airflow.providers.amazon.aws.operators.quicksight¶
Module Contents¶
Classes¶
Creates and starts a new SPICE ingestion for a dataset. |
Attributes¶
- 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.BaseOperatorCreates 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 create ingestion
- 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 (str | None) – Which AWS region the connection should use. (templated) If this is None or empty then the default boto3 behaviour is used.