[jira] [Created] (SPARK-21641) Combining windowing (groupBy) and mapGroupsWithState (groupByKey) in Spark Structured Streaming

["Tudor Miu (JIRA)" <ji...@apache.org>]

Tudor Miu created SPARK-21641:
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             Summary: 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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