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
Returns
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.
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
Returns
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.
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: UsefilterSql insteadThe fields of a filter.
You can construct more complex filters using and and or. For example, to construct a filter equivalent to
(value > 0 AND value <= 100) OR status = "confirmed"
you could write
{
"column": "value",
"operator": "GREATER_THAN",
"value": "0",
"and": [{
"column": "value",
"operator": "LESS_THAN_OR_EQUAL_TO",
"value": "0"
}],
"or": [{
"column": "status",
"operator": "EQUALS",
"value": "confirmed"
}]
}
Note that and takes precedence over or.
The name of the column to filter on.
The operation to perform when comparing the column and filter values.
See FilterOperator
The value to compare the column to.
Additional filters to AND with this one. AND takes precedence over OR.
Additional filters to OR with this one. AND takes precedence over OR.
Returns
The 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 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.
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
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: UsefilterSql insteadThe fields of a filter.
You can construct more complex filters using and and or. For example, to construct a filter equivalent to
(value > 0 AND value <= 100) OR status = "confirmed"
you could write
{
"column": "value",
"operator": "GREATER_THAN",
"value": "0",
"and": [{
"column": "value",
"operator": "LESS_THAN_OR_EQUAL_TO",
"value": "0"
}],
"or": [{
"column": "status",
"operator": "EQUALS",
"value": "confirmed"
}]
}
Note that and takes precedence over or.
The name of the column to filter on.
The operation to perform when comparing the column and filter values.
See FilterOperator
The value to compare the column to.
Additional filters to AND with this one. AND takes precedence over OR.
Additional filters to OR with this one. AND takes precedence over OR.
Returns
The 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 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.
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
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
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 secondP1_SMALL: Max records per second: 25,000,000 records per secondP1_MEDIUM: Max records per second: 100,000,000 records per secondP1_LARGE: Max records per second: 250,000,000 records per secondP1_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
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
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 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 secondP1_SMALL: Max records per second: 25,000,000 records per secondP1_MEDIUM: Max records per second: 100,000,000 records per secondP1_LARGE: Max records per second: 250,000,000 records per secondP1_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
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
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
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
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 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
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
reconnectDataSource
Attempts to reconnect a Data Source. The mutation then returns the Data Source object.
Arguments
Returns
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 Data Source’s creation date and time in UTC.
The Data Source’s last modification date and time in UTC.
The Data Source’s creator. It can be either a User ID, an Application ID, or “system” if it was created by Propel.
The Data Source’s last modifier. It can be either a User ID, an Application ID, or “system” if it was modified by Propel.
The Data Source’s type.
The types of Data Sources.
WEBHOOK: Indicates a Webhook Data Source.TWILIO_SEGMENT: Indicates a Twilio Segment Data Source.S3: Indicates an Amazon S3 Data Source.Redshift: Indicates a Redshift Data Source.POSTGRESQL: Indicates a PostgreSQL Data Source.KAFKA: Indicates a Kafka Data Source.Http: Indicates an Http Data Source.CLICKHOUSE: Indicates a ClickHouse Data Source.AMAZON_DYNAMODB: Indicates an Amazon DynamoDB Data Source.AMAZON_DATA_FIREHOSE: Indicates an Amazon Data Firehose Data Source.Snowflake: Indicates a Snowflake Data Source.INTERNAL: Indicates an internal Data Source.
The Data Source’s status.
The status of a Data Source.
CREATED: The Data Source has been created, but it is not connected yet.CONNECTING: Propel is attempting to connect the Data Source.CONNECTED: The Data Source is connected.BROKEN: The Data Source failed to connect.DELETING: Propel is deleting the Data Source.
The Data Source’s connection settings.
The 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
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).
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
introspectTables
Introspects the tables in a Data Source.
Returns the tables along with when they were last cached from the Data Source.
Arguments
Returns
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.
testDataSource
Tests that Propel can actually connect to the data warehouse. Updates the status.
Arguments
Returns
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
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.
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.
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 insteadThe 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
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 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 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 list of measures (numeric columns) in the Data Pool.
Arguments
A list of setup tasks performed on the Data Pool during its most recent setup attempt.
Settings related to Data Pool syncing.
See DataPoolSyncing
The Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order.
Arguments
The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order.
Arguments
The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order.
Arguments
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
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
The Data Pool’s table settings.
See TableSettings
The Data Pool’s columns that participate in its PARTITION BY clause.
See DataPoolColumn
The Data Pool’s columns that participate in its PRIMARY KEY clause.
See DataPoolColumn
The Data Pool’s columns that participate in its ORDER BY clause.
See DataPoolColumn
The Data Pool’s tenant ID, if configured.
deprecated: Will be removed; use Data Pool Access Policies insteadSee 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 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.
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
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.
retryDataPoolSetup
Retries to set up the Data Pool identified by the given ID.
Arguments
Returns
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 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.CONNECTINGCONNECTEDBROKENPAUSINGPAUSEDDELETING: 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.
The Data Pool column connection’s edges.
The Data Pool column connection’s nodes.
See DataPoolColumn
The list of measures (numeric columns) in the Data Pool.
Arguments
The Data Pool column connection object.
Learn more about pagination in GraphQL.
The Data Pool column connection’s edges.
The Data Pool column connection’s nodes.
See DataPoolColumn
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).
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.
The syncing interval.
Note that the syncing interval is approximate. For example, setting the syncing interval to EVERY_1_HOUR
does not mean that syncing will occur exactly on the hour. Instead, the syncing interval starts relative to
when the Data Pool goes LIVE, and Propel will attempt to sync approximately every hour. Additionally,
if you pause or resume syncing, this too can shift the syncing interval around.
The 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 Deletion Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order.
Arguments
The Add Column Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order.
Arguments
The UpdateDataPoolRecords Jobs that were historically issued to this Data Pool, sorted by creation time, in descending order.
Arguments
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
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.