[jira] [Work stopped] (KAFKA-3511) Add common aggregation functions like Sum and Avg as build-ins in Kafka Streams DSL

["Eno Thereska (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/KAFKA-3511?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Work on KAFKA-3511 stopped by Eno Thereska.
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> Add common aggregation functions like Sum and Avg as build-ins in Kafka Streams DSL
> -----------------------------------------------------------------------------------
>
>                 Key: KAFKA-3511
>                 URL: https://issues.apache.org/jira/browse/KAFKA-3511
>             Project: Kafka
>          Issue Type: Bug
>          Components: streams
>            Reporter: Guozhang Wang
>            Assignee: Eno Thereska
>              Labels: api
>             Fix For: 0.10.1.0
>
>
> Currently we have the following aggregation APIs in the Streams DSL:
> {code}
> KStream.aggregateByKey(..)
> KStream.reduceByKey(..)
> KStream.countByKey(..)
> KTable.groupBy(...).aggregate(..)
> KTable.groupBy(...).reduce(..)
> KTable.groupBy(...).count(..)
> {code}
> And it is better to add common aggregation functions like Sum and Avg as built-in into the Streams DSL. A few questions to ask though:
> 1. Should we add those built-in functions as, for example {{KTable.groupBy(...).sum(...)} or {{KTable.groupBy(...).aggregate(SUM, ...)}}. Please see the comments below for detailed pros and cons.
> 2. If we go with the second option above, should we replace the countByKey / count operators with aggregate(COUNT) as well? Personally I (Guozhang) feel it is not necessary, as COUNT is a special aggregate function since we do not need to map on any value fields; this is the same approach as in Spark as well, where Count is built-in as first-citizen in the DSL, and others are built-in as {{aggregate(SUM)}}, etc.



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