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https://issues.apache.org/jira/browse/SPARK-1476?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16998752#comment-16998752
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Shirish commented on SPARK-1476:
--------------------------------
This is an old chain that I happen to land on to. I am interested in the
following points mentioned by [~mridulm80]. Did anyone ever get to
implementing MultiOutputs map without needing to use cache? If not, is there a
pointer I can get on how to get started.
_"_[~matei] _Interesting that you should mention about splitting output of a
map into multiple blocks__._
_We are actually thinking about that in a different context - akin to
MultiOutputs in hadoop or SPLIT in pig : without needing to cache the
intermediate output; but directly emit values to different blocks/rdd's based
on the output of a map or some such."_
> 2GB limit in spark for blocks
> -----------------------------
>
> Key: SPARK-1476
> URL: https://issues.apache.org/jira/browse/SPARK-1476
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Environment: all
> Reporter: Mridul Muralidharan
> Priority: Critical
> Attachments: 2g_fix_proposal.pdf
>
>
> The underlying abstraction for blocks in spark is a ByteBuffer : which limits
> the size of the block to 2GB.
> This has implication not just for managed blocks in use, but also for shuffle
> blocks (memory mapped blocks are limited to 2gig, even though the api allows
> for long), ser-deser via byte array backed outstreams (SPARK-1391), etc.
> This is a severe limitation for use of spark when used on non trivial
> datasets.
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