[GitHub] [airflow] mik-laj commented on pull request #8809: [AIRFLOW-6294] Create guide for Dataflow operators

[GitBox <gi...@apache.org>]

mik-laj commented on pull request #8809:
URL: https://github.com/apache/airflow/pull/8809#issuecomment-626441074


   In my opinion, we need to add some information.
   * new section which will describe the ways to run a pipeline. Currently, the pipeline can be started using a local running executable (DataflowCreateJavaJobOperator, DataflowCreatePythonJobOperator) or Dataflow Template (DataflowTemplatedJobStartOperator) or via KubernetesPodOperator). A description that describes the differences between these methods would be useful.
   * A new section that will describe the differences between asynchronic and blocking execution modes. You should not use blocking pipelines, because it causes a background process to run, which supervises the execution of the job, This is not positive for two reasons - increase consumption of resources and prevents Airflow supervision over the job
   * information that Python operators allow you to specify the Apache Beam version, but if no version is specified, the local version from the environment will be used
   
   


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