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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 04:15:09 UTC

[jira] [Resolved] (SPARK-20414) avoid creating only 16 reducers when calling topByKey()

     [ https://issues.apache.org/jira/browse/SPARK-20414?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-20414.
----------------------------------
    Resolution: Incomplete

> avoid creating only 16 reducers when calling topByKey()
> -------------------------------------------------------
>
>                 Key: SPARK-20414
>                 URL: https://issues.apache.org/jira/browse/SPARK-20414
>             Project: Spark
>          Issue Type: Improvement
>          Components: MLlib
>    Affects Versions: 2.1.0
>            Reporter: Yang Yang
>            Priority: Minor
>              Labels: bulk-closed
>
> currently in the MLlib topByKey() function, it directly calls aggregateByKey(), which by default uses very few partitions/reducers, in my experience I see only 16 reducers for a 100GB input.
> the aggregateByKey() has an optional reducer count, adding this option to the top level topByKey()



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