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https://issues.apache.org/jira/browse/SPARK-14746?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15250229#comment-15250229
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Shivaram Venkataraman commented on SPARK-14746:
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Yeah I can see that RDD pipe is limited and it would be good to have some
better support for calling into R from a Scala / Java environment. However I
feel this is introducing a new paradigm in DataFrame / Spark where one can mix
and match languages (so far we have built things to be used in Python / R) and
I don't know if this is a route we want to go down ([~rxin] ?) . My other
reason considering this as lower priority is that this is useful for users who
are proficient in more than 1 language which I think is a smaller set of users.
> Support transformations in R source code for Dataset/DataFrame
> --------------------------------------------------------------
>
> Key: SPARK-14746
> URL: https://issues.apache.org/jira/browse/SPARK-14746
> Project: Spark
> Issue Type: New Feature
> Components: SparkR, SQL
> Reporter: Sun Rui
>
> there actually is a desired scenario mentioned several times in the Spark
> mailing list that users are writing Scala/Java Spark applications (not
> SparkR) but want to use R functions in some transformations. typically this
> can be achieved by calling Pipe() in RDD. However, there are limitations on
> pipe(). So we can support applying a R function in source code format to a
> Dataset/DataFrame (Thus SparkR is not needed for serializing an R function.)
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