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https://issues.apache.org/jira/browse/KAFKA-3576?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15328242#comment-15328242
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Matthias J. Sax commented on KAFKA-3576:
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I see two points:
(1) this is similar to SQL / Pig or Spark DSL (this was also the motivation for
[KAFKA-3337])
(2) user ofter forgot the {{through()}} in
{{stream.selectKey(...).through(...).aggregateByKey(...)}} which is a
no-intuitive operation
(2a) even if [KAFKA-3561] tackles the {{through}} problem, an explicit
{{groupBy}} makes the re-distribution overhead explicit
> Unify KStream and KTable API
> ----------------------------
>
> Key: KAFKA-3576
> URL: https://issues.apache.org/jira/browse/KAFKA-3576
> Project: Kafka
> Issue Type: Sub-task
> Components: streams
> Reporter: Matthias J. Sax
> Assignee: Guozhang Wang
> Labels: api
> Fix For: 0.10.1.0
>
>
> For KTable aggregations, it has a pattern of
> {{table.groupBy(...).aggregate(...)}}, and the data is repartitioned in an
> inner topic based on the selected key in {{groupBy(...)}}.
> For KStream aggregations, though, it has a pattern of
> {{stream.selectKey(...).through(...).aggregateByKey(...)}}. In other words,
> users need to manually use a topic to repartition data, and the syntax is a
> bit different with KTable as well.
> h2. Goal
> To have similar APIs for aggregations of KStream and KTable
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