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https://issues.apache.org/jira/browse/SPARK-2532?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14148666#comment-14148666
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Andrew Ash commented on SPARK-2532:
-----------------------------------
[~pwendell] should we close this ticket and track the individual items
separately? It sounds like we should expect consolidated shuffle to work in
1.1 and any issues should have separate tickets filed for them. I know
[~mridulm80] has several fixes on his branch that should be cherry picked over
at some point as well though.
> Fix issues with consolidated shuffle
> ------------------------------------
>
> Key: SPARK-2532
> URL: https://issues.apache.org/jira/browse/SPARK-2532
> Project: Spark
> Issue Type: Bug
> Components: Shuffle, Spark Core
> Affects Versions: 1.1.0
> Environment: All
> Reporter: Mridul Muralidharan
> Assignee: Mridul Muralidharan
> Priority: Critical
>
> Will file PR with changes as soon as merge is done (earlier merge became
> outdated in 2 weeks unfortunately :) ).
> Consolidated shuffle is broken in multiple ways in spark :
> a) Task failure(s) can cause the state to become inconsistent.
> b) Multiple revert's or combination of close/revert/close can cause the state
> to be inconsistent.
> (As part of exception/error handling).
> c) Some of the api in block writer causes implementation issues - for
> example: a revert is always followed by close : but the implemention tries to
> keep them separate, resulting in surface for errors.
> d) Fetching data from consolidated shuffle files can go badly wrong if the
> file is being actively written to : it computes length by subtracting next
> offset from current offset (or length if this is last offset)- the latter
> fails when fetch is happening in parallel to write.
> Note, this happens even if there are no task failures of any kind !
> This usually results in stream corruption or decompression errors.
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