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https://issues.apache.org/jira/browse/SPARK-1476?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13968974#comment-13968974
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Patrick Wendell commented on SPARK-1476:
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Okay sounds good - a POC like that would be really helpful. We've run some very
large shuffles recently and couldn't isolate any problems except for
SPARK-1239, which should only be a small change.
If there are some smaller fixes you run into then by all means submit them
directly. If it requires large architectural changes I'd recommend having a
design doc before submitting a pull request, because people will want to
discuss the overall approach. I.e. we should avoid being "break-fix" and think
about the long term design implications of chagnes.
> 2GB limit in spark for blocks
> -----------------------------
>
> Key: SPARK-1476
> URL: https://issues.apache.org/jira/browse/SPARK-1476
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Environment: all
> Reporter: Mridul Muralidharan
> Assignee: Mridul Muralidharan
> Priority: Critical
> Fix For: 1.1.0
>
>
> 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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