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  1. Spark
  2. SPARK-24156

Enable no-data micro batches for more eager streaming state clean up



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


      Currently, MicroBatchExecution in Structured Streaming runs batches only when there is new data to process. This is sensible in most cases as we dont want to unnecessarily use resources when there is nothing new to process. However, in some cases of stateful streaming queries, this delays state clean up as well as clean-up based output. For example, consider a streaming aggregation query with watermark-based state cleanup. The watermark is updated after every batch with new data completes. The updated value is used in the next batch to clean up state, and output finalized aggregates in append mode. However, if there is no data, then the next batch does not occur, and cleanup/output gets delayed unnecessarily. This is true for all stateful streaming operators - aggregation, deduplication, joins, mapGroupsWithState

      This issue tracks the work to enable no-data batches in MicroBatchExecution. The major challenge is that all the tests of relevant stateful operations add dummy data to force another batch for testing the state cleanup. So a lot of the tests are going to be changed. So my plan is to enable no-data batches for different stateful operators one at a time.




            tdas Tathagata Das
            tdas Tathagata Das
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