GitHub user ashwinshankar77 opened a pull request:
https://github.com/apache/spark/pull/15267
[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 https://github.com/ashwinshankar77/spark SPARK-17667
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/15267.patch
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 <ashan...@netflix.com>
Date: 2016-09-27T18:23:52Z
Make locking fine grained in YarnAllocator#enqueueGetLossReasonRequest
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