Github user vanzin commented on the issue:
https://github.com/apache/spark/pull/13482
> So why don't we just take out the notifyAll call when we get a
GetExecutorLossReason?
If that helps it's ok too. It would probably increase a little bit the time
for the driver to know
Github user tgravescs commented on the issue:
https://github.com/apache/spark/pull/13482
So why don't we just take out the notifyAll call when we get a
GetExecutorLossReason?
We can add a parameter to resetAllocatorInterval() and resets the interval
it but doesn't call the
Github user andrewor14 commented on the issue:
https://github.com/apache/spark/pull/13482
I think this is important to fix for 2.0 but I personally found the changes
in this patch rather confusing. If there's a simpler workaround we could do
(such as the solution I suggested, if that
Github user andrewor14 commented on the issue:
https://github.com/apache/spark/pull/13482
@rdblue the reason for the hang is the `GetExecutorLossReason` right? AFAIK
we send one to the AM every time an executor dies. What if we just keep a set
of executor IDs we're waiting to kill on
Github user vanzin commented on the issue:
https://github.com/apache/spark/pull/13482
Seems like an ok workaround to me; we really should spend some time looking
at removing some of those locks and avoiding `askWithRetry` (which shouldn't
ever be needed with a reliable RPC library
Github user vanzin commented on the issue:
https://github.com/apache/spark/pull/13482
@rdblue could you follow the usual convention in the pr title
(`[SPARK-15725][yarn] Blah`)? thx
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Github user rdblue commented on the issue:
https://github.com/apache/spark/pull/13482
cc @vanzin @tgravescs
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Github user rdblue commented on the issue:
https://github.com/apache/spark/pull/13482
@yhuai, @rxin, we should consider this work-around for 2.0 if it isn't too
late. We see a lot of apps fail because the driver and AM lock up.
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Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/13482
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Github user AmplabJenkins commented on the issue:
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Github user SparkQA commented on the issue:
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