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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/02/13 08:51:00 UTC
[jira] [Resolved] (SPARK-26858) Vectorized gapplyCollect, Arrow
optimization in native R function execution
[ https://issues.apache.org/jira/browse/SPARK-26858?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-26858.
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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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