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from __future__ import annotations

from typing import TYPE_CHECKING, Sequence

from airflow.models import BaseOperator
from import QuickSightHook

    from airflow.utils.context import Context

[docs]DEFAULT_CONN_ID = "aws_default"
[docs]class QuickSightCreateIngestionOperator(BaseOperator): """ Creates and starts a new SPICE ingestion for a dataset. Also, helps to Refresh existing SPICE datasets. .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:QuickSightCreateIngestionOperator` :param data_set_id: ID of the dataset used in the ingestion. :param ingestion_id: ID for the ingestion. :param ingestion_type: Type of ingestion. Values Can be INCREMENTAL_REFRESH or FULL_REFRESH. Default FULL_REFRESH. :param wait_for_completion: If wait is set to True, the time interval, in seconds, that the operation waits to check the status of the Amazon QuickSight Ingestion. :param check_interval: 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 :param aws_conn_id: 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). :param region: Which AWS region the connection should use. (templated) If this is None or empty then the default boto3 behaviour is used. """
[docs] template_fields: Sequence[str] = ( "data_set_id", "ingestion_id", "ingestion_type", "wait_for_completion", "check_interval", "aws_conn_id", "region",
[docs] ui_color = "#ffd700"
def __init__( self, data_set_id: str, ingestion_id: str, ingestion_type: str = "FULL_REFRESH", wait_for_completion: bool = True, check_interval: int = 30, aws_conn_id: str = DEFAULT_CONN_ID, region: str | None = None, **kwargs, ): self.data_set_id = data_set_id self.ingestion_id = ingestion_id self.ingestion_type = ingestion_type self.wait_for_completion = wait_for_completion self.check_interval = check_interval self.aws_conn_id = aws_conn_id self.region = region super().__init__(**kwargs)
[docs] def execute(self, context: Context): hook = QuickSightHook( aws_conn_id=self.aws_conn_id, region_name=self.region, )"Running the Amazon QuickSight SPICE Ingestion on Dataset ID: %s", self.data_set_id) return hook.create_ingestion( data_set_id=self.data_set_id, ingestion_id=self.ingestion_id, ingestion_type=self.ingestion_type, wait_for_completion=self.wait_for_completion, check_interval=self.check_interval,

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