Hey Josh,
I am still trying to prune this to a minimal example, but it has been
tricky since scale seems to be a factor. The job runs over ~720GB of data
(the cluster's total RAM is around ~900GB, split across 32 executors). I've
managed to run it over a vastly smaller data set without issues. Curiously,
when I run it over slightly smaller data set of ~230GB (using sort-based
shuffle), my job also fails, but I see no shuffle errors in the executor
logs. All I see is the error below from the driver (this is also what the
driver prints when erroring out on the large data set, but I assumed the
executor errors to be the root cause).
Any idea on where to look in the interim for more hints? I'll continue to
try to get to a minimal repro.
2014-12-30 21:35:34,539 INFO
[sparkDriver-akka.actor.default-dispatcher-14]
spark.MapOutputTrackerMasterActor (Logging.scala:logInfo(59)) - Asked to
send map output locations for shuffle 0 to
sparkexecu...@ip-10-20-80-60.us-west-1.compute.internal:39739
2014-12-30 21:35:39,512 INFO
[sparkDriver-akka.actor.default-dispatcher-17]
spark.MapOutputTrackerMasterActor (Logging.scala:logInfo(59)) - Asked to
send map output locations for shuffle 0 to
sparkexecu...@ip-10-20-80-62.us-west-1.compute.internal:42277
2014-12-30 21:35:58,893 WARN
[sparkDriver-akka.actor.default-dispatcher-16]
remote.ReliableDeliverySupervisor (Slf4jLogger.scala:apply$mcV$sp(71)) -
Association with remote system
[akka.tcp://sparkyar...@ip-10-20-80-64.us-west-1.compute.internal:49584]
has failed, address is now gated for [5000] ms. Reason is: [Disassociated].
2014-12-30 21:35:59,044 ERROR [Yarn application state monitor]
cluster.YarnClientSchedulerBackend (Logging.scala:logError(75)) - Yarn
application has already exited with state FINISHED!
2014-12-30 21:35:59,056 INFO [Yarn application state monitor]
handler.ContextHandler (ContextHandler.java:doStop(788)) - stopped
o.e.j.s.ServletContextHandler{/stages/stage/kill,null}
[...]
2014-12-30 21:35:59,111 INFO [Yarn application state monitor] ui.SparkUI
(Logging.scala:logInfo(59)) - Stopped Spark web UI at
http://ip-10-20-80-37.us-west-1.compute.internal:4040
2014-12-30 21:35:59,130 INFO [Yarn application state monitor]
scheduler.DAGScheduler (Logging.scala:logInfo(59)) - Stopping DAGScheduler
2014-12-30 21:35:59,131 INFO [Yarn application state monitor]
cluster.YarnClientSchedulerBackend (Logging.scala:logInfo(59)) - Shutting
down all executors
2014-12-30 21:35:59,132 INFO
[sparkDriver-akka.actor.default-dispatcher-14]
cluster.YarnClientSchedulerBackend (Logging.scala:logInfo(59)) - Asking
each executor to shut down
2014-12-30 21:35:59,132 INFO [Thread-2] scheduler.DAGScheduler
(Logging.scala:logInfo(59)) - Job 1 failed: collect at
/home/hadoop/test_scripts/test.py:63, took 980.751936 s
Traceback (most recent call last):
File "/home/hadoop/test_scripts/test.py", line 63, in <module>
result = j.collect()
File "/home/hadoop/spark/python/pyspark/rdd.py", line 676, in collect
bytesInJava = self._jrdd.collect().iterator()
File
"/home/hadoop/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py",
line 538, in __call__
File
"/home/hadoop/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line
300, in get_return_value
py4j.protocol.Py4JJavaError2014-12-30 21:35:59,140 INFO [Yarn application
state monitor] cluster.YarnClientSchedulerBackend
(Logging.scala:logInfo(59)) - Stopped
: An error occurred while calling o117.collect.
: org.apache.spark.SparkException: Job cancelled because SparkContext was
shut down
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:702)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:701)
at scala.collection.mutable.HashSet.foreach(HashSet.scala:79)
at
org.apache.spark.scheduler.DAGScheduler.cleanUpAfterSchedulerStop(DAGScheduler.scala:701)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessActor.postStop(DAGScheduler.scala:1428)
at akka.actor.Actor$class.aroundPostStop(Actor.scala:475)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessActor.aroundPostStop(DAGScheduler.scala:1375)
at
akka.actor.dungeon.FaultHandling$class.akka$actor$dungeon$FaultHandling$$finishTerminate(FaultHandling.scala:210)
at
akka.actor.dungeon.FaultHandling$class.terminate(FaultHandling.scala:172)
at akka.actor.ActorCell.terminate(ActorCell.scala:369)
at akka.actor.ActorCell.invokeAll$1(ActorCell.scala:462)
at akka.actor.ActorCell.systemInvoke(ActorCell.scala:478)
at akka.dispatch.Mailbox.processAllSystemMessages(Mailbox.scala:263)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at
akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393)
at
scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at
scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at
scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at
scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
Thank you!
-Sven
On Tue, Dec 30, 2014 at 12:15 PM, Josh Rosen <rosenvi...@gmail.com> wrote:
> Hi Sven,
>
> Do you have a small example program that you can share which will allow me
> to reproduce this issue? If you have a workload that runs into this, you
> should be able to keep iteratively simplifying the job and reducing the
> data set size until you hit a fairly minimal reproduction (assuming the
> issue is deterministic, which it sounds like it is).
>
> On Tue, Dec 30, 2014 at 9:49 AM, Sven Krasser <kras...@gmail.com> wrote:
>
>> Hey all,
>>
>> Since upgrading to 1.2.0 a pyspark job that worked fine in 1.1.1 fails
>> during shuffle. I've tried reverting from the sort-based shuffle back to
>> the hash one, and that fails as well. Does anyone see similar problems or
>> has an idea on where to look next?
>>
>> For the sort-based shuffle I get a bunch of exception like this in the
>> executor logs:
>>
>> 2014-12-30 03:13:04,061 ERROR [Executor task launch worker-2]
>> executor.Executor (Logging.scala:logError(96)) - Exception in task 4523.0 in
>> stage 1.0 (TID 4524)
>> org.apache.spark.SparkException: PairwiseRDD: unexpected value:
>> List([B@130dc7ad)
>> at
>> org.apache.spark.api.python.PairwiseRDD$$anonfun$compute$2.apply(PythonRDD.scala:307)
>> at
>> org.apache.spark.api.python.PairwiseRDD$$anonfun$compute$2.apply(PythonRDD.scala:305)
>> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>> at
>> org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:219)
>> at
>> org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:65)
>> at
>> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
>> at
>> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
>> at org.apache.spark.scheduler.Task.run(Task.scala:56)
>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
>> at
>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>> at
>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>> at java.lang.Thread.run(Thread.java:745)
>>
>> For the hash-based shuffle, there are now a bunch of these exceptions in the
>> logs:
>>
>>
>> 2014-12-30 04:14:01,688 ERROR [Executor task launch worker-0]
>> executor.Executor (Logging.scala:logError(96)) - Exception in task 4479.0 in
>> stage 1.0 (TID 4480)
>> java.io.FileNotFoundException:
>> /mnt/var/lib/hadoop/tmp/nm-local-dir/usercache/hadoop/appcache/application_1419905501183_0004/spark-local-20141230035728-8fc0/23/merged_shuffle_1_68_0
>> (No such file or directory)
>> at java.io.FileOutputStream.open(Native Method)
>> at java.io.FileOutputStream.<init>(FileOutputStream.java:221)
>> at
>> org.apache.spark.storage.DiskBlockObjectWriter.open(BlockObjectWriter.scala:123)
>> at
>> org.apache.spark.storage.DiskBlockObjectWriter.write(BlockObjectWriter.scala:192)
>> at
>> org.apache.spark.shuffle.hash.HashShuffleWriter$$anonfun$write$1.apply(HashShuffleWriter.scala:67)
>> at
>> org.apache.spark.shuffle.hash.HashShuffleWriter$$anonfun$write$1.apply(HashShuffleWriter.scala:65)
>> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
>> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
>> at
>> org.apache.spark.shuffle.hash.HashShuffleWriter.write(HashShuffleWriter.scala:65)
>> at
>> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
>> at
>> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
>> at org.apache.spark.scheduler.Task.run(Task.scala:56)
>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
>> at
>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>> at
>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>> at java.lang.Thread.run(Thread.java:745)
>>
>> Thank you!
>> -Sven
>>
>>
>>
>> --
>> http://sites.google.com/site/krasser/?utm_source=sig
>>
>
>
--
http://sites.google.com/site/krasser/?utm_source=sig
