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the last change was just log level change so this lgtm.
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Github user tgravescs commented on the pull request:
https://github.com/apache/spark/pull/7431#issuecomment-122892629
It doesn't necessarily mean executor is in bad state but it could be in a
bad state. I've seen very weird things happen on machines before so personally
I don't
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Github user vanzin commented on the pull request:
https://github.com/apache/spark/pull/7431#issuecomment-122402046
If that executor was somehow in a weird state we would want it removed.
Feels to me like Spark's own heartbeat would take care of that failure
mode. The NM
Github user tgravescs commented on the pull request:
https://github.com/apache/spark/pull/7431#issuecomment-122399579
thats not necessarily true. if a NM goes away for long enough the RM will
assume all containers on it are gone too so you would get the notification
saying they are
Github user mridulm closed the pull request at:
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Github user vanzin commented on the pull request:
https://github.com/apache/spark/pull/7431#issuecomment-122034172
I can try it out (I'll also add some logging in my internal build to make
sure the code is actually being exercised).
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Github user tgravescs commented on the pull request:
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The changes look good. To manually test this can't you just remove/kill a
nodemanager that has an executor on it? Perhaps there is a race between when
yarn tells us
Github user tgravescs commented on the pull request:
https://github.com/apache/spark/pull/7243#issuecomment-122001174
@mridulm can you close this then in favor of #7431
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Github user vanzin commented on the pull request:
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(BTW to test this, killing the NM is not enough, since that doesn't seem to
cause child containers to be killed.)
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Github user vanzin commented on the pull request:
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So now that I tried the new code path (which works), I'm a little skeptical
that sending a message back to the driver is really needed. The driver already
removes the
Github user tgravescs commented on the pull request:
https://github.com/apache/spark/pull/7431#issuecomment-122150692
https://issues.apache.org/jira/browse/SPARK-8297?focusedCommentId=14583560page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-14583560
Github user tgravescs commented on a diff in the pull request:
https://github.com/apache/spark/pull/7431#discussion_r34857066
--- Diff:
yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala ---
@@ -430,6 +435,18 @@ private[yarn] class YarnAllocator(
Github user vanzin commented on the pull request:
https://github.com/apache/spark/pull/7431#issuecomment-122156071
I'm guessing there might be situations it doesn't recognize the
disconnect right away.
That's the only case in which this code might help; but does that really
Github user andrewor14 commented on a diff in the pull request:
https://github.com/apache/spark/pull/7431#discussion_r34853110
--- Diff:
yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala ---
@@ -430,6 +435,18 @@ private[yarn] class YarnAllocator(
Github user andrewor14 commented on the pull request:
https://github.com/apache/spark/pull/7431#issuecomment-122138316
Yeah it seems like a race condition between the two detection code paths.
If they are both guaranteed to be called, then we're always going to end up
with `ERROR:
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Github user vanzin commented on the pull request:
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This is an updated version of #7243, which also works in yarn-client mode.
/cc @mridulm @tgravescs
I ran a bunch of tests on yarn client and cluster
Github user mridulm commented on the pull request:
https://github.com/apache/spark/pull/7431#issuecomment-121762507
Looks good to me ! If Tom does not come back with objections I am +1 on
this.
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GitHub user vanzin opened a pull request:
https://github.com/apache/spark/pull/7431
[SPARK-8297] [YARN] Scheduler backend is not notified in case node fails
in YARN
This change adds code to notify the scheduler backend when a container dies
in YARN.
You can merge this pull
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Github user vanzin commented on the pull request:
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What about `yarn-client`? `ApplicationMaster` already has a way to talk to
the driver regardless of the deploy mode (see `AMEndpoint`, and the equivalent
on the driver
Github user tgravescs commented on the pull request:
https://github.com/apache/spark/pull/7243#issuecomment-119271350
nice catch mridul. The logic looks fine other then the note from @vanzin.
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Github user mridulm commented on the pull request:
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@tgravescs pls take a look, thanks.
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Github user mridulm commented on the pull request:
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The failures (in YarnClusterSuite) are unrelated to this change - and
happen with a clean checkout as well.
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Github user vanzin commented on a diff in the pull request:
https://github.com/apache/spark/pull/7243#discussion_r34062845
--- Diff:
yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala ---
@@ -218,11 +218,12 @@ private[spark] class ApplicationMaster(
Github user vanzin commented on the pull request:
https://github.com/apache/spark/pull/7243#issuecomment-119359707
The endpoint is for messages from core to yarn if I am not wrong ?
If you look at `AMEndpoint`, it has a reference to the driver endpoint, so
you should be able
Github user mridulm commented on a diff in the pull request:
https://github.com/apache/spark/pull/7243#discussion_r34098979
--- Diff:
yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala ---
@@ -218,11 +218,12 @@ private[spark] class ApplicationMaster(
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Github user vanzin commented on the pull request:
https://github.com/apache/spark/pull/7243#issuecomment-119371331
It's ok if you don't want to work on the full fix, I'm just wary of pushing
a change to master that only fixes part of the problem, when the change to fix
everything
Github user vanzin commented on a diff in the pull request:
https://github.com/apache/spark/pull/7243#discussion_r34097612
--- Diff:
yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala ---
@@ -218,11 +218,12 @@ private[spark] class ApplicationMaster(
Github user mridulm commented on the pull request:
https://github.com/apache/spark/pull/7243#issuecomment-119359281
@vanzin The endpoint is for messages from core to yarn if I am not wrong ?
This would flow the other way - from yarn to core.
Or am I missing something ?
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/7243#issuecomment-119363708
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Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/7243#issuecomment-119363736
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