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https://issues.apache.org/jira/browse/SPARK-26759?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon updated SPARK-26759:
---------------------------------
Fix Version/s: 3.0.0
> Arrow optimization in SparkR's interoperability
> -----------------------------------------------
>
> Key: SPARK-26759
> URL: https://issues.apache.org/jira/browse/SPARK-26759
> Project: Spark
> Issue Type: Umbrella
> Components: SparkR, SQL
> Affects Versions: 3.0.0
> Reporter: Hyukjin Kwon
> Assignee: Hyukjin Kwon
> Priority: Major
> Labels: release-notes
> Fix For: 3.0.0
>
>
> Arrow 0.12.0 is release and it contains R API. We could optimize Spark
> DaraFrame <> R DataFrame interoperability.
> For instance see the examples below:
> - {{dapply}}
> {code:java}
> df <- createDataFrame(mtcars)
> collect(dapply(df,
> function(r.data.frame) {
> data.frame(r.data.frame$gear)
> },
> structType("gear long")))
> {code}
> - {{gapply}}
> {code:java}
> df <- createDataFrame(mtcars)
> collect(gapply(df,
> "gear",
> function(key, group) {
> data.frame(gear = key[[1]], disp = mean(group$disp) >
> group$disp)
> },
> structType("gear double, disp boolean")))
> {code}
> - R DataFrame -> Spark DataFrame
> {code:java}
> createDataFrame(mtcars)
> {code}
> - Spark DataFrame -> R DataFrame
> {code:java}
> collect(df)
> head(df)
> {code}
> Currently, some of communication path between R side and JVM side has to
> buffer the data and flush it at once due to ARROW-4512. I don't target to fix
> it under this umbrella.
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