spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Hossein Falaki (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-17790) Support for parallelizing data.frame larger than 2GB
Date Wed, 05 Oct 2016 21:28:20 GMT

    [ https://issues.apache.org/jira/browse/SPARK-17790?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15549996#comment-15549996
] 

Hossein Falaki commented on SPARK-17790:
----------------------------------------

Thanks for pointing it out. SPARK-6235 seems to be an umbrella ticket. This  one can be a
subtask of it.

> 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: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org


Mime
View raw message