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https://issues.apache.org/jira/browse/SPARK-21641?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16199811#comment-16199811
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kant kodali commented on SPARK-21641:
-------------------------------------
[~marmbrus]
> Combining windowing (groupBy) and mapGroupsWithState (groupByKey) in Spark
> Structured Streaming
> -----------------------------------------------------------------------------------------------
>
> Key: SPARK-21641
> URL: https://issues.apache.org/jira/browse/SPARK-21641
> Project: Spark
> Issue Type: Improvement
> Components: Structured Streaming
> Affects Versions: 2.2.0
> Reporter: Tudor Miu
>
> Given a stream of timestamped data with watermarking, there seems to be no
> way to combine (1) the {{groupBy}} operation to achieve windowing by the
> timestamp field and other grouping criteria with (2) the {{groupByKey}}
> operation in order to apply {{mapGroupsWithState }}to the groups for custom
> sessionization.
> For context:
> - calling {{groupBy}}, which supports windowing, on a Dataset returns a
> {{RelationalGroupedDataset}} which does not have {{mapGroupsWithState}}.
> - calling {{groupByKey}}, which supports {{mapGroupsWithState}}, returns a
> {{KeyValueGroupedDataset}}, but that has no support for windowing.
> The suggestion is to _somehow_ unify the two APIs.
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