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From "Hyukjin Kwon (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (SPARK-26858) Vectorized gapplyCollect, Arrow optimization in native R function execution
Date Wed, 13 Feb 2019 08:51:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-26858?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Hyukjin Kwon resolved SPARK-26858.
----------------------------------
    Resolution: Later

> Vectorized gapplyCollect, Arrow optimization in native R function execution
> ---------------------------------------------------------------------------
>
>                 Key: SPARK-26858
>                 URL: https://issues.apache.org/jira/browse/SPARK-26858
>             Project: Spark
>          Issue Type: Sub-task
>          Components: SparkR, SQL
>    Affects Versions: 3.0.0
>            Reporter: Hyukjin Kwon
>            Assignee: Hyukjin Kwon
>            Priority: Major
>
> Unlike gapply, gapplyCollect requires additional ser/de steps because it can omit the
schema, and Spark SQL doesn't know the return type before actually execution happens.
> In original code path, it's done via using binary schema. Once gapply is done (SPARK-26761).
we can mimic this approach in vectorized gapply to support gapplyCollect.



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