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Azure Data Factory Operators
============================
Azure Data Factory is Azure's cloud ETL service for scale-out serverless data integration and data transformation.
It offers a code-free UI for intuitive authoring and single-pane-of-glass monitoring and management.

.. _howto/operator:AzureDataFactoryRunPipelineOperator:

AzureDataFactoryRunPipelineOperator
-----------------------------------
Use the :class:`~airflow.providers.microsoft.azure.operators.data_factory.AzureDataFactoryRunPipelineOperator` to execute a pipeline within a data factory.
By default, the operator will periodically check on the status of the executed pipeline to terminate with a "Succeeded" status.
This functionality can be disabled for an asynchronous wait -- typically with the :class:`~airflow.providers.microsoft.azure.sensors.data_factory.AzureDataFactoryPipelineRunSensor` -- by setting ``wait_for_termination`` to False.

Below is an example of using this operator to execute an Azure Data Factory pipeline.

  .. exampleinclude:: /../../tests/system/providers/microsoft/azure/example_adf_run_pipeline.py
      :language: python
      :dedent: 0
      :start-after: [START howto_operator_adf_run_pipeline]
      :end-before: [END howto_operator_adf_run_pipeline]

Here is a different example of using this operator to execute a pipeline but coupled with the :class:`~airflow.providers.microsoft.azure.sensors.data_factory.AzureDataFactoryPipelineRunSensor` to perform an asynchronous wait.

    .. exampleinclude:: /../../tests/system/providers/microsoft/azure/example_adf_run_pipeline.py
        :language: python
        :dedent: 0
        :start-after: [START howto_operator_adf_run_pipeline_async]
        :end-before: [END howto_operator_adf_run_pipeline_async]

Reference
---------

For further information, please refer to the Microsoft documentation:

  * `Azure Data Factory Documentation <https://docs.microsoft.com/en-us/azure/data-factory/>`__