[
https://issues.apache.org/jira/browse/SPARK-17790?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15549980#comment-15549980
]
Sean Owen commented on SPARK-17790:
-----------------------------------
This duplicates https://issues.apache.org/jira/browse/SPARK-6235 ? or is a
subset?
> Support for parallelizing data.frame larger than 2GB
> ----------------------------------------------------
>
> Key: SPARK-17790
> URL: https://issues.apache.org/jira/browse/SPARK-17790
> Project: Spark
> Issue Type: Story
> 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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
