: Sums the values of the specified column for every record that matches the Metric Filters. For time series, it will sum the values for each time granularity. * `COUNT_DISTINCT`: Counts the number of distinct values in the specified column for every record that matches the Metric Filters. For time series, it will count the distinct values for each time granularity. * `AVERAGE`: Averages the values of the specified column for every record that matches the Metric Filters. For time series, it will average the values for each time granularity. * `MIN`: Selects the minimum value of the specified column for every record that matches the Metric Filters. For time series, it will select the minimum value for each time granularity. * `MAX`: Selects the maximum value of the specified column for every record that matches the Metric Filters. For time series, it will select the maximum value for each time granularity. * `CUSTOM`: Aggregates values based on the provided custom expression. The settings for the Metric. The settings are specific to the Metric's type. A Metric's settings, depending on its type. Settings for Count Metrics. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. You can provide the filters in the form of SQL. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. deprecated: Use `filterSql` instead See Filter Settings for Sum Metrics. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. You can provide the filters in the form of SQL. The Dimension to be summed. See Dimension Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. deprecated: Use `filterSql` instead See Filter Settings for Count Distinct Metrics. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. You can provide the filters in the form of SQL. The Dimension where the count distinct operation is going to be performed. See Dimension Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. deprecated: Use `filterSql` instead See Filter Settings for Average Metrics. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. You can provide the filters in the form of SQL. The Dimension to be averaged. See Dimension Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. deprecated: Use `filterSql` instead See Filter Settings for Min Metrics. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. You can provide the filters in the form of SQL. The Dimension to select the minimum from. See Dimension Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. deprecated: Use `filterSql` instead See Filter Settings for Max Metrics. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. You can provide the filters in the form of SQL. The Dimension to select the maximum from. See Dimension Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. deprecated: Use `filterSql` instead See Filter Settings for Custom Metrics. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. You can provide the filters in the form of SQL. The expression that defines the aggregation function for this Metric. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. deprecated: Use `filterSql` instead See Filter The Metric's measure. Access this from the Metric's `settings` object instead. deprecated: Use the Metric `settings` object instead. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats Statistics about a particular Dimension. An array of unique values for the Dimension, up to 1,000. Empty if the Dimension contains more than 1,000 unique values. Fetching unique values incurs query costs. ### Arguments The minimum value of the Dimension. The maximum value of the Dimension. The average value of the Dimension. Empty for non-numeric Dimensions. The Query statistics and metadata. See QueryInfo Query the Metric in counter format. Returns the Metric's value for the given time range and filters. deprecated: Use the top-level `counter` query instead ### Arguments The fields for querying a Metric in counter format. A Metric's counter query returns a single value over a given time range. The Metric to query. You can query a pre-configured Metric by ID or name, or you can query an ad hoc Metric that you define inline. The ID of a pre-configured Metric. The name of a pre-configured Metric. An ad hoc Custom Metric. See CustomMetricQueryInput An ad hoc Count Metric. See CountMetricQueryInput An ad hoc Sum Metric. See SumMetricQueryInput An ad hoc Average Metric. See AverageMetricQueryInput An ad hoc Min Metric. See MinMetricQueryInput An ad hoc Max Metric. See MaxMetricQueryInput An ad hoc Count Distinct Metric. See CountDistinctMetricQueryInput The time range for calculating the counter. The fields required to specify the time range for a time series, counter, or leaderboard Metric query. If no relative or absolute time ranges are provided, Propel defaults to an absolute time range beginning with the earliest record in the Metric's Data Pool and ending with the latest record. If both relative and absolute time ranges are provided, the relative time range will take precedence. If a `LAST_N` relative time period is selected, an `n` ≥ 1 must be provided. If no `n` is provided or `n` \< 1, a `BAD_REQUEST` error will be returned. The timestamp field to use when querying. Defaults to the timestamp configured on the Data Pool or Metric, if any. Set this to filter on an alternative timestamp field. The relative time period. See RelativeTimeRange The number of time units for the `LAST_N` relative periods. The optional start timestamp (inclusive). Defaults to the timestamp of the earliest record in the Data Pool. The optional end timestamp (exclusive). Defaults to the timestamp of the latest record in the Data Pool. The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The Query Filters to apply before retrieving the counter data, in the form of SQL. If no Query Filters are provided, all data is included. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the counter data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The counter response object. It contains a single Metric value for the given time range and Query Filters. The value of the counter. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. See Propeller The Query status. See QueryStatus The Query type. See QueryType The Query subtype. See QuerySubtype The SQL the query executed. Query the Metric in time series format. Returns arrays of timestamps and the Metric's values for the given time range and filters. deprecated: Use the top-level `timeSeries` query instead ### Arguments The fields for querying a Metric in time series format. A Metric's time series query returns the values over a given time range aggregated by a given time granularity; day, month, or year, for example. The Metric to Query. It can be a pre-created one or it can be inlined here. The ID of a pre-configured Metric. The name of a pre-configured Metric. An ad hoc Custom Metric. See CustomMetricQueryInput An ad hoc Count Metric. See CountMetricQueryInput An ad hoc Sum Metric. See SumMetricQueryInput An ad hoc Average Metric. See AverageMetricQueryInput An ad hoc Min Metric. See MinMetricQueryInput An ad hoc Max Metric. See MaxMetricQueryInput An ad hoc Count Distinct Metric. See CountDistinctMetricQueryInput The time range for calculating the time series. The fields required to specify the time range for a time series, counter, or leaderboard Metric query. If no relative or absolute time ranges are provided, Propel defaults to an absolute time range beginning with the earliest record in the Metric's Data Pool and ending with the latest record. If both relative and absolute time ranges are provided, the relative time range will take precedence. If a `LAST_N` relative time period is selected, an `n` ≥ 1 must be provided. If no `n` is provided or `n` \< 1, a `BAD_REQUEST` error will be returned. The timestamp field to use when querying. Defaults to the timestamp configured on the Data Pool or Metric, if any. Set this to filter on an alternative timestamp field. The relative time period. See RelativeTimeRange The number of time units for the `LAST_N` relative periods. The optional start timestamp (inclusive). Defaults to the timestamp of the earliest record in the Data Pool. The optional end timestamp (exclusive). Defaults to the timestamp of the latest record in the Data Pool. The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The time granularity (hour, day, month, etc.) to aggregate the Metric values by. The available time series granularities. Granularities define the unit of time to aggregate the Metric data for a time series query. For example, if the granularity is set to `DAY`, then the the time series query will return a label and a value for each day. If there are no records for a given time series granularity, Propel will return the label and a value of "0" so that the time series can be properly visualized. * `MINUTE`: Aggregates values by minute intervals. * `FIVE_MINUTES`: Aggregates values by 5-minute intervals. * `TEN_MINUTES`: Aggregates values by 10-minute intervals. * `FIFTEEN_MINUTES`: Aggregates values by 15-minute intervals. * `HOUR`: Aggregates values by hourly intervals. * `DAY`: Aggregates values by daily intervals. * `WEEK`: Aggregates values by weekly intervals. * `MONTH`: Aggregates values by monthly intervals. * `YEAR`: Aggregates values by yearly intervals. The Query Filters to apply before retrieving the time series data, in the form of SQL. If no Query Filters are provided, all data is included. Columns to group by. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the time series data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The time series response object. It contains an array of time series labels and an array of Metric values for the given time range and Query Filters. The time series labels. The time series values. The time series values for each group in `groupBy`, if specified. The time series response object for a group specified in `groupBy`. It contains an array of time series labels and an array of Metric values for a particular group. The time series group's columns. The time series group's labels. The time series group's values. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. See Propeller The Query status. See QueryStatus The Query type. See QueryType The Query subtype. See QuerySubtype The SQL the query executed. Query the Metric in leaderboard format. Returns a table (array of rows) with the selected dimensions and the Metric's corresponding values for the given time range and filters. deprecated: Use the top-level `leaderboard` query instead ### Arguments The fields for querying a Metric in leaderboard format. A Metric's leaderboard query returns an ordered table of Dimension and Metric values over a given time range. The Metric to query. You can query a pre-configured Metric by ID or name, or you can query an ad hoc Metric that you define inline. The ID of a pre-configured Metric. The name of a pre-configured Metric. An ad hoc Custom Metric. See CustomMetricQueryInput An ad hoc Count Metric. See CountMetricQueryInput An ad hoc Sum Metric. See SumMetricQueryInput An ad hoc Average Metric. See AverageMetricQueryInput An ad hoc Min Metric. See MinMetricQueryInput An ad hoc Max Metric. See MaxMetricQueryInput An ad hoc Count Distinct Metric. See CountDistinctMetricQueryInput The time range for calculating the leaderboard. The fields required to specify the time range for a time series, counter, or leaderboard Metric query. If no relative or absolute time ranges are provided, Propel defaults to an absolute time range beginning with the earliest record in the Metric's Data Pool and ending with the latest record. If both relative and absolute time ranges are provided, the relative time range will take precedence. If a `LAST_N` relative time period is selected, an `n` ≥ 1 must be provided. If no `n` is provided or `n` \< 1, a `BAD_REQUEST` error will be returned. The timestamp field to use when querying. Defaults to the timestamp configured on the Data Pool or Metric, if any. Set this to filter on an alternative timestamp field. The relative time period. See RelativeTimeRange The number of time units for the `LAST_N` relative periods. The optional start timestamp (inclusive). Defaults to the timestamp of the earliest record in the Data Pool. The optional end timestamp (exclusive). Defaults to the timestamp of the latest record in the Data Pool. The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". One or many Dimensions to group the Metric values by. Typically, Dimensions in a leaderboard are what you want to compare and rank. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The sort order of the rows. It can be ascending (`ASC`) or descending (`DESC`) order. Defaults to descending (`DESC`) order when not provided. The available sort orders. * `ASC`: Sort in ascending order. * `DESC`: Sort in descending order. The number of rows to be returned. It can be a number between 1 and 1,000. The Query Filters to apply before retrieving the leaderboard data, in the form of SQL. If no Query Filters are provided, all data is included. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the leaderboard data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The leaderboard response object. It contains an array of headers and a table (array of rows) with the selected Dimensions and corresponding Metric values for the given time range and Query Filters. The table headers. It contains the Dimension and Metric names. An ordered array of rows. Each row contains the Dimension values and the corresponding Metric value. A Dimension value can be empty. A Metric value will never be empty. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. See Propeller The Query status. See QueryStatus The Query type. See QueryType The Query subtype. See QuerySubtype The SQL the query executed. List the Policies associated to the Metric. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Whether or not access control is enabled for the Metric. deprecated: Use Data Pool Access Policies instead ## CountMetricSettings Settings for Count Metrics. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. You can provide the filters in the form of SQL. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. The available Filter operators. * `EQUALS`: Selects values that are equal to the specified value. * `NOT_EQUALS`: Selects values that are not equal to the specified value. * `GREATER_THAN`: Selects values that are greater than the specified value. * `GREATER_THAN_OR_EQUAL_TO`: Selects values that are greater or equal to the specified value. * `LESS_THAN`: Selects values that are less than the specified value. * `LESS_THAN_OR_EQUAL_TO`: Selects values that are less or equal to the specified value. * `IS_NULL`: Selects values that are null. This operator does not accept a value. * `IS_NOT_NULL`: Selects values that are not null. This operator does not accept a value. * `LIKE`: Selects values that match the specified pattern. * `NOT_LIKE`: "Selects values that do not match the specified pattern. The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. ## SumMetricSettings Settings for Sum Metrics. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. You can provide the filters in the form of SQL. The Dimension to be summed. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats Statistics about a particular Dimension. An array of unique values for the Dimension, up to 1,000. Empty if the Dimension contains more than 1,000 unique values. Fetching unique values incurs query costs. ### Arguments The minimum value of the Dimension. The maximum value of the Dimension. The average value of the Dimension. Empty for non-numeric Dimensions. The Query statistics and metadata. See QueryInfo Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. The available Filter operators. * `EQUALS`: Selects values that are equal to the specified value. * `NOT_EQUALS`: Selects values that are not equal to the specified value. * `GREATER_THAN`: Selects values that are greater than the specified value. * `GREATER_THAN_OR_EQUAL_TO`: Selects values that are greater or equal to the specified value. * `LESS_THAN`: Selects values that are less than the specified value. * `LESS_THAN_OR_EQUAL_TO`: Selects values that are less or equal to the specified value. * `IS_NULL`: Selects values that are null. This operator does not accept a value. * `IS_NOT_NULL`: Selects values that are not null. This operator does not accept a value. * `LIKE`: Selects values that match the specified pattern. * `NOT_LIKE`: "Selects values that do not match the specified pattern. The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. ## CountDistinctMetricSettings Settings for Count Distinct Metrics. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. You can provide the filters in the form of SQL. The Dimension where the count distinct operation is going to be performed. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats Statistics about a particular Dimension. An array of unique values for the Dimension, up to 1,000. Empty if the Dimension contains more than 1,000 unique values. Fetching unique values incurs query costs. ### Arguments The minimum value of the Dimension. The maximum value of the Dimension. The average value of the Dimension. Empty for non-numeric Dimensions. The Query statistics and metadata. See QueryInfo Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. The available Filter operators. * `EQUALS`: Selects values that are equal to the specified value. * `NOT_EQUALS`: Selects values that are not equal to the specified value. * `GREATER_THAN`: Selects values that are greater than the specified value. * `GREATER_THAN_OR_EQUAL_TO`: Selects values that are greater or equal to the specified value. * `LESS_THAN`: Selects values that are less than the specified value. * `LESS_THAN_OR_EQUAL_TO`: Selects values that are less or equal to the specified value. * `IS_NULL`: Selects values that are null. This operator does not accept a value. * `IS_NOT_NULL`: Selects values that are not null. This operator does not accept a value. * `LIKE`: Selects values that match the specified pattern. * `NOT_LIKE`: "Selects values that do not match the specified pattern. The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. ## AverageMetricSettings Settings for Average Metrics. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. You can provide the filters in the form of SQL. The Dimension to be averaged. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats Statistics about a particular Dimension. An array of unique values for the Dimension, up to 1,000. Empty if the Dimension contains more than 1,000 unique values. Fetching unique values incurs query costs. ### Arguments The minimum value of the Dimension. The maximum value of the Dimension. The average value of the Dimension. Empty for non-numeric Dimensions. The Query statistics and metadata. See QueryInfo Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. The available Filter operators. * `EQUALS`: Selects values that are equal to the specified value. * `NOT_EQUALS`: Selects values that are not equal to the specified value. * `GREATER_THAN`: Selects values that are greater than the specified value. * `GREATER_THAN_OR_EQUAL_TO`: Selects values that are greater or equal to the specified value. * `LESS_THAN`: Selects values that are less than the specified value. * `LESS_THAN_OR_EQUAL_TO`: Selects values that are less or equal to the specified value. * `IS_NULL`: Selects values that are null. This operator does not accept a value. * `IS_NOT_NULL`: Selects values that are not null. This operator does not accept a value. * `LIKE`: Selects values that match the specified pattern. * `NOT_LIKE`: "Selects values that do not match the specified pattern. The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. ## MinMetricSettings Settings for Min Metrics. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. You can provide the filters in the form of SQL. The Dimension to select the minimum from. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats Statistics about a particular Dimension. An array of unique values for the Dimension, up to 1,000. Empty if the Dimension contains more than 1,000 unique values. Fetching unique values incurs query costs. ### Arguments The minimum value of the Dimension. The maximum value of the Dimension. The average value of the Dimension. Empty for non-numeric Dimensions. The Query statistics and metadata. See QueryInfo Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. The available Filter operators. * `EQUALS`: Selects values that are equal to the specified value. * `NOT_EQUALS`: Selects values that are not equal to the specified value. * `GREATER_THAN`: Selects values that are greater than the specified value. * `GREATER_THAN_OR_EQUAL_TO`: Selects values that are greater or equal to the specified value. * `LESS_THAN`: Selects values that are less than the specified value. * `LESS_THAN_OR_EQUAL_TO`: Selects values that are less or equal to the specified value. * `IS_NULL`: Selects values that are null. This operator does not accept a value. * `IS_NOT_NULL`: Selects values that are not null. This operator does not accept a value. * `LIKE`: Selects values that match the specified pattern. * `NOT_LIKE`: "Selects values that do not match the specified pattern. The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. ## MaxMetricSettings Settings for Max Metrics. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. You can provide the filters in the form of SQL. The Dimension to select the maximum from. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats Statistics about a particular Dimension. An array of unique values for the Dimension, up to 1,000. Empty if the Dimension contains more than 1,000 unique values. Fetching unique values incurs query costs. ### Arguments The minimum value of the Dimension. The maximum value of the Dimension. The average value of the Dimension. Empty for non-numeric Dimensions. The Query statistics and metadata. See QueryInfo Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. The available Filter operators. * `EQUALS`: Selects values that are equal to the specified value. * `NOT_EQUALS`: Selects values that are not equal to the specified value. * `GREATER_THAN`: Selects values that are greater than the specified value. * `GREATER_THAN_OR_EQUAL_TO`: Selects values that are greater or equal to the specified value. * `LESS_THAN`: Selects values that are less than the specified value. * `LESS_THAN_OR_EQUAL_TO`: Selects values that are less or equal to the specified value. * `IS_NULL`: Selects values that are null. This operator does not accept a value. * `IS_NOT_NULL`: Selects values that are not null. This operator does not accept a value. * `LIKE`: Selects values that match the specified pattern. * `NOT_LIKE`: "Selects values that do not match the specified pattern. The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. ## CustomMetricSettings Settings for Custom Metrics. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. You can provide the filters in the form of SQL. The expression that defines the aggregation function for this Metric. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Metric Filters are present, all records will be included. To filter at query time, add Dimensions and use the `filters` property on the `timeSeriesInput`, `counterInput`, or `leaderboardInput` objects. There is no need to add `filters` to be able to filter at query time. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. The available Filter operators. * `EQUALS`: Selects values that are equal to the specified value. * `NOT_EQUALS`: Selects values that are not equal to the specified value. * `GREATER_THAN`: Selects values that are greater than the specified value. * `GREATER_THAN_OR_EQUAL_TO`: Selects values that are greater or equal to the specified value. * `LESS_THAN`: Selects values that are less than the specified value. * `LESS_THAN_OR_EQUAL_TO`: Selects values that are less or equal to the specified value. * `IS_NULL`: Selects values that are null. This operator does not accept a value. * `IS_NOT_NULL`: Selects values that are not null. This operator does not accept a value. * `LIKE`: Selects values that match the specified pattern. * `NOT_LIKE`: "Selects values that do not match the specified pattern. The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. ## MetricResponse The result of a mutation which creates or modifies a Metric. The Metric which was created or modified. The Metric object. A Metric is a business indicator measured over time. The Metric's unique identifier. The Metric's unique name. The Metric's description. The Metric's Account. The Account object. The Account's unique identifier. The Metric's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Metric's creation date and time in UTC. The Metric's last modification date and time in UTC. The Metric's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Metric's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool that powers this Metric. See DataPool The Metric's Dimensions. These Dimensions are available to Query Filters. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats See DimensionStatistics The Metric's timestamp, if any. This is the same as its Data Pool's timestamp, if any. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats See DimensionStatistics List the Boosters associated to the Metric. ### Arguments See BoosterConnection The Metric's type. The different Metric types determine how the values are calculated. The available Metric types. * `COUNT`: Counts the number of records that matches the Metric Filters. For time series, it will count the values for each time granularity. * `SUM`: Sums the values of the specified column for every record that matches the Metric Filters. For time series, it will sum the values for each time granularity. * `COUNT_DISTINCT`: Counts the number of distinct values in the specified column for every record that matches the Metric Filters. For time series, it will count the distinct values for each time granularity. * `AVERAGE`: Averages the values of the specified column for every record that matches the Metric Filters. For time series, it will average the values for each time granularity. * `MIN`: Selects the minimum value of the specified column for every record that matches the Metric Filters. For time series, it will select the minimum value for each time granularity. * `MAX`: Selects the maximum value of the specified column for every record that matches the Metric Filters. For time series, it will select the maximum value for each time granularity. * `CUSTOM`: Aggregates values based on the provided custom expression. The settings for the Metric. The settings are specific to the Metric's type. A Metric's settings, depending on its type. See CountMetricSettings See SumMetricSettings See CountDistinctMetricSettings See AverageMetricSettings See MinMetricSettings See MaxMetricSettings See CustomMetricSettings The Metric's measure. Access this from the Metric's `settings` object instead. deprecated: Use the Metric `settings` object instead. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats See DimensionStatistics Query the Metric in counter format. Returns the Metric's value for the given time range and filters. deprecated: Use the top-level `counter` query instead ### Arguments The fields for querying a Metric in counter format. A Metric's counter query returns a single value over a given time range. The Metric to query. You can query a pre-configured Metric by ID or name, or you can query an ad hoc Metric that you define inline. See MetricInput The time range for calculating the counter. See TimeRangeInput The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The Query Filters to apply before retrieving the counter data, in the form of SQL. If no Query Filters are provided, all data is included. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the counter data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead See FilterInput The counter response object. It contains a single Metric value for the given time range and Query Filters. The value of the counter. The Query statistics and metadata. See QueryInfo Query the Metric in time series format. Returns arrays of timestamps and the Metric's values for the given time range and filters. deprecated: Use the top-level `timeSeries` query instead ### Arguments The fields for querying a Metric in time series format. A Metric's time series query returns the values over a given time range aggregated by a given time granularity; day, month, or year, for example. The Metric to Query. It can be a pre-created one or it can be inlined here. See MetricInput The time range for calculating the time series. See TimeRangeInput The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The time granularity (hour, day, month, etc.) to aggregate the Metric values by. See TimeSeriesGranularity The Query Filters to apply before retrieving the time series data, in the form of SQL. If no Query Filters are provided, all data is included. Columns to group by. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the time series data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead See FilterInput The time series response object. It contains an array of time series labels and an array of Metric values for the given time range and Query Filters. The time series labels. The time series values. The time series values for each group in `groupBy`, if specified. See TimeSeriesResponseGroup The Query statistics and metadata. See QueryInfo Query the Metric in leaderboard format. Returns a table (array of rows) with the selected dimensions and the Metric's corresponding values for the given time range and filters. deprecated: Use the top-level `leaderboard` query instead ### Arguments The fields for querying a Metric in leaderboard format. A Metric's leaderboard query returns an ordered table of Dimension and Metric values over a given time range. The Metric to query. You can query a pre-configured Metric by ID or name, or you can query an ad hoc Metric that you define inline. See MetricInput The time range for calculating the leaderboard. See TimeRangeInput The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". One or many Dimensions to group the Metric values by. Typically, Dimensions in a leaderboard are what you want to compare and rank. See DimensionInput The sort order of the rows. It can be ascending (`ASC`) or descending (`DESC`) order. Defaults to descending (`DESC`) order when not provided. See Sort The number of rows to be returned. It can be a number between 1 and 1,000. The Query Filters to apply before retrieving the leaderboard data, in the form of SQL. If no Query Filters are provided, all data is included. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the leaderboard data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead See FilterInput The leaderboard response object. It contains an array of headers and a table (array of rows) with the selected Dimensions and corresponding Metric values for the given time range and Query Filters. The table headers. It contains the Dimension and Metric names. An ordered array of rows. Each row contains the Dimension values and the corresponding Metric value. A Dimension value can be empty. A Metric value will never be empty. The Query statistics and metadata. See QueryInfo List the Policies associated to the Metric. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Whether or not access control is enabled for the Metric. deprecated: Use Data Pool Access Policies instead ## ValidateExpressionResult Response returned by the validateExpression query for validating expressions in Custom Metrics. Returns whether the expression is valid or not with a reason explaining why. True if the expression is valid, false otherwise. The reason for why the expression is not valid in case it isn't, null otherwise. ## TimeSeriesResponse The time series response object. It contains an array of time series labels and an array of Metric values for the given time range and Query Filters. The time series labels. The time series values. The time series values for each group in `groupBy`, if specified. The time series response object for a group specified in `groupBy`. It contains an array of time series labels and an array of Metric values for a particular group. The time series group's columns. The time series group's labels. The time series group's values. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Query status. The Query status. * `COMPLETED`: The Query was completed succesfully. * `ERROR`: The Query experienced an error. * `TIMED_OUT`: The Query timed out. The Query type. The Query type. * `METRIC`: Indicates a Metric Query. * `STATS`: Indicates a Dimension Stats Query. * `REPORT`: Indicates a Report Query. * `RECORDS`: Indicates a Record Table Query. * `RECORDS_BY_UNIQUE_ID`: Indicates records queried by unique ID. * `SQL`: Indicates a SQL Query. * `TOP_VALUES`: Indicates a Top Values Query. The Query subtype. The Query subtype. * `COUNTER`: Indicates a Metric counter Query. * `TIME_SERIES`: Indicates a Metric time series Query. * `LEADERBOARD`: Indicates a Metric leaderboard Query. The SQL the query executed. ## TimeSeriesResponseGroup The time series response object for a group specified in `groupBy`. It contains an array of time series labels and an array of Metric values for a particular group. The time series group's columns. The time series group's labels. The time series group's values. ## CounterResponse The counter response object. It contains a single Metric value for the given time range and Query Filters. The value of the counter. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Query status. The Query status. * `COMPLETED`: The Query was completed succesfully. * `ERROR`: The Query experienced an error. * `TIMED_OUT`: The Query timed out. The Query type. The Query type. * `METRIC`: Indicates a Metric Query. * `STATS`: Indicates a Dimension Stats Query. * `REPORT`: Indicates a Report Query. * `RECORDS`: Indicates a Record Table Query. * `RECORDS_BY_UNIQUE_ID`: Indicates records queried by unique ID. * `SQL`: Indicates a SQL Query. * `TOP_VALUES`: Indicates a Top Values Query. The Query subtype. The Query subtype. * `COUNTER`: Indicates a Metric counter Query. * `TIME_SERIES`: Indicates a Metric time series Query. * `LEADERBOARD`: Indicates a Metric leaderboard Query. The SQL the query executed. ## LeaderboardResponse The leaderboard response object. It contains an array of headers and a table (array of rows) with the selected Dimensions and corresponding Metric values for the given time range and Query Filters. The table headers. It contains the Dimension and Metric names. An ordered array of rows. Each row contains the Dimension values and the corresponding Metric value. A Dimension value can be empty. A Metric value will never be empty. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Query status. The Query status. * `COMPLETED`: The Query was completed succesfully. * `ERROR`: The Query experienced an error. * `TIMED_OUT`: The Query timed out. The Query type. The Query type. * `METRIC`: Indicates a Metric Query. * `STATS`: Indicates a Dimension Stats Query. * `REPORT`: Indicates a Report Query. * `RECORDS`: Indicates a Record Table Query. * `RECORDS_BY_UNIQUE_ID`: Indicates records queried by unique ID. * `SQL`: Indicates a SQL Query. * `TOP_VALUES`: Indicates a Top Values Query. The Query subtype. The Query subtype. * `COUNTER`: Indicates a Metric counter Query. * `TIME_SERIES`: Indicates a Metric time series Query. * `LEADERBOARD`: Indicates a Metric leaderboard Query. The SQL the query executed. ## QueryInfo The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Query status. The Query status. * `COMPLETED`: The Query was completed succesfully. * `ERROR`: The Query experienced an error. * `TIMED_OUT`: The Query timed out. The Query type. The Query type. * `METRIC`: Indicates a Metric Query. * `STATS`: Indicates a Dimension Stats Query. * `REPORT`: Indicates a Report Query. * `RECORDS`: Indicates a Record Table Query. * `RECORDS_BY_UNIQUE_ID`: Indicates records queried by unique ID. * `SQL`: Indicates a SQL Query. * `TOP_VALUES`: Indicates a Top Values Query. The Query subtype. The Query subtype. * `COUNTER`: Indicates a Metric counter Query. * `TIME_SERIES`: Indicates a Metric time series Query. * `LEADERBOARD`: Indicates a Metric leaderboard Query. The SQL the query executed. ## Booster Boosters allow you to optimize Metric Queries for a subset of commonly used Dimensions. A Metric can have one or many Boosters to optimize for the different Query patterns. Boosters can be understood as an aggregating index. The index is formed from left to right as follows: 1. The Data Pool's Tenant ID column (if present) 2. Metric Filter columns (if present) 3. Query Filter Dimensions (see `dimensions`) 4. The Data Pool's timestamp column The Booster's unique identifier. The Booster's Account. The Account object. The Account's unique identifier. The Booster's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. The Booster's creation date and time in UTC. The Booster's last modification date and time in UTC. The Booster's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Booster's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Metric this Booster is associated to. See Metric The status of the Booster (once LIVE it will be available for speeding up Metric queries). The Booster status. * `CREATED`: The Booster has been created. Propel will start optimizing the Data Pool soon. * `OPTIMIZING`: Propel is setting up the Booster and optimizing the Data Pool. * `LIVE`: The Booster is now live and available to speed up Metric queries. * `FAILED`: Propel failed to setup the Booster. Please write to support. Alternatively, you can delete the Booster and try again. * `DELETING`: Propel is deleting the Booster and all of its associated data. If the Booster fails during the optimization process, this field includes a descriptive error message. The error object. The error code. The error message. When the Booster is OPTIMIZING, this represents its progress as a number from 0 to 1. In all other states, progress is null. Dimensions included in the Booster. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats Statistics about a particular Dimension. An array of unique values for the Dimension, up to 1,000. Empty if the Dimension contains more than 1,000 unique values. Fetching unique values incurs query costs. ### Arguments The minimum value of the Dimension. The maximum value of the Dimension. The average value of the Dimension. Empty for non-numeric Dimensions. The Query statistics and metadata. See QueryInfo The number of records in the Booster. The amount of storage in terabytes used by the Booster. ## BoosterResponse The result of a mutation which creates or modifies a Booster. The Booster which was created or modified. Boosters allow you to optimize Metric Queries for a subset of commonly used Dimensions. A Metric can have one or many Boosters to optimize for the different Query patterns. Boosters can be understood as an aggregating index. The index is formed from left to right as follows: 1. The Data Pool's Tenant ID column (if present) 2. Metric Filter columns (if present) 3. Query Filter Dimensions (see `dimensions`) 4. The Data Pool's timestamp column The Booster's unique identifier. The Booster's Account. The Account object. The Account's unique identifier. The Booster's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Booster's creation date and time in UTC. The Booster's last modification date and time in UTC. The Booster's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Booster's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Metric this Booster is associated to. See Metric The status of the Booster (once LIVE it will be available for speeding up Metric queries). The Booster status. * `CREATED`: The Booster has been created. Propel will start optimizing the Data Pool soon. * `OPTIMIZING`: Propel is setting up the Booster and optimizing the Data Pool. * `LIVE`: The Booster is now live and available to speed up Metric queries. * `FAILED`: Propel failed to setup the Booster. Please write to support. Alternatively, you can delete the Booster and try again. * `DELETING`: Propel is deleting the Booster and all of its associated data. If the Booster fails during the optimization process, this field includes a descriptive error message. The error object. The error code. The error message. When the Booster is OPTIMIZING, this represents its progress as a number from 0 to 1. In all other states, progress is null. Dimensions included in the Booster. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats See DimensionStatistics The number of records in the Booster. The amount of storage in terabytes used by the Booster. ## Policy The Policy type. It governs an Application's access to a Metric's data. The Policy's unique identifier. The Policy's Account. The Account object. The Account's unique identifier. The Policy's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. The Policy's creation date and time in UTC. The Policy's last modification date and time in UTC. The Policy's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Policy's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The type of Policy. The types of Policies that can be applied to a Metric. * `ALL_ACCESS`: Grants access to all Metric data. * `TENANT_ACCESS`: Grants access to a specified tenant's Metric data. The Application that is granted access. See Application The Metric that the Application is granted access to. See Metric ## PolicyResponse The result of a mutation which creates or modifies a Policy. The Policy which was created or modified. The Policy type. It governs an Application's access to a Metric's data. The Policy's unique identifier. The Policy's Account. The Account object. The Account's unique identifier. The Policy's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Policy's creation date and time in UTC. The Policy's last modification date and time in UTC. The Policy's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Policy's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The type of Policy. The types of Policies that can be applied to a Metric. * `ALL_ACCESS`: Grants access to all Metric data. * `TENANT_ACCESS`: Grants access to a specified tenant's Metric data. The Application that is granted access. See Application The Metric that the Application is granted access to. See Metric ## DeletionJob Deletion Job scheduled for a specific Data Pool. The Deletion Job represents the asynchronous process of deleting data given some filters inside a Data Pool. It tracks the deletion process until it is finished, showing the progress and the outcome when it is finished. The Deletion Job's ID. The Deletion Job's creation date and time in UTC. Who created the Deletion Job. The Deletion Job's last modification date and time in UTC. Who last modified the Deletion Job. Account to which the Deletion Job belongs. The Account object. The Account's unique identifier. Environment to which the Deletion Job belongs. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. The Data Pool whose records will be deleted by the Deletion Job. See DataPool The current Deletion Job's status. * `CREATED`: The Job was created, but is not yet being executed. * `IN_PROGRESS`: The Job is executing. * `SUCCEEDED`: The Job succeeded. * `FAILED`: The Job failed. Check the error message. The filters that will be used for deleting data, in the form of SQL. Data matching the filters will be deleted. The error that occurred while deleting data, if any. The error object. The error code. The error message. The current progress of the Deletion Job, from 0.0 to 1.0. The time at which the Deletion Job started. The time at which the Deletion Job succeeded. The time at which the Deletion Job failed. The list of filters that will be used for deleting data. Data matching the filters will be deleted. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. The available Filter operators. * `EQUALS`: Selects values that are equal to the specified value. * `NOT_EQUALS`: Selects values that are not equal to the specified value. * `GREATER_THAN`: Selects values that are greater than the specified value. * `GREATER_THAN_OR_EQUAL_TO`: Selects values that are greater or equal to the specified value. * `LESS_THAN`: Selects values that are less than the specified value. * `LESS_THAN_OR_EQUAL_TO`: Selects values that are less or equal to the specified value. * `IS_NULL`: Selects values that are null. This operator does not accept a value. * `IS_NOT_NULL`: Selects values that are not null. This operator does not accept a value. * `LIKE`: Selects values that match the specified pattern. * `NOT_LIKE`: "Selects values that do not match the specified pattern. The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. ## RequestDeleteResponse The response returned by the Deletion Job. The Deletion Job that was just created. Deletion Job scheduled for a specific Data Pool. The Deletion Job represents the asynchronous process of deleting data given some filters inside a Data Pool. It tracks the deletion process until it is finished, showing the progress and the outcome when it is finished. The Deletion Job's ID. The Deletion Job's creation date and time in UTC. Who created the Deletion Job. The Deletion Job's last modification date and time in UTC. Who last modified the Deletion Job. Account to which the Deletion Job belongs. The Account object. The Account's unique identifier. Environment to which the Deletion Job belongs. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool whose records will be deleted by the Deletion Job. See DataPool The current Deletion Job's status. * `CREATED`: The Job was created, but is not yet being executed. * `IN_PROGRESS`: The Job is executing. * `SUCCEEDED`: The Job succeeded. * `FAILED`: The Job failed. Check the error message. The filters that will be used for deleting data, in the form of SQL. Data matching the filters will be deleted. The error that occurred while deleting data, if any. The error object. The error code. The error message. The current progress of the Deletion Job, from 0.0 to 1.0. The time at which the Deletion Job started. The time at which the Deletion Job succeeded. The time at which the Deletion Job failed. The list of filters that will be used for deleting data. Data matching the filters will be deleted. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. ## DeletionJobResponse The response returned by the Deletion Job. The Deletion Job that was just created. Deletion Job scheduled for a specific Data Pool. The Deletion Job represents the asynchronous process of deleting data given some filters inside a Data Pool. It tracks the deletion process until it is finished, showing the progress and the outcome when it is finished. The Deletion Job's ID. The Deletion Job's creation date and time in UTC. Who created the Deletion Job. The Deletion Job's last modification date and time in UTC. Who last modified the Deletion Job. Account to which the Deletion Job belongs. The Account object. The Account's unique identifier. Environment to which the Deletion Job belongs. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool whose records will be deleted by the Deletion Job. See DataPool The current Deletion Job's status. * `CREATED`: The Job was created, but is not yet being executed. * `IN_PROGRESS`: The Job is executing. * `SUCCEEDED`: The Job succeeded. * `FAILED`: The Job failed. Check the error message. The filters that will be used for deleting data, in the form of SQL. Data matching the filters will be deleted. The error that occurred while deleting data, if any. The error object. The error code. The error message. The current progress of the Deletion Job, from 0.0 to 1.0. The time at which the Deletion Job started. The time at which the Deletion Job succeeded. The time at which the Deletion Job failed. The list of filters that will be used for deleting data. Data matching the filters will be deleted. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. ## AddColumnToDataPoolJob AddColumnToDataPoolJob scheduled for a specific Data Pool. The Add Column Job represents the asynchronous process of adding a column, given its name and type, to a Data Pool. It tracks the process of adding a column until it is finished, showing the progress and the outcome when it is finished. The AddColumnToDataPoolJob's ID. The AddColumnToDataPoolJob's creation date and time in UTC. Who created the AddColumnToDataPoolJob. The AddColumnToDataPoolJob's last modification date and time in UTC. Who modified the AddColumnToDataPoolJob last. Account to which the AddColumnToDataPoolJob belongs. The Account object. The Account's unique identifier. Environment to which the AddColumnToDataPoolJob belongs. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. The Data Pool to which a column will be added by the Job. See DataPool The current AddColumnToDataPoolJob's status. * `CREATED`: The Job was created, but is not yet being executed. * `IN_PROGRESS`: The Job is executing. * `SUCCEEDED`: The Job succeeded. * `FAILED`: The Job failed. Check the error message. Name of the new column. Type of the new column. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. The ClickHouse type of the new column when `columnType` is set to `CLICKHOUSE`. JSON property to which the new column corresponds. The error that occurred while adding the column data, if any. The error object. The error code. The error message. The current progress of the AddColumnToDataPool Job, from 0.0 to 1.0. The time at which the AddColumnToDataPool Job started. The time at which the AddColumnToDataPool Job succeeded. The time at which the AddColumnToDataPool Job failed. ## AddColumnToDataPoolJobResponse The response returned by the Add Column Job. The AddColumnToDataPool Job that was just created. AddColumnToDataPoolJob scheduled for a specific Data Pool. The Add Column Job represents the asynchronous process of adding a column, given its name and type, to a Data Pool. It tracks the process of adding a column until it is finished, showing the progress and the outcome when it is finished. The AddColumnToDataPoolJob's ID. The AddColumnToDataPoolJob's creation date and time in UTC. Who created the AddColumnToDataPoolJob. The AddColumnToDataPoolJob's last modification date and time in UTC. Who modified the AddColumnToDataPoolJob last. Account to which the AddColumnToDataPoolJob belongs. The Account object. The Account's unique identifier. Environment to which the AddColumnToDataPoolJob belongs. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool to which a column will be added by the Job. See DataPool The current AddColumnToDataPoolJob's status. * `CREATED`: The Job was created, but is not yet being executed. * `IN_PROGRESS`: The Job is executing. * `SUCCEEDED`: The Job succeeded. * `FAILED`: The Job failed. Check the error message. Name of the new column. Type of the new column. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. The ClickHouse type of the new column when `columnType` is set to `CLICKHOUSE`. JSON property to which the new column corresponds. The error that occurred while adding the column data, if any. The error object. The error code. The error message. The current progress of the AddColumnToDataPool Job, from 0.0 to 1.0. The time at which the AddColumnToDataPool Job started. The time at which the AddColumnToDataPool Job succeeded. The time at which the AddColumnToDataPool Job failed. ## UpdateDataPoolRecordsJob UpdateDataPoolRecords Job scheduled for a specific Data Pool. The Update Data Pool Records Job represents the asynchronous process of updating records given some filters, inside a Data Pool. It tracks the process of updating records until it is finished, showing the progress and the outcome when it is finished. The UpdateDataPoolRecords Job's ID The UpdateDataPoolRecords Job's creation date and time in UTC Who created the UpdateDataPoolRecords Job The UpdateDataPoolRecords Job's last modification date and time in UTC Who last modified the UpdateDataPoolRecords Job Account to which the UpdateDataPoolRecords Job belongs The Account object. The Account's unique identifier. Environment to which the UpdateDataPoolRecords Job belongs The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. The Data Pool whose records will be updated by the UpdateDataPoolRecords Job See DataPool The current UpdateDataPoolRecords Job's status * `CREATED`: The Job was created, but is not yet being executed. * `IN_PROGRESS`: The Job is executing. * `SUCCEEDED`: The Job succeeded. * `FAILED`: The Job failed. Check the error message. The filters that will be used for updating data, in the form of SQL. Data matching the filters will be updated. Describes how the job will update the records. The fields for creating an Update Data Pool Records Job. ``` { "column": "status", "expression": "'completed'" } { "column": "counter", "expression": "counter + 1" } { "column": "full_name", "expression": "concat(first_name, ' ', last_name)" } ``` The name of the column to update. The value to which the column will be updated. Once evaluated, it should be of the same data type as the column. The error that occurred while updating data, if any. The error object. The error code. The error message. The current progress of the UpdateDataPoolRecords Job, from 0.0 to 1.0. The time at which the UpdateDataPoolRecords Job started. The time at which the UpdateDataPoolRecords Job succeeded. The time at which the UpdateDataPoolRecords Job failed. The list of filters that will be used for updating data. Data matching the filters will be updated. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. The available Filter operators. * `EQUALS`: Selects values that are equal to the specified value. * `NOT_EQUALS`: Selects values that are not equal to the specified value. * `GREATER_THAN`: Selects values that are greater than the specified value. * `GREATER_THAN_OR_EQUAL_TO`: Selects values that are greater or equal to the specified value. * `LESS_THAN`: Selects values that are less than the specified value. * `LESS_THAN_OR_EQUAL_TO`: Selects values that are less or equal to the specified value. * `IS_NULL`: Selects values that are null. This operator does not accept a value. * `IS_NOT_NULL`: Selects values that are not null. This operator does not accept a value. * `LIKE`: Selects values that match the specified pattern. * `NOT_LIKE`: "Selects values that do not match the specified pattern. The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. ## UpdateDataPoolRecordsJobResponse The response returned by the Update Data Pool Records Job. The UpdateDataPoolRecords Job that was just created. UpdateDataPoolRecords Job scheduled for a specific Data Pool. The Update Data Pool Records Job represents the asynchronous process of updating records given some filters, inside a Data Pool. It tracks the process of updating records until it is finished, showing the progress and the outcome when it is finished. The UpdateDataPoolRecords Job's ID The UpdateDataPoolRecords Job's creation date and time in UTC Who created the UpdateDataPoolRecords Job The UpdateDataPoolRecords Job's last modification date and time in UTC Who last modified the UpdateDataPoolRecords Job Account to which the UpdateDataPoolRecords Job belongs The Account object. The Account's unique identifier. Environment to which the UpdateDataPoolRecords Job belongs The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool whose records will be updated by the UpdateDataPoolRecords Job See DataPool The current UpdateDataPoolRecords Job's status * `CREATED`: The Job was created, but is not yet being executed. * `IN_PROGRESS`: The Job is executing. * `SUCCEEDED`: The Job succeeded. * `FAILED`: The Job failed. Check the error message. The filters that will be used for updating data, in the form of SQL. Data matching the filters will be updated. Describes how the job will update the records. The fields for creating an Update Data Pool Records Job. ``` { "column": "status", "expression": "'completed'" } { "column": "counter", "expression": "counter + 1" } { "column": "full_name", "expression": "concat(first_name, ' ', last_name)" } ``` The name of the column to update. The value to which the column will be updated. Once evaluated, it should be of the same data type as the column. The error that occurred while updating data, if any. The error object. The error code. The error message. The current progress of the UpdateDataPoolRecords Job, from 0.0 to 1.0. The time at which the UpdateDataPoolRecords Job started. The time at which the UpdateDataPoolRecords Job succeeded. The time at which the UpdateDataPoolRecords Job failed. The list of filters that will be used for updating data. Data matching the filters will be updated. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. ## DataPoolAccessPolicy The ID of the Data Pool Access Policy. The Data Pool Access Policy's unique name. The Data Pool Access Policy's description. The Data Pool Access Policy's Account. The Account object. The Account's unique identifier. The Data Pool Access Policy's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. The Data Pool Access Policy's creation date and time in UTC. The Data Pool Access Policy's last modification date and time in UTC. The Data Pool Access Policy's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool Access Policy's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool to which the Access Policy belongs. See DataPool Columns that the Access Policy makes available for querying. Row-level filters that the Access Policy applies before executing queries, in the form of SQL. Applications that are assigned to this Data Pool Access Policy. ### Arguments See ApplicationConnection Row-level filters that the Access Policy applies before executing queries. deprecated: Use `filtersSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. The available Filter operators. * `EQUALS`: Selects values that are equal to the specified value. * `NOT_EQUALS`: Selects values that are not equal to the specified value. * `GREATER_THAN`: Selects values that are greater than the specified value. * `GREATER_THAN_OR_EQUAL_TO`: Selects values that are greater or equal to the specified value. * `LESS_THAN`: Selects values that are less than the specified value. * `LESS_THAN_OR_EQUAL_TO`: Selects values that are less or equal to the specified value. * `IS_NULL`: Selects values that are null. This operator does not accept a value. * `IS_NOT_NULL`: Selects values that are not null. This operator does not accept a value. * `LIKE`: Selects values that match the specified pattern. * `NOT_LIKE`: "Selects values that do not match the specified pattern. The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. ## DataPoolAccessPolicyResponse The Data Pool Access Policy. The ID of the Data Pool Access Policy. The Data Pool Access Policy's unique name. The Data Pool Access Policy's description. The Data Pool Access Policy's Account. The Account object. The Account's unique identifier. The Data Pool Access Policy's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool Access Policy's creation date and time in UTC. The Data Pool Access Policy's last modification date and time in UTC. The Data Pool Access Policy's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool Access Policy's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool to which the Access Policy belongs. See DataPool Columns that the Access Policy makes available for querying. Row-level filters that the Access Policy applies before executing queries, in the form of SQL. Applications that are assigned to this Data Pool Access Policy. ### Arguments See ApplicationConnection Row-level filters that the Access Policy applies before executing queries. deprecated: Use `filtersSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. Creates an Environment and returns the newly created Environment (or an error if creating the Environment fails). ### Arguments The fields for creating an Environment. The Environment's unique name. The Environment's description. The result of a mutation which creates or modifies an Environment. The Environment which was created or modified. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account Modifies an Environment with the provided fields. If any of the optional fields are omitted, those properties will be unchanged on the Environment. ### Arguments The fields for modifying an Environment. The Environment's unique name. The Environment's description. The result of a mutation which creates or modifies an Environment. The Environment which was created or modified. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account Deletes a Environment by ID and returns its ID if the Environment was deleted successfully. ### Arguments Creates a Data Pool Access Policy for the specified Data Pool. ### Arguments The Data Pool Access Policy's unique name. If not specified, Propel will set the ID as unique name. The Data Pool Access Policy's description. The Data Pool to which the Access Policy belongs. Columns that the Access Policy makes available for querying. If set to `["*"]`, all columns will be available for querying. Row-level filters that the Access Policy applies before executing queries, in the form of SQL. Row-level filters that the Access Policy applies before executing queries. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The Data Pool Access Policy. The ID of the Data Pool Access Policy. The Data Pool Access Policy's unique name. The Data Pool Access Policy's description. The Data Pool Access Policy's Account. See Account The Data Pool Access Policy's Environment. See Environment The Data Pool Access Policy's creation date and time in UTC. The Data Pool Access Policy's last modification date and time in UTC. The Data Pool Access Policy's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool Access Policy's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool to which the Access Policy belongs. See DataPool Columns that the Access Policy makes available for querying. Row-level filters that the Access Policy applies before executing queries, in the form of SQL. Applications that are assigned to this Data Pool Access Policy. ### Arguments See ApplicationConnection Row-level filters that the Access Policy applies before executing queries. deprecated: Use `filtersSql` instead See Filter Modifies a Data Pool Access Policy with the provided unique name, description, columns and rows. If any of the optional arguments are omitted, those properties will be unchanged on the Data Pool Access Policy. ### Arguments The Data Pool Access Policy's new unique name. The Data Pool Access Policy's new description. Columns that the Access Policy makes available for querying. If not provided this property will not be modified. Row-level filters that the Access Policy applies before executing queries, in the form of SQL. If not provided this property will not be modified. Row-level filters that the Access Policy applies before executing queries. If not provided this property will not be modified. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The Data Pool Access Policy. The ID of the Data Pool Access Policy. The Data Pool Access Policy's unique name. The Data Pool Access Policy's description. The Data Pool Access Policy's Account. See Account The Data Pool Access Policy's Environment. See Environment The Data Pool Access Policy's creation date and time in UTC. The Data Pool Access Policy's last modification date and time in UTC. The Data Pool Access Policy's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool Access Policy's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool to which the Access Policy belongs. See DataPool Columns that the Access Policy makes available for querying. Row-level filters that the Access Policy applies before executing queries, in the form of SQL. Applications that are assigned to this Data Pool Access Policy. ### Arguments See ApplicationConnection Row-level filters that the Access Policy applies before executing queries. deprecated: Use `filtersSql` instead See Filter Deletes a Data Pool Access Policy by ID and returns its ID if the Data Pool Access Policy was deleted successfully. ### Arguments Assign a Data Pool Access Policy to an Application. The Data Pool Access Policy will restrict the Data Pool rows and columns that the Application can query. If the Data Pool has `accessControlEnabled` set to true, the Application *must* have a Data Pool Access Policy assigned in order to query the Data Pool. An Application can have at most one Data Pool Access Policy assigned for a given Data Pool. If an Application already has a Data Pool Access Policy for a given Data Pool, and you call this mutation with another Data Pool Access Policy for the same Data Pool, the Application's Data Pool Access Policy will be replaced. ### Arguments Unassign a Data Pool Access Policy from an Application. Once unassigned, whether the Application will be able to query the Data Pool is controlled by the Data Pool's `accessControlEnabled` property. If `accessControlEnabled` is true, the Application will no longer be able to query the Data Pool. If `accessControlEnabled` is false, the Application will be able to query *all* data in the Data Pool, unrestricted. ### Arguments Creates a new Application and returns the newly created Application (or an error message if creating the Application fails). Required scopes: * APPLICATION\_ADMIN ```graphql theme={"system"} mutation { createApplication( input: { uniqueName: "example_sample_application" description: "My dashboard app" scopes: [DATA_POOL_QUERY] propeller: P1_X_SMALL } ) { ... on ApplicationResponse { application { id uniqueName } } ... on FailureResponse { error { code message } } } } ``` ### Arguments The fields for creating an Application. The Application's unique name. If not specified, Propel will set the ID as unique name. The Application's description. The Application's Propeller. If no Propeller is provided, Propel will set the Propeller to `P1_X_SMALL`. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Application's API authorization scopes. If specified, at least one scope must be provided; otherwise, all scopes will be granted to the Application by default. The API operations an Application is authorized to perform. * `ADMIN`: Grant read/write access to Data Sources, Data Pools, Metrics and Policies. * `APPLICATION_ADMIN`: Grant read/write access to Applications. * `DATA_POOL_QUERY`: Grant read access to query Data Pools. * `DATA_POOL_READ`: Grant read access to read Data Pools. * `DATA_POOL_STATS`: Grant read access to fetch column statistics from Data Pools. * `ENVIRONMENT_ADMIN`: Grant read/write access to Environments. * `METRIC_QUERY`: Grant read access to query Metrics. * `METRIC_STATS`: Grant read access to fetch Dimension statistics from Metrics. * `METRIC_READ`: Grant read access to Metrics. This does not allow querying Metrics. For that, see `METRIC_QUERY`. The result of a mutation which creates or modifies an Application. If successful, an `ApplicationResponse` will be returned; otherwise, a `FailureResponse` will be returned. The result of a mutation which creates or modifies an Application. The Application which was created or modified. See Application The failure response object. The error that caused the failure. See Error Modifies an Application with the provided unique name, description, Propeller, and scopes. If any of the optional arguments are omitted, those properties will be unchanged on the Application. ### Arguments The fields for modifying an Application. The ID or unique name of the Application to modify. The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The Application's new unique name. The Application's new description. The Application's new Propeller. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Application's new API authorization scopes. The API operations an Application is authorized to perform. * `ADMIN`: Grant read/write access to Data Sources, Data Pools, Metrics and Policies. * `APPLICATION_ADMIN`: Grant read/write access to Applications. * `DATA_POOL_QUERY`: Grant read access to query Data Pools. * `DATA_POOL_READ`: Grant read access to read Data Pools. * `DATA_POOL_STATS`: Grant read access to fetch column statistics from Data Pools. * `ENVIRONMENT_ADMIN`: Grant read/write access to Environments. * `METRIC_QUERY`: Grant read access to query Metrics. * `METRIC_STATS`: Grant read access to fetch Dimension statistics from Metrics. * `METRIC_READ`: Grant read access to Metrics. This does not allow querying Metrics. For that, see `METRIC_QUERY`. The result of a mutation which creates or modifies an Application. If successful, an `ApplicationResponse` will be returned; otherwise, a `FailureResponse` will be returned. The result of a mutation which creates or modifies an Application. The Application which was created or modified. See Application The failure response object. The error that caused the failure. See Error Deletes an Application by ID and returns its ID if the Application was deleted successfully. ### Arguments Deletes an Application by unique name and returns its ID if the Application was deleted successfully. ### Arguments Creates a new Data Source from the given Snowflake database using the specified Snowflake account, warehouse, schema, username, and role. Returns the newly created Data Source (or an error message if creating the Data Source fails). ### Arguments The fields for creating a Snowflake Data Source. The Data Source's unique name. If not specified, Propel will set the ID as unique name. The Data Source's description. The Data Source's connection settings. The fields for creating a Snowflake Data Source's connection settings. The Snowflake account. Only include the part before the "snowflakecomputing.com" part of your Snowflake URL (make sure you are in classic console, not Snowsight). For AWS-based accounts, this looks like "znXXXXX.us-east-2.aws". For Google Cloud-based accounts, this looks like "ffXXXXX.us-central1.gcp". The Snowflake database name. The Snowflake warehouse name. It should be "PROPELLING" if you used the default name in the setup script. The Snowflake schema. The Snowflake username. It should be "PROPEL" if you used the default name in the setup script. The Snowflake password. The Snowflake role. It should be "PROPELLER" if you used the default name in the setup script. The result of a mutation which creates or modifies a DataSource. If successful, an `DataSourceResponse` will be returned; otherwise, a `FailureResponse` will be returned. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. See DataSource The failure response object. The error that caused the failure. See Error Modifies a Data Source with the provided unique name, description, and connection settings. If any of the optional arguments are omitted, those properties will be unchanged on the Data Source. ### Arguments The fields for modifying a Snowflake Data Source. The ID or unique name of the Data Source to modify. The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The Data Source's new unique name. The Data Source's new description. The Data Source's new connection settings. The fields for modifying a Snowflake Data Source's connection settings. The Snowflake account. Only include the part before the "snowflakecomputing.com" part of your Snowflake URL (make sure you are in classic console, not Snowsight). For AWS-based accounts, this looks like "znXXXXX.us-east-2.aws". For Google Cloud-based accounts, this looks like "ffXXXXX.us-central1.gcp". If not provided this property will not be modified. The Snowflake database name. If not provided this property will not be modified. The Snowflake warehouse name. It should be "PROPELLING" if you used the default name in the setup script. If not provided this property will not be modified. The Snowflake schema. If not provided this property will not be modified. The Snowflake username. It should be "PROPEL" if you used the default name in the setup script. If not provided this property will not be modified. The Snowflake password. If not provided this property will not be modified. The Snowflake role. It should be "PROPELLER" if you used the default name in the setup script. If not provided this property will not be modified. The result of a mutation which creates or modifies a DataSource. If successful, an `DataSourceResponse` will be returned; otherwise, a `FailureResponse` will be returned. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. See DataSource The failure response object. The error that caused the failure. See Error Attempts to reconnect a Data Source. The mutation then returns the Data Source object. ### Arguments The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. The Account object. The Account's unique identifier. The Data Source's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. The types of Data Sources. * `WEBHOOK`: Indicates a Webhook Data Source. * `TWILIO_SEGMENT`: Indicates a Twilio Segment Data Source. * `S3`: Indicates an Amazon S3 Data Source. * `Redshift`: Indicates a Redshift Data Source. * `POSTGRESQL`: Indicates a PostgreSQL Data Source. * `KAFKA`: Indicates a Kafka Data Source. * `Http`: Indicates an Http Data Source. * `CLICKHOUSE`: Indicates a ClickHouse Data Source. * `AMAZON_DYNAMODB`: Indicates an Amazon DynamoDB Data Source. * `AMAZON_DATA_FIREHOSE`: Indicates an Amazon Data Firehose Data Source. * `Snowflake`: Indicates a Snowflake Data Source. * `INTERNAL`: Indicates an internal Data Source. The Data Source's status. The status of a Data Source. * `CREATED`: The Data Source has been created, but it is not connected yet. * `CONNECTING`: Propel is attempting to connect the Data Source. * `CONNECTED`: The Data Source is connected. * `BROKEN`: The Data Source failed to connect. * `DELETING`: Propel is deleting the Data Source. The Data Source's connection settings. See SnowflakeConnectionSettings See InternalConnectionSettings See AmazonDataFirehoseConnectionSettings See AmazonDynamoDBConnectionSettings See ClickHouseConnectionSettings See HttpConnectionSettings See KafkaConnectionSettings See PostgreSqlConnectionSettings See S3ConnectionSettings See TwilioSegmentConnectionSettings See WebhookConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. The Data Source Check object. Data Source Checks are executed when setting up your Data Source. They check that Propel will be able to receive data and setup Data Pools. The exact Checks to perform vary by Data Source. For example, Snowflake-backed Data Sources will have their own specific Checks. The name of the Data Source Check to be performed. A description of the Data Source Check to be performed. The status of the Data Source Check (all checks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataSourceCheckStatus If the Data Source Check failed, this field includes a descriptive error message. See Error The time at which the Data Source Check was performed. If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead The error object. The error code. The error message. Introspects the tables in a Data Source. Returns the tables along with when they were last cached from the Data Source. ### Arguments The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The table introspection object. When setting up a Data Source, Propel may need to introspect tables in order to determine what tables and columns are available to create Data Pools from. The table introspection represents the lifecycle of this operation (whether it's in-progress, succeeded, or failed) and the resulting tables and columns. These will be captured as table and column objects, respectively. The Data Source the table introspection was performed for. See DataSource The status of the table introspection. The status of a table introspection. * `NOT_STARTED`: The table introspection has not started. * `STARTED`: The table introspection has started. * `SUCCEEDED`: The table introspection succeeded. * `FAILED`: The table introspection failed. The table introspection's creation date and time in UTC. The table introspection's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The table introspection's last modification date and time in UTC. The table introspection's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The number of tables introspected. The tables introspected. ### Arguments See TableConnection Tests that Propel can actually connect to the data warehouse. Updates the status. ### Arguments The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The result of a mutation which creates or modifies a DataSource. If successful, an `DataSourceResponse` will be returned; otherwise, a `FailureResponse` will be returned. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. See DataSource The failure response object. The error that caused the failure. See Error Deletes a Data Source by ID and returns its ID if the Data Source was deleted successfully. ### Arguments Deletes a Data Source by unique name and returns its ID if the Data Source was deleted successfully. ### Arguments Creates a new Data Pool. Returns the newly created Data Pool or an error message if it fails. ```graphql theme={"system"} mutation { createDataPoolV2(input: { dataSource: "DSOXXXXX" table: "tacosoft_sales_analytics" timestamp: { columnName: "timestamp" } columns: [ { columnName: "timestamp", type: TIMESTAMP, isNullable: true }, { columnName: "order_id", type: STRING, isNullable: true }, { columnName: "taco_name", type: STRING, isNullable: true }, { columnName: "toppings", type: JSON, isNullable: true }, { columnName: "quantity", type: INT32, isNullable: true }, { columnName: "taco_unit_price", type: INT32, isNullable: true }, { columnName: "taco_total_price", type: INT32, isNullable: true } ] }) { dataPool { id uniqueName tableSettings { orderBy engine { ... on MergeTreeTableEngine { type } ... on ReplacingMergeTreeTableEngine { type ver } ... on SummingMergeTreeTableEngine { type columns } ... on AggregatingMergeTreeTableEngine { type } ... on PostgreSqlTableEngine { type } } } } } } ``` ### Arguments The fields for creating a Data Pool. The Data Source that will be used to create the Data Pool. The table that the Data Pool will sync from. The table's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It's part of what makes Propel fast for larger data sets. It will also serve as the time dimension for your Metrics. If you do not provide a primary timestamp column, you will need to supply an alternate timestamp when querying your Data Pool or its Metrics using the TimeRangeInput. The fields to specify the Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. The Data Pool's unique name. If not specified, Propel will set the ID as the unique name. The Data Pool's description. The list of columns. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type to use when `type` is set to `CLICKHOUSE`. Whether the column is nullable, meaning whether it accepts a null value. The Data Pool's syncing settings. The fields for modifying the Data Pool syncing. See DataPoolSyncInterval Enables or disables access control for the Data Pool. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. Override the Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse, and a default will be chosen based on the Data Pool's `timestamp` and `uniqueId` values, if any. You can override these defaults in order to specify a custom table engine, custom ORDER BY, etc. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. This field is optional. A default will be chosen based on the Data Pool's `timestamp` and `uniqueId` values, if specified. See TableEngineInput The PARTITION BY clause for the Data Pool's table. This field is optional. A default will be chosen based on the Data Pool's `timestamp` and `uniqueId` values, if specified. The PRIMARY KEY clause for the Data Pool's table. This field is optional. A default will be chosen based on the Data Pool's `timestamp` and `uniqueId` values, if specified. The ORDER BY clause for the Data Pool's table. This field is optional. A default will be chosen based on the Data Pool's `timestamp` and `uniqueId` values, if specified. The TTL clause for the Data Pool's table. The Data Pool's optional tenant ID column. The tenant ID column is used to control access to your data with access policies. deprecated: Will be removed; use Data Pool Access Policies instead The fields to specify the Data Pool's tenant ID column. The tenant ID column is used to control access to your data with access policies. The name of the column that represents the tenant ID. The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. The fields to specify the Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. The name of the column that represents the unique ID. The result of a mutation which creates or modifies a Data Pool. The Data Pool which was created or modified. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId Modifies a Data Pool with the provided unique name, description, and data retention time. If any of the optional arguments are omitted, those properties will be unchanged on the Data Pool. ### Arguments The fields for modifying a Data Pool. The ID or unique name of the Data Pool to modify. The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The Data Pool's new unique name. The Data Pool's new description. The Data Pool's new data retention in days. The Data Pool's new syncing settings. The fields for modifying the Data Pool syncing. See DataPoolSyncInterval The table's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It's part of what makes Propel fast for larger data sets. It will also serve as the time dimension for your Metrics. If you do not provide a primary timestamp column, you will need to supply an alternate timestamp when querying your Data Pool or its Metrics using the TimeRangeInput. The fields to specify the Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. Enables or disables access control for the Data Pool. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. The result of a mutation which creates or modifies a Data Pool. If successful, an `DataPoolResponse` will be returned; otherwise, a `FailureResponse` will be returned. The result of a mutation which creates or modifies a Data Pool. The Data Pool which was created or modified. See DataPool The failure response object. The error that caused the failure. See Error Retries to set up the Data Pool identified by the given ID. ### Arguments The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. The Account object. The Account's unique identifier. The Data Pool's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. The status of a Data Pool. * `CREATED`: The Data Pool has been created and will be set up soon. * `PENDING`: Propel is attempting to set up the Data Pool. * `LIVE`: The Data Pool is set up and serving data. Check its Syncs to monitor data ingestion. * `SETUP_FAILED`: The Data Pool setup failed. Check its Setup Tasks before re-attempting setup. * `CONNECTING` * `CONNECTED` * `BROKEN` * `PAUSING` * `PAUSED` * `DELETING`: Propel is deleting the Data Pool and all of its associated data. The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. A Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. The primary timestamp column's type. The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo The list of measures (numeric columns) in the Data Pool. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo A list of setup tasks performed on the Data Pool during its most recent setup attempt. The Data Pool Setup Task object. Data Pool Setup Tasks are executed when setting up your Data Pool. They ensure Propel will be able to sync records from your Data Source to your Data Pool. The exact Setup Tasks to perform vary by Data Source. For example, Data Pools pointing to a Snowflake-backed Data Sources will have their own specific Setup Tasks. The name of the Data Pool Setup Task to be performed. A description of the Data Pool Setup Task to be performed. The status of the Data Pool Setup Task (all setup tasks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataPoolSetupTaskStatus If the Data Pool Setup Task failed, this field includes a descriptive error message. See Error The time at which the Data Pool Setup Task was completed. Settings related to Data Pool syncing. Settings related to Data Pool syncing. Indicates whether syncing is enabled or disabled. See DataPoolSyncStatus The syncing interval. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. See DataPoolSyncInterval The date and time of the most recent Sync in UTC. The list of Syncs of the Data Pool. ### Arguments The filter to apply when listing the Syncs for a Data Pool. * `EMPTY`: Returns only Syncs with empty records. * `NOT_EMPTY`: Returns only Syncs that contain one or more records. * `ALL`: Returns all Syncs, regardless of whether they contain records or not. See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments Response returned by the validateExpression query for validating expressions in Custom Metrics. Returns whether the expression is valid or not with a reason explaining why. True if the expression is valid, false otherwise. The reason for why the expression is not valid in case it isn't, null otherwise. The Data Pool's table settings. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. See TableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The Data Pool's columns that participate in its PARTITION BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its PRIMARY KEY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its ORDER BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead deprecated: Refer to `setupTasks` instead The error object. The error code. The error message. The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead A Data Pool's tenant ID column. The tenant ID column is used to control access to your data with access policies. The name of the column that represents the tenant ID. The tenant ID column's type. The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. A Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. The name of the column that represents the unique ID. Retries to set up the Data Pool identified by the given unique name. ### Arguments The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. The Account object. The Account's unique identifier. The Data Pool's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. The status of a Data Pool. * `CREATED`: The Data Pool has been created and will be set up soon. * `PENDING`: Propel is attempting to set up the Data Pool. * `LIVE`: The Data Pool is set up and serving data. Check its Syncs to monitor data ingestion. * `SETUP_FAILED`: The Data Pool setup failed. Check its Setup Tasks before re-attempting setup. * `CONNECTING` * `CONNECTED` * `BROKEN` * `PAUSING` * `PAUSED` * `DELETING`: Propel is deleting the Data Pool and all of its associated data. The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. A Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. The primary timestamp column's type. The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo The list of measures (numeric columns) in the Data Pool. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo A list of setup tasks performed on the Data Pool during its most recent setup attempt. The Data Pool Setup Task object. Data Pool Setup Tasks are executed when setting up your Data Pool. They ensure Propel will be able to sync records from your Data Source to your Data Pool. The exact Setup Tasks to perform vary by Data Source. For example, Data Pools pointing to a Snowflake-backed Data Sources will have their own specific Setup Tasks. The name of the Data Pool Setup Task to be performed. A description of the Data Pool Setup Task to be performed. The status of the Data Pool Setup Task (all setup tasks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataPoolSetupTaskStatus If the Data Pool Setup Task failed, this field includes a descriptive error message. See Error The time at which the Data Pool Setup Task was completed. Settings related to Data Pool syncing. Settings related to Data Pool syncing. Indicates whether syncing is enabled or disabled. See DataPoolSyncStatus The syncing interval. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. See DataPoolSyncInterval The date and time of the most recent Sync in UTC. The list of Syncs of the Data Pool. ### Arguments The filter to apply when listing the Syncs for a Data Pool. * `EMPTY`: Returns only Syncs with empty records. * `NOT_EMPTY`: Returns only Syncs that contain one or more records. * `ALL`: Returns all Syncs, regardless of whether they contain records or not. See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments Response returned by the validateExpression query for validating expressions in Custom Metrics. Returns whether the expression is valid or not with a reason explaining why. True if the expression is valid, false otherwise. The reason for why the expression is not valid in case it isn't, null otherwise. The Data Pool's table settings. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. See TableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The Data Pool's columns that participate in its PARTITION BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its PRIMARY KEY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its ORDER BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead deprecated: Refer to `setupTasks` instead The error object. The error code. The error message. The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead A Data Pool's tenant ID column. The tenant ID column is used to control access to your data with access policies. The name of the column that represents the tenant ID. The tenant ID column's type. The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. A Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. The name of the column that represents the unique ID. Extracts the schema from the table and updates the schema object. ### Arguments The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The result of a mutation which creates or modifies a Data Pool. If successful, an `DataPoolResponse` will be returned; otherwise, a `FailureResponse` will be returned. The result of a mutation which creates or modifies a Data Pool. The Data Pool which was created or modified. See DataPool The failure response object. The error that caused the failure. See Error Tests that Propel has access to the Data Pool's table in its corresponding Data Source and will be able to Sync data. Updates the status. ### Arguments The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The result of a mutation which creates or modifies a Data Pool. If successful, an `DataPoolResponse` will be returned; otherwise, a `FailureResponse` will be returned. The result of a mutation which creates or modifies a Data Pool. The Data Pool which was created or modified. See DataPool The failure response object. The error that caused the failure. See Error Deletes a Data Pool by ID and returns its ID if the Data Pool was deleted successfully. ### Arguments Deletes a Data Pool by unique name and returns its ID if the Data Pool was deleted successfully. ### Arguments Disables syncing of a Data Pool. ### Arguments The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. The Account object. The Account's unique identifier. The Data Pool's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. The status of a Data Pool. * `CREATED`: The Data Pool has been created and will be set up soon. * `PENDING`: Propel is attempting to set up the Data Pool. * `LIVE`: The Data Pool is set up and serving data. Check its Syncs to monitor data ingestion. * `SETUP_FAILED`: The Data Pool setup failed. Check its Setup Tasks before re-attempting setup. * `CONNECTING` * `CONNECTED` * `BROKEN` * `PAUSING` * `PAUSED` * `DELETING`: Propel is deleting the Data Pool and all of its associated data. The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. A Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. The primary timestamp column's type. The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo The list of measures (numeric columns) in the Data Pool. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo A list of setup tasks performed on the Data Pool during its most recent setup attempt. The Data Pool Setup Task object. Data Pool Setup Tasks are executed when setting up your Data Pool. They ensure Propel will be able to sync records from your Data Source to your Data Pool. The exact Setup Tasks to perform vary by Data Source. For example, Data Pools pointing to a Snowflake-backed Data Sources will have their own specific Setup Tasks. The name of the Data Pool Setup Task to be performed. A description of the Data Pool Setup Task to be performed. The status of the Data Pool Setup Task (all setup tasks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataPoolSetupTaskStatus If the Data Pool Setup Task failed, this field includes a descriptive error message. See Error The time at which the Data Pool Setup Task was completed. Settings related to Data Pool syncing. Settings related to Data Pool syncing. Indicates whether syncing is enabled or disabled. See DataPoolSyncStatus The syncing interval. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. See DataPoolSyncInterval The date and time of the most recent Sync in UTC. The list of Syncs of the Data Pool. ### Arguments The filter to apply when listing the Syncs for a Data Pool. * `EMPTY`: Returns only Syncs with empty records. * `NOT_EMPTY`: Returns only Syncs that contain one or more records. * `ALL`: Returns all Syncs, regardless of whether they contain records or not. See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments Response returned by the validateExpression query for validating expressions in Custom Metrics. Returns whether the expression is valid or not with a reason explaining why. True if the expression is valid, false otherwise. The reason for why the expression is not valid in case it isn't, null otherwise. The Data Pool's table settings. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. See TableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The Data Pool's columns that participate in its PARTITION BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its PRIMARY KEY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its ORDER BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead deprecated: Refer to `setupTasks` instead The error object. The error code. The error message. The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead A Data Pool's tenant ID column. The tenant ID column is used to control access to your data with access policies. The name of the column that represents the tenant ID. The tenant ID column's type. The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. A Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. The name of the column that represents the unique ID. Re-enables syncing of a Data Pool. ### Arguments The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. The Account object. The Account's unique identifier. The Data Pool's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. The status of a Data Pool. * `CREATED`: The Data Pool has been created and will be set up soon. * `PENDING`: Propel is attempting to set up the Data Pool. * `LIVE`: The Data Pool is set up and serving data. Check its Syncs to monitor data ingestion. * `SETUP_FAILED`: The Data Pool setup failed. Check its Setup Tasks before re-attempting setup. * `CONNECTING` * `CONNECTED` * `BROKEN` * `PAUSING` * `PAUSED` * `DELETING`: Propel is deleting the Data Pool and all of its associated data. The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. A Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. The primary timestamp column's type. The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo The list of measures (numeric columns) in the Data Pool. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo A list of setup tasks performed on the Data Pool during its most recent setup attempt. The Data Pool Setup Task object. Data Pool Setup Tasks are executed when setting up your Data Pool. They ensure Propel will be able to sync records from your Data Source to your Data Pool. The exact Setup Tasks to perform vary by Data Source. For example, Data Pools pointing to a Snowflake-backed Data Sources will have their own specific Setup Tasks. The name of the Data Pool Setup Task to be performed. A description of the Data Pool Setup Task to be performed. The status of the Data Pool Setup Task (all setup tasks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataPoolSetupTaskStatus If the Data Pool Setup Task failed, this field includes a descriptive error message. See Error The time at which the Data Pool Setup Task was completed. Settings related to Data Pool syncing. Settings related to Data Pool syncing. Indicates whether syncing is enabled or disabled. See DataPoolSyncStatus The syncing interval. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. See DataPoolSyncInterval The date and time of the most recent Sync in UTC. The list of Syncs of the Data Pool. ### Arguments The filter to apply when listing the Syncs for a Data Pool. * `EMPTY`: Returns only Syncs with empty records. * `NOT_EMPTY`: Returns only Syncs that contain one or more records. * `ALL`: Returns all Syncs, regardless of whether they contain records or not. See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments Response returned by the validateExpression query for validating expressions in Custom Metrics. Returns whether the expression is valid or not with a reason explaining why. True if the expression is valid, false otherwise. The reason for why the expression is not valid in case it isn't, null otherwise. The Data Pool's table settings. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. See TableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The Data Pool's columns that participate in its PARTITION BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its PRIMARY KEY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its ORDER BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead deprecated: Refer to `setupTasks` instead The error object. The error code. The error message. The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead A Data Pool's tenant ID column. The tenant ID column is used to control access to your data with access policies. The name of the column that represents the tenant ID. The tenant ID column's type. The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. A Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. The name of the column that represents the unique ID. Creates a new Count Metric from the given Data Pool and returns the newly created Metric (or an error message if creating the Metric fails). ### Arguments The fields for creating a new Count Metric. The Data Pool that powers this Metric. The Metric's unique name. If not specified, Propel will set the ID as unique name. The Metric's description. The Metric's Filters, in the form of SQL. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Filters are present, all records will be included. The Metric's Dimensions. Dimensions define the columns that will be available to filter the Metric at query time. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The Metric's Filters. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Filters are present, all records will be included. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The result of a mutation which creates or modifies a Metric. The Metric which was created or modified. The Metric object. A Metric is a business indicator measured over time. The Metric's unique identifier. The Metric's unique name. The Metric's description. The Metric's Account. See Account The Metric's Environment. See Environment The Metric's creation date and time in UTC. The Metric's last modification date and time in UTC. The Metric's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Metric's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool that powers this Metric. See DataPool The Metric's Dimensions. These Dimensions are available to Query Filters. See Dimension The Metric's timestamp, if any. This is the same as its Data Pool's timestamp, if any. See Dimension List the Boosters associated to the Metric. ### Arguments See BoosterConnection The Metric's type. The different Metric types determine how the values are calculated. See MetricType The settings for the Metric. The settings are specific to the Metric's type. See MetricSettings The Metric's measure. Access this from the Metric's `settings` object instead. deprecated: Use the Metric `settings` object instead. See Dimension Query the Metric in counter format. Returns the Metric's value for the given time range and filters. deprecated: Use the top-level `counter` query instead ### Arguments See CounterInput See CounterResponse Query the Metric in time series format. Returns arrays of timestamps and the Metric's values for the given time range and filters. deprecated: Use the top-level `timeSeries` query instead ### Arguments See TimeSeriesInput See TimeSeriesResponse Query the Metric in leaderboard format. Returns a table (array of rows) with the selected dimensions and the Metric's corresponding values for the given time range and filters. deprecated: Use the top-level `leaderboard` query instead ### Arguments See LeaderboardInput See LeaderboardResponse List the Policies associated to the Metric. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Whether or not access control is enabled for the Metric. deprecated: Use Data Pool Access Policies instead Creates a new Count Distinct Metric from the given Data Pool and returns the newly created Metric (or an error message if creating the Metric fails). ### Arguments The fields for creating a new Count Distinct Metric. The Data Pool that powers this Metric. The Metric's unique name. If not specified, Propel will set the ID as unique name. The Metric's description. The Metric's Filters, in the form of SQL. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Filters are present, all records will be included. The Metric's Dimensions. Dimensions define the columns that will be available to filter the Metric at query time. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The Dimension over which the count distinct operation is going to be performed. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The Metric's Filters. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Filters are present, all records will be included. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The result of a mutation which creates or modifies a Metric. The Metric which was created or modified. The Metric object. A Metric is a business indicator measured over time. The Metric's unique identifier. The Metric's unique name. The Metric's description. The Metric's Account. See Account The Metric's Environment. See Environment The Metric's creation date and time in UTC. The Metric's last modification date and time in UTC. The Metric's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Metric's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool that powers this Metric. See DataPool The Metric's Dimensions. These Dimensions are available to Query Filters. See Dimension The Metric's timestamp, if any. This is the same as its Data Pool's timestamp, if any. See Dimension List the Boosters associated to the Metric. ### Arguments See BoosterConnection The Metric's type. The different Metric types determine how the values are calculated. See MetricType The settings for the Metric. The settings are specific to the Metric's type. See MetricSettings The Metric's measure. Access this from the Metric's `settings` object instead. deprecated: Use the Metric `settings` object instead. See Dimension Query the Metric in counter format. Returns the Metric's value for the given time range and filters. deprecated: Use the top-level `counter` query instead ### Arguments See CounterInput See CounterResponse Query the Metric in time series format. Returns arrays of timestamps and the Metric's values for the given time range and filters. deprecated: Use the top-level `timeSeries` query instead ### Arguments See TimeSeriesInput See TimeSeriesResponse Query the Metric in leaderboard format. Returns a table (array of rows) with the selected dimensions and the Metric's corresponding values for the given time range and filters. deprecated: Use the top-level `leaderboard` query instead ### Arguments See LeaderboardInput See LeaderboardResponse List the Policies associated to the Metric. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Whether or not access control is enabled for the Metric. deprecated: Use Data Pool Access Policies instead Creates a new Sum Metric from the given Data Pool and returns the newly created Metric (or an error message if creating the Metric fails). ### Arguments The fields for creating a new Sum Metric. The Data Pool that powers this Metric. The Metric's unique name. If not specified, Propel will set the ID as unique name. The Metric's description. The Metric's Filters, in the form of SQL. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Filters are present, all records will be included. The Metric's Dimensions. Dimensions define the columns that will be available to filter the Metric at query time. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The column to be summed. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The Metric's Filters. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Filters are present, all records will be included. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The result of a mutation which creates or modifies a Metric. The Metric which was created or modified. The Metric object. A Metric is a business indicator measured over time. The Metric's unique identifier. The Metric's unique name. The Metric's description. The Metric's Account. See Account The Metric's Environment. See Environment The Metric's creation date and time in UTC. The Metric's last modification date and time in UTC. The Metric's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Metric's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool that powers this Metric. See DataPool The Metric's Dimensions. These Dimensions are available to Query Filters. See Dimension The Metric's timestamp, if any. This is the same as its Data Pool's timestamp, if any. See Dimension List the Boosters associated to the Metric. ### Arguments See BoosterConnection The Metric's type. The different Metric types determine how the values are calculated. See MetricType The settings for the Metric. The settings are specific to the Metric's type. See MetricSettings The Metric's measure. Access this from the Metric's `settings` object instead. deprecated: Use the Metric `settings` object instead. See Dimension Query the Metric in counter format. Returns the Metric's value for the given time range and filters. deprecated: Use the top-level `counter` query instead ### Arguments See CounterInput See CounterResponse Query the Metric in time series format. Returns arrays of timestamps and the Metric's values for the given time range and filters. deprecated: Use the top-level `timeSeries` query instead ### Arguments See TimeSeriesInput See TimeSeriesResponse Query the Metric in leaderboard format. Returns a table (array of rows) with the selected dimensions and the Metric's corresponding values for the given time range and filters. deprecated: Use the top-level `leaderboard` query instead ### Arguments See LeaderboardInput See LeaderboardResponse List the Policies associated to the Metric. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Whether or not access control is enabled for the Metric. deprecated: Use Data Pool Access Policies instead Creates a new Average Metric from the given Data Pool and returns the newly created Metric (or an error message if creating the Metric fails). ### Arguments The fields for creating a new Average Metric. The Data Pool that powers this Metric. The Metric's unique name. The Metric's description. The Metric's Filters, in the form of SQL. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Filters are present, all records will be included. The Metric's Dimensions. Dimensions define the columns that will be available to filter the Metric at query time. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The column to be averaged. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The Metric's Filters. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Filters are present, all records will be included. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The result of a mutation which creates or modifies a Metric. The Metric which was created or modified. The Metric object. A Metric is a business indicator measured over time. The Metric's unique identifier. The Metric's unique name. The Metric's description. The Metric's Account. See Account The Metric's Environment. See Environment The Metric's creation date and time in UTC. The Metric's last modification date and time in UTC. The Metric's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Metric's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool that powers this Metric. See DataPool The Metric's Dimensions. These Dimensions are available to Query Filters. See Dimension The Metric's timestamp, if any. This is the same as its Data Pool's timestamp, if any. See Dimension List the Boosters associated to the Metric. ### Arguments See BoosterConnection The Metric's type. The different Metric types determine how the values are calculated. See MetricType The settings for the Metric. The settings are specific to the Metric's type. See MetricSettings The Metric's measure. Access this from the Metric's `settings` object instead. deprecated: Use the Metric `settings` object instead. See Dimension Query the Metric in counter format. Returns the Metric's value for the given time range and filters. deprecated: Use the top-level `counter` query instead ### Arguments See CounterInput See CounterResponse Query the Metric in time series format. Returns arrays of timestamps and the Metric's values for the given time range and filters. deprecated: Use the top-level `timeSeries` query instead ### Arguments See TimeSeriesInput See TimeSeriesResponse Query the Metric in leaderboard format. Returns a table (array of rows) with the selected dimensions and the Metric's corresponding values for the given time range and filters. deprecated: Use the top-level `leaderboard` query instead ### Arguments See LeaderboardInput See LeaderboardResponse List the Policies associated to the Metric. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Whether or not access control is enabled for the Metric. deprecated: Use Data Pool Access Policies instead Creates a new Min Metric from the given Data Pool and returns the newly created Metric (or an error message if creating the Metric fails). ### Arguments The fields for creating a new Minimum (Min) Metric. The Data Pool that powers this Metric. The Metric's unique name. If not specified, Propel will set the ID as unique name. The Metric's description. The Metric's Filters, in the form of SQL. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Filters are present, all records will be included. The Metric's Dimensions. Dimensions define the columns that will be available to filter the Metric at query time. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The Metric's Filters. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Filters are present, all records will be included. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The result of a mutation which creates or modifies a Metric. The Metric which was created or modified. The Metric object. A Metric is a business indicator measured over time. The Metric's unique identifier. The Metric's unique name. The Metric's description. The Metric's Account. See Account The Metric's Environment. See Environment The Metric's creation date and time in UTC. The Metric's last modification date and time in UTC. The Metric's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Metric's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool that powers this Metric. See DataPool The Metric's Dimensions. These Dimensions are available to Query Filters. See Dimension The Metric's timestamp, if any. This is the same as its Data Pool's timestamp, if any. See Dimension List the Boosters associated to the Metric. ### Arguments See BoosterConnection The Metric's type. The different Metric types determine how the values are calculated. See MetricType The settings for the Metric. The settings are specific to the Metric's type. See MetricSettings The Metric's measure. Access this from the Metric's `settings` object instead. deprecated: Use the Metric `settings` object instead. See Dimension Query the Metric in counter format. Returns the Metric's value for the given time range and filters. deprecated: Use the top-level `counter` query instead ### Arguments See CounterInput See CounterResponse Query the Metric in time series format. Returns arrays of timestamps and the Metric's values for the given time range and filters. deprecated: Use the top-level `timeSeries` query instead ### Arguments See TimeSeriesInput See TimeSeriesResponse Query the Metric in leaderboard format. Returns a table (array of rows) with the selected dimensions and the Metric's corresponding values for the given time range and filters. deprecated: Use the top-level `leaderboard` query instead ### Arguments See LeaderboardInput See LeaderboardResponse List the Policies associated to the Metric. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Whether or not access control is enabled for the Metric. deprecated: Use Data Pool Access Policies instead Creates a new Max Metric from the given Data Pool and returns the newly created Metric (or an error message if creating the Metric fails). ### Arguments The fields for creating a new Maximum (Max) Metric. The Data Pool that powers this Metric. The Metric's unique name. If not specified, Propel will set the ID as unique name. The Metric's description. The Metric's Filters, in the form of SQL. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Filters are present, all records will be included. The Metric's Dimensions. Dimensions define the columns that will be available to filter the Metric at query time. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The column to calculate the maximum from. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The Metric's Filters. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Filters are present, all records will be included. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The result of a mutation which creates or modifies a Metric. The Metric which was created or modified. The Metric object. A Metric is a business indicator measured over time. The Metric's unique identifier. The Metric's unique name. The Metric's description. The Metric's Account. See Account The Metric's Environment. See Environment The Metric's creation date and time in UTC. The Metric's last modification date and time in UTC. The Metric's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Metric's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool that powers this Metric. See DataPool The Metric's Dimensions. These Dimensions are available to Query Filters. See Dimension The Metric's timestamp, if any. This is the same as its Data Pool's timestamp, if any. See Dimension List the Boosters associated to the Metric. ### Arguments See BoosterConnection The Metric's type. The different Metric types determine how the values are calculated. See MetricType The settings for the Metric. The settings are specific to the Metric's type. See MetricSettings The Metric's measure. Access this from the Metric's `settings` object instead. deprecated: Use the Metric `settings` object instead. See Dimension Query the Metric in counter format. Returns the Metric's value for the given time range and filters. deprecated: Use the top-level `counter` query instead ### Arguments See CounterInput See CounterResponse Query the Metric in time series format. Returns arrays of timestamps and the Metric's values for the given time range and filters. deprecated: Use the top-level `timeSeries` query instead ### Arguments See TimeSeriesInput See TimeSeriesResponse Query the Metric in leaderboard format. Returns a table (array of rows) with the selected dimensions and the Metric's corresponding values for the given time range and filters. deprecated: Use the top-level `leaderboard` query instead ### Arguments See LeaderboardInput See LeaderboardResponse List the Policies associated to the Metric. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Whether or not access control is enabled for the Metric. deprecated: Use Data Pool Access Policies instead Creates a new Custom Metric from the given Data Pool and returns the newly created Metric (or an error message if creating the Metric fails). ### Arguments The fields for creating a new Custom Metric. The Data Pool that powers this Metric. The Metric's unique name. If not specified, Propel will set the ID as unique name. The Metric's description. The Metric's Filters, in the form of SQL. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Filters are present, all records will be included. The Metric's Dimensions. Dimensions define the columns that will be available to filter the Metric at query time. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The expression that defines the aggregation function for this Metric. The Metric's Filters. Metric Filters allow defining a Metric with a subset of records from the given Data Pool. If no Filters are present, all records will be included. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The result of a mutation which creates or modifies a Metric. The Metric which was created or modified. The Metric object. A Metric is a business indicator measured over time. The Metric's unique identifier. The Metric's unique name. The Metric's description. The Metric's Account. See Account The Metric's Environment. See Environment The Metric's creation date and time in UTC. The Metric's last modification date and time in UTC. The Metric's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Metric's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool that powers this Metric. See DataPool The Metric's Dimensions. These Dimensions are available to Query Filters. See Dimension The Metric's timestamp, if any. This is the same as its Data Pool's timestamp, if any. See Dimension List the Boosters associated to the Metric. ### Arguments See BoosterConnection The Metric's type. The different Metric types determine how the values are calculated. See MetricType The settings for the Metric. The settings are specific to the Metric's type. See MetricSettings The Metric's measure. Access this from the Metric's `settings` object instead. deprecated: Use the Metric `settings` object instead. See Dimension Query the Metric in counter format. Returns the Metric's value for the given time range and filters. deprecated: Use the top-level `counter` query instead ### Arguments See CounterInput See CounterResponse Query the Metric in time series format. Returns arrays of timestamps and the Metric's values for the given time range and filters. deprecated: Use the top-level `timeSeries` query instead ### Arguments See TimeSeriesInput See TimeSeriesResponse Query the Metric in leaderboard format. Returns a table (array of rows) with the selected dimensions and the Metric's corresponding values for the given time range and filters. deprecated: Use the top-level `leaderboard` query instead ### Arguments See LeaderboardInput See LeaderboardResponse List the Policies associated to the Metric. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Whether or not access control is enabled for the Metric. deprecated: Use Data Pool Access Policies instead Modifies a Metric by ID with the provided unique name, description, and Dimensions. If any of the optional arguments are omitted, those properties will be unchanged on the Metric. ### Arguments The fields for modifying a Metric. The ID of the Metric to modify. The Metric's new unique name. The Metric's new description. The Metric's new Dimensions. Used to add or remove Dimensions. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The Metric's new Filters, in the form of SQL. Used to add or remove Metric Filters. Enables or disables access control for the Metric. The Metric's new Filters. Used to add or remove Metric Filters. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The result of a mutation which creates or modifies a Metric. The Metric which was created or modified. The Metric object. A Metric is a business indicator measured over time. The Metric's unique identifier. The Metric's unique name. The Metric's description. The Metric's Account. See Account The Metric's Environment. See Environment The Metric's creation date and time in UTC. The Metric's last modification date and time in UTC. The Metric's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Metric's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool that powers this Metric. See DataPool The Metric's Dimensions. These Dimensions are available to Query Filters. See Dimension The Metric's timestamp, if any. This is the same as its Data Pool's timestamp, if any. See Dimension List the Boosters associated to the Metric. ### Arguments See BoosterConnection The Metric's type. The different Metric types determine how the values are calculated. See MetricType The settings for the Metric. The settings are specific to the Metric's type. See MetricSettings The Metric's measure. Access this from the Metric's `settings` object instead. deprecated: Use the Metric `settings` object instead. See Dimension Query the Metric in counter format. Returns the Metric's value for the given time range and filters. deprecated: Use the top-level `counter` query instead ### Arguments See CounterInput See CounterResponse Query the Metric in time series format. Returns arrays of timestamps and the Metric's values for the given time range and filters. deprecated: Use the top-level `timeSeries` query instead ### Arguments See TimeSeriesInput See TimeSeriesResponse Query the Metric in leaderboard format. Returns a table (array of rows) with the selected dimensions and the Metric's corresponding values for the given time range and filters. deprecated: Use the top-level `leaderboard` query instead ### Arguments See LeaderboardInput See LeaderboardResponse List the Policies associated to the Metric. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Whether or not access control is enabled for the Metric. deprecated: Use Data Pool Access Policies instead Migrates a Metric from one Data Pool to another. ### Arguments The fields for migrating a Metric's Data Pool. The Metric that is going to be migrated. The DataPool to which the Metric is going to be migrated. The Metric object. A Metric is a business indicator measured over time. The Metric's unique identifier. The Metric's unique name. The Metric's description. The Metric's Account. The Account object. The Account's unique identifier. The Metric's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Metric's creation date and time in UTC. The Metric's last modification date and time in UTC. The Metric's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Metric's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool that powers this Metric. See DataPool The Metric's Dimensions. These Dimensions are available to Query Filters. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats See DimensionStatistics The Metric's timestamp, if any. This is the same as its Data Pool's timestamp, if any. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats See DimensionStatistics List the Boosters associated to the Metric. ### Arguments See BoosterConnection The Metric's type. The different Metric types determine how the values are calculated. The available Metric types. * `COUNT`: Counts the number of records that matches the Metric Filters. For time series, it will count the values for each time granularity. * `SUM`: Sums the values of the specified column for every record that matches the Metric Filters. For time series, it will sum the values for each time granularity. * `COUNT_DISTINCT`: Counts the number of distinct values in the specified column for every record that matches the Metric Filters. For time series, it will count the distinct values for each time granularity. * `AVERAGE`: Averages the values of the specified column for every record that matches the Metric Filters. For time series, it will average the values for each time granularity. * `MIN`: Selects the minimum value of the specified column for every record that matches the Metric Filters. For time series, it will select the minimum value for each time granularity. * `MAX`: Selects the maximum value of the specified column for every record that matches the Metric Filters. For time series, it will select the maximum value for each time granularity. * `CUSTOM`: Aggregates values based on the provided custom expression. The settings for the Metric. The settings are specific to the Metric's type. A Metric's settings, depending on its type. See CountMetricSettings See SumMetricSettings See CountDistinctMetricSettings See AverageMetricSettings See MinMetricSettings See MaxMetricSettings See CustomMetricSettings The Metric's measure. Access this from the Metric's `settings` object instead. deprecated: Use the Metric `settings` object instead. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats See DimensionStatistics Query the Metric in counter format. Returns the Metric's value for the given time range and filters. deprecated: Use the top-level `counter` query instead ### Arguments The fields for querying a Metric in counter format. A Metric's counter query returns a single value over a given time range. The Metric to query. You can query a pre-configured Metric by ID or name, or you can query an ad hoc Metric that you define inline. See MetricInput The time range for calculating the counter. See TimeRangeInput The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The Query Filters to apply before retrieving the counter data, in the form of SQL. If no Query Filters are provided, all data is included. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the counter data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead See FilterInput The counter response object. It contains a single Metric value for the given time range and Query Filters. The value of the counter. The Query statistics and metadata. See QueryInfo Query the Metric in time series format. Returns arrays of timestamps and the Metric's values for the given time range and filters. deprecated: Use the top-level `timeSeries` query instead ### Arguments The fields for querying a Metric in time series format. A Metric's time series query returns the values over a given time range aggregated by a given time granularity; day, month, or year, for example. The Metric to Query. It can be a pre-created one or it can be inlined here. See MetricInput The time range for calculating the time series. See TimeRangeInput The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The time granularity (hour, day, month, etc.) to aggregate the Metric values by. See TimeSeriesGranularity The Query Filters to apply before retrieving the time series data, in the form of SQL. If no Query Filters are provided, all data is included. Columns to group by. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the time series data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead See FilterInput The time series response object. It contains an array of time series labels and an array of Metric values for the given time range and Query Filters. The time series labels. The time series values. The time series values for each group in `groupBy`, if specified. See TimeSeriesResponseGroup The Query statistics and metadata. See QueryInfo Query the Metric in leaderboard format. Returns a table (array of rows) with the selected dimensions and the Metric's corresponding values for the given time range and filters. deprecated: Use the top-level `leaderboard` query instead ### Arguments The fields for querying a Metric in leaderboard format. A Metric's leaderboard query returns an ordered table of Dimension and Metric values over a given time range. The Metric to query. You can query a pre-configured Metric by ID or name, or you can query an ad hoc Metric that you define inline. See MetricInput The time range for calculating the leaderboard. See TimeRangeInput The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". One or many Dimensions to group the Metric values by. Typically, Dimensions in a leaderboard are what you want to compare and rank. See DimensionInput The sort order of the rows. It can be ascending (`ASC`) or descending (`DESC`) order. Defaults to descending (`DESC`) order when not provided. See Sort The number of rows to be returned. It can be a number between 1 and 1,000. The Query Filters to apply before retrieving the leaderboard data, in the form of SQL. If no Query Filters are provided, all data is included. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the leaderboard data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead See FilterInput The leaderboard response object. It contains an array of headers and a table (array of rows) with the selected Dimensions and corresponding Metric values for the given time range and Query Filters. The table headers. It contains the Dimension and Metric names. An ordered array of rows. Each row contains the Dimension values and the corresponding Metric value. A Dimension value can be empty. A Metric value will never be empty. The Query statistics and metadata. See QueryInfo List the Policies associated to the Metric. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Whether or not access control is enabled for the Metric. deprecated: Use Data Pool Access Policies instead Deletes a Metric by ID and returns its ID if the Metric was deleted successfully. ### Arguments Deletes a Metric by unique name and returns its ID if the Metric was deleted successfully. ### Arguments Creates a new Booster for the given Metric and returns the newly created Booster. A Booster significantly improves the query performance for a Metric. ### Arguments The fields for creating a new Booster. Boosters can be understood as an aggregating index. The index is formed from left to right as follows: 1. The Data Pool's Tenant ID column (if present) 2. Metric Filter columns (if present) 3. Query Filter Dimensions (see `dimensions`) 4. The Data Pool's timestamp column The Booster's Metric. Dimensions to include in the Booster. Follow these guidelines when specifying Dimensions: 1. Specify Dimensions in descending order of importance for filtering and in ascending order of cardinality. 2. Take into consideration hierarchical relationships as well (for example, a "country" Dimension should appear before a "state" Dimension). The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The result of a mutation which creates or modifies a Booster. The Booster which was created or modified. Boosters allow you to optimize Metric Queries for a subset of commonly used Dimensions. A Metric can have one or many Boosters to optimize for the different Query patterns. Boosters can be understood as an aggregating index. The index is formed from left to right as follows: 1. The Data Pool's Tenant ID column (if present) 2. Metric Filter columns (if present) 3. Query Filter Dimensions (see `dimensions`) 4. The Data Pool's timestamp column The Booster's unique identifier. The Booster's Account. See Account The Booster's Environment. See Environment The Booster's creation date and time in UTC. The Booster's last modification date and time in UTC. The Booster's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Booster's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Metric this Booster is associated to. See Metric The status of the Booster (once LIVE it will be available for speeding up Metric queries). See BoosterStatus If the Booster fails during the optimization process, this field includes a descriptive error message. See Error When the Booster is OPTIMIZING, this represents its progress as a number from 0 to 1. In all other states, progress is null. Dimensions included in the Booster. See Dimension The number of records in the Booster. The amount of storage in terabytes used by the Booster. Deletes a Booster by ID and then returns the same ID if the Booster was deleted successfully. A Booster significantly improves the query performance for a Metric. ### Arguments Schedules a new Deletion Job on the specified Data Pool. ### Arguments The fields for creating a Deletion Job. The Data Pool that is going to get the data deleted The filters that will be used for deleting data, in the form of SQL. Data matching these filters will be deleted. The list of filters that will be used for deleting data. Data matching these filters will be deleted. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The response returned by the Deletion Job. The Deletion Job that was just created. Deletion Job scheduled for a specific Data Pool. The Deletion Job represents the asynchronous process of deleting data given some filters inside a Data Pool. It tracks the deletion process until it is finished, showing the progress and the outcome when it is finished. The Deletion Job's ID. The Deletion Job's creation date and time in UTC. Who created the Deletion Job. The Deletion Job's last modification date and time in UTC. Who last modified the Deletion Job. Account to which the Deletion Job belongs. See Account Environment to which the Deletion Job belongs. See Environment The Data Pool whose records will be deleted by the Deletion Job. See DataPool The current Deletion Job's status. See JobStatus The filters that will be used for deleting data, in the form of SQL. Data matching the filters will be deleted. The error that occurred while deleting data, if any. See Error The current progress of the Deletion Job, from 0.0 to 1.0. The time at which the Deletion Job started. The time at which the Deletion Job succeeded. The time at which the Deletion Job failed. The list of filters that will be used for deleting data. Data matching the filters will be deleted. deprecated: Use `filterSql` instead See Filter Schedules a new AddColumnToDataPoolJob on the specified Data Pool. ### Arguments The fields for creating an Add Column Job. The Data Pool to which the column will be added. Name of the new column. Type of the new column. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. The ClickHouse type of the new column when `columnType` is set to `CLICKHOUSE`. JSON property to which the new column corresponds. The response returned by the Add Column Job. The AddColumnToDataPool Job that was just created. AddColumnToDataPoolJob scheduled for a specific Data Pool. The Add Column Job represents the asynchronous process of adding a column, given its name and type, to a Data Pool. It tracks the process of adding a column until it is finished, showing the progress and the outcome when it is finished. The AddColumnToDataPoolJob's ID. The AddColumnToDataPoolJob's creation date and time in UTC. Who created the AddColumnToDataPoolJob. The AddColumnToDataPoolJob's last modification date and time in UTC. Who modified the AddColumnToDataPoolJob last. Account to which the AddColumnToDataPoolJob belongs. See Account Environment to which the AddColumnToDataPoolJob belongs. See Environment The Data Pool to which a column will be added by the Job. See DataPool The current AddColumnToDataPoolJob's status. See JobStatus Name of the new column. Type of the new column. See ColumnType The ClickHouse type of the new column when `columnType` is set to `CLICKHOUSE`. JSON property to which the new column corresponds. The error that occurred while adding the column data, if any. See Error The current progress of the AddColumnToDataPool Job, from 0.0 to 1.0. The time at which the AddColumnToDataPool Job started. The time at which the AddColumnToDataPool Job succeeded. The time at which the AddColumnToDataPool Job failed. Schedules a new UpdateDataPoolRecords Job on the specified Data Pool. ### Arguments The fields for creating an Update Data Pool Records Job. The Data Pool that is going to get its records updated. The filters that will be used for updating records, in the form of SQL. Records matching these filters will be updated. Describes how the job will update the records. The fields for creating an Update Data Pool Records Job. ``` { "column": "status", "expression": "'completed'" } { "column": "counter", "expression": "counter + 1" } { "column": "full_name", "expression": "concat(first_name, ' ', last_name)" } ``` The name of the column to update. The value to which the column will be updated. Once evaluated, it should be of the same data type as the column. The list of filters that will be used for updating records. Records matching these filters will be updated. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The response returned by the Update Data Pool Records Job. The UpdateDataPoolRecords Job that was just created. UpdateDataPoolRecords Job scheduled for a specific Data Pool. The Update Data Pool Records Job represents the asynchronous process of updating records given some filters, inside a Data Pool. It tracks the process of updating records until it is finished, showing the progress and the outcome when it is finished. The UpdateDataPoolRecords Job's ID The UpdateDataPoolRecords Job's creation date and time in UTC Who created the UpdateDataPoolRecords Job The UpdateDataPoolRecords Job's last modification date and time in UTC Who last modified the UpdateDataPoolRecords Job Account to which the UpdateDataPoolRecords Job belongs See Account Environment to which the UpdateDataPoolRecords Job belongs See Environment The Data Pool whose records will be updated by the UpdateDataPoolRecords Job See DataPool The current UpdateDataPoolRecords Job's status See JobStatus The filters that will be used for updating data, in the form of SQL. Data matching the filters will be updated. Describes how the job will update the records. See UpdateDataPoolRecordsJobSetColumn The error that occurred while updating data, if any. See Error The current progress of the UpdateDataPoolRecords Job, from 0.0 to 1.0. The time at which the UpdateDataPoolRecords Job started. The time at which the UpdateDataPoolRecords Job succeeded. The time at which the UpdateDataPoolRecords Job failed. The list of filters that will be used for updating data. Data matching the filters will be updated. deprecated: Use `filterSql` instead See Filter Manually trigger a Sync for a Data Pool. ### Arguments The Sync object. This represents the process of syncing data from your Data Source (for example, a Snowflake data warehouse) to your Data Pool. The Sync's unique identifier. The Sync's Account. The Account object. The Account's unique identifier. The Sync's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Sync's creation date and time in UTC. The Sync's last modification date and time in UTC. The Sync's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Sync's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Sync's Data Pool. See DataPool The Sync's Data Pool's Data Source. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error The number of new, updated, and deleted records contained within the Sync, if known. This excludes filtered records. The (compressed) size of the Sync, in bytes, if known. The status of the Sync (all Syncs begin as SYNCING before transitioning to SUCCEEDED or FAILED). The status of a Sync. * `SYNCING`: Propel is actively syncing records contained within the Sync. * `SUCCEEDED`: The Sync succeeded. Propel successfully synced all records contained within the Sync. * `FAILED`: The Sync failed. Propel failed to sync some or all records contained within the Sync. * `DELETING`: Propel is deleting the Sync. The time at which the Sync started. The time at which the Sync succeeded. The time at which the Sync failed. If the Sync failed, this represents the reason the Sync failed. The error object. The error code. The error message. The number of new records contained within the Sync, if known. This excludes filtered records. deprecated: All records are considered to be processed; see `processedRecords` instead The number of updated records contained within the Sync, if known. This excludes filtered records. deprecated: All records are considered to be processed; see `processedRecords` instead The number of deleted records contained within the Sync, if known. This excludes filtered records. deprecated: All records are considered to be processed; see `processedRecords` instead The number of filtered records contained within the Sync, due to issues such as a missing timestamp Dimension, if any are known to be invalid. deprecated: All records are considered to be processed; see `processedRecords` instead Manually trigger a re-Sync for a Data Pool. ### Arguments The Sync object. This represents the process of syncing data from your Data Source (for example, a Snowflake data warehouse) to your Data Pool. The Sync's unique identifier. The Sync's Account. The Account object. The Account's unique identifier. The Sync's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Sync's creation date and time in UTC. The Sync's last modification date and time in UTC. The Sync's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Sync's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Sync's Data Pool. See DataPool The Sync's Data Pool's Data Source. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error The number of new, updated, and deleted records contained within the Sync, if known. This excludes filtered records. The (compressed) size of the Sync, in bytes, if known. The status of the Sync (all Syncs begin as SYNCING before transitioning to SUCCEEDED or FAILED). The status of a Sync. * `SYNCING`: Propel is actively syncing records contained within the Sync. * `SUCCEEDED`: The Sync succeeded. Propel successfully synced all records contained within the Sync. * `FAILED`: The Sync failed. Propel failed to sync some or all records contained within the Sync. * `DELETING`: Propel is deleting the Sync. The time at which the Sync started. The time at which the Sync succeeded. The time at which the Sync failed. If the Sync failed, this represents the reason the Sync failed. The error object. The error code. The error message. The number of new records contained within the Sync, if known. This excludes filtered records. deprecated: All records are considered to be processed; see `processedRecords` instead The number of updated records contained within the Sync, if known. This excludes filtered records. deprecated: All records are considered to be processed; see `processedRecords` instead The number of deleted records contained within the Sync, if known. This excludes filtered records. deprecated: All records are considered to be processed; see `processedRecords` instead The number of filtered records contained within the Sync, due to issues such as a missing timestamp Dimension, if any are known to be invalid. deprecated: All records are considered to be processed; see `processedRecords` instead Creates a new Materialized View. Returns the newly created Materialized View (or an error message if creating the Materialized View fails). ### Arguments The fields for creating a Materialized View. The Materialized View's unique name. If not specified, Propel will set the ID as the unique name. The Materialized View's description. The SQL that the Materialized View will execute. By default, a destination Data Pool with default settings will be created for the Materialized View; however, you can customize the destination Data Pool (or point to an existing Data Pool), by setting this field. Use this to target an existing Data Pool or the engine settings of a new Data Pool. The fields for targeting an existing Data Pool or a new Data Pool. If specified, the Materialized View will target an existing Data Pool. Ensure the Data Pool's schema is compatible with your Materialized View's SQL statement. See DataPoolInput If specified, the Materialized View will create and target a new Data Pool. You can further customize the new Data Pool's engine settings. See CreateMaterializedViewDestinationNewDataPoolInput By default, a Materialized View only applies to records added after its creation. This option allows to backfill all the data that was present before the Materialized View creation. Whether historical data should be backfilled or not Defines the order in which historical data is backfilled. Defaults to `OLDEST_FIRST` if not specified. See PartitionOrder The result of a mutation which creates or modifies a Materialized View. The Materialized View which was created or modified. The Materialized View's unique identifier. The Materialized View's unique name. The Materialized View's description. The Materialized View's Account. See Account The Materialized View's Environment. See Environment The Materialized View's creation date and time in UTC. The Materialized View's last modification date and time in UTC. The Materialized View's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Materialized View's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The SQL that the Materialized View executes. The Materialized View's destination (AKA "target") Data Pool. See DataPool The Materialized View's source Data Pool. See DataPool Other Data Pools queried by the Materialized View. See DataPool Modifies a Materialized View. If any of the optional arguments are omitted, those properties will be unchanged on the Materialized View. ### Arguments The fields for modifying a Materialized View. The ID of the Materialized View to modify. The Materialized View's new unique name. The Materialized View's new description. The result of a mutation which creates or modifies a Materialized View. The Materialized View which was created or modified. The Materialized View's unique identifier. The Materialized View's unique name. The Materialized View's description. The Materialized View's Account. See Account The Materialized View's Environment. See Environment The Materialized View's creation date and time in UTC. The Materialized View's last modification date and time in UTC. The Materialized View's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Materialized View's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The SQL that the Materialized View executes. The Materialized View's destination (AKA "target") Data Pool. See DataPool The Materialized View's source Data Pool. See DataPool Other Data Pools queried by the Materialized View. See DataPool Deletes a Materialized View and returns its ID if the Materialized View was deleted successfully. Note that deleting a Materialized View does not delete its target Data Pool. If you want to delete its target Data Pool, you must use the `deleteDataPool` mutation. ### Arguments Creates a new Amazon Data Firehose Data Source from the given settings. Returns the newly created Data Source (or an error message if creating the Data Source fails). ### Arguments The Amazon Data Firehose Data Source's connection settings The Amazon Data Firehose Data Source's connection settings. Enables or disables access control for the Data Pool. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. HTTP basic access authentication credentials. You must configure these same credentials to be included in the `X-Amz-Firehose-Access-Key` header when Amazon Data Firehose issues requests to its custom HTTP endpoint. See HttpBasicAuthInput Additional columns for the table in Propel. See AmazonDataFirehoseDataSourceColumnInput Override the Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse, and a default will be chosen based on the Data Pool's `timestamp` value, if any. You can override these defaults in order to specify a custom table engine, custom ORDER BY, etc. See TableSettingsInput The primary timestamp column, if any. The Amazon Data Firehose Data Source's description. The Amazon Data Firehose Data Source's unique name. If not specified, Propel will set the ID as unique name. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error Modifies the Data Source by the ID or unique name provided with the given unique name, description, and connection settings. If any of the optional arguments are omitted, those properties will be unchanged on the Data Source. ### Arguments The Amazon Data Firehose Data Source's new connection settings. If not provided this property will not be modified. The Amazon Data Firehose Data Source's connection settings. HTTP basic access authentication credentials. You must configure these same credentials to be included in the `X-Amz-Firehose-Access-Key` header when Amazon Data Firehose issues requests to its custom HTTP endpoint. If not provided this property will not be modified. See HttpBasicAuthInput The Amazon Data Firehose Data Source's new description. If not provided this property will not be modified. The ID or unique name of the Amazon Data Firehose Data Source to modify. The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The Amazon Data Firehose Data Source's new unique name. If not provided this property will not be modified. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error Creates a new Amazon DynamoDB Data Source from the given settings. Returns the newly created Data Source (or an error message if creating the Data Source fails). ### Arguments The Amazon DynamoDB Data Source's connection settings The Amazon DynamoDB Data Source's connection settings. Enables or disables access control for the Data Pool. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. HTTP basic access authentication credentials. You must configure these same credentials to be included in the `X-Amz-Firehose-Access-Key` header when Amazon Data Firehose transmits records from your DynamoDB table to its custom HTTP endpoint. See HttpBasicAuthInput Additional columns for the table in Propel. See AmazonDynamoDBDataSourceColumnInput Override the Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse, and a default will be chosen based on the Data Pool's `timestamp` value, if any. You can override these defaults in order to specify a custom table engine, custom ORDER BY, etc. See TableSettingsInput The primary timestamp column, if any. The Amazon DynamoDB Data Source's description. The Amazon DynamoDB Data Source's unique name. If not specified, Propel will set the ID as unique name. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error Modifies the Data Source by the ID or unique name provided with the given unique name, description, and connection settings. If any of the optional arguments are omitted, those properties will be unchanged on the Data Source. ### Arguments The Amazon DynamoDB Data Source's new connection settings. If not provided this property will not be modified. The Amazon DynamoDB Data Source's connection settings. HTTP basic access authentication credentials. You must configure these same credentials to be included in the `X-Amz-Firehose-Access-Key` header when Amazon Data Firehose transmits records from your DynamoDB table to its custom HTTP endpoint. If not provided this property will not be modified. See HttpBasicAuthInput The Amazon DynamoDB Data Source's new description. If not provided this property will not be modified. The ID or unique name of the Amazon DynamoDB Data Source to modify. The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The Amazon DynamoDB Data Source's new unique name. If not provided this property will not be modified. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error This mutation creates a new ClickHouse Data Source. The mutation returns the newly created Data Source (or an error message if creating the Data Source fails). ### Arguments The ClickHouse Data Source's connection settings The ClickHouse Data Source connection settings. Which database to connect to The password for the provided user The URL where the ClickHouse host is listening to HTTP\[S] connections The user for authenticating against the ClickHouse host The ClickHouse Data Source's description. The ClickHouse Data Source's unique name. If not specified, Propel will set the ID as unique name. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error This mutation selects a Data Source by its ID or unique name and modifies it to have the given unique name, description, and connection settings. If any of the optional arguments are omitted, those properties will be unchanged on the Data Source. ### Arguments The ClickHouse Data Source's new connection settings. If not provided this property will not be modified. The ClickHouse Data Source connection settings. Which database to connect to If not provided this property will not be modified. The password for the provided user If not provided this property will not be modified. The URL where the ClickHouse host is listening to HTTP\[S] connections If not provided this property will not be modified. The user for authenticating against the ClickHouse host If not provided this property will not be modified. The ClickHouse Data Source's new description. If not provided this property will not be modified. The ID or unique name of the ClickHouse Data Source to modify. The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The ClickHouse Data Source's new unique name. If not provided this property will not be modified. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error Creates a new HTTP Data Source from the given settings. Returns the newly created Data Source (or an error message if creating the Data Source fails). ### Arguments The HTTP Data Source's connection settings The HTTP Data Source connection settings. The HTTP Basic authentication settings for uploading new data. If this parameter is not provided, anyone with the URL to your tables will be able to upload data. While it's OK to test without HTTP Basic authentication, we recommend enabling it. See HttpBasicAuthInput The HTTP Data Source's tables. See HttpDataSourceTableInput The HTTP Data Source's description. The HTTP Data Source's unique name. If not specified, Propel will set the ID as unique name. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error This mutation selects a Data Source by its ID or unique name and modifies it to have the given unique name, description, and connection settings. If any of the optional arguments are omitted, those properties will be unchanged on the Data Source. ### Arguments The HTTP Data Source's new connection settings. If not provided this property will not be modified. The HTTP Data Source connection settings. The HTTP Basic authentication settings for uploading new data. If this parameter is not provided, anyone with the URL to your tables will be able to upload data. While it's OK to test without HTTP Basic authentication, we recommend enabling it. If not provided this property will not be modified. See HttpBasicAuthInput Set this to `false` to disable HTTP Basic authentication. Any previously stored HTTP Basic authentication settings will be cleared out. If not provided this property will not be modified. The HTTP Data Source's tables. If not provided this property will not be modified. See HttpDataSourceTableInput The HTTP Data Source's new description. If not provided this property will not be modified. The ID or unique name of the HTTP Data Source to modify. The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The HTTP Data Source's new unique name. If not provided this property will not be modified. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error This mutation creates a new Kafka Data Source. The mutation returns the newly created Data Source (or an error message if creating the Data Source fails). ### Arguments The Kafka Data Source's connection settings The Kafka Data Source connection settings. The type of authentication to use. Can be SCRAM-SHA-256, SCRAM-SHA-512, PLAIN or NONE The bootstrap server(s) to connect to The password for the provided user Whether the the connection to the Kafka servers is encrypted or not The user for authenticating against the Kafka servers The Kafka Data Source's description. The Kafka Data Source's unique name. If not specified, Propel will set the ID as unique name. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error This mutation selects a Data Source by its ID or unique name and modifies it to have the given unique name, description, and connection settings. If any of the optional arguments are omitted, those properties will be unchanged on the Data Source. ### Arguments The Kafka Data Source's new connection settings. If not provided this property will not be modified. The Kafka Data Source connection settings. The type of authentication to use. Can be SCRAM-SHA-256, SCRAM-SHA-512, PLAIN or NONE If not provided this property will not be modified. The bootstrap server(s) to connect to If not provided this property will not be modified. The password for the provided user If not provided this property will not be modified. Whether the the connection to the Kafka servers is encrypted or not If not provided this property will not be modified. The user for authenticating against the Kafka servers If not provided this property will not be modified. The Kafka Data Source's new description. If not provided this property will not be modified. The ID or unique name of the Kafka Data Source to modify. The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The Kafka Data Source's new unique name. If not provided this property will not be modified. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error Creates a new PostgreSQL Data Source. Returns the newly created Data Source (or an error message if creating the Data Source fails). Example: ```graphql theme={"system"} mutation { createPostgreSqlDataSource(input: { uniqueName: "example_postgresql_data_source" description: "My PostgreSQL Data Source" connectionSettings: { database: "example_database" schema: "public" host: "postgresql.example.com" port: 5432 user: "user" password: "password" } }) { dataSource { id uniqueName } } } ``` Replace the placeholder values with your actual configuration. ### Arguments The PostgreSQL Data Source's connection settings The PostgreSQL Data Source connection settings. Which database to connect to The host where PostgreSQL is listening The password for the provided user The port where PostgreSQL is listening (usually 5432) Which schema to use The user for authenticating against PostgreSQL The PostgreSQL Data Source's description. The PostgreSQL Data Source's unique name. If not specified, Propel will set the ID as unique name. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error Selects a Data Source by its ID or unique name and modifies it to have the given unique name, description, and connection settings. If any of the optional arguments are omitted, those properties will be unchanged on the Data Source. ### Arguments The PostgreSQL Data Source's new connection settings. If not provided this property will not be modified. The PostgreSQL Data Source connection settings. Which database to connect to If not provided this property will not be modified. The host where PostgreSQL is listening If not provided this property will not be modified. The password for the provided user If not provided this property will not be modified. The port where PostgreSQL is listening (usually 5432) If not provided this property will not be modified. Which schema to use If not provided this property will not be modified. The user for authenticating against PostgreSQL If not provided this property will not be modified. The PostgreSQL Data Source's new description. If not provided this property will not be modified. The ID or unique name of the PostgreSQL Data Source to modify. The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The PostgreSQL Data Source's new unique name. If not provided this property will not be modified. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error Creates a new Amazon S3 Data Source pointed at the specified Amazon S3 bucket. Returns the newly created Data Source (or an error message if creating the Data Source fails). ### Arguments The Amazon S3 Data Source's connection settings The connection settings for an Amazon S3 Data Source. These include the Amazon S3 bucket name, the AWS access key ID, and the tables (along with their paths). We do not allow fetching the AWS secret access key after it has been set. The AWS access key ID for an IAM user with sufficient access to the Amazon S3 bucket. The AWS secret access key for an IAM user with sufficient access to the Amazon S3 bucket. The name of the Amazon S3 bucket. The Amazon S3 Data Source's tables. See S3DataSourceTableInput The Amazon S3 Data Source's description. The Amazon S3 Data Source's unique name. If not specified, Propel will set the ID as unique name. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error This mutation selects a Data Source by its ID or unique name and modifies it to have the given unique name, description, and connection settings. If any of the optional arguments are omitted, those properties will be unchanged on the Data Source. ### Arguments The Amazon S3 Data Source's new connection settings. If not provided this property will not be modified. The connection settings for an Amazon S3 Data Source. These include the Amazon S3 bucket name, the AWS access key ID, and the tables (along with their paths). We do not allow fetching the AWS secret access key after it has been set. The AWS access key ID for an IAM user with sufficient access to the Amazon S3 bucket. If not provided this property will not be modified. The AWS secret access key for an IAM user with sufficient access to the Amazon S3 bucket. If not provided this property will not be modified. The name of the Amazon S3 bucket. If not provided this property will not be modified. The Amazon S3 Data Source's tables. If not provided this property will not be modified. See S3DataSourceTableInput The Amazon S3 Data Source's new description. If not provided this property will not be modified. The ID or unique name of the Amazon S3 Data Source to modify. The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The Amazon S3 Data Source's new unique name. If not provided this property will not be modified. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error Creates a new Twilio Segment Data Source from the given settings. Returns the newly created Data Source (or an error message if creating the Data Source fails). ### Arguments The Twilio Segment Data Source's connection settings The Twilio Segment Data Source connection settings. Enables or disables access control for the Data Pool. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. The HTTP basic authentication settings for the Twilio Segment Data Source URL. If this parameter is not provided, anyone with the webhook URL will be able to send events. While it's OK to test without HTTP Basic authentication, we recommend enabling it. See HttpBasicAuthInput The additional columns for the table in Propel. See TwilioSegmentDataSourceColumnInput Override the Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse, and a default will be chosen based on the Data Pool's `timestamp` and `uniqueId` values, if any. You can override these defaults in order to specify a custom table engine, custom ORDER BY, etc. See TableSettingsInput The primary timestamp column, if any. The Twilio Segment Data Source's description. The Twilio Segment Data Source's unique name. If not specified, Propel will set the ID as unique name. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error Modifies the Data Source by the ID or unique name provided with the given unique name, description, and connection settings. If any of the optional arguments are omitted, those properties will be unchanged on the Data Source. ### Arguments The Twilio Segment Data Source's new connection settings. If not provided this property will not be modified. The Twilio Segment Data Source connection settings. The HTTP basic authentication settings for the Twilio Segment Data Source URL. If this parameter is not provided, anyone with the webhook URL will be able to send events. While it's OK to test without HTTP Basic authentication, we recommend enabling it. If not provided this property will not be modified. See HttpBasicAuthInput Set this to `false` to disable HTTP Basic authentication. Any previously stored HTTP Basic authentication settings will be cleared out. If not provided this property will not be modified. The Twilio Segment Data Source's new description. If not provided this property will not be modified. The ID or unique name of the Twilio Segment Data Source to modify. The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The Twilio Segment Data Source's new unique name. If not provided this property will not be modified. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error Creates a new Webhook Data Source from the given settings. Returns the newly created Data Source (or an error message if creating the Data Source fails). ### Arguments The Webhook Data Source's connection settings The Webhook Data Source connection settings. Enables or disables access control for the Data Pool. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. The HTTP basic authentication settings for the Webhook Data Source URL. If this parameter is not provided, anyone with the webhook URL will be able to send events. While it's OK to test without HTTP Basic authentication, we recommend enabling it. See HttpBasicAuthInput The additional columns for the table in Propel. See WebhookDataSourceColumnInput Override the Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse, and a default will be chosen based on the Data Pool's `timestamp` and `uniqueId` values, if any. You can override these defaults in order to specify a custom table engine, custom ORDER BY, etc. See TableSettingsInput The tenant ID column, if any. The primary timestamp column, if any. The unique ID column, if any. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated. The Webhook Data Source's description. The Webhook Data Source's unique name. If not specified, Propel will set the ID as unique name. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error Modifies the Data Source by the ID or unique name provided with the given unique name, description, and connection settings. If any of the optional arguments are omitted, those properties will be unchanged on the Data Source. ### Arguments The Webhook Data Source's new connection settings. If not provided this property will not be modified. The Webhook Data Source connection settings. The HTTP basic authentication settings for the Webhook Data Source URL. If this parameter is not provided, anyone with the webhook URL will be able to send events. While it's OK to test without HTTP Basic authentication, we recommend enabling it. If not provided this property will not be modified. See HttpBasicAuthInput Set this to `false` to disable HTTP Basic authentication. Any previously stored HTTP Basic authentication settings will be cleared out. If not provided this property will not be modified. The Webhook Data Source's new description. If not provided this property will not be modified. The ID or unique name of the Webhook Data Source to modify. The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The Webhook Data Source's new unique name. If not provided this property will not be modified. The result of a mutation which creates or modifies a Data Source. The Data Source which was created or modified. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error Deprecated. Use `retryDataPoolSetup` instead. deprecated: Use `retryDataPoolSetup` instead ### Arguments The ID or unique name input. If both ID and unique name are provided, the ID will take precedence. The unique identifier of the object. The unique name of the object. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. The Account object. The Account's unique identifier. The Data Pool's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. The status of a Data Pool. * `CREATED`: The Data Pool has been created and will be set up soon. * `PENDING`: Propel is attempting to set up the Data Pool. * `LIVE`: The Data Pool is set up and serving data. Check its Syncs to monitor data ingestion. * `SETUP_FAILED`: The Data Pool setup failed. Check its Setup Tasks before re-attempting setup. * `CONNECTING` * `CONNECTED` * `BROKEN` * `PAUSING` * `PAUSED` * `DELETING`: Propel is deleting the Data Pool and all of its associated data. The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. A Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. The primary timestamp column's type. The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo The list of measures (numeric columns) in the Data Pool. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo A list of setup tasks performed on the Data Pool during its most recent setup attempt. The Data Pool Setup Task object. Data Pool Setup Tasks are executed when setting up your Data Pool. They ensure Propel will be able to sync records from your Data Source to your Data Pool. The exact Setup Tasks to perform vary by Data Source. For example, Data Pools pointing to a Snowflake-backed Data Sources will have their own specific Setup Tasks. The name of the Data Pool Setup Task to be performed. A description of the Data Pool Setup Task to be performed. The status of the Data Pool Setup Task (all setup tasks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataPoolSetupTaskStatus If the Data Pool Setup Task failed, this field includes a descriptive error message. See Error The time at which the Data Pool Setup Task was completed. Settings related to Data Pool syncing. Settings related to Data Pool syncing. Indicates whether syncing is enabled or disabled. See DataPoolSyncStatus The syncing interval. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. See DataPoolSyncInterval The date and time of the most recent Sync in UTC. The list of Syncs of the Data Pool. ### Arguments The filter to apply when listing the Syncs for a Data Pool. * `EMPTY`: Returns only Syncs with empty records. * `NOT_EMPTY`: Returns only Syncs that contain one or more records. * `ALL`: Returns all Syncs, regardless of whether they contain records or not. See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments Response returned by the validateExpression query for validating expressions in Custom Metrics. Returns whether the expression is valid or not with a reason explaining why. True if the expression is valid, false otherwise. The reason for why the expression is not valid in case it isn't, null otherwise. The Data Pool's table settings. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. See TableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The Data Pool's columns that participate in its PARTITION BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its PRIMARY KEY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its ORDER BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead deprecated: Refer to `setupTasks` instead The error object. The error code. The error message. The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead A Data Pool's tenant ID column. The tenant ID column is used to control access to your data with access policies. The name of the column that represents the tenant ID. The tenant ID column's type. The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. A Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. The name of the column that represents the unique ID. Creates a new Policy granting an Application access to a Metric's data. deprecated: Use Data Pool Access Policies instead ### Arguments The fields for creating a Policy. The Metric to which the Policy will be applied. The type of Policy to create. The types of Policies that can be applied to a Metric. * `ALL_ACCESS`: Grants access to all Metric data. * `TENANT_ACCESS`: Grants access to a specified tenant's Metric data. The Application that will be granted access to the Metric. The result of a mutation which creates or modifies a Policy. The Policy which was created or modified. The Policy type. It governs an Application's access to a Metric's data. The Policy's unique identifier. The Policy's Account. See Account The Policy's Environment. See Environment The Policy's creation date and time in UTC. The Policy's last modification date and time in UTC. The Policy's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Policy's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The type of Policy. See PolicyType The Application that is granted access. See Application The Metric that the Application is granted access to. See Metric Modifies an existing Policy. You can modify the Application's level of access to the Metric's data. deprecated: Use Data Pool Access Policies instead ### Arguments The fields for modifying a Policy. The Policy's unique identifier. The type of Policy. The types of Policies that can be applied to a Metric. * `ALL_ACCESS`: Grants access to all Metric data. * `TENANT_ACCESS`: Grants access to a specified tenant's Metric data. The result of a mutation which creates or modifies a Policy. The Policy which was created or modified. The Policy type. It governs an Application's access to a Metric's data. The Policy's unique identifier. The Policy's Account. See Account The Policy's Environment. See Environment The Policy's creation date and time in UTC. The Policy's last modification date and time in UTC. The Policy's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Policy's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The type of Policy. See PolicyType The Application that is granted access. See Application The Metric that the Application is granted access to. See Metric Deletes a Policy. The associated Application will no longer have access to the Metric's data. deprecated: Use Data Pool Access Policies instead ### Arguments Schedules a new Deletion Job on the specified Data Pool. deprecated: This has been renamed to `createDeletionJob` ### Arguments The fields for creating a Deletion Job. The Data Pool that is going to get the data deleted The filters that will be used for deleting data, in the form of SQL. Data matching these filters will be deleted. The list of filters that will be used for deleting data. Data matching these filters will be deleted. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The response returned by the Deletion Job. The Deletion Job that was just created. Deletion Job scheduled for a specific Data Pool. The Deletion Job represents the asynchronous process of deleting data given some filters inside a Data Pool. It tracks the deletion process until it is finished, showing the progress and the outcome when it is finished. The Deletion Job's ID. The Deletion Job's creation date and time in UTC. Who created the Deletion Job. The Deletion Job's last modification date and time in UTC. Who last modified the Deletion Job. Account to which the Deletion Job belongs. See Account Environment to which the Deletion Job belongs. See Environment The Data Pool whose records will be deleted by the Deletion Job. See DataPool The current Deletion Job's status. See JobStatus The filters that will be used for deleting data, in the form of SQL. Data matching the filters will be deleted. The error that occurred while deleting data, if any. See Error The current progress of the Deletion Job, from 0.0 to 1.0. The time at which the Deletion Job started. The time at which the Deletion Job succeeded. The time at which the Deletion Job failed. The list of filters that will be used for deleting data. Data matching the filters will be deleted. deprecated: Use `filterSql` instead See Filter ## SqlColumnResponse The name of the returned column. The returned column's type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Whether the column is nullable, meaning whether it accepts a null value. ## SqlResponse Response from the SQL API. The column names in the same order as present in the `data` field. The name of the returned column. The returned column's type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Whether the column is nullable, meaning whether it accepts a null value. The data gathered by the SQL query. The data is returned in an N x M matrix format, where the first dimension are the rows retrieved, and the second dimension are the columns. Each cell can be either a string or null, and the string can represent a number, text, date or boolean value. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Query status. The Query status. * `COMPLETED`: The Query was completed succesfully. * `ERROR`: The Query experienced an error. * `TIMED_OUT`: The Query timed out. The Query type. The Query type. * `METRIC`: Indicates a Metric Query. * `STATS`: Indicates a Dimension Stats Query. * `REPORT`: Indicates a Report Query. * `RECORDS`: Indicates a Record Table Query. * `RECORDS_BY_UNIQUE_ID`: Indicates records queried by unique ID. * `SQL`: Indicates a SQL Query. * `TOP_VALUES`: Indicates a Top Values Query. The Query subtype. The Query subtype. * `COUNTER`: Indicates a Metric counter Query. * `TIME_SERIES`: Indicates a Metric time series Query. * `LEADERBOARD`: Indicates a Metric leaderboard Query. The SQL the query executed. ## DescribeSqlResponse Response from the describe SQL API. The columns that the query would return. The name of the returned column. The returned column's type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Whether the column is nullable, meaning whether it accepts a null value. ## DataGridConnection The Data Grid connection. It includes `headers` and `rows` for a single page of a Data Grid table. It also allows paging forward and backward to other pages of the Data Grid table. The Data Grid table's headers. An array of arrays containing the values of the Data Grid table's rows. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Query status. The Query status. * `COMPLETED`: The Query was completed succesfully. * `ERROR`: The Query experienced an error. * `TIMED_OUT`: The Query timed out. The Query type. The Query type. * `METRIC`: Indicates a Metric Query. * `STATS`: Indicates a Dimension Stats Query. * `REPORT`: Indicates a Report Query. * `RECORDS`: Indicates a Record Table Query. * `RECORDS_BY_UNIQUE_ID`: Indicates records queried by unique ID. * `SQL`: Indicates a SQL Query. * `TOP_VALUES`: Indicates a Top Values Query. The Query subtype. The Query subtype. * `COUNTER`: Indicates a Metric counter Query. * `TIME_SERIES`: Indicates a Metric time series Query. * `LEADERBOARD`: Indicates a Metric leaderboard Query. The SQL the query executed. The Data Grid table's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. The Data Grid table's edges. The Data Grid edge object. The edge's node. The Data Grid table's node. This type represents a single row of a Data Grid table. The Data Grid table's headers. An array of the values for the row. The edge's cursor. The Data Grid table's nodes. The Data Grid table's node. This type represents a single row of a Data Grid table. The Data Grid table's headers. An array of the values for the row. ## DataGridEdge The Data Grid edge object. The edge's node. The Data Grid table's node. This type represents a single row of a Data Grid table. The Data Grid table's headers. An array of the values for the row. The edge's cursor. ## DataGridNode The Data Grid table's node. This type represents a single row of a Data Grid table. The Data Grid table's headers. An array of the values for the row. ## RecordsByUniqueIdResponse The Data Pool columns for the record. An array of values for the record. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Query status. The Query status. * `COMPLETED`: The Query was completed succesfully. * `ERROR`: The Query experienced an error. * `TIMED_OUT`: The Query timed out. The Query type. The Query type. * `METRIC`: Indicates a Metric Query. * `STATS`: Indicates a Dimension Stats Query. * `REPORT`: Indicates a Report Query. * `RECORDS`: Indicates a Record Table Query. * `RECORDS_BY_UNIQUE_ID`: Indicates records queried by unique ID. * `SQL`: Indicates a SQL Query. * `TOP_VALUES`: Indicates a Top Values Query. The Query subtype. The Query subtype. * `COUNTER`: Indicates a Metric counter Query. * `TIME_SERIES`: Indicates a Metric time series Query. * `LEADERBOARD`: Indicates a Metric leaderboard Query. The SQL the query executed. ## TopValuesResponse An array with the list of values. Returns the Application specified by the given ID. ### Arguments The Application object. Propel Applications represent the web or mobile app you are building. They provide the API credentials that allow your client- or server-side app to access the Propel API. The Application's Propeller determines the speed and cost of your Metric Queries. The Application's unique identifier. The Application's unique name. The Application's description. The Application's Account. The Account object. The Account's unique identifier. The Application's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Application's creation date and time in UTC. The Application's last modification date and time in UTC. The Application's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Application's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Application's OAuth 2.0 client identifier. The Application's OAuth 2.0 client secret. The Application's Propeller. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Application's OAuth 2.0 scopes. The API operations an Application is authorized to perform. * `ADMIN`: Grant read/write access to Data Sources, Data Pools, Metrics and Policies. * `APPLICATION_ADMIN`: Grant read/write access to Applications. * `DATA_POOL_QUERY`: Grant read access to query Data Pools. * `DATA_POOL_READ`: Grant read access to read Data Pools. * `DATA_POOL_STATS`: Grant read access to fetch column statistics from Data Pools. * `ENVIRONMENT_ADMIN`: Grant read/write access to Environments. * `METRIC_QUERY`: Grant read access to query Metrics. * `METRIC_STATS`: Grant read access to fetch Dimension statistics from Metrics. * `METRIC_READ`: Grant read access to Metrics. This does not allow querying Metrics. For that, see `METRIC_QUERY`. A paginated list of Data Pool Access Policies associated with the Application. ### Arguments See DataPoolAccessPolicyConnection A paginated list of Policies associated with the Application. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Returns the Application with the given unique name. ### Arguments The Application object. Propel Applications represent the web or mobile app you are building. They provide the API credentials that allow your client- or server-side app to access the Propel API. The Application's Propeller determines the speed and cost of your Metric Queries. The Application's unique identifier. The Application's unique name. The Application's description. The Application's Account. The Account object. The Account's unique identifier. The Application's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Application's creation date and time in UTC. The Application's last modification date and time in UTC. The Application's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Application's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Application's OAuth 2.0 client identifier. The Application's OAuth 2.0 client secret. The Application's Propeller. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Application's OAuth 2.0 scopes. The API operations an Application is authorized to perform. * `ADMIN`: Grant read/write access to Data Sources, Data Pools, Metrics and Policies. * `APPLICATION_ADMIN`: Grant read/write access to Applications. * `DATA_POOL_QUERY`: Grant read access to query Data Pools. * `DATA_POOL_READ`: Grant read access to read Data Pools. * `DATA_POOL_STATS`: Grant read access to fetch column statistics from Data Pools. * `ENVIRONMENT_ADMIN`: Grant read/write access to Environments. * `METRIC_QUERY`: Grant read access to query Metrics. * `METRIC_STATS`: Grant read access to fetch Dimension statistics from Metrics. * `METRIC_READ`: Grant read access to Metrics. This does not allow querying Metrics. For that, see `METRIC_QUERY`. A paginated list of Data Pool Access Policies associated with the Application. ### Arguments See DataPoolAccessPolicyConnection A paginated list of Policies associated with the Application. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Returns the Applications within the Environment. The `applications` query uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments The Application connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Application connection's edges. The Application edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See Application The Application connection's nodes. The Application object. Propel Applications represent the web or mobile app you are building. They provide the API credentials that allow your client- or server-side app to access the Propel API. The Application's Propeller determines the speed and cost of your Metric Queries. The Application's unique identifier. The Application's unique name. The Application's description. The Application's Account. See Account The Application's Environment. See Environment The Application's creation date and time in UTC. The Application's last modification date and time in UTC. The Application's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Application's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Application's OAuth 2.0 client identifier. The Application's OAuth 2.0 client secret. The Application's Propeller. See Propeller The Application's OAuth 2.0 scopes. See ApplicationScope A paginated list of Data Pool Access Policies associated with the Application. ### Arguments See DataPoolAccessPolicyConnection A paginated list of Policies associated with the Application. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection The Application connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. Returns the Data Source specified by the given ID. ```graphql theme={"system"} query { dataSource(id: "DSOXXXXX") { id uniqueName type tables (first: 100){ nodes { id name columns (first: 100) { nodes { name type isNullable supportedDataPoolColumnTypes } } } } } } ``` ### Arguments The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. The Account object. The Account's unique identifier. The Data Source's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. The types of Data Sources. * `WEBHOOK`: Indicates a Webhook Data Source. * `TWILIO_SEGMENT`: Indicates a Twilio Segment Data Source. * `S3`: Indicates an Amazon S3 Data Source. * `Redshift`: Indicates a Redshift Data Source. * `POSTGRESQL`: Indicates a PostgreSQL Data Source. * `KAFKA`: Indicates a Kafka Data Source. * `Http`: Indicates an Http Data Source. * `CLICKHOUSE`: Indicates a ClickHouse Data Source. * `AMAZON_DYNAMODB`: Indicates an Amazon DynamoDB Data Source. * `AMAZON_DATA_FIREHOSE`: Indicates an Amazon Data Firehose Data Source. * `Snowflake`: Indicates a Snowflake Data Source. * `INTERNAL`: Indicates an internal Data Source. The Data Source's status. The status of a Data Source. * `CREATED`: The Data Source has been created, but it is not connected yet. * `CONNECTING`: Propel is attempting to connect the Data Source. * `CONNECTED`: The Data Source is connected. * `BROKEN`: The Data Source failed to connect. * `DELETING`: Propel is deleting the Data Source. The Data Source's connection settings. See SnowflakeConnectionSettings See InternalConnectionSettings See AmazonDataFirehoseConnectionSettings See AmazonDynamoDBConnectionSettings See ClickHouseConnectionSettings See HttpConnectionSettings See KafkaConnectionSettings See PostgreSqlConnectionSettings See S3ConnectionSettings See TwilioSegmentConnectionSettings See WebhookConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. The Data Source Check object. Data Source Checks are executed when setting up your Data Source. They check that Propel will be able to receive data and setup Data Pools. The exact Checks to perform vary by Data Source. For example, Snowflake-backed Data Sources will have their own specific Checks. The name of the Data Source Check to be performed. A description of the Data Source Check to be performed. The status of the Data Source Check (all checks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataSourceCheckStatus If the Data Source Check failed, this field includes a descriptive error message. See Error The time at which the Data Source Check was performed. If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead The error object. The error code. The error message. Returns the Data Source specified by the given unique name. ### Arguments The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. The Account object. The Account's unique identifier. The Data Source's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. The types of Data Sources. * `WEBHOOK`: Indicates a Webhook Data Source. * `TWILIO_SEGMENT`: Indicates a Twilio Segment Data Source. * `S3`: Indicates an Amazon S3 Data Source. * `Redshift`: Indicates a Redshift Data Source. * `POSTGRESQL`: Indicates a PostgreSQL Data Source. * `KAFKA`: Indicates a Kafka Data Source. * `Http`: Indicates an Http Data Source. * `CLICKHOUSE`: Indicates a ClickHouse Data Source. * `AMAZON_DYNAMODB`: Indicates an Amazon DynamoDB Data Source. * `AMAZON_DATA_FIREHOSE`: Indicates an Amazon Data Firehose Data Source. * `Snowflake`: Indicates a Snowflake Data Source. * `INTERNAL`: Indicates an internal Data Source. The Data Source's status. The status of a Data Source. * `CREATED`: The Data Source has been created, but it is not connected yet. * `CONNECTING`: Propel is attempting to connect the Data Source. * `CONNECTED`: The Data Source is connected. * `BROKEN`: The Data Source failed to connect. * `DELETING`: Propel is deleting the Data Source. The Data Source's connection settings. See SnowflakeConnectionSettings See InternalConnectionSettings See AmazonDataFirehoseConnectionSettings See AmazonDynamoDBConnectionSettings See ClickHouseConnectionSettings See HttpConnectionSettings See KafkaConnectionSettings See PostgreSqlConnectionSettings See S3ConnectionSettings See TwilioSegmentConnectionSettings See WebhookConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. The Data Source Check object. Data Source Checks are executed when setting up your Data Source. They check that Propel will be able to receive data and setup Data Pools. The exact Checks to perform vary by Data Source. For example, Snowflake-backed Data Sources will have their own specific Checks. The name of the Data Source Check to be performed. A description of the Data Source Check to be performed. The status of the Data Source Check (all checks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataSourceCheckStatus If the Data Source Check failed, this field includes a descriptive error message. See Error The time at which the Data Source Check was performed. If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead The error object. The error code. The error message. Returns the Data Sources within the Environment. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. The `dataSources` query uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments The Data Source connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Source connection's edges. The Data Source edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See DataSource The Data Source connection's nodes. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error The Data Source connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. Returns the Data Pool specified by the given ID. A Data Pool is a cached table hydrated from your data warehouse optimized for high-concurrency and low-latency queries. ### Arguments The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. The Account object. The Account's unique identifier. The Data Pool's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. The status of a Data Pool. * `CREATED`: The Data Pool has been created and will be set up soon. * `PENDING`: Propel is attempting to set up the Data Pool. * `LIVE`: The Data Pool is set up and serving data. Check its Syncs to monitor data ingestion. * `SETUP_FAILED`: The Data Pool setup failed. Check its Setup Tasks before re-attempting setup. * `CONNECTING` * `CONNECTED` * `BROKEN` * `PAUSING` * `PAUSED` * `DELETING`: Propel is deleting the Data Pool and all of its associated data. The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. A Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. The primary timestamp column's type. The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo The list of measures (numeric columns) in the Data Pool. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo A list of setup tasks performed on the Data Pool during its most recent setup attempt. The Data Pool Setup Task object. Data Pool Setup Tasks are executed when setting up your Data Pool. They ensure Propel will be able to sync records from your Data Source to your Data Pool. The exact Setup Tasks to perform vary by Data Source. For example, Data Pools pointing to a Snowflake-backed Data Sources will have their own specific Setup Tasks. The name of the Data Pool Setup Task to be performed. A description of the Data Pool Setup Task to be performed. The status of the Data Pool Setup Task (all setup tasks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataPoolSetupTaskStatus If the Data Pool Setup Task failed, this field includes a descriptive error message. See Error The time at which the Data Pool Setup Task was completed. Settings related to Data Pool syncing. Settings related to Data Pool syncing. Indicates whether syncing is enabled or disabled. See DataPoolSyncStatus The syncing interval. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. See DataPoolSyncInterval The date and time of the most recent Sync in UTC. The list of Syncs of the Data Pool. ### Arguments The filter to apply when listing the Syncs for a Data Pool. * `EMPTY`: Returns only Syncs with empty records. * `NOT_EMPTY`: Returns only Syncs that contain one or more records. * `ALL`: Returns all Syncs, regardless of whether they contain records or not. See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments Response returned by the validateExpression query for validating expressions in Custom Metrics. Returns whether the expression is valid or not with a reason explaining why. True if the expression is valid, false otherwise. The reason for why the expression is not valid in case it isn't, null otherwise. The Data Pool's table settings. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. See TableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The Data Pool's columns that participate in its PARTITION BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its PRIMARY KEY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its ORDER BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead deprecated: Refer to `setupTasks` instead The error object. The error code. The error message. The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead A Data Pool's tenant ID column. The tenant ID column is used to control access to your data with access policies. The name of the column that represents the tenant ID. The tenant ID column's type. The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. A Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. The name of the column that represents the unique ID. Returns the Data Pool specified by the given unique name. A Data Pool is a cached table hydrated from your data warehouse optimized for high-concurrency and low-latency queries. ### Arguments The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. The Account object. The Account's unique identifier. The Data Pool's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. The status of a Data Pool. * `CREATED`: The Data Pool has been created and will be set up soon. * `PENDING`: Propel is attempting to set up the Data Pool. * `LIVE`: The Data Pool is set up and serving data. Check its Syncs to monitor data ingestion. * `SETUP_FAILED`: The Data Pool setup failed. Check its Setup Tasks before re-attempting setup. * `CONNECTING` * `CONNECTED` * `BROKEN` * `PAUSING` * `PAUSED` * `DELETING`: Propel is deleting the Data Pool and all of its associated data. The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. A Data Pool's primary timestamp column. Propel uses the primary timestamp to order and partition your data in Data Pools. It will serve as the time dimension for your Metrics. The name of the column that represents the primary timestamp. The primary timestamp column's type. The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo The list of measures (numeric columns) in the Data Pool. ### Arguments The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. See DataPoolColumnEdge The Data Pool column connection's nodes. See DataPoolColumn The Data Pool column connection's page info. See PageInfo A list of setup tasks performed on the Data Pool during its most recent setup attempt. The Data Pool Setup Task object. Data Pool Setup Tasks are executed when setting up your Data Pool. They ensure Propel will be able to sync records from your Data Source to your Data Pool. The exact Setup Tasks to perform vary by Data Source. For example, Data Pools pointing to a Snowflake-backed Data Sources will have their own specific Setup Tasks. The name of the Data Pool Setup Task to be performed. A description of the Data Pool Setup Task to be performed. The status of the Data Pool Setup Task (all setup tasks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataPoolSetupTaskStatus If the Data Pool Setup Task failed, this field includes a descriptive error message. See Error The time at which the Data Pool Setup Task was completed. Settings related to Data Pool syncing. Settings related to Data Pool syncing. Indicates whether syncing is enabled or disabled. See DataPoolSyncStatus The syncing interval. Note that the syncing interval is approximate. For example, setting the syncing interval to `EVERY_1_HOUR` does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to when the Data Pool goes `LIVE`, and Propel will attempt to sync approximately every hour. Additionally, if you pause or resume syncing, this too can shift the syncing interval around. See DataPoolSyncInterval The date and time of the most recent Sync in UTC. The list of Syncs of the Data Pool. ### Arguments The filter to apply when listing the Syncs for a Data Pool. * `EMPTY`: Returns only Syncs with empty records. * `NOT_EMPTY`: Returns only Syncs that contain one or more records. * `ALL`: Returns all Syncs, regardless of whether they contain records or not. See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments Response returned by the validateExpression query for validating expressions in Custom Metrics. Returns whether the expression is valid or not with a reason explaining why. True if the expression is valid, false otherwise. The reason for why the expression is not valid in case it isn't, null otherwise. The Data Pool's table settings. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. See TableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The Data Pool's columns that participate in its PARTITION BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its PRIMARY KEY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool's columns that participate in its ORDER BY clause. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead deprecated: Refer to `setupTasks` instead The error object. The error code. The error message. The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead A Data Pool's tenant ID column. The tenant ID column is used to control access to your data with access policies. The name of the column that represents the tenant ID. The tenant ID column's type. The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. A Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. The name of the column that represents the unique ID. Returns the Data Pools within the Environment. A Data Pool is a cached table hydrated from your data warehouse optimized for high-concurrency and low-latency queries. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. The `dataPools` query uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments The Data Pool connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool connection's edges. See DataPoolEdge The Data Pool connection's nodes. See DataPool The Data Pool connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. Returns the Environment specified by the given ID. ### Arguments The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. The Account object. The Account's unique identifier. Returns the Materialized Views within the Environment. The `materializedViews` query uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments The Materialized View connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Materialized View connection's edges. The Materialized View edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See MaterializedView The Materialized View connection's nodes. The Materialized View's unique identifier. The Materialized View's unique name. The Materialized View's description. The Materialized View's Account. See Account The Materialized View's Environment. See Environment The Materialized View's creation date and time in UTC. The Materialized View's last modification date and time in UTC. The Materialized View's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Materialized View's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The SQL that the Materialized View executes. The Materialized View's destination (AKA "target") Data Pool. See DataPool The Materialized View's source Data Pool. See DataPool Other Data Pools queried by the Materialized View. See DataPool The Materialized View connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. Returns the Data Pool Access Policy specified by the given ID. A Data Pool Access Policy limits the data that Applications can access within a Data Pool. ### Arguments The ID of the Data Pool Access Policy. The Data Pool Access Policy's unique name. The Data Pool Access Policy's description. The Data Pool Access Policy's Account. The Account object. The Account's unique identifier. The Data Pool Access Policy's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool Access Policy's creation date and time in UTC. The Data Pool Access Policy's last modification date and time in UTC. The Data Pool Access Policy's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool Access Policy's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool to which the Access Policy belongs. See DataPool Columns that the Access Policy makes available for querying. Row-level filters that the Access Policy applies before executing queries, in the form of SQL. Applications that are assigned to this Data Pool Access Policy. ### Arguments See ApplicationConnection Row-level filters that the Access Policy applies before executing queries. deprecated: Use `filtersSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. Returns the Metric specified by the given ID. A Metric is a business indicator measured over time. ### Arguments The Metric object. A Metric is a business indicator measured over time. The Metric's unique identifier. The Metric's unique name. The Metric's description. The Metric's Account. The Account object. The Account's unique identifier. The Metric's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Metric's creation date and time in UTC. The Metric's last modification date and time in UTC. The Metric's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Metric's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool that powers this Metric. See DataPool The Metric's Dimensions. These Dimensions are available to Query Filters. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats See DimensionStatistics The Metric's timestamp, if any. This is the same as its Data Pool's timestamp, if any. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats See DimensionStatistics List the Boosters associated to the Metric. ### Arguments See BoosterConnection The Metric's type. The different Metric types determine how the values are calculated. The available Metric types. * `COUNT`: Counts the number of records that matches the Metric Filters. For time series, it will count the values for each time granularity. * `SUM`: Sums the values of the specified column for every record that matches the Metric Filters. For time series, it will sum the values for each time granularity. * `COUNT_DISTINCT`: Counts the number of distinct values in the specified column for every record that matches the Metric Filters. For time series, it will count the distinct values for each time granularity. * `AVERAGE`: Averages the values of the specified column for every record that matches the Metric Filters. For time series, it will average the values for each time granularity. * `MIN`: Selects the minimum value of the specified column for every record that matches the Metric Filters. For time series, it will select the minimum value for each time granularity. * `MAX`: Selects the maximum value of the specified column for every record that matches the Metric Filters. For time series, it will select the maximum value for each time granularity. * `CUSTOM`: Aggregates values based on the provided custom expression. The settings for the Metric. The settings are specific to the Metric's type. A Metric's settings, depending on its type. See CountMetricSettings See SumMetricSettings See CountDistinctMetricSettings See AverageMetricSettings See MinMetricSettings See MaxMetricSettings See CustomMetricSettings The Metric's measure. Access this from the Metric's `settings` object instead. deprecated: Use the Metric `settings` object instead. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats See DimensionStatistics Query the Metric in counter format. Returns the Metric's value for the given time range and filters. deprecated: Use the top-level `counter` query instead ### Arguments The fields for querying a Metric in counter format. A Metric's counter query returns a single value over a given time range. The Metric to query. You can query a pre-configured Metric by ID or name, or you can query an ad hoc Metric that you define inline. See MetricInput The time range for calculating the counter. See TimeRangeInput The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The Query Filters to apply before retrieving the counter data, in the form of SQL. If no Query Filters are provided, all data is included. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the counter data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead See FilterInput The counter response object. It contains a single Metric value for the given time range and Query Filters. The value of the counter. The Query statistics and metadata. See QueryInfo Query the Metric in time series format. Returns arrays of timestamps and the Metric's values for the given time range and filters. deprecated: Use the top-level `timeSeries` query instead ### Arguments The fields for querying a Metric in time series format. A Metric's time series query returns the values over a given time range aggregated by a given time granularity; day, month, or year, for example. The Metric to Query. It can be a pre-created one or it can be inlined here. See MetricInput The time range for calculating the time series. See TimeRangeInput The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The time granularity (hour, day, month, etc.) to aggregate the Metric values by. See TimeSeriesGranularity The Query Filters to apply before retrieving the time series data, in the form of SQL. If no Query Filters are provided, all data is included. Columns to group by. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the time series data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead See FilterInput The time series response object. It contains an array of time series labels and an array of Metric values for the given time range and Query Filters. The time series labels. The time series values. The time series values for each group in `groupBy`, if specified. See TimeSeriesResponseGroup The Query statistics and metadata. See QueryInfo Query the Metric in leaderboard format. Returns a table (array of rows) with the selected dimensions and the Metric's corresponding values for the given time range and filters. deprecated: Use the top-level `leaderboard` query instead ### Arguments The fields for querying a Metric in leaderboard format. A Metric's leaderboard query returns an ordered table of Dimension and Metric values over a given time range. The Metric to query. You can query a pre-configured Metric by ID or name, or you can query an ad hoc Metric that you define inline. See MetricInput The time range for calculating the leaderboard. See TimeRangeInput The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". One or many Dimensions to group the Metric values by. Typically, Dimensions in a leaderboard are what you want to compare and rank. See DimensionInput The sort order of the rows. It can be ascending (`ASC`) or descending (`DESC`) order. Defaults to descending (`DESC`) order when not provided. See Sort The number of rows to be returned. It can be a number between 1 and 1,000. The Query Filters to apply before retrieving the leaderboard data, in the form of SQL. If no Query Filters are provided, all data is included. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the leaderboard data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead See FilterInput The leaderboard response object. It contains an array of headers and a table (array of rows) with the selected Dimensions and corresponding Metric values for the given time range and Query Filters. The table headers. It contains the Dimension and Metric names. An ordered array of rows. Each row contains the Dimension values and the corresponding Metric value. A Dimension value can be empty. A Metric value will never be empty. The Query statistics and metadata. See QueryInfo List the Policies associated to the Metric. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Whether or not access control is enabled for the Metric. deprecated: Use Data Pool Access Policies instead Returns the Metric specified by the given unique name. A Metric is a business indicator measured over time. ### Arguments The Metric object. A Metric is a business indicator measured over time. The Metric's unique identifier. The Metric's unique name. The Metric's description. The Metric's Account. The Account object. The Account's unique identifier. The Metric's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Metric's creation date and time in UTC. The Metric's last modification date and time in UTC. The Metric's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Metric's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool that powers this Metric. See DataPool The Metric's Dimensions. These Dimensions are available to Query Filters. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats See DimensionStatistics The Metric's timestamp, if any. This is the same as its Data Pool's timestamp, if any. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats See DimensionStatistics List the Boosters associated to the Metric. ### Arguments See BoosterConnection The Metric's type. The different Metric types determine how the values are calculated. The available Metric types. * `COUNT`: Counts the number of records that matches the Metric Filters. For time series, it will count the values for each time granularity. * `SUM`: Sums the values of the specified column for every record that matches the Metric Filters. For time series, it will sum the values for each time granularity. * `COUNT_DISTINCT`: Counts the number of distinct values in the specified column for every record that matches the Metric Filters. For time series, it will count the distinct values for each time granularity. * `AVERAGE`: Averages the values of the specified column for every record that matches the Metric Filters. For time series, it will average the values for each time granularity. * `MIN`: Selects the minimum value of the specified column for every record that matches the Metric Filters. For time series, it will select the minimum value for each time granularity. * `MAX`: Selects the maximum value of the specified column for every record that matches the Metric Filters. For time series, it will select the maximum value for each time granularity. * `CUSTOM`: Aggregates values based on the provided custom expression. The settings for the Metric. The settings are specific to the Metric's type. A Metric's settings, depending on its type. See CountMetricSettings See SumMetricSettings See CountDistinctMetricSettings See AverageMetricSettings See MinMetricSettings See MaxMetricSettings See CustomMetricSettings The Metric's measure. Access this from the Metric's `settings` object instead. deprecated: Use the Metric `settings` object instead. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats See DimensionStatistics Query the Metric in counter format. Returns the Metric's value for the given time range and filters. deprecated: Use the top-level `counter` query instead ### Arguments The fields for querying a Metric in counter format. A Metric's counter query returns a single value over a given time range. The Metric to query. You can query a pre-configured Metric by ID or name, or you can query an ad hoc Metric that you define inline. See MetricInput The time range for calculating the counter. See TimeRangeInput The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The Query Filters to apply before retrieving the counter data, in the form of SQL. If no Query Filters are provided, all data is included. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the counter data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead See FilterInput The counter response object. It contains a single Metric value for the given time range and Query Filters. The value of the counter. The Query statistics and metadata. See QueryInfo Query the Metric in time series format. Returns arrays of timestamps and the Metric's values for the given time range and filters. deprecated: Use the top-level `timeSeries` query instead ### Arguments The fields for querying a Metric in time series format. A Metric's time series query returns the values over a given time range aggregated by a given time granularity; day, month, or year, for example. The Metric to Query. It can be a pre-created one or it can be inlined here. See MetricInput The time range for calculating the time series. See TimeRangeInput The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The time granularity (hour, day, month, etc.) to aggregate the Metric values by. See TimeSeriesGranularity The Query Filters to apply before retrieving the time series data, in the form of SQL. If no Query Filters are provided, all data is included. Columns to group by. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the time series data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead See FilterInput The time series response object. It contains an array of time series labels and an array of Metric values for the given time range and Query Filters. The time series labels. The time series values. The time series values for each group in `groupBy`, if specified. See TimeSeriesResponseGroup The Query statistics and metadata. See QueryInfo Query the Metric in leaderboard format. Returns a table (array of rows) with the selected dimensions and the Metric's corresponding values for the given time range and filters. deprecated: Use the top-level `leaderboard` query instead ### Arguments The fields for querying a Metric in leaderboard format. A Metric's leaderboard query returns an ordered table of Dimension and Metric values over a given time range. The Metric to query. You can query a pre-configured Metric by ID or name, or you can query an ad hoc Metric that you define inline. See MetricInput The time range for calculating the leaderboard. See TimeRangeInput The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". One or many Dimensions to group the Metric values by. Typically, Dimensions in a leaderboard are what you want to compare and rank. See DimensionInput The sort order of the rows. It can be ascending (`ASC`) or descending (`DESC`) order. Defaults to descending (`DESC`) order when not provided. See Sort The number of rows to be returned. It can be a number between 1 and 1,000. The Query Filters to apply before retrieving the leaderboard data, in the form of SQL. If no Query Filters are provided, all data is included. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the leaderboard data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead See FilterInput The leaderboard response object. It contains an array of headers and a table (array of rows) with the selected Dimensions and corresponding Metric values for the given time range and Query Filters. The table headers. It contains the Dimension and Metric names. An ordered array of rows. Each row contains the Dimension values and the corresponding Metric value. A Dimension value can be empty. A Metric value will never be empty. The Query statistics and metadata. See QueryInfo List the Policies associated to the Metric. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection Whether or not access control is enabled for the Metric. deprecated: Use Data Pool Access Policies instead Returns the Metrics within the Environment. A Metric is a business indicator measured over time. Each Metric is associated with one Data Pool, which is a cached table hydrated from your data warehouse optimized for high-concurrency and low-latency queries. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. The `metrics` query uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments The Metric connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Metric connection's edges. See MetricEdge The Metric connection's nodes. See Metric The Metric connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. Returns the Booster specified by the given ID. A Booster significantly improves the query performance for a Metric. ### Arguments Boosters allow you to optimize Metric Queries for a subset of commonly used Dimensions. A Metric can have one or many Boosters to optimize for the different Query patterns. Boosters can be understood as an aggregating index. The index is formed from left to right as follows: 1. The Data Pool's Tenant ID column (if present) 2. Metric Filter columns (if present) 3. Query Filter Dimensions (see `dimensions`) 4. The Data Pool's timestamp column The Booster's unique identifier. The Booster's Account. The Account object. The Account's unique identifier. The Booster's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Booster's creation date and time in UTC. The Booster's last modification date and time in UTC. The Booster's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Booster's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Metric this Booster is associated to. See Metric The status of the Booster (once LIVE it will be available for speeding up Metric queries). The Booster status. * `CREATED`: The Booster has been created. Propel will start optimizing the Data Pool soon. * `OPTIMIZING`: Propel is setting up the Booster and optimizing the Data Pool. * `LIVE`: The Booster is now live and available to speed up Metric queries. * `FAILED`: Propel failed to setup the Booster. Please write to support. Alternatively, you can delete the Booster and try again. * `DELETING`: Propel is deleting the Booster and all of its associated data. If the Booster fails during the optimization process, this field includes a descriptive error message. The error object. The error code. The error message. When the Booster is OPTIMIZING, this represents its progress as a number from 0 to 1. In all other states, progress is null. Dimensions included in the Booster. The Dimension object that represents a column in a table. The column name it represents. The column data type. Whether the column is nullable. Whether the column is a unique key. deprecated: This is Snowflake-specific, and will be removed The statistics for the dimension values. Fetching statistics incurs query costs. deprecated: Issue normal queries for calculating stats See DimensionStatistics The number of records in the Booster. The amount of storage in terabytes used by the Booster. Returns a Policy by ID. ### Arguments The Policy type. It governs an Application's access to a Metric's data. The Policy's unique identifier. The Policy's Account. The Account object. The Account's unique identifier. The Policy's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Policy's creation date and time in UTC. The Policy's last modification date and time in UTC. The Policy's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Policy's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The type of Policy. The types of Policies that can be applied to a Metric. * `ALL_ACCESS`: Grants access to all Metric data. * `TENANT_ACCESS`: Grants access to a specified tenant's Metric data. The Application that is granted access. See Application The Metric that the Application is granted access to. See Metric Returns a Sync by ID. ### Arguments The Sync object. This represents the process of syncing data from your Data Source (for example, a Snowflake data warehouse) to your Data Pool. The Sync's unique identifier. The Sync's Account. The Account object. The Account's unique identifier. The Sync's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Sync's creation date and time in UTC. The Sync's last modification date and time in UTC. The Sync's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Sync's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Sync's Data Pool. See DataPool The Sync's Data Pool's Data Source. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error The number of new, updated, and deleted records contained within the Sync, if known. This excludes filtered records. The (compressed) size of the Sync, in bytes, if known. The status of the Sync (all Syncs begin as SYNCING before transitioning to SUCCEEDED or FAILED). The status of a Sync. * `SYNCING`: Propel is actively syncing records contained within the Sync. * `SUCCEEDED`: The Sync succeeded. Propel successfully synced all records contained within the Sync. * `FAILED`: The Sync failed. Propel failed to sync some or all records contained within the Sync. * `DELETING`: Propel is deleting the Sync. The time at which the Sync started. The time at which the Sync succeeded. The time at which the Sync failed. If the Sync failed, this represents the reason the Sync failed. The error object. The error code. The error message. The number of new records contained within the Sync, if known. This excludes filtered records. deprecated: All records are considered to be processed; see `processedRecords` instead The number of updated records contained within the Sync, if known. This excludes filtered records. deprecated: All records are considered to be processed; see `processedRecords` instead The number of deleted records contained within the Sync, if known. This excludes filtered records. deprecated: All records are considered to be processed; see `processedRecords` instead The number of filtered records contained within the Sync, due to issues such as a missing timestamp Dimension, if any are known to be invalid. deprecated: All records are considered to be processed; see `processedRecords` instead Returns a table by ID. ### Arguments The table object. Once a table introspection succeeds, it creates a new table object for every table it introspected. The table's ID. The table's name. The Data Source to which the table belongs. See DataSource The number of rows contained within the table at the time of introspection. Check the table's `cachedAt` time, since this info can become out of date. The size of the table (in bytes) at the time of introspection. Check the table's `cachedAt` time, since this info can become out of date. The time at which the table was cached (i.e., the time at which it was introspected). The time at which the table was created. This is the same as its `cachedAt` time. The table's creator. This corresponds to the initiator of the table Introspection. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The table's columns. ### Arguments The column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The time at which the columns were cached (i.e., the time at which they were introspected). The column connection's edges. See ColumnEdge The column connection's nodes. See Column The column connection's page info. See PageInfo The table's columns which can be used as a timestamp for a Data Pool. ### Arguments The column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The time at which the columns were cached (i.e., the time at which they were introspected). The column connection's edges. See ColumnEdge The column connection's nodes. See Column The column connection's page info. See PageInfo The table's columns which can be used as a measure for a Metric. ### Arguments The column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The time at which the columns were cached (i.e., the time at which they were introspected). The column connection's edges. See ColumnEdge The column connection's nodes. See Column The column connection's page info. See PageInfo Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the table obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Build a report, or table, consisting of multiple Metrics broken down by one-or-more dimensions. The first few columns of the report are the dimensions you choose to break down by. The subsequent columns are the Metrics you choose to query. By default, the report sorts on the first Metric in descending order, but you can configure this with the `orderByMetric` and `sort` inputs. Finally, reports use cursor-based pagination. You can control page size with the `first` and `last` inputs. ### Arguments The fields for querying a Metric Report. A Metric Report is a table whose columns include dimensions and Metric values, calculated over a given time range. The time range for calculating the Metric Report. The fields required to specify the time range for a time series, counter, or leaderboard Metric query. If no relative or absolute time ranges are provided, Propel defaults to an absolute time range beginning with the earliest record in the Metric's Data Pool and ending with the latest record. If both relative and absolute time ranges are provided, the relative time range will take precedence. If a `LAST_N` relative time period is selected, an `n` ≥ 1 must be provided. If no `n` is provided or `n` \< 1, a `BAD_REQUEST` error will be returned. The timestamp field to use when querying. Defaults to the timestamp configured on the Data Pool or Metric, if any. Set this to filter on an alternative timestamp field. The relative time period. See RelativeTimeRange The number of time units for the `LAST_N` relative periods. The optional start timestamp (inclusive). Defaults to the timestamp of the earliest record in the Data Pool. The optional end timestamp (exclusive). Defaults to the timestamp of the latest record in the Data Pool. The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". One or many dimensions to group the Metric values by. Typically, dimensions in a report are what you want to compare and rank. The fields for specifying a dimension to include in a Metric Report. The column name of the dimension to include in a Metric Report. This must match the name of a Data Pool column. The name to display in the `headers` array when displaying the report. This defaults to the column name if unspecified. The sort order for the dimension. It can be ascending (`ASC`) or descending (`DESC`) order. Defaults to ascending (`ASC`) order when not provided. See Sort One or more Metrics to include in the Metric Report. These will be broken down by `dimensions`. The fields for specifying a Metric to include in a Metric Report. The Metric to query. You can query a pre-configured Metric by ID or name, or you can query an ad hoc Metric that you define inline. See MetricInput The name to display in the `headers` array when displaying the report. This defaults to the Metric's unique name if unspecified. The Query Filters to apply when calculating the Metric, in the form of SQL. The sort order for the Metric. It can be ascending (`ASC`) or descending (`DESC`) order. Defaults to descending (`DESC`) order when not provided. See Sort The Metric's unique name. If not specified, Propel will lookup the Metric by ID. deprecated: Use `metric` The Metric's ID. If not specified, Propel will lookup the Metric by unique name. deprecated: Use `metric` The Query Filters to apply when calculating the Metric. deprecated: Use `filterSql` instead See FilterInput The Query Filters to apply when building the Metric Report, in the form of SQL. These can be used to filter out rows. The index of the column to order the Metric Report by. The index is 1-based and defaults to the first Metric column. In other words, by default, reports are ordered by the first Metric; however, you can order by the second Metric, third Metric, etc., by overriding the `orderByColumn` input. You can also order by dimensions this way. The number of rows to be returned when paging forward. It can be a number between 1 and 1,000. The cursor to use when paging forward. The number of rows to be returned when paging forward. It can be a number between 1 and 1,000. The cursor to use when paging backward. The Query Filters to apply when building the Metric Report. These can be used to filter out rows. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The Metric Report connection object. It includes `headers` and `rows` for a single page of a report. It also allows paging forward and backward to other pages of the report. The report connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. The report connection's edges. The Metric Report edge object. The edge's node. See MetricReportNode The edge's cursor. The report connection's nodes. The Metric Report node object. This type represents a single row of a report. An ordered array of display names for your dimensions and Metrics, as defined in the report input. Use this to display your table's header. An ordered array of columns. Each column contains the dimension and Metric values for a single row, as defined in the report input. Use this to display a single row within your table. An ordered array of display names for your dimensions and Metrics, as defined in the report input. Use this to display your table's header. An ordered array of rows. Each row contains dimension and Metric values, as defined in the report input. Use these to display the rows of your table. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. See Propeller The Query status. See QueryStatus The Query type. See QueryType The Query subtype. See QuerySubtype The SQL the query executed. Query Data Pools using SQL. ### Arguments Input to the SqlV1 api. The SQL query. The SQL dialect to use. If not provided, the query is parsed on a best-effort basis. The SQL dialect to use when parsing queries. * `POSTGRESQL`: Parse as PostgreSQL-compatible SQL. * `CLICKHOUSE`: Parse as ClickHouse-compatible SQL. Response from the SQL API. The column names in the same order as present in the `data` field. The name of the returned column. The returned column's type. See ColumnType Whether the column is nullable, meaning whether it accepts a null value. The data gathered by the SQL query. The data is returned in an N x M matrix format, where the first dimension are the rows retrieved, and the second dimension are the columns. Each cell can be either a string or null, and the string can represent a number, text, date or boolean value. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. See Propeller The Query status. See QueryStatus The Query type. See QueryType The Query subtype. See QuerySubtype The SQL the query executed. Describe SQL statements Data Pools. ### Arguments Input for describing SqlV1 inputs. The SQL query. The SQL dialect to use. If not provided, the query is parsed on a best-effort basis. The SQL dialect to use when parsing queries. * `POSTGRESQL`: Parse as PostgreSQL-compatible SQL. * `CLICKHOUSE`: Parse as ClickHouse-compatible SQL. Response from the describe SQL API. The columns that the query would return. The name of the returned column. The returned column's type. See ColumnType Whether the column is nullable, meaning whether it accepts a null value. Returns the individual records of a Data Pool with the convenience of built-in pagination, filtering, and sorting. ### Arguments The fields for querying Data Grid records. The Data Pool to be queried. The ID of the Data Pool. The name of the Data Pool. The time range for retrieving the records. The fields required to specify the time range for a time series, counter, or leaderboard Metric query. If no relative or absolute time ranges are provided, Propel defaults to an absolute time range beginning with the earliest record in the Metric's Data Pool and ending with the latest record. If both relative and absolute time ranges are provided, the relative time range will take precedence. If a `LAST_N` relative time period is selected, an `n` ≥ 1 must be provided. If no `n` is provided or `n` \< 1, a `BAD_REQUEST` error will be returned. The timestamp field to use when querying. Defaults to the timestamp configured on the Data Pool or Metric, if any. Set this to filter on an alternative timestamp field. The relative time period. See RelativeTimeRange The number of time units for the `LAST_N` relative periods. The optional start timestamp (inclusive). Defaults to the timestamp of the earliest record in the Data Pool. The optional end timestamp (exclusive). Defaults to the timestamp of the latest record in the Data Pool. The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The columns to retrieve. The index of the column to order the table by. The index is 1-based. If not provided, records will be ordered by their timestamp by default. The sort order of the rows. It can be ascending (`ASC`) or descending (`DESC`) order. Defaults to descending (`DESC`) order when not provided. The available sort orders. * `ASC`: Sort in ascending order. * `DESC`: Sort in descending order. The filters to apply to the records, in the form of SQL. You may only filter on columns included in the `columns` array input. The number of rows to be returned when paging forward. It can be a number between 1 and 1,000. The cursor to use when paging forward. The number of rows to be returned when paging forward. It can be a number between 1 and 1,000. The cursor to use when paging backward. The filters to apply to the records. You may only filter on columns included in the `columns` array input. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The Data Grid connection. It includes `headers` and `rows` for a single page of a Data Grid table. It also allows paging forward and backward to other pages of the Data Grid table. The Data Grid table's headers. An array of arrays containing the values of the Data Grid table's rows. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. See Propeller The Query status. See QueryStatus The Query type. See QueryType The Query subtype. See QuerySubtype The SQL the query executed. The Data Grid table's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. The Data Grid table's edges. The Data Grid edge object. The edge's node. See DataGridNode The edge's cursor. The Data Grid table's nodes. The Data Grid table's node. This type represents a single row of a Data Grid table. The Data Grid table's headers. An array of the values for the row. Returns records by the given unique IDs. ### Arguments The fields for querying records by unique ID. The Data Pool to be queried. A Data Pool ID or unique name can be provided. The ID of the Data Pool. The name of the Data Pool. The columns to retrieve. The unique IDs of the records to retrieve. The Data Pool columns for the record. An array of values for the record. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. See Propeller The Query status. See QueryStatus The Query type. See QueryType The Query subtype. See QuerySubtype The SQL the query executed. Returns an array of the most frequent values in a given column. The resulting array is sorted in descending order of approximate frequency of values. ### Arguments The fields for querying the top values in a given column. The Data Pool to be queried. A Data Pool ID or unique name can be provided. The ID of the Data Pool. The name of the Data Pool. The column to fetch the unique values from. The time range for calculating the top values. The fields required to specify the time range for a time series, counter, or leaderboard Metric query. If no relative or absolute time ranges are provided, Propel defaults to an absolute time range beginning with the earliest record in the Metric's Data Pool and ending with the latest record. If both relative and absolute time ranges are provided, the relative time range will take precedence. If a `LAST_N` relative time period is selected, an `n` ≥ 1 must be provided. If no `n` is provided or `n` \< 1, a `BAD_REQUEST` error will be returned. The timestamp field to use when querying. Defaults to the timestamp configured on the Data Pool or Metric, if any. Set this to filter on an alternative timestamp field. The relative time period. See RelativeTimeRange The number of time units for the `LAST_N` relative periods. The optional start timestamp (inclusive). Defaults to the timestamp of the earliest record in the Data Pool. The optional end timestamp (exclusive). Defaults to the timestamp of the latest record in the Data Pool. The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The maximum number of values to return. It can be a number between 1 and 1,000. If the parameter is omitted, default value 10 is used. An array with the list of values. Query a metric in counter format. Returns a single metric value for the given time range and filters. ### Arguments The fields for querying a Metric in counter format. A Metric's counter query returns a single value over a given time range. The Metric to query. You can query a pre-configured Metric by ID or name, or you can query an ad hoc Metric that you define inline. The ID of a pre-configured Metric. The name of a pre-configured Metric. An ad hoc Custom Metric. See CustomMetricQueryInput An ad hoc Count Metric. See CountMetricQueryInput An ad hoc Sum Metric. See SumMetricQueryInput An ad hoc Average Metric. See AverageMetricQueryInput An ad hoc Min Metric. See MinMetricQueryInput An ad hoc Max Metric. See MaxMetricQueryInput An ad hoc Count Distinct Metric. See CountDistinctMetricQueryInput The time range for calculating the counter. The fields required to specify the time range for a time series, counter, or leaderboard Metric query. If no relative or absolute time ranges are provided, Propel defaults to an absolute time range beginning with the earliest record in the Metric's Data Pool and ending with the latest record. If both relative and absolute time ranges are provided, the relative time range will take precedence. If a `LAST_N` relative time period is selected, an `n` ≥ 1 must be provided. If no `n` is provided or `n` \< 1, a `BAD_REQUEST` error will be returned. The timestamp field to use when querying. Defaults to the timestamp configured on the Data Pool or Metric, if any. Set this to filter on an alternative timestamp field. The relative time period. See RelativeTimeRange The number of time units for the `LAST_N` relative periods. The optional start timestamp (inclusive). Defaults to the timestamp of the earliest record in the Data Pool. The optional end timestamp (exclusive). Defaults to the timestamp of the latest record in the Data Pool. The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The Query Filters to apply before retrieving the counter data, in the form of SQL. If no Query Filters are provided, all data is included. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the counter data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The counter response object. It contains a single Metric value for the given time range and Query Filters. The value of the counter. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. See Propeller The Query status. See QueryStatus The Query type. See QueryType The Query subtype. See QuerySubtype The SQL the query executed. Query metrics in counter format. Returns a metric value for each input in the array of inputs. ### Arguments The fields for querying a Metric in counter format. A Metric's counter query returns a single value over a given time range. The Metric to query. You can query a pre-configured Metric by ID or name, or you can query an ad hoc Metric that you define inline. The ID of a pre-configured Metric. The name of a pre-configured Metric. An ad hoc Custom Metric. See CustomMetricQueryInput An ad hoc Count Metric. See CountMetricQueryInput An ad hoc Sum Metric. See SumMetricQueryInput An ad hoc Average Metric. See AverageMetricQueryInput An ad hoc Min Metric. See MinMetricQueryInput An ad hoc Max Metric. See MaxMetricQueryInput An ad hoc Count Distinct Metric. See CountDistinctMetricQueryInput The time range for calculating the counter. The fields required to specify the time range for a time series, counter, or leaderboard Metric query. If no relative or absolute time ranges are provided, Propel defaults to an absolute time range beginning with the earliest record in the Metric's Data Pool and ending with the latest record. If both relative and absolute time ranges are provided, the relative time range will take precedence. If a `LAST_N` relative time period is selected, an `n` ≥ 1 must be provided. If no `n` is provided or `n` \< 1, a `BAD_REQUEST` error will be returned. The timestamp field to use when querying. Defaults to the timestamp configured on the Data Pool or Metric, if any. Set this to filter on an alternative timestamp field. The relative time period. See RelativeTimeRange The number of time units for the `LAST_N` relative periods. The optional start timestamp (inclusive). Defaults to the timestamp of the earliest record in the Data Pool. The optional end timestamp (exclusive). Defaults to the timestamp of the latest record in the Data Pool. The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The Query Filters to apply before retrieving the counter data, in the form of SQL. If no Query Filters are provided, all data is included. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the counter data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The counter response object. It contains a single Metric value for the given time range and Query Filters. The value of the counter. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. See Propeller The Query status. See QueryStatus The Query type. See QueryType The Query subtype. See QuerySubtype The SQL the query executed. Query a metric in time series format. Returns arrays of timestamps and metric values for the given time range and filters. ### Arguments The fields for querying a Metric in time series format. A Metric's time series query returns the values over a given time range aggregated by a given time granularity; day, month, or year, for example. The Metric to Query. It can be a pre-created one or it can be inlined here. The ID of a pre-configured Metric. The name of a pre-configured Metric. An ad hoc Custom Metric. See CustomMetricQueryInput An ad hoc Count Metric. See CountMetricQueryInput An ad hoc Sum Metric. See SumMetricQueryInput An ad hoc Average Metric. See AverageMetricQueryInput An ad hoc Min Metric. See MinMetricQueryInput An ad hoc Max Metric. See MaxMetricQueryInput An ad hoc Count Distinct Metric. See CountDistinctMetricQueryInput The time range for calculating the time series. The fields required to specify the time range for a time series, counter, or leaderboard Metric query. If no relative or absolute time ranges are provided, Propel defaults to an absolute time range beginning with the earliest record in the Metric's Data Pool and ending with the latest record. If both relative and absolute time ranges are provided, the relative time range will take precedence. If a `LAST_N` relative time period is selected, an `n` ≥ 1 must be provided. If no `n` is provided or `n` \< 1, a `BAD_REQUEST` error will be returned. The timestamp field to use when querying. Defaults to the timestamp configured on the Data Pool or Metric, if any. Set this to filter on an alternative timestamp field. The relative time period. See RelativeTimeRange The number of time units for the `LAST_N` relative periods. The optional start timestamp (inclusive). Defaults to the timestamp of the earliest record in the Data Pool. The optional end timestamp (exclusive). Defaults to the timestamp of the latest record in the Data Pool. The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". The time granularity (hour, day, month, etc.) to aggregate the Metric values by. The available time series granularities. Granularities define the unit of time to aggregate the Metric data for a time series query. For example, if the granularity is set to `DAY`, then the the time series query will return a label and a value for each day. If there are no records for a given time series granularity, Propel will return the label and a value of "0" so that the time series can be properly visualized. * `MINUTE`: Aggregates values by minute intervals. * `FIVE_MINUTES`: Aggregates values by 5-minute intervals. * `TEN_MINUTES`: Aggregates values by 10-minute intervals. * `FIFTEEN_MINUTES`: Aggregates values by 15-minute intervals. * `HOUR`: Aggregates values by hourly intervals. * `DAY`: Aggregates values by daily intervals. * `WEEK`: Aggregates values by weekly intervals. * `MONTH`: Aggregates values by monthly intervals. * `YEAR`: Aggregates values by yearly intervals. The Query Filters to apply before retrieving the time series data, in the form of SQL. If no Query Filters are provided, all data is included. Columns to group by. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the time series data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The time series response object. It contains an array of time series labels and an array of Metric values for the given time range and Query Filters. The time series labels. The time series values. The time series values for each group in `groupBy`, if specified. The time series response object for a group specified in `groupBy`. It contains an array of time series labels and an array of Metric values for a particular group. The time series group's columns. The time series group's labels. The time series group's values. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. See Propeller The Query status. See QueryStatus The Query type. See QueryType The Query subtype. See QuerySubtype The SQL the query executed. Query a metric in leaderboard format. Returns a table (array of rows) with the selected dimensions and the metric's corresponding values for the given time range and filters. ### Arguments The fields for querying a Metric in leaderboard format. A Metric's leaderboard query returns an ordered table of Dimension and Metric values over a given time range. The Metric to query. You can query a pre-configured Metric by ID or name, or you can query an ad hoc Metric that you define inline. The ID of a pre-configured Metric. The name of a pre-configured Metric. An ad hoc Custom Metric. See CustomMetricQueryInput An ad hoc Count Metric. See CountMetricQueryInput An ad hoc Sum Metric. See SumMetricQueryInput An ad hoc Average Metric. See AverageMetricQueryInput An ad hoc Min Metric. See MinMetricQueryInput An ad hoc Max Metric. See MaxMetricQueryInput An ad hoc Count Distinct Metric. See CountDistinctMetricQueryInput The time range for calculating the leaderboard. The fields required to specify the time range for a time series, counter, or leaderboard Metric query. If no relative or absolute time ranges are provided, Propel defaults to an absolute time range beginning with the earliest record in the Metric's Data Pool and ending with the latest record. If both relative and absolute time ranges are provided, the relative time range will take precedence. If a `LAST_N` relative time period is selected, an `n` ≥ 1 must be provided. If no `n` is provided or `n` \< 1, a `BAD_REQUEST` error will be returned. The timestamp field to use when querying. Defaults to the timestamp configured on the Data Pool or Metric, if any. Set this to filter on an alternative timestamp field. The relative time period. See RelativeTimeRange The number of time units for the `LAST_N` relative periods. The optional start timestamp (inclusive). Defaults to the timestamp of the earliest record in the Data Pool. The optional end timestamp (exclusive). Defaults to the timestamp of the latest record in the Data Pool. The time zone to use. Dates and times are always returned in UTC, but setting the time zone influences relative time ranges and granularities. You can set this to "America/Los\_Angeles", "Europe/Berlin", or any other value in the [IANA time zone database](https://en.wikipedia.org/wiki/Tz_database). Defaults to "UTC". One or many Dimensions to group the Metric values by. Typically, Dimensions in a leaderboard are what you want to compare and rank. The fields for creating or modifying a Dimension. The name of the column to create the Dimension from. The sort order of the rows. It can be ascending (`ASC`) or descending (`DESC`) order. Defaults to descending (`DESC`) order when not provided. The available sort orders. * `ASC`: Sort in ascending order. * `DESC`: Sort in descending order. The number of rows to be returned. It can be a number between 1 and 1,000. The Query Filters to apply before retrieving the leaderboard data, in the form of SQL. If no Query Filters are provided, all data is included. The ID of the Metric to query. Required if `metricName` is not specified. deprecated: Use `metric` The name of the Metric to query. Required if `metricId` is not specified. deprecated: Use `metric` The Query Filters to apply before retrieving the leaderboard data. If no Query Filters are provided, all data is included. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. The leaderboard response object. It contains an array of headers and a table (array of rows) with the selected Dimensions and corresponding Metric values for the given time range and Query Filters. The table headers. It contains the Dimension and Metric names. An ordered array of rows. Each row contains the Dimension values and the corresponding Metric value. A Dimension value can be empty. A Metric value will never be empty. The Query statistics and metadata. The Query Info object. It contains metadata and statistics about a Query performed. The Query's unique identifier. The date and time in UTC when the Query was created. The unique identifier of the actor that performed the Query. The date and time in UTC when the Query was last modified. The unique identifier of the actor that modified the Query. The bytes processed by the Query. The duration of the Query in milliseconds. The number of records processed by the Query. The bytes returned by the Query. The number of records returned by the Query. If the Query was boosted, the Booster that was used. See Booster The Propeller used for this query. See Propeller The Query status. See QueryStatus The Query type. See QueryType The Query subtype. See QuerySubtype The SQL the query executed. Returns the Deletion Job specified by the given ID. The Deletion Job represents the asynchronous process of deleting data given some filters inside a Data Pool. ### Arguments Deletion Job scheduled for a specific Data Pool. The Deletion Job represents the asynchronous process of deleting data given some filters inside a Data Pool. It tracks the deletion process until it is finished, showing the progress and the outcome when it is finished. The Deletion Job's ID. The Deletion Job's creation date and time in UTC. Who created the Deletion Job. The Deletion Job's last modification date and time in UTC. Who last modified the Deletion Job. Account to which the Deletion Job belongs. The Account object. The Account's unique identifier. Environment to which the Deletion Job belongs. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool whose records will be deleted by the Deletion Job. See DataPool The current Deletion Job's status. * `CREATED`: The Job was created, but is not yet being executed. * `IN_PROGRESS`: The Job is executing. * `SUCCEEDED`: The Job succeeded. * `FAILED`: The Job failed. Check the error message. The filters that will be used for deleting data, in the form of SQL. Data matching the filters will be deleted. The error that occurred while deleting data, if any. The error object. The error code. The error message. The current progress of the Deletion Job, from 0.0 to 1.0. The time at which the Deletion Job started. The time at which the Deletion Job succeeded. The time at which the Deletion Job failed. The list of filters that will be used for deleting data. Data matching the filters will be deleted. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. Returns the AddColumnToDataPoolJob specified by the given ID. The AddColumnToDataPoolJob represents the asynchronous process of adding a column, given its name and type, to a Data Pool. ### Arguments AddColumnToDataPoolJob scheduled for a specific Data Pool. The Add Column Job represents the asynchronous process of adding a column, given its name and type, to a Data Pool. It tracks the process of adding a column until it is finished, showing the progress and the outcome when it is finished. The AddColumnToDataPoolJob's ID. The AddColumnToDataPoolJob's creation date and time in UTC. Who created the AddColumnToDataPoolJob. The AddColumnToDataPoolJob's last modification date and time in UTC. Who modified the AddColumnToDataPoolJob last. Account to which the AddColumnToDataPoolJob belongs. The Account object. The Account's unique identifier. Environment to which the AddColumnToDataPoolJob belongs. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool to which a column will be added by the Job. See DataPool The current AddColumnToDataPoolJob's status. * `CREATED`: The Job was created, but is not yet being executed. * `IN_PROGRESS`: The Job is executing. * `SUCCEEDED`: The Job succeeded. * `FAILED`: The Job failed. Check the error message. Name of the new column. Type of the new column. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. The ClickHouse type of the new column when `columnType` is set to `CLICKHOUSE`. JSON property to which the new column corresponds. The error that occurred while adding the column data, if any. The error object. The error code. The error message. The current progress of the AddColumnToDataPool Job, from 0.0 to 1.0. The time at which the AddColumnToDataPool Job started. The time at which the AddColumnToDataPool Job succeeded. The time at which the AddColumnToDataPool Job failed. Returns the AddColumnToDataPool Job specified by a given status. ### Arguments * `CREATED`: The Job was created, but is not yet being executed. * `IN_PROGRESS`: The Job is executing. * `SUCCEEDED`: The Job succeeded. * `FAILED`: The Job failed. Check the error message. The Add column to Data Pool Job connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Add column to Data Pool Job connection's edges. See AddColumnToDataPoolJobEdge The Add column to Data Pool Job connection's nodes. See AddColumnToDataPoolJob The Add column to Data Pool Job connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. Returns the UpdateDataPoolRecords Job specified by the given ID. The UpdateDataPoolRecords Job represents the asynchronous process of updating records inside a Data Pool. ### Arguments UpdateDataPoolRecords Job scheduled for a specific Data Pool. The Update Data Pool Records Job represents the asynchronous process of updating records given some filters, inside a Data Pool. It tracks the process of updating records until it is finished, showing the progress and the outcome when it is finished. The UpdateDataPoolRecords Job's ID The UpdateDataPoolRecords Job's creation date and time in UTC Who created the UpdateDataPoolRecords Job The UpdateDataPoolRecords Job's last modification date and time in UTC Who last modified the UpdateDataPoolRecords Job Account to which the UpdateDataPoolRecords Job belongs The Account object. The Account's unique identifier. Environment to which the UpdateDataPoolRecords Job belongs The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Pool whose records will be updated by the UpdateDataPoolRecords Job See DataPool The current UpdateDataPoolRecords Job's status * `CREATED`: The Job was created, but is not yet being executed. * `IN_PROGRESS`: The Job is executing. * `SUCCEEDED`: The Job succeeded. * `FAILED`: The Job failed. Check the error message. The filters that will be used for updating data, in the form of SQL. Data matching the filters will be updated. Describes how the job will update the records. The fields for creating an Update Data Pool Records Job. ``` { "column": "status", "expression": "'completed'" } { "column": "counter", "expression": "counter + 1" } { "column": "full_name", "expression": "concat(first_name, ' ', last_name)" } ``` The name of the column to update. The value to which the column will be updated. Once evaluated, it should be of the same data type as the column. The error that occurred while updating data, if any. The error object. The error code. The error message. The current progress of the UpdateDataPoolRecords Job, from 0.0 to 1.0. The time at which the UpdateDataPoolRecords Job started. The time at which the UpdateDataPoolRecords Job succeeded. The time at which the UpdateDataPoolRecords Job failed. The list of filters that will be used for updating data. Data matching the filters will be updated. deprecated: Use `filterSql` instead The fields of a filter. You can construct more complex filters using `and` and `or`. For example, to construct a filter equivalent to ``` (value > 0 AND value <= 100) OR status = "confirmed" ``` you could write ``` { "column": "value", "operator": "GREATER_THAN", "value": "0", "and": [{ "column": "value", "operator": "LESS_THAN_OR_EQUAL_TO", "value": "0" }], "or": [{ "column": "status", "operator": "EQUALS", "value": "confirmed" }] } ``` Note that `and` takes precedence over `or`. The name of the column to filter on. The operation to perform when comparing the column and filter values. See FilterOperator The value to compare the column to. Additional filters to AND with this one. AND takes precedence over OR. Additional filters to OR with this one. AND takes precedence over OR. Returns the UpdateDataPoolRecords Job specified by a given status. ### Arguments * `CREATED`: The Job was created, but is not yet being executed. * `IN_PROGRESS`: The Job is executing. * `SUCCEEDED`: The Job succeeded. * `FAILED`: The Job failed. Check the error message. The Update Data Pool records Job connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Update Data Pool records Job connection's edges. See UpdateDataPoolRecordsJobEdge The Update Data Pool records Job connection's nodes. See UpdateDataPoolRecordsJob The Update Data Pool records Job connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. Returns the Materialized View specified by the given ID. ### Arguments The Materialized View's unique identifier. The Materialized View's unique name. The Materialized View's description. The Materialized View's Account. The Account object. The Account's unique identifier. The Materialized View's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Materialized View's creation date and time in UTC. The Materialized View's last modification date and time in UTC. The Materialized View's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Materialized View's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The SQL that the Materialized View executes. The Materialized View's destination (AKA "target") Data Pool. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId The Materialized View's source Data Pool. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId Other Data Pools queried by the Materialized View. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId Returns the Materialized View specified by its unique name. ### Arguments The Materialized View's unique identifier. The Materialized View's unique name. The Materialized View's description. The Materialized View's Account. The Account object. The Account's unique identifier. The Materialized View's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Materialized View's creation date and time in UTC. The Materialized View's last modification date and time in UTC. The Materialized View's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Materialized View's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The SQL that the Materialized View executes. The Materialized View's destination (AKA "target") Data Pool. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId The Materialized View's source Data Pool. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId Other Data Pools queried by the Materialized View. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId ## AddColumnToDataPoolJobConnection The Add column to Data Pool Job connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Add column to Data Pool Job connection's edges. See AddColumnToDataPoolJobEdge The Add column to Data Pool Job connection's nodes. See AddColumnToDataPoolJob The Add column to Data Pool Job connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## AddColumnToDataPoolJobEdge The Add column to Data Pool Job edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See AddColumnToDataPoolJob ## ApplicationConnection The Application connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Application connection's edges. The Application edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. The Application object. Propel Applications represent the web or mobile app you are building. They provide the API credentials that allow your client- or server-side app to access the Propel API. The Application's Propeller determines the speed and cost of your Metric Queries. The Application's unique identifier. The Application's unique name. The Application's description. The Application's Account. See Account The Application's Environment. See Environment The Application's creation date and time in UTC. The Application's last modification date and time in UTC. The Application's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Application's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Application's OAuth 2.0 client identifier. The Application's OAuth 2.0 client secret. The Application's Propeller. See Propeller The Application's OAuth 2.0 scopes. See ApplicationScope A paginated list of Data Pool Access Policies associated with the Application. ### Arguments See DataPoolAccessPolicyConnection A paginated list of Policies associated with the Application. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection The Application connection's nodes. The Application object. Propel Applications represent the web or mobile app you are building. They provide the API credentials that allow your client- or server-side app to access the Propel API. The Application's Propeller determines the speed and cost of your Metric Queries. The Application's unique identifier. The Application's unique name. The Application's description. The Application's Account. The Account object. The Account's unique identifier. The Application's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Application's creation date and time in UTC. The Application's last modification date and time in UTC. The Application's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Application's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Application's OAuth 2.0 client identifier. The Application's OAuth 2.0 client secret. The Application's Propeller. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Application's OAuth 2.0 scopes. The API operations an Application is authorized to perform. * `ADMIN`: Grant read/write access to Data Sources, Data Pools, Metrics and Policies. * `APPLICATION_ADMIN`: Grant read/write access to Applications. * `DATA_POOL_QUERY`: Grant read access to query Data Pools. * `DATA_POOL_READ`: Grant read access to read Data Pools. * `DATA_POOL_STATS`: Grant read access to fetch column statistics from Data Pools. * `ENVIRONMENT_ADMIN`: Grant read/write access to Environments. * `METRIC_QUERY`: Grant read access to query Metrics. * `METRIC_STATS`: Grant read access to fetch Dimension statistics from Metrics. * `METRIC_READ`: Grant read access to Metrics. This does not allow querying Metrics. For that, see `METRIC_QUERY`. A paginated list of Data Pool Access Policies associated with the Application. ### Arguments See DataPoolAccessPolicyConnection A paginated list of Policies associated with the Application. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection The Application connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## ApplicationEdge The Application edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. The Application object. Propel Applications represent the web or mobile app you are building. They provide the API credentials that allow your client- or server-side app to access the Propel API. The Application's Propeller determines the speed and cost of your Metric Queries. The Application's unique identifier. The Application's unique name. The Application's description. The Application's Account. The Account object. The Account's unique identifier. The Application's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Application's creation date and time in UTC. The Application's last modification date and time in UTC. The Application's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Application's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Application's OAuth 2.0 client identifier. The Application's OAuth 2.0 client secret. The Application's Propeller. A Propeller determines your Application's query processing power. The larger the Propeller, the faster the queries and the higher the cost. Every Propel Application (and therefore every set of API credentials) has a Propeller that determines the speed and cost of queries. * `P1_X_SMALL`: Max records per second: 5,000,000 records per second * `P1_SMALL`: Max records per second: 25,000,000 records per second * `P1_MEDIUM`: Max records per second: 100,000,000 records per second * `P1_LARGE`: Max records per second: 250,000,000 records per second * `P1_X_LARGE`: Max records per second: 500,000,000 records per second The Application's OAuth 2.0 scopes. The API operations an Application is authorized to perform. * `ADMIN`: Grant read/write access to Data Sources, Data Pools, Metrics and Policies. * `APPLICATION_ADMIN`: Grant read/write access to Applications. * `DATA_POOL_QUERY`: Grant read access to query Data Pools. * `DATA_POOL_READ`: Grant read access to read Data Pools. * `DATA_POOL_STATS`: Grant read access to fetch column statistics from Data Pools. * `ENVIRONMENT_ADMIN`: Grant read/write access to Environments. * `METRIC_QUERY`: Grant read access to query Metrics. * `METRIC_STATS`: Grant read access to fetch Dimension statistics from Metrics. * `METRIC_READ`: Grant read access to Metrics. This does not allow querying Metrics. For that, see `METRIC_QUERY`. A paginated list of Data Pool Access Policies associated with the Application. ### Arguments See DataPoolAccessPolicyConnection A paginated list of Policies associated with the Application. deprecated: Use Data Pool Access Policies instead ### Arguments See PolicyConnection ## BoosterConnection The Booster connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Booster connection's edges. See BoosterEdge The Booster connection's nodes. See Booster The Booster connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## BoosterEdge The Booster edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See Booster ## ColumnConnection The column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The time at which the columns were cached (i.e., the time at which they were introspected). The column connection's edges. The column edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. The column object. Once a table introspection succeeds, it creates a new table object for every table it introspected. Within each table object, it also creates a column object for every column it introspected. The column's name. The column's type. Whether the column is nullable, meaning whether it accepts a null value. The time at which the column was cached (i.e., the time at which it was introspected). The time at which the column was created. This is the same as its `cachedAt` time. The column's creator. This corresponds to the initiator of the table introspection. It can be either a User ID, an Application ID, or "system" if it was created by Propel. This is the suggested Data Pool column type to use when converting this Data Source column to a Data Pool column. Propel makes this suggestion based on the Data Source column type. If the Data Source column type is unsupported, this field returns `null`. Sometimes, you know better which Data Pool column type to convert to. In these cases, you can refer to `supportedDataPoolColumnTypes` for the full set of supported conversions. See ColumnType This is the set of supported Data Pool column types you can use when converting this Data Source column to a Data Pool column. If the Data Source column type is unsupported, this field returns an empty array. For example, a numeric Data Source column type could be converted to a narrower or wider numeric Data Pool column type; a string-valued Data Source column type could be mapped to a date or timestamp Data Pool column type. See ColumnType Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed The column connection's nodes. The column object. Once a table introspection succeeds, it creates a new table object for every table it introspected. Within each table object, it also creates a column object for every column it introspected. The column's name. The column's type. Whether the column is nullable, meaning whether it accepts a null value. The time at which the column was cached (i.e., the time at which it was introspected). The time at which the column was created. This is the same as its `cachedAt` time. The column's creator. This corresponds to the initiator of the table introspection. It can be either a User ID, an Application ID, or "system" if it was created by Propel. This is the suggested Data Pool column type to use when converting this Data Source column to a Data Pool column. Propel makes this suggestion based on the Data Source column type. If the Data Source column type is unsupported, this field returns `null`. Sometimes, you know better which Data Pool column type to convert to. In these cases, you can refer to `supportedDataPoolColumnTypes` for the full set of supported conversions. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. This is the set of supported Data Pool column types you can use when converting this Data Source column to a Data Pool column. If the Data Source column type is unsupported, this field returns an empty array. For example, a numeric Data Source column type could be converted to a narrower or wider numeric Data Pool column type; a string-valued Data Source column type could be mapped to a date or timestamp Data Pool column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed The column connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## ColumnEdge The column edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. The column object. Once a table introspection succeeds, it creates a new table object for every table it introspected. Within each table object, it also creates a column object for every column it introspected. The column's name. The column's type. Whether the column is nullable, meaning whether it accepts a null value. The time at which the column was cached (i.e., the time at which it was introspected). The time at which the column was created. This is the same as its `cachedAt` time. The column's creator. This corresponds to the initiator of the table introspection. It can be either a User ID, an Application ID, or "system" if it was created by Propel. This is the suggested Data Pool column type to use when converting this Data Source column to a Data Pool column. Propel makes this suggestion based on the Data Source column type. If the Data Source column type is unsupported, this field returns `null`. Sometimes, you know better which Data Pool column type to convert to. In these cases, you can refer to `supportedDataPoolColumnTypes` for the full set of supported conversions. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. This is the set of supported Data Pool column types you can use when converting this Data Source column to a Data Pool column. If the Data Source column type is unsupported, this field returns an empty array. For example, a numeric Data Source column type could be converted to a narrower or wider numeric Data Pool column type; a string-valued Data Source column type could be mapped to a date or timestamp Data Pool column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed Information about the column obtained from Snowflake. deprecated: This is Snowflake-specific, and will be removed ## DataPoolAccessPolicyConnection The Data Pool Access Policy connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool Access Policy connection's edges. See DataPoolAccessPolicyEdge The Data Pool Access Policy connection's nodes. See DataPoolAccessPolicy The Data Pool Access Policy connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## DataPoolAccessPolicyEdge The Data Pool Access Policy edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See DataPoolAccessPolicy ## DataPoolColumnConnection The Data Pool column connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool column connection's edges. The Data Pool column edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. See ColumnType The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool column connection's nodes. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead The Data Pool column connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## DataPoolColumnEdge The Data Pool column edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. The name of the Data Source column that this Data Pool column derives from. The Data Pool column's type. This may differ from the corresponding Data Source column's type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. The ClickHouse type. This is the exact representation of the type in ClickHouse. Whether the column is nullable, meaning whether it accepts a null value. The name of the Data Source column that this Data Pool column derives from. deprecated: Start using `columnName` instead ## DataPoolConnection The Data Pool connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Pool connection's edges. See DataPoolEdge The Data Pool connection's nodes. See DataPool The Data Pool connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## DataPoolEdge The Data Pool edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See DataPool ## DataSourceConnection The Data Source connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Data Source connection's edges. The Data Source edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. See Account The Data Source's Environment. See Environment The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. See DataSourceType The Data Source's status. See DataSourceStatus The Data Source's connection settings. See ConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. See DataSourceCheck If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead See Error The Data Source connection's nodes. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. The Account object. The Account's unique identifier. The Data Source's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. The types of Data Sources. * `WEBHOOK`: Indicates a Webhook Data Source. * `TWILIO_SEGMENT`: Indicates a Twilio Segment Data Source. * `S3`: Indicates an Amazon S3 Data Source. * `Redshift`: Indicates a Redshift Data Source. * `POSTGRESQL`: Indicates a PostgreSQL Data Source. * `KAFKA`: Indicates a Kafka Data Source. * `Http`: Indicates an Http Data Source. * `CLICKHOUSE`: Indicates a ClickHouse Data Source. * `AMAZON_DYNAMODB`: Indicates an Amazon DynamoDB Data Source. * `AMAZON_DATA_FIREHOSE`: Indicates an Amazon Data Firehose Data Source. * `Snowflake`: Indicates a Snowflake Data Source. * `INTERNAL`: Indicates an internal Data Source. The Data Source's status. The status of a Data Source. * `CREATED`: The Data Source has been created, but it is not connected yet. * `CONNECTING`: Propel is attempting to connect the Data Source. * `CONNECTED`: The Data Source is connected. * `BROKEN`: The Data Source failed to connect. * `DELETING`: Propel is deleting the Data Source. The Data Source's connection settings. See SnowflakeConnectionSettings See InternalConnectionSettings See AmazonDataFirehoseConnectionSettings See AmazonDynamoDBConnectionSettings See ClickHouseConnectionSettings See HttpConnectionSettings See KafkaConnectionSettings See PostgreSqlConnectionSettings See S3ConnectionSettings See TwilioSegmentConnectionSettings See WebhookConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. The Data Source Check object. Data Source Checks are executed when setting up your Data Source. They check that Propel will be able to receive data and setup Data Pools. The exact Checks to perform vary by Data Source. For example, Snowflake-backed Data Sources will have their own specific Checks. The name of the Data Source Check to be performed. A description of the Data Source Check to be performed. The status of the Data Source Check (all checks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataSourceCheckStatus If the Data Source Check failed, this field includes a descriptive error message. See Error The time at which the Data Source Check was performed. If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead The error object. The error code. The error message. The Data Source connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## DataSourceEdge The Data Source edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. The Data Source object. A Data Source is a connection to your data warehouse. It has the necessary connection details for Propel to access Snowflake or any other supported Data Source. The Data Source's unique identifier. The Data Source's unique name. The Data Source's description. The Data Source's Account. The Account object. The Account's unique identifier. The Data Source's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Data Source's creation date and time in UTC. The Data Source's last modification date and time in UTC. The Data Source's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Source's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Source's type. The types of Data Sources. * `WEBHOOK`: Indicates a Webhook Data Source. * `TWILIO_SEGMENT`: Indicates a Twilio Segment Data Source. * `S3`: Indicates an Amazon S3 Data Source. * `Redshift`: Indicates a Redshift Data Source. * `POSTGRESQL`: Indicates a PostgreSQL Data Source. * `KAFKA`: Indicates a Kafka Data Source. * `Http`: Indicates an Http Data Source. * `CLICKHOUSE`: Indicates a ClickHouse Data Source. * `AMAZON_DYNAMODB`: Indicates an Amazon DynamoDB Data Source. * `AMAZON_DATA_FIREHOSE`: Indicates an Amazon Data Firehose Data Source. * `Snowflake`: Indicates a Snowflake Data Source. * `INTERNAL`: Indicates an internal Data Source. The Data Source's status. The status of a Data Source. * `CREATED`: The Data Source has been created, but it is not connected yet. * `CONNECTING`: Propel is attempting to connect the Data Source. * `CONNECTED`: The Data Source is connected. * `BROKEN`: The Data Source failed to connect. * `DELETING`: Propel is deleting the Data Source. The Data Source's connection settings. See SnowflakeConnectionSettings See InternalConnectionSettings See AmazonDataFirehoseConnectionSettings See AmazonDynamoDBConnectionSettings See ClickHouseConnectionSettings See HttpConnectionSettings See KafkaConnectionSettings See PostgreSqlConnectionSettings See S3ConnectionSettings See TwilioSegmentConnectionSettings See WebhookConnectionSettings The tables contained within the Data Source, according to the most recent table introspection. ### Arguments See TableConnection A list of table introspections performed for the Data Source. You can see how tables and columns changed over time by paging through this list. ### Arguments See TableIntrospectionConnection A list of checks performed on the Data Source during its most recent connection attempt. The Data Source Check object. Data Source Checks are executed when setting up your Data Source. They check that Propel will be able to receive data and setup Data Pools. The exact Checks to perform vary by Data Source. For example, Snowflake-backed Data Sources will have their own specific Checks. The name of the Data Source Check to be performed. A description of the Data Source Check to be performed. The status of the Data Source Check (all checks begin as NOT\_STARTED before transitioning to SUCCEEDED or FAILED). See DataSourceCheckStatus If the Data Source Check failed, this field includes a descriptive error message. See Error The time at which the Data Source Check was performed. If you list Data Pools via the `dataPools` field on a Data Source, you will get Data Pools for the Data Source. The `dataPools` field uses cursor-based pagination typical of GraphQL APIs. You can use the pairs of parameters `first` and `after` or `last` and `before` to page forward or backward through the results, respectively. For forward pagination, the `first` parameter defines the number of results to return, and the `after` parameter defines the cursor to continue from. You should pass the cursor for the *last* result of the current page to `after`. For backward pagination, the `last` parameter defines the number of results to return, and the `before` parameter defines the cursor to continue from. You should pass the cursor for the *first* result of the current page to `before`. ### Arguments See DataPoolConnection deprecated: Refer to `checks` instead The error object. The error code. The error message. ## DeletionJobConnection The Deletion Job connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Deletion Job connection's edges. See DeletionJobEdge The Deletion Job connection's nodes. See DeletionJob The Deletion Job connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## DeletionJobEdge The Deletion Job edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See DeletionJob ## MaterializedViewConnection The Materialized View connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Materialized View connection's edges. The Materialized View edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. The Materialized View's unique identifier. The Materialized View's unique name. The Materialized View's description. The Materialized View's Account. See Account The Materialized View's Environment. See Environment The Materialized View's creation date and time in UTC. The Materialized View's last modification date and time in UTC. The Materialized View's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Materialized View's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The SQL that the Materialized View executes. The Materialized View's destination (AKA "target") Data Pool. See DataPool The Materialized View's source Data Pool. See DataPool Other Data Pools queried by the Materialized View. See DataPool The Materialized View connection's nodes. The Materialized View's unique identifier. The Materialized View's unique name. The Materialized View's description. The Materialized View's Account. The Account object. The Account's unique identifier. The Materialized View's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Materialized View's creation date and time in UTC. The Materialized View's last modification date and time in UTC. The Materialized View's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Materialized View's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The SQL that the Materialized View executes. The Materialized View's destination (AKA "target") Data Pool. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId The Materialized View's source Data Pool. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId Other Data Pools queried by the Materialized View. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId The Materialized View connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## MaterializedViewEdge The Materialized View edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. The Materialized View's unique identifier. The Materialized View's unique name. The Materialized View's description. The Materialized View's Account. The Account object. The Account's unique identifier. The Materialized View's Environment. The Environments object. Environments are independent and isolated Propel workspaces for development, staging (testing), and production workloads. Environments are hosted in a specific region, initially in us-east-2 only. The Environment's unique identifier. The Environment's unique name. The Environment's description. The Environment's creation date and time in UTC. The Environment's last modification date and time in UTC. The Environment's creator. It can be either a User ID, an Environment ID, or "system" if it was created by Propel. The Environment's last modifier. It can be either a User ID, an Environment ID, or "system" if it was modified by Propel. The Environment's Account. See Account The Materialized View's creation date and time in UTC. The Materialized View's last modification date and time in UTC. The Materialized View's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Materialized View's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The SQL that the Materialized View executes. The Materialized View's destination (AKA "target") Data Pool. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId The Materialized View's source Data Pool. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId Other Data Pools queried by the Materialized View. The Data Pool object. Data Pools are Propel's high-speed data store and cache The Data Pool's unique identifier. The Data Pool's unique name. The Data Pool's description. The Data Pool's Account. See Account The Data Pool's Environment. See Environment The Data Pool's creation date and time in UTC. The Data Pool's last modification date and time in UTC. The Data Pool's creator. It can be either a User ID, an Application ID, or "system" if it was created by Propel. The Data Pool's last modifier. It can be either a User ID, an Application ID, or "system" if it was modified by Propel. The Data Pool's Data Source. See DataSource The Data Pool's status. See DataPoolStatus The Data Pool's data retention in days (not yet supported). The name of the Data Pool's table. The Data Pool's primary timestamp column, if any. See Timestamp The number of records in the Data Pool. The amount of storage in terabytes used by the Data Pool. The Data Pool's columns. ### Arguments See DataPoolColumnConnection The list of measures (numeric columns) in the Data Pool. ### Arguments See DataPoolColumnConnection A list of setup tasks performed on the Data Pool during its most recent setup attempt. See DataPoolSetupTask Settings related to Data Pool syncing. See DataPoolSyncing The list of Syncs of the Data Pool. ### Arguments See SyncsFilter See SyncConnection The list of Metrics powered by the Data Pool. ### Arguments See MetricConnection The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See DeletionJobConnection The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See AddColumnToDataPoolJobConnection The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order. ### Arguments See UpdateDataPoolRecordsJobConnection Whether the Data Pool has access control enabled or not. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. A paginated list of Data Pool Access Policies available on the Data Pool. ### Arguments See DataPoolAccessPolicyConnection Validates a custom expression against the Data Pool's available columns. If the provided expression is invalid, the ValidateExpressionResult response will contain a reason explaining why. ### Arguments See ValidateExpressionResult The Data Pool's table settings. See TableSettings The Data Pool's columns that participate in its PARTITION BY clause. See DataPoolColumn The Data Pool's columns that participate in its PRIMARY KEY clause. See DataPoolColumn The Data Pool's columns that participate in its ORDER BY clause. See DataPoolColumn deprecated: Refer to `setupTasks` instead See Error The Data Pool's tenant ID, if configured. deprecated: Will be removed; use Data Pool Access Policies instead See Tenant The Data Pool's unique ID column. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated within the Data Pool. deprecated: Will be removed; use table settings to define the primary key. See UniqueId ## MetricConnection The Metric connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Metric connection's edges. See MetricEdge The Metric connection's nodes. See Metric The Metric connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## MetricEdge The Metric edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See Metric ## PolicyConnection The Policy connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Policy connection's edges. See PolicyEdge The Policy connection's nodes. See Policy The Policy connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## PolicyEdge The Policy edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See Policy ## SyncConnection The Sync connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Sync connection's edges. See SyncEdge The Sync connection's nodes. See Sync The Sync connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## SyncEdge The Sync edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See Sync ## TableConnection The table connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The time at which the tables were cached (i.e., the time at which they were introspected). The table connection's edges. See TableEdge The table connection's nodes. See Table The table connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## TableEdge The table edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See Table ## TableIntrospectionConnection The table introspection connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The table introspection connection's edges. See TableIntrospectionEdge The table introspection connection's nodes. See TableIntrospection The table introspection connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## TableIntrospectionEdge The table introspection edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See TableIntrospection ## UpdateDataPoolRecordsJobConnection The Update Data Pool records Job connection object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The Update Data Pool records Job connection's edges. See UpdateDataPoolRecordsJobEdge The Update Data Pool records Job connection's nodes. See UpdateDataPoolRecordsJob The Update Data Pool records Job connection's page info. The page info object used for pagination. Points to the first item returned in the results. Used when paginating backward. Points to the last item returned in the results. Used when paginating forward. A boolean that indicates whether a next page of results exists. Can be used to display a "next page" button in user interfaces, for example. A boolean that indicates whether a previous page of results exists. Can be used to display a "previous page" button in user interfaces, for example. ## UpdateDataPoolRecordsJobEdge The Update Data Pool records Job edge object. Learn more about [pagination in GraphQL](https://www.propeldata.com/docs/api/pagination). The edge's cursor. The edge's node. See UpdateDataPoolRecordsJob ## AmazonDataFirehoseConnectionSettings The Amazon Data Firehose Data Source's connection settings. Enables or disables access control for the Data Pool. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. HTTP basic access authentication credentials. You must configure these same credentials to be included in the `X-Amz-Firehose-Access-Key` header when Amazon Data Firehose issues requests to its custom HTTP endpoint. The HTTP Basic authentication settings. Username for HTTP Basic authentication that must be included in the Authorization header when uploading new data. Password for HTTP Basic authentication that must be included in the Authorization header when uploading new data. Additional columns for the table in Propel. A column in an Amazon Data Firehose Data Source's table. The column name. The JSON property that the column will be derived from. For example, if you send a JSON event like this: ```json theme={"system"} { "greeting": { "message": "hello, world" } } ``` Then you can use the JSON property "greeting.message" to extract "hello, world" to a column. The column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Whether the column's type is nullable or not. Copy this value into the URL field when configuring your Amazon Data Firehose to deliver to a custom HTTP endpoint. Override the Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse, and a default will be chosen based on the Data Pool's `timestamp` value, if any. You can override these defaults in order to specify a custom table engine, custom ORDER BY, etc. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. A Data Pool's table engine. See MergeTreeTableEngine See ReplacingMergeTreeTableEngine See SummingMergeTreeTableEngine See AggregatingMergeTreeTableEngine See PostgreSqlTableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The primary timestamp column, if any. Copy this value into the `X-Amz-Firehose-Access-Key` header when configuring your Amazon Data Firehose to deliver to a custom HTTP endpoint. ## AmazonDynamoDBConnectionSettings The Amazon DynamoDB Data Source's connection settings. Enables or disables access control for the Data Pool. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. HTTP basic access authentication credentials. You must configure these same credentials to be included in the `X-Amz-Firehose-Access-Key` header when Amazon Data Firehose transmits records from your DynamoDB table to its custom HTTP endpoint. The HTTP Basic authentication settings. Username for HTTP Basic authentication that must be included in the Authorization header when uploading new data. Password for HTTP Basic authentication that must be included in the Authorization header when uploading new data. Additional columns for the table in Propel. A column in an Amazon DynamoDB Data Source's table. The column name. The JSON property that the column will be derived from. For example, if you send a JSON event like this: ```json theme={"system"} { "greeting": { "message": "hello, world" } } ``` Then you can use the JSON property "greeting.message" to extract "hello, world" to a column. The column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Whether the column's type is nullable or not. Copy this value into the URL field when configuring your Amazon Data Firehose to transmit records from your DynamoDB table to a custom HTTP endpoint. Override the Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse, and a default will be chosen based on the Data Pool's `timestamp` value, if any. You can override these defaults in order to specify a custom table engine, custom ORDER BY, etc. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. A Data Pool's table engine. See MergeTreeTableEngine See ReplacingMergeTreeTableEngine See SummingMergeTreeTableEngine See AggregatingMergeTreeTableEngine See PostgreSqlTableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The primary timestamp column, if any. Copy this value into the `X-Amz-Firehose-Access-Key` header when configuring your Amazon Data Firehose to transmit records from your DynamoDB table to its custom HTTP endpoint. ## ClickHouseConnectionSettings The ClickHouse Data Source connection settings. Which database to connect to The password for the provided user Whether the user has readonly permissions or not for querying ClickHouse The URL where the ClickHouse host is listening to HTTP\[S] connections The user for authenticating against the ClickHouse host ## HttpConnectionSettings The HTTP Data Source connection settings. The HTTP Basic authentication settings for uploading new data. If this parameter is not provided, anyone with the URL to your tables will be able to upload data. While it's OK to test without HTTP Basic authentication, we recommend enabling it. The HTTP Basic authentication settings. Username for HTTP Basic authentication that must be included in the Authorization header when uploading new data. Password for HTTP Basic authentication that must be included in the Authorization header when uploading new data. The HTTP Data Source's tables. An HTTP Data Source's table. The ID of the table The name of the table All the columns present in the table A column in an HTTP Data Source's table. The column name. It has to be unique within a table. The column type. See ColumnType The ClickHouse type to use when `type` is set to `CLICKHOUSE`. Whether the column's type is nullable or not. ## KafkaConnectionSettings The Kafka Data Source connection settings. The type of authentication to use. Can be SCRAM-SHA-256, SCRAM-SHA-512, PLAIN or NONE The bootstrap server(s) to connect to The password for the provided user Whether the the connection to the Kafka servers is encrypted or not The user for authenticating against the Kafka servers ## PostgreSqlConnectionSettings The PostgreSQL Data Source connection settings. Which database to connect to The host where PostgreSQL is listening The port where PostgreSQL is listening (usually 5432) Which schema to use The user for authenticating against PostgreSQL ## S3ConnectionSettings The connection settings for an Amazon S3 Data Source. These include the Amazon S3 bucket name, the AWS access key ID, and the tables (along with their paths). We do not allow fetching the AWS secret access key after it has been set. The AWS access key ID for an IAM user with sufficient access to the Amazon S3 bucket. The name of the Amazon S3 bucket. The Amazon S3 Data Source's tables. An Amazon S3 Data Source's table. The ID of the table The name of the table The path to the table's files in Amazon S3. All the columns present in the table A column in an Amazon S3 Data Source's table. The column name. The column type. See ColumnType Whether the column's type is nullable or not. ## TwilioSegmentConnectionSettings The Twilio Segment Data Source connection settings. Enables or disables access control for the Data Pool. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. The HTTP basic authentication settings for the Twilio Segment Data Source URL. If this parameter is not provided, anyone with the webhook URL will be able to send events. While it's OK to test without HTTP Basic authentication, we recommend enabling it. The HTTP Basic authentication settings. Username for HTTP Basic authentication that must be included in the Authorization header when uploading new data. Password for HTTP Basic authentication that must be included in the Authorization header when uploading new data. The additional columns for the table in Propel. A column in a Twilio Segment Data Source's table. The column name. The JSON property that the column will be derived from. For example, if you POST a JSON event like this: ```json theme={"system"} { "greeting": { "message": "hello, world" } } ``` Then you can use the JSON property "greeting.message" to extract "hello, world" to a column. The column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Whether the column's type is nullable or not. Override the Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse, and a default will be chosen based on the Data Pool's `timestamp` and `uniqueId` values, if any. You can override these defaults in order to specify a custom table engine, custom ORDER BY, etc. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. A Data Pool's table engine. See MergeTreeTableEngine See ReplacingMergeTreeTableEngine See SummingMergeTreeTableEngine See AggregatingMergeTreeTableEngine See PostgreSqlTableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The primary timestamp column, if any. The webhook URL that Twilio Segment should POST events to. ## WebhookConnectionSettings The Webhook Data Source connection settings. Enables or disables access control for the Data Pool. If the Data Pool has access control enabled, Applications must be assigned Data Pool Access Policies in order to query the Data Pool and its Metrics. The HTTP basic authentication settings for the Webhook Data Source URL. If this parameter is not provided, anyone with the webhook URL will be able to send events. While it's OK to test without HTTP Basic authentication, we recommend enabling it. The HTTP Basic authentication settings. Username for HTTP Basic authentication that must be included in the Authorization header when uploading new data. Password for HTTP Basic authentication that must be included in the Authorization header when uploading new data. The additional columns for the table in Propel. A column in a Webhook Data Source's table. The column name. The JSON property that the column will be derived from. For example, if you POST a JSON event like this: ```json theme={"system"} { "greeting": { "message": "hello, world" } } ``` Then you can use the JSON property "greeting.message" to extract "hello, world" to a column. The column type. The Propel data types. * `BOOLEAN`: True or false. * `STRING`: A variable-length string. * `FLOAT`: A 32-bit signed double-precision floating point number. * `DOUBLE`: A 64-bit signed double-precision floating point number. * `INT8`: An 8-bit signed integer, with a minimum value of -2⁷ and a maximum value of 2⁷-1. * `INT16`: A 16-bit signed integer, with a minimum value of -2¹⁵ and a maximum value of 2¹⁵-1. * `INT32`: A 32-bit signed integer, with a minimum value of -2³¹ and a maximum value of 2³¹-1. * `INT64`: A 64-bit signed integer, with a minimum value of -2⁶³ and a maximum value of 2⁶³-1. * `DATE`: A date without a timestamp. For example, "YYYY-MM-DD". * `TIMESTAMP`: A date with a timestamp. For example, "yyy-MM-dd HH:mm:ss". * `JSON`: A JavaScript Object Notation (JSON) document. * `CLICKHOUSE`: A ClickHouse-specific type. Whether the column's type is nullable or not. Override the Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse, and a default will be chosen based on the Data Pool's `timestamp` and `uniqueId` values, if any. You can override these defaults in order to specify a custom table engine, custom ORDER BY, etc. A Data Pool's table settings. These describe how the Data Pool's table is created in ClickHouse. The ClickHouse table engine for the Data Pool's table. A Data Pool's table engine. See MergeTreeTableEngine See ReplacingMergeTreeTableEngine See SummingMergeTreeTableEngine See AggregatingMergeTreeTableEngine See PostgreSqlTableEngine The PARTITION BY clause for the Data Pool's table. The PRIMARY KEY clause for the Data Pool's table. The ORDER BY clause for the Data Pool's table. The TTL clause for the Data Pool's table. The primary timestamp column, if any. The Webhook URL for posting JSON events The tenant ID column, if any. deprecated: Will be removed; use Data Pool Access Policies instead. The unique ID column, if any. Propel uses the primary timestamp and a unique ID to compose a primary key for determining whether records should be inserted, deleted, or updated. deprecated: Will be removed; use Table Settings to define the primary key.