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https://issues.apache.org/jira/browse/SPARK-1476?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13967720#comment-13967720
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Patrick Wendell edited comment on SPARK-1476 at 4/13/14 3:35 AM:
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This says it's a "severe limitation" - but why not just use more, smaller
blocks? I think Spark's design assumes in various places that block's are not
extremely large. Think of it like e.g. the HDFS block size... it can't be
arbitrary large.
was (Author: pwendell):
This says it's a "severe limitation" - but why not just use more, smaller
blocks? I Spark's design assumes in various places that block's are not
extremely large. Think of it like e.g. the HDFS block size... it can't be
arbitrary large.
> 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
> 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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