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https://issues.apache.org/jira/browse/SPARK-1476?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14099072#comment-14099072
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Mridul Muralidharan commented on SPARK-1476:
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Based on discussions we had with others, apparently 1.1 was not a good vehicle
for this proposal.
Further, since there was no interest in this jira/comments on the proposal, we
put the effort on the backburner.
We plan to push atleast some of the bugs fixed as part of this effort -
consolidated shuffle did get resolved in 1.1 and probably a few more might be
contributed back in 1.2 time permitting (disk backed map output tracking for
example looks like a good candidate).
But bulk of the change is pervasive and at times a bit invasive and at odds
with some of the other changes (for example, zero-copy); shepherding it might
be a bit time consuming for me given other deliverables.
If there is renewed interest in this to get it integrated into a spark release,
I can try to push for it to be resurrected and submitted.
> 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
> Assignee: 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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