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https://issues.apache.org/jira/browse/SPARK-24156?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wenchen Fan resolved SPARK-24156.
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Resolution: Fixed
Fix Version/s: 2.4.0
> Enable no-data micro batches for more eager streaming state clean up
> ---------------------------------------------------------------------
>
> Key: SPARK-24156
> URL: https://issues.apache.org/jira/browse/SPARK-24156
> Project: Spark
> Issue Type: Improvement
> Components: Structured Streaming
> Affects Versions: 2.3.0
> Reporter: Tathagata Das
> Assignee: Tathagata Das
> Priority: Major
> Fix For: 2.4.0
>
>
> 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.
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