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https://issues.apache.org/jira/browse/KAFKA-3337?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15244674#comment-15244674
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ASF GitHub Bot commented on KAFKA-3337:
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GitHub user mjsax opened a pull request:
https://github.com/apache/kafka/pull/1231
KAFKA-3337: [WIP] Extract selector as a separate groupBy operator for
KTable aggregations
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/mjsax/kafka
kafka-3337-extact-key-selector-from-agg
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/kafka/pull/1231.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #1231
----
commit 8b6e3f6b9097ae78e1737bf1fadd3647d8a20a5d
Author: Matthias J. Sax <[email protected]>
Date: 2016-04-17T12:24:29Z
KAFKA-3337: [WIP] Extract selector as a separate groupBy operator for
KTable aggregations
----
> Extract selector as a separate groupBy operator for KTable aggregations
> -----------------------------------------------------------------------
>
> Key: KAFKA-3337
> URL: https://issues.apache.org/jira/browse/KAFKA-3337
> Project: Kafka
> Issue Type: Sub-task
> Components: streams
> Reporter: Guozhang Wang
> Assignee: Matthias J. Sax
> Labels: api, newbie++
> Fix For: 0.10.0.0
>
>
> Currently KTable aggregation takes a selector used for selecting the
> aggregate key.and an aggregator for aggregating the values with the same
> selected key, which makes the function a little bit "heavy":
> {code}
> table.groupBy(initializer, adder, substractor, selector, /* optional serde*/);
> {code}
> It is better to extract the selector in a separate groupBy function such that
> {code}
> KTableGrouped KTable#groupBy(selector);
> KTable KTableGrouped#aggregate(initializer, adder, substractor, /* optional
> serde*/);
> {code}
> Note that "KTableGrouped" only have APIs for aggregate and reduce, and none
> else. So users have to follow the pattern below:
> {code}
> table.groupBy(...).aggregate(...);
> {code}
> This pattern is more natural for users who are familiar with SQL / Pig or
> Spark DSL, etc.
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