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https://issues.apache.org/jira/browse/KAFKA-7293?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16722943#comment-16722943
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Matthias J. Sax commented on KAFKA-7293:
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>From my understanding, nothing would happen (ie, no exception) but the
>computation will we executed, but compute an incorrect result.
> Merge followed by groupByKey/join might violate co-partioning
> -------------------------------------------------------------
>
> Key: KAFKA-7293
> URL: https://issues.apache.org/jira/browse/KAFKA-7293
> Project: Kafka
> Issue Type: Improvement
> Components: streams
> Reporter: Matthias J. Sax
> Priority: Major
>
> The merge() operations can be applied to input KStreams that have a different
> number of tasks (ie, input topic partitions). For this case, the input topics
> are not co-partitioned and thus the result KStream is not partitioned even if
> each input KStream is partitioned by its own.
> Because, no "repartitionRequired" flag is set on the input KStreams, the flag
> is also not set on the output KStream. Hence, if a groupByKey() or join()
> operation is applied the output KStream, we don't insert a repartition topic.
> However, repartitioning would be required because the KStream is not
> partitioned.
> We cannot detect this during compile time, because the number or partitions
> is unknown, and thus, we cannot decide if repartitioning is required or not.
> However, we can add a runtime check similar to joins() that checks if data is
> correctly (co-)partitioned and if not, we can raise a runtime exception.
> Note, for merge() in contrast to join(), we should only check for
> co-partitioning, if the merge() is followed by a groupByKey() or join()
> operations.
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