[
https://issues.apache.org/jira/browse/SPARK-26858?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16766943#comment-16766943
]
Hyukjin Kwon commented on SPARK-26858:
--------------------------------------
BTW, just for clarification, in case of the way 1., the code changes are not a
lot but pretty hacky to transfer schema read from Arrow batch.
I think we had similar discussion about this in Pandas Grouped Map and ended up
with forcing users to set the explicit schema.
> 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.
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
