[jira] [Assigned] (KAFKA-7293) Merge followed by groupByKey/join might violate co-partioning

["Lee Dongjin (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/KAFKA-7293?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Lee Dongjin reassigned KAFKA-7293:
----------------------------------

    Assignee: Lee Dongjin

> 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
>            Assignee: Lee Dongjin
>            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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