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https://issues.apache.org/jira/browse/SPARK-28650?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Shixiong Zhu resolved SPARK-28650.
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Fix Version/s: 2.4.5
Assignee: Jungtaek Lim
Resolution: Fixed
> Fix the guarantee of ForeachWriter
> ----------------------------------
>
> Key: SPARK-28650
> URL: https://issues.apache.org/jira/browse/SPARK-28650
> Project: Spark
> Issue Type: Documentation
> Components: Structured Streaming
> Affects Versions: 2.4.3
> Reporter: Shixiong Zhu
> Assignee: Jungtaek Lim
> Priority: Major
> Fix For: 2.4.5
>
>
> Right now ForeachWriter has the following guarantee:
> {code}
> If the streaming query is being executed in the micro-batch mode, then every
> partition
> represented by a unique tuple (partitionId, epochId) is guaranteed to have
> the same data.
> Hence, (partitionId, epochId) can be used to deduplicate and/or
> transactionally commit data
> and achieve exactly-once guarantees.
> {code}
>
> But we can break this easily actually when restarting a query but a batch is
> re-run (e.g., upgrade Spark)
> * Source returns a different DataFrame that has a different partition number
> (e.g., we start to not create empty partitions in Kafka Source V2).
> * A new added optimization rule may change the number of partitions in the
> new run.
> * Change the file split size in the new run.
> Since we cannot guarantee that the same (partitionId, epochId) has the same
> data. We should update the document for "ForeachWriter".
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