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From ashwinshankar77 <>
Subject [GitHub] spark pull request #15267: [SPARK-17667] [YARN][WIP]Make locking fine graine...
Date Tue, 27 Sep 2016 19:06:17 GMT
GitHub user ashwinshankar77 opened a pull request:

    [SPARK-17667] [YARN][WIP]Make locking fine grained in YarnAllocator#enqueueGetLossReasonRequest

    ## What changes were proposed in this pull request?
    Following up on the discussion in SPARK-15725, one of the reason for AM hanging with dynamic
allocation(DA) is the way locking is done in YarnAllocator. We noticed that when executors
go down during the shrink phase of DA, AM gets locked up. On taking thread dump, we see threads
trying to get loss for reason via YarnAllocator#enqueueGetLossReasonRequest, and they are
all BLOCKED waiting for lock acquired by allocate call. This gets worse when the number of
executors go down are in the thousands, and I've seen AM hang in the order of minutes. This
patch is created to make the locking little more fine grained by remembering the executors
that were killed via AM, and then serve the GetExecutorLossReason requests with that information.
    This patch is not final. I want to get inputs on how I can go about removing executors
from the `executorsKilledByDriver` set. Also if there is a better way to solve this, would
be happy to make the changes.
    ## How was this patch tested?
    This was tested in our cluster with manually scaling the number of executors to thousands
and then shrinking them down to something small, and made sure that we don't see BLOCKED threads
stuck at YarnAllocator#enqueueGetLossReasonRequest.

You can merge this pull request into a Git repository by running:

    $ git pull SPARK-17667

Alternatively you can review and apply these changes as the patch at:

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #15267
commit 859718c95e3864855be98c5d09e74c652eda31b9
Author: Ashwin Shankar <>
Date:   2016-09-27T18:23:52Z

    Make locking fine grained in YarnAllocator#enqueueGetLossReasonRequest


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