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https://issues.apache.org/jira/browse/SPARK-12635?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15095955#comment-15095955
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Dmitriy Selivanov commented on SPARK-12635:
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Thanks for clarification! I want to make a try, but not sure when I will have
enough time.
I have a question. Why not just use org.rosuda.REngine.REXP class from rJava
and don't create data.frame at jvm side? http://rforge.net/org/doc/
>From a brief look over sparkR code I can't understand why we reimplement
>binary interface between R and java. Why don't we use existing interface? (I
>can miss something). Also I see this 1 year old thread:
>https://sparkr.atlassian.net/browse/SPARKR-145, but it ends with no decision.
> More efficient (column batch) serialization for Python/R
> --------------------------------------------------------
>
> Key: SPARK-12635
> URL: https://issues.apache.org/jira/browse/SPARK-12635
> Project: Spark
> Issue Type: New Feature
> Components: PySpark, SparkR, SQL
> Reporter: Reynold Xin
>
> Serialization between Scala / Python / R is pretty slow. Python and R both
> work pretty well with column batch interface (e.g. numpy arrays). Technically
> we should be able to just pass column batches around with minimal
> serialization (maybe even zero copy memory).
> Note that this depends on some internal refactoring to use a column batch
> interface in Spark SQL.
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