> ## Documentation Index
> Fetch the complete documentation index at: https://www.propeldata.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Mutations
> Available mutations in the Management API
## createEnvironment
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.
### Returns
Non-null
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.
See Account
## modifyEnvironment
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.
### Returns
Non-null
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.
See Account
## deleteEnvironment
Deletes a Environment by ID and returns its ID if the Environment was deleted successfully.
### Arguments
## createDataPoolAccessPolicy
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.
### Returns
Non-null
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.
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
## modifyDataPoolAccessPolicy
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.
### Returns
Non-null
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.
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
## deleteDataPoolAccessPolicy
Deletes a Data Pool Access Policy by ID and returns its ID if the Data Pool Access Policy was deleted successfully.
### Arguments
## assignDataPoolAccessPolicyToApplication
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
## unAssignDataPoolAccessPolicyFromApplication
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
## createApplication
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`.
### Returns
Nullable
ApplicationOrFailureResponse
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
## modifyApplication
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`.
### Returns
Nullable
ApplicationOrFailureResponse
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
## deleteApplication
Deletes an Application by ID and returns its ID if the Application was deleted successfully.
### Arguments
## deleteApplicationByName
Deletes an Application by unique name and returns its ID if the Application was deleted successfully.
### Arguments
## createSnowflakeDataSource
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.
### Returns
Nullable
DataSourceOrFailureResponse
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
## modifySnowflakeDataSource
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.
### Returns
Nullable
DataSourceOrFailureResponse
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
## reconnectDataSource
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.
### Returns
Nullable
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
The error object.
The error code.
The error message.
## introspectTables
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.
### Returns
Nullable
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
## testDataSource
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.
### Returns
Nullable
DataSourceOrFailureResponse
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
## deleteDataSource
Deletes a Data Source by ID and returns its ID if the Data Source was deleted successfully.
### Arguments
## deleteDataSourceByName
Deletes a Data Source by unique name and returns its ID if the Data Source was deleted successfully.
### Arguments
## createDataPoolV2
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.
### Returns
Nullable
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.
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 DataPoolColumndeprecated: 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
## modifyDataPool
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.
### Returns
Nullable
DataPoolOrFailureResponse
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
## retryDataPoolSetup
Retries to set up the Data Pool identified by the given ID.
### Arguments
### Returns
Nullable
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.
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` insteaddeprecated: 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.
## retryDataPoolSetupByName
Retries to set up the Data Pool identified by the given unique name.
### Arguments
### Returns
Nullable
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.
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` insteaddeprecated: 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.
## inspectDataPoolSchema
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.
### Returns
Nullable
DataPoolOrFailureResponse
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
## testDataPool
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.
### Returns
Nullable
DataPoolOrFailureResponse
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
## deleteDataPool
Deletes a Data Pool by ID and returns its ID if the Data Pool was deleted successfully.
### Arguments
## deleteDataPoolByName
Deletes a Data Pool by unique name and returns its ID if the Data Pool was deleted successfully.
### Arguments
## disableSyncing
Disables syncing of a Data Pool.
### Arguments
### Returns
Nullable
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.
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` insteaddeprecated: 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.
## enableSyncing
Re-enables syncing of a Data Pool.
### Arguments
### Returns
Nullable
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.
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` insteaddeprecated: 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.
## createCountMetric
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.
### Returns
Nullable
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.
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
## createCountDistinctMetric
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.
### Returns
Nullable
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.
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
## createSumMetric
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.
### Returns
Nullable
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.
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
## createAverageMetric
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.
### Returns
Nullable
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.
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
## createMinMetric
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.
### Returns
Nullable
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.
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
## createMaxMetric
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.
### Returns
Nullable
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.
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
## createCustomMetric
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.
### Returns
Nullable
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.
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
## modifyMetric
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.
### Returns
Nullable
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.
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
## migrateMetric
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.
### Returns
Nullable
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.
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
## deleteMetric
Deletes a Metric by ID and returns its ID if the Metric was deleted successfully.
### Arguments
## deleteMetricByName
Deletes a Metric by unique name and returns its ID if the Metric was deleted successfully.
### Arguments
## createBooster
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.
### Returns
Nullable
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.
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.
## deleteBooster
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
## createDeletionJob
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.
### Returns
Non-null
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.
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
## createAddColumnToDataPoolJob
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.
### Returns
Non-null
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.
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.
## createUpdateDataPoolRecordsJob
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.
### Returns
Non-null
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
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
## syncDataPool
Manually trigger a Sync for a Data Pool.
### Arguments
### Returns
Nullable
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.
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 DataPoolConnectiondeprecated: 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
## resyncDataPool
Manually trigger a re-Sync for a Data Pool.
### Arguments
### Returns
Nullable
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.
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 DataPoolConnectiondeprecated: 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
## createMaterializedView
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
### Returns
Non-null
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.
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
## modifyMaterializedView
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.
### Returns
Non-null
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.
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
## deleteMaterializedView
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
## createAmazonDataFirehoseDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## modifyAmazonDataFirehoseDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## createAmazonDynamoDBDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## modifyAmazonDynamoDBDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## createClickHouseDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## modifyClickHouseDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## createHttpDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## modifyHttpDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## createKafkaDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## modifyKafkaDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## createPostgreSqlDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## modifyPostgreSqlDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## createS3DataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## modifyS3DataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## createTwilioSegmentDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## modifyTwilioSegmentDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## createWebhookDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## modifyWebhookDataSource
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.
### Returns
Non-null
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.
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 DataPoolConnectiondeprecated: Refer to `checks` instead
See Error
## reconnectDataPool
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.
### Returns
Nullable
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.
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` insteaddeprecated: 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.
## createPolicy
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.
### Returns
Nullable
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.
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
## modifyPolicy
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.
### Returns
Nullable
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.
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
## deletePolicy
Deletes a Policy. The associated Application will no longer have access to the Metric's data.
deprecated: Use Data Pool Access Policies instead
### Arguments
## requestDelete
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.
### Returns
Non-null
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.
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