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https://issues.apache.org/jira/browse/SPARK-20414?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon updated SPARK-20414:
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Labels: bulk-closed (was: )
> 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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