airflow.providers.amazon.aws.operators.quicksight

Module Contents

Classes

QuickSightCreateIngestionOperator

Creates and starts a new SPICE ingestion for a dataset.

Attributes

DEFAULT_CONN_ID

airflow.providers.amazon.aws.operators.quicksight.DEFAULT_CONN_ID = aws_default[source]
class airflow.providers.amazon.aws.operators.quicksight.QuickSightCreateIngestionOperator(data_set_id, ingestion_id, ingestion_type='FULL_REFRESH', wait_for_completion=True, check_interval=30, aws_conn_id=DEFAULT_CONN_ID, region=None, **kwargs)[source]

Bases: airflow.models.BaseOperator

Creates and starts a new SPICE ingestion for a dataset. Also, helps to Refresh existing SPICE datasets.

See also

For more information on how to use this operator, take a look at the guide: Amazon QuickSight CreateIngestion Operator

Parameters

  • data_set_id (str) -- ID of the dataset used in the ingestion.

  • ingestion_id (str) -- ID for the ingestion.

  • ingestion_type (str) -- Type of ingestion. Values Can be INCREMENTAL_REFRESH or FULL_REFRESH. Default FULL_REFRESH.

  • wait_for_completion (bool) -- If wait is set to True, the time interval, in seconds, that the operation waits to check the status of the Amazon QuickSight Ingestion.

  • check_interval (int) -- if wait is set to be true, this is the time interval in seconds which the operator will check the status of the Amazon QuickSight Ingestion

  • aws_conn_id (str) -- The Airflow connection used for AWS credentials. (templated) If this is None or empty then the default boto3 behaviour is used. If running Airflow in a distributed manner and aws_conn_id is None or empty, then the default boto3 configuration would be used (and must be maintained on each worker node).

  • region (Optional[str]) -- Which AWS region the connection should use. (templated) If this is None or empty then the default boto3 behaviour is used.

template_fields :Sequence[str] = ['data_set_id', 'ingestion_id', 'ingestion_type', 'wait_for_completion', 'check_interval',...[source]
ui_color = #ffd700[source]
execute(self, context)[source]

This is the main method to derive when creating an operator. Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

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