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https://issues.apache.org/jira/browse/KAFKA-3542?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15236304#comment-15236304
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Guozhang Wang commented on KAFKA-3542:
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[~gfodor] Kafka Streams already such kind of repartitioning in implementing its
join / aggregate operators in the high-level DSLs, where the intermediate topic
is created when building the topology and managed by the library itself. Are
there any issues that you cannot use its provided join operators directly?
> Add "repartition (+ join)" operations to streams
> ------------------------------------------------
>
> Key: KAFKA-3542
> URL: https://issues.apache.org/jira/browse/KAFKA-3542
> Project: Kafka
> Issue Type: Improvement
> Components: streams
> Affects Versions: 0.10.0.0
> Reporter: Greg Fodor
> Assignee: Guozhang Wang
> Priority: Minor
>
> A common operation in Kafka Streams seems to be to repartition the stream
> onto a different column, usually for joining. The current way I've been doing
> this:
> - Perform a map on the stream to the same value with a new key (the key we're
> going to join on, usually a foreign key)
> - Sink the stream into a new topic
> - Create a new stream sourcing that topic
> - Perform the join
> Note that without explicitly sinking the intermediate topic, the topology
> will fail to build because of the assertion that both sides of a join are
> connected to source nodes. When you perform a map, the link between the
> source nodes and the tail node of the topology is broken (by setting the
> source nodes to null) so you are forced to sink to use that output in a join.
> It seems that this pattern could possibly be rolled into much simpler
> operation(s). For example, the map could be changed into a "repartition"
> method where you just return the new key. And the join itself could be
> simplified by letting you specify a re-partition function on either side of
> the join and create the intermediate topic implicitly.
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