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  1. Spark
  2. SPARK-24565

Add API for in Structured Streaming for exposing output rows of each microbatch as a DataFrame



    • Improvement
    • Status: Resolved
    • Major
    • Resolution: Fixed
    • 2.3.0
    • 2.4.0
    • Structured Streaming
    • None


      Currently, the micro-batches in the MicroBatchExecution is not exposed to the user through any public API. This was because we did not want to expose the micro-batches, so that all the APIs we expose, we can eventually support them in the Continuous engine. But now that we have a better sense of building a ContinuousExecution, I am considering adding APIs which will run only the MicroBatchExecution. I have quite a few use cases where exposing the micro-batch output as a dataframe is useful.

      • Pass the output rows of each batch to a library that is designed only the batch jobs (example, uses many ML libraries need to collect() while learning).
      • Reuse batch data sources for output whose streaming version does not exist (e.g. redshift data source).
      • Writer the output rows to multiple places by writing twice for each batch. This is not the most elegant thing to do for multiple-output streaming queries but is likely to be better than running two streaming queries processing the same data twice.

      The proposal is to add a method foreachBatch(f: Dataset[T] => Unit) to Scala/Java/Python DataStreamWriter.




            tdas Tathagata Das
            tdas Tathagata Das
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