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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2019/06/03 09:52:00 UTC

[jira] [Assigned] (SPARK-27925) Better control numBins of curves in BinaryClassificationMetrics

     [ https://issues.apache.org/jira/browse/SPARK-27925?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-27925:
------------------------------------

    Assignee: Apache Spark

> Better control numBins of curves in BinaryClassificationMetrics
> ---------------------------------------------------------------
>
>                 Key: SPARK-27925
>                 URL: https://issues.apache.org/jira/browse/SPARK-27925
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>    Affects Versions: 3.0.0
>            Reporter: zhengruifeng
>            Assignee: Apache Spark
>            Priority: Major
>
> In case of large datasets with tens of thousands of partitions, current curve down-sampling method tend to generate much more bins than the value set by #numBins.
> Since in current impl, grouping is done within partitions, that is to say, each partition contains at least one bin.
> A more reasonable way is to bring the grouping op forward into the sort op, then we can directly set the #bins as the #partitions, and regard one partition as one bin.
>  



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