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https://issues.apache.org/jira/browse/SPARK-17790?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hossein Falaki updated SPARK-17790:
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Summary: Support for parallelizing R data.frame larger than 2GB (was:
Support for parallelizing data.frame larger than 2GB)
> Support for parallelizing R data.frame larger than 2GB
> ------------------------------------------------------
>
> Key: SPARK-17790
> URL: https://issues.apache.org/jira/browse/SPARK-17790
> Project: Spark
> Issue Type: Sub-task
> Components: SparkR
> Affects Versions: 2.0.1
> Reporter: Hossein Falaki
>
> This issue is a more specific version of SPARK-17762.
> Supporting larger than 2GB arguments is more general and arguably harder to
> do because the limit exists both in R and JVM (because we receive data as a
> ByteArray). However, to support parallalizing R data.frames that are larger
> than 2GB we can do what PySpark does.
> PySpark uses files to transfer bulk data between Python and JVM. It has
> worked well for the large community of Spark Python users.
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