Agreed. Also I'm happy to test any patches since I have a consistent repro now (see one of my first responses in this thread)
On Fri, Feb 7, 2014 at 12:51 AM, Mridul Muralidharan <[email protected]>wrote: > This looks like the most reasonable approach to resolve this ! > > Regards, > Mridul > > > On Fri, Feb 7, 2014 at 1:43 PM, Tathagata Das > <[email protected]> wrote: > > Or we can try adding a shutdown hook in the > > Executor< > https://github.com/apache/incubator-spark/blob/master/core/src/main/scala/org/apache/spark/executor/Executor.scala?source=c#L127 > >to > > call threadPool.shutdownNow(). May have to catch the > > InterruptedException and handle it gracefully out > > here< > https://github.com/apache/incubator-spark/blob/master/core/src/main/scala/org/apache/spark/executor/Executor.scala?source=c#L255 > > > > . > > > > TD > > > > > > On Thu, Feb 6, 2014 at 11:49 PM, Andrew Ash <[email protected]> > wrote: > > > >> I think we can enumerate all current threads with the ThreadMXBean, > filter > >> to those threads with the name of executor pool in them, and interrupt > >> them. > >> > >> > >> > http://docs.oracle.com/javase/6/docs/api/java/lang/management/ManagementFactory.html#getThreadMXBean%28%29 > >> > >> The executor threads are currently named according to the pattern > "Executor > >> task launch worker-X" > >> > >> > >> On Thu, Feb 6, 2014 at 11:45 PM, Tathagata Das > >> <[email protected]>wrote: > >> > >> > That definitely sound more reliable. Worth trying out if there is a > >> > reliable way of reproducing the deadlock-like scenario. > >> > > >> > TD > >> > > >> > > >> > On Thu, Feb 6, 2014 at 11:38 PM, Matei Zaharia < > [email protected] > >> > >wrote: > >> > > >> > > I don't think we necessarily want to do this through the > DAGScheduler > >> > > because the worker might also shut down due to some unusual > termination > >> > > condition, like the driver node crashing. Can't we do it at the top > of > >> > the > >> > > shutdown hook instead? If all the threads are in the same thread > pool > >> it > >> > > might be possible to interrupt or stop the whole pool. > >> > > > >> > > Matei > >> > > > >> > > On Feb 6, 2014, at 11:30 PM, Andrew Ash <[email protected]> > wrote: > >> > > > >> > > > That's genius. Of course when a worker is told to shutdown it > should > >> > > > interrupt its worker threads -- I think that would address this > >> issue. > >> > > > > >> > > > Are you thinking to put > >> > > > > >> > > > running.map(_.jobId).foreach { handleJobCancellation } > >> > > > > >> > > > at the top of the StopDAGScheduler block? > >> > > > > >> > > > > >> > > > On Thu, Feb 6, 2014 at 11:05 PM, Tathagata Das > >> > > > <[email protected]>wrote: > >> > > > > >> > > >> Its highly likely that the executor with the threadpool that runs > >> the > >> > > tasks > >> > > >> are the only set of threads that writes to disk. The tasks are > >> > designed > >> > > to > >> > > >> be interrupted when the corresponding job is cancelled. So a > >> > reasonably > >> > > >> simple way could be to actually cancel the currently active jobs, > >> > which > >> > > >> would send the signal to the worker to stop the tasks. Currently, > >> the > >> > > >> DAGScheduler< > >> > > >> > >> > > > >> > > >> > https://github.com/apache/incubator-spark/blob/master/core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala#L610 > >> > > >>> does > >> > > >> not seem to actually cancel the jobs, only mark them as failed. > So > >> it > >> > > >> may be a simple addition. > >> > > >> > >> > > >> There may be some complications with the external spilling of > >> shuffle > >> > > data > >> > > >> to disk not stopping immediately when the task is marked for > >> killing. > >> > > Gotta > >> > > >> try it out. > >> > > >> > >> > > >> TD > >> > > >> > >> > > >> On Thu, Feb 6, 2014 at 10:39 PM, Andrew Ash < > [email protected]> > >> > > wrote: > >> > > >> > >> > > >>> There is probably just one threadpool that has task threads -- > is > >> it > >> > > >>> possible to enumerate and interrupt just those? We may need to > >> keep > >> > > >> string > >> > > >>> a reference to that threadpool through to the shutdown thread to > >> make > >> > > >> that > >> > > >>> happen. > >> > > >>> > >> > > >>> > >> > > >>> On Thu, Feb 6, 2014 at 10:36 PM, Mridul Muralidharan < > >> > [email protected] > >> > > >>>> wrote: > >> > > >>> > >> > > >>>> Ideally, interrupting the thread writing to disk should be > >> > sufficient > >> > > >>>> - though since we are in middle of shutdown when this is > >> happening, > >> > it > >> > > >>>> is best case effort anyway. > >> > > >>>> Identifying which threads to interrupt will be interesting > since > >> > most > >> > > >>>> of them are driven by threadpool's and we cant list all threads > >> and > >> > > >>>> interrupt all of them ! > >> > > >>>> > >> > > >>>> > >> > > >>>> Regards, > >> > > >>>> Mridul > >> > > >>>> > >> > > >>>> > >> > > >>>> On Fri, Feb 7, 2014 at 5:57 AM, Andrew Ash < > [email protected]> > >> > > >> wrote: > >> > > >>>>> I think the solution where we stop the writing threads and > then > >> let > >> > > >> the > >> > > >>>>> deleting threads completely clean up is the best option since > the > >> > > >> final > >> > > >>>>> state doesn't have half-deleted temp dirs scattered across the > >> > > >> cluster. > >> > > >>>>> > >> > > >>>>> How feasible do you think it'd be to interrupt the other > threads? > >> > > >>>>> > >> > > >>>>> > >> > > >>>>> On Thu, Feb 6, 2014 at 10:54 AM, Mridul Muralidharan < > >> > > >> [email protected] > >> > > >>>>> wrote: > >> > > >>>>> > >> > > >>>>>> Looks like a pathological corner case here - where the the > >> delete > >> > > >>>>>> thread is not getting run while the OS is busy prioritizing > the > >> > > >> thread > >> > > >>>>>> writing data (probably with heavy gc too). > >> > > >>>>>> Ideally, the delete thread would list files, remove them and > >> then > >> > > >> fail > >> > > >>>>>> when it tries to remove the non empty directory (since other > >> > thread > >> > > >>>>>> might be creating more in parallel). > >> > > >>>>>> > >> > > >>>>>> > >> > > >>>>>> Regards, > >> > > >>>>>> Mridul > >> > > >>>>>> > >> > > >>>>>> > >> > > >>>>>> On Thu, Feb 6, 2014 at 4:19 PM, Andrew Ash < > >> [email protected]> > >> > > >>>> wrote: > >> > > >>>>>>> Got a repro locally on my MBP (the other was on a CentOS > >> > machine). > >> > > >>>>>>> > >> > > >>>>>>> Build spark, run a master and a worker with the > >> sbin/start-all.sh > >> > > >>>> script, > >> > > >>>>>>> then run this in a shell: > >> > > >>>>>>> > >> > > >>>>>>> import org.apache.spark.storage.StorageLevel._ > >> > > >>>>>>> val s = sc.parallelize(1 to > >> > > >>> 1000000000).persist(MEMORY_AND_DISK_SER); > >> > > >>>>>>> s.count > >> > > >>>>>>> > >> > > >>>>>>> After about a minute, this line appears in the shell logging > >> > > >> output: > >> > > >>>>>>> > >> > > >>>>>>> 14/02/06 02:44:44 WARN BlockManagerMasterActor: Removing > >> > > >>> BlockManager > >> > > >>>>>>> BlockManagerId(0, aash-mbp.dyn.yojoe.local, 57895, 0) with > no > >> > > >> recent > >> > > >>>>>> heart > >> > > >>>>>>> beats: 57510ms exceeds 45000ms > >> > > >>>>>>> > >> > > >>>>>>> Ctrl-C the shell. In jps there is now a worker, a master, > and > >> a > >> > > >>>>>>> CoarseGrainedExecutorBackend. > >> > > >>>>>>> > >> > > >>>>>>> Run jstack on the CGEBackend JVM, and I got the attached > >> > > >>> stacktraces. > >> > > >>>> I > >> > > >>>>>>> waited around for 15min then kill -9'd the JVM and restarted > >> the > >> > > >>>> process. > >> > > >>>>>>> > >> > > >>>>>>> I wonder if what's happening here is that the threads that > are > >> > > >>> spewing > >> > > >>>>>> data > >> > > >>>>>>> to disk (as that parallelize and persist would do) can > write to > >> > > >> disk > >> > > >>>>>> faster > >> > > >>>>>>> than the cleanup threads can delete from disk. > >> > > >>>>>>> > >> > > >>>>>>> What do you think of that theory? > >> > > >>>>>>> > >> > > >>>>>>> > >> > > >>>>>>> Andrew > >> > > >>>>>>> > >> > > >>>>>>> > >> > > >>>>>>> > >> > > >>>>>>> On Thu, Feb 6, 2014 at 2:30 AM, Mridul Muralidharan < > >> > > >>> [email protected] > >> > > >>>>> > >> > > >>>>>>> wrote: > >> > > >>>>>>>> > >> > > >>>>>>>> shutdown hooks should not take 15 mins are you mentioned ! > >> > > >>>>>>>> On the other hand, how busy was your disk when this was > >> > > >> happening ? > >> > > >>>>>>>> (either due to spark or something else ?) > >> > > >>>>>>>> > >> > > >>>>>>>> It might just be that there was a lot of stuff to remove ? > >> > > >>>>>>>> > >> > > >>>>>>>> Regards, > >> > > >>>>>>>> Mridul > >> > > >>>>>>>> > >> > > >>>>>>>> > >> > > >>>>>>>> On Thu, Feb 6, 2014 at 3:50 PM, Andrew Ash < > >> > [email protected] > >> > > >>> > >> > > >>>>>> wrote: > >> > > >>>>>>>>> Hi Spark devs, > >> > > >>>>>>>>> > >> > > >>>>>>>>> Occasionally when hitting Ctrl-C in the scala spark shell > on > >> > > >>> 0.9.0 > >> > > >>>> one > >> > > >>>>>>>>> of > >> > > >>>>>>>>> my workers goes dead in the spark master UI. I'm using > the > >> > > >>>> standalone > >> > > >>>>>>>>> cluster and didn't ever see this while using 0.8.0 so I > think > >> > > >> it > >> > > >>>> may > >> > > >>>>>> be > >> > > >>>>>>>>> a > >> > > >>>>>>>>> regression. > >> > > >>>>>>>>> > >> > > >>>>>>>>> When I prod on the hung CoarseGrainedExecutorBackend JVM > with > >> > > >>>> jstack > >> > > >>>>>> and > >> > > >>>>>>>>> jmap -heap, it doesn't respond unless I add the -F force > >> flag. > >> > > >>> The > >> > > >>>>>> heap > >> > > >>>>>>>>> isn't full, but there are some interesting bits in the > >> jstack. > >> > > >>>> Poking > >> > > >>>>>>>>> around a little, I think there may be some kind of > deadlock > >> in > >> > > >>> the > >> > > >>>>>>>>> shutdown > >> > > >>>>>>>>> hooks. > >> > > >>>>>>>>> > >> > > >>>>>>>>> Below are the threads I think are most interesting: > >> > > >>>>>>>>> > >> > > >>>>>>>>> Thread 14308: (state = BLOCKED) > >> > > >>>>>>>>> - java.lang.Shutdown.exit(int) @bci=96, line=212 > (Interpreted > >> > > >>>> frame) > >> > > >>>>>>>>> - java.lang.Runtime.exit(int) @bci=14, line=109 > (Interpreted > >> > > >>>> frame) > >> > > >>>>>>>>> - java.lang.System.exit(int) @bci=4, line=962 (Interpreted > >> > > >>> frame) > >> > > >>>>>>>>> - > >> > > >>>>>>>>> > >> > > >>>>>>>>> > >> > > >>>>>> > >> > > >>>> > >> > > >>> > >> > > >> > >> > > > >> > > >> > org.apache.spark.executor.CoarseGrainedExecutorBackend$$anonfun$receive$1.applyOrElse(java.lang.Object, > >> > > >>>>>>>>> scala.Function1) @bci=352, line=81 (Interpreted frame) > >> > > >>>>>>>>> - akka.actor.ActorCell.receiveMessage(java.lang.Object) > >> > > >> @bci=25, > >> > > >>>>>>>>> line=498 > >> > > >>>>>>>>> (Interpreted frame) > >> > > >>>>>>>>> - akka.actor.ActorCell.invoke(akka.dispatch.Envelope) > >> @bci=39, > >> > > >>>>>> line=456 > >> > > >>>>>>>>> (Interpreted frame) > >> > > >>>>>>>>> - akka.dispatch.Mailbox.processMailbox(int, long) @bci=24, > >> > > >>>> line=237 > >> > > >>>>>>>>> (Interpreted frame) > >> > > >>>>>>>>> - akka.dispatch.Mailbox.run() @bci=20, line=219 > (Interpreted > >> > > >>>> frame) > >> > > >>>>>>>>> - > >> > > >>>> > akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec() > >> > > >>>>>>>>> @bci=4, line=386 (Interpreted frame) > >> > > >>>>>>>>> - scala.concurrent.forkjoin.ForkJoinTask.doExec() @bci=10, > >> > > >>>> line=260 > >> > > >>>>>>>>> (Compiled frame) > >> > > >>>>>>>>> - > >> > > >>>>>>>>> > >> > > >>>>>>>>> > >> > > >>>>>> > >> > > >>>> > >> > > >>> > >> > > >> > >> > > > >> > > >> > scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(scala.concurrent.forkjoin.ForkJoinTask) > >> > > >>>>>>>>> @bci=10, line=1339 (Compiled frame) > >> > > >>>>>>>>> - > >> > > >>>>>>>>> > >> > > >>>>>>>>> > >> > > >>>>>> > >> > > >>>> > >> > > >>> > >> > > >> > >> > > > >> > > >> > scala.concurrent.forkjoin.ForkJoinPool.runWorker(scala.concurrent.forkjoin.ForkJoinPool$WorkQueue) > >> > > >>>>>>>>> @bci=11, line=1979 (Compiled frame) > >> > > >>>>>>>>> - scala.concurrent.forkjoin.ForkJoinWorkerThread.run() > >> > > >> @bci=14, > >> > > >>>>>>>>> line=107 > >> > > >>>>>>>>> (Interpreted frame) > >> > > >>>>>>>>> > >> > > >>>>>>>>> Thread 3865: (state = BLOCKED) > >> > > >>>>>>>>> - java.lang.Object.wait(long) @bci=0 (Interpreted frame) > >> > > >>>>>>>>> - java.lang.Thread.join(long) @bci=38, line=1280 > (Interpreted > >> > > >>>> frame) > >> > > >>>>>>>>> - java.lang.Thread.join() @bci=2, line=1354 (Interpreted > >> > > >> frame) > >> > > >>>>>>>>> - java.lang.ApplicationShutdownHooks.runHooks() @bci=87, > >> > > >>> line=106 > >> > > >>>>>>>>> (Interpreted frame) > >> > > >>>>>>>>> - java.lang.ApplicationShutdownHooks$1.run() @bci=0, > line=46 > >> > > >>>>>>>>> (Interpreted > >> > > >>>>>>>>> frame) > >> > > >>>>>>>>> - java.lang.Shutdown.runHooks() @bci=39, line=123 > >> (Interpreted > >> > > >>>> frame) > >> > > >>>>>>>>> - java.lang.Shutdown.sequence() @bci=26, line=167 > >> (Interpreted > >> > > >>>> frame) > >> > > >>>>>>>>> - java.lang.Shutdown.exit(int) @bci=96, line=212 > (Interpreted > >> > > >>>> frame) > >> > > >>>>>>>>> - java.lang.Terminator$1.handle(sun.misc.Signal) @bci=8, > >> > > >> line=52 > >> > > >>>>>>>>> (Interpreted frame) > >> > > >>>>>>>>> - sun.misc.Signal$1.run() @bci=8, line=212 (Interpreted > >> frame) > >> > > >>>>>>>>> - java.lang.Thread.run() @bci=11, line=744 (Interpreted > >> frame) > >> > > >>>>>>>>> > >> > > >>>>>>>>> > >> > > >>>>>>>>> Thread 3987: (state = BLOCKED) > >> > > >>>>>>>>> - java.io.UnixFileSystem.list(java.io.File) @bci=0 > >> > > >> (Interpreted > >> > > >>>>>> frame) > >> > > >>>>>>>>> - java.io.File.list() @bci=29, line=1116 (Interpreted > frame) > >> > > >>>>>>>>> - java.io.File.listFiles() @bci=1, line=1201 (Compiled > frame) > >> > > >>>>>>>>> - > org.apache.spark.util.Utils$.listFilesSafely(java.io.File) > >> > > >>>> @bci=1, > >> > > >>>>>>>>> line=466 (Interpreted frame) > >> > > >>>>>>>>> - > >> org.apache.spark.util.Utils$.deleteRecursively(java.io.File) > >> > > >>>>>> @bci=9, > >> > > >>>>>>>>> line=478 (Compiled frame) > >> > > >>>>>>>>> - > >> > > >>>>>>>>> > >> > > >>>>>>>>> > >> > > >>>>>> > >> > > >>>> > >> > > >>> > >> > > >> > >> > > > >> > > >> > org.apache.spark.util.Utils$$anonfun$deleteRecursively$1.apply(java.io.File) > >> > > >>>>>>>>> @bci=4, line=479 (Compiled frame) > >> > > >>>>>>>>> - > >> > > >>>>>>>>> > >> > > >>>>>>>>> > >> > > >>>>>> > >> > > >>>> > >> > > >>> > >> > > >> > >> > > > >> > > >> > org.apache.spark.util.Utils$$anonfun$deleteRecursively$1.apply(java.lang.Object) > >> > > >>>>>>>>> @bci=5, line=478 (Compiled frame) > >> > > >>>>>>>>> - > >> > > >>>>>>>>> > >> > > >>>>>>>>> > >> > > >>>>>> > >> > > >>>> > >> > > >>> > >> > > >> > >> > > > >> > > >> > scala.collection.IndexedSeqOptimized$class.foreach(scala.collection.IndexedSeqOptimized, > >> > > >>>>>>>>> scala.Function1) @bci=22, line=33 (Compiled frame) > >> > > >>>>>>>>> - > >> > > >> scala.collection.mutable.WrappedArray.foreach(scala.Function1) > >> > > >>>>>>>>> @bci=2, > >> > > >>>>>>>>> line=34 (Compiled frame) > >> > > >>>>>>>>> - > >> org.apache.spark.util.Utils$.deleteRecursively(java.io.File) > >> > > >>>>>> @bci=19, > >> > > >>>>>>>>> line=478 (Interpreted frame) > >> > > >>>>>>>>> - > >> > > >>>>>>>>> > >> > > >>>>>>>>> > >> > > >>>>>> > >> > > >>>> > >> > > >>> > >> > > >> > >> > > > >> > > >> > org.apache.spark.storage.DiskBlockManager$$anon$1$$anonfun$run$2.apply(java.io.File) > >> > > >>>>>>>>> @bci=14, line=141 (Interpreted frame) > >> > > >>>>>>>>> - > >> > > >>>>>>>>> > >> > > >>>>>>>>> > >> > > >>>>>> > >> > > >>>> > >> > > >>> > >> > > >> > >> > > > >> > > >> > org.apache.spark.storage.DiskBlockManager$$anon$1$$anonfun$run$2.apply(java.lang.Object) > >> > > >>>>>>>>> @bci=5, line=139 (Interpreted frame) > >> > > >>>>>>>>> - > >> > > >>>>>>>>> > >> > > >>>>>>>>> > >> > > >>>>>> > >> > > >>>> > >> > > >>> > >> > > >> > >> > > > >> > > >> > scala.collection.IndexedSeqOptimized$class.foreach(scala.collection.IndexedSeqOptimized, > >> > > >>>>>>>>> scala.Function1) @bci=22, line=33 (Compiled frame) > >> > > >>>>>>>>> - > >> > > >>> scala.collection.mutable.ArrayOps$ofRef.foreach(scala.Function1) > >> > > >>>>>>>>> @bci=2, > >> > > >>>>>>>>> line=108 (Interpreted frame) > >> > > >>>>>>>>> - org.apache.spark.storage.DiskBlockManager$$anon$1.run() > >> > > >>> @bci=39, > >> > > >>>>>>>>> line=139 (Interpreted frame) > >> > > >>>>>>>>> > >> > > >>>>>>>>> > >> > > >>>>>>>>> I think what happened here is that thread 14308 received > the > >> > > >> akka > >> > > >>>>>>>>> "shutdown" message and called System.exit(). This started > >> > > >> thread > >> > > >>>>>> 3865, > >> > > >>>>>>>>> which is the JVM shutting itself down. Part of that > process > >> is > >> > > >>>>>> running > >> > > >>>>>>>>> the > >> > > >>>>>>>>> shutdown hooks, so it started thread 3987. That thread is > >> the > >> > > >>>>>> shutdown > >> > > >>>>>>>>> hook from addShutdownHook() in DiskBlockManager.scala, > which > >> > > >>> looks > >> > > >>>>>> like > >> > > >>>>>>>>> this: > >> > > >>>>>>>>> > >> > > >>>>>>>>> private def addShutdownHook() { > >> > > >>>>>>>>> localDirs.foreach(localDir => > >> > > >>>>>>>>> Utils.registerShutdownDeleteDir(localDir)) > >> > > >>>>>>>>> Runtime.getRuntime.addShutdownHook(new Thread("delete > >> Spark > >> > > >>>> local > >> > > >>>>>>>>> dirs") { > >> > > >>>>>>>>> override def run() { > >> > > >>>>>>>>> logDebug("Shutdown hook called") > >> > > >>>>>>>>> localDirs.foreach { localDir => > >> > > >>>>>>>>> try { > >> > > >>>>>>>>> if > (!Utils.hasRootAsShutdownDeleteDir(localDir)) > >> > > >>>>>>>>> Utils.deleteRecursively(localDir) > >> > > >>>>>>>>> } catch { > >> > > >>>>>>>>> case t: Throwable => > >> > > >>>>>>>>> logError("Exception while deleting local > spark > >> > > >> dir: > >> > > >>>> " + > >> > > >>>>>>>>> localDir, t) > >> > > >>>>>>>>> } > >> > > >>>>>>>>> } > >> > > >>>>>>>>> > >> > > >>>>>>>>> if (shuffleSender != null) { > >> > > >>>>>>>>> shuffleSender.stop() > >> > > >>>>>>>>> } > >> > > >>>>>>>>> } > >> > > >>>>>>>>> }) > >> > > >>>>>>>>> } > >> > > >>>>>>>>> > >> > > >>>>>>>>> It goes through and deletes the directories recursively. > I > >> was > >> > > >>>>>> thinking > >> > > >>>>>>>>> there might be some issues with concurrently-running > shutdown > >> > > >>> hooks > >> > > >>>>>>>>> deleting things out from underneath each other (shutdown > hook > >> > > >>>> javadocs > >> > > >>>>>>>>> say > >> > > >>>>>>>>> they're all started in parallel if multiple hooks are > added) > >> > > >>>> causing > >> > > >>>>>> the > >> > > >>>>>>>>> File.list() in that last thread to take quite some time. > >> > > >>>>>>>>> > >> > > >>>>>>>>> While I was looking through the stacktrace the JVM finally > >> > > >> exited > >> > > >>>>>> (after > >> > > >>>>>>>>> 15-20min at least) so I won't be able to debug more until > >> this > >> > > >>> bug > >> > > >>>>>>>>> strikes > >> > > >>>>>>>>> again. > >> > > >>>>>>>>> > >> > > >>>>>>>>> Any ideas on what might be going on here? > >> > > >>>>>>>>> > >> > > >>>>>>>>> Thanks! > >> > > >>>>>>>>> Andrew > >> > > >>>>>>> > >> > > >>>>>>> > >> > > >>>>>> > >> > > >>>> > >> > > >>> > >> > > >> > >> > > > >> > > > >> > > >> >
