Thanks for the updates, Ori. I'm not familiar with Scala. Just curious, if what you suspect is true, is it a bug of Scala?
Thank you~ Xintong Song On Tue, Jul 7, 2020 at 1:41 PM Ori Popowski <ori....@gmail.com> wrote: > Hi, > > I just wanted to update that the problem is now solved! > > I suspect that Scala's flatten() method has a memory problem on very > large lists (> 2 billion elements). When using Scala Lists, the memory > seems to leak but the app keeps running, and when using Scala Vectors, a > weird IllegalArgumentException is thrown [1]. > > I implemented my own flatten() method using Arrays and quickly ran into > NegativeArraySizeException since the integer representing the array size > wrapped around at Integer.MaxValue and became negative. After I started > catching this exception all my cluster problems just resolved. Checkpoints, > the heartbeat timeout, and also the memory and CPU utilization. > > I still need to confirm my suspicion towards Scala's flatten() though, > since I haven't "lab-tested" it. > > [1] https://github.com/NetLogo/NetLogo/issues/1830 > > On Sun, Jul 5, 2020 at 2:21 PM Ori Popowski <ori....@gmail.com> wrote: > >> Hi, >> >> I initially thought this, so this is why my heap is almost 30GiB. >> However, I started to analyze the Java Flight Recorder files, and I >> suspect there's a memory leak in Scala's flatten() method. >> I changed the line that uses flatten(), and instead of flatten() I'm >> just creating a ByteArray the size flatten() would have returned, and I >> no longer have the heartbeat problem. >> >> So now my code is >> val recordingData = recordingBytes.flatten >> >> instead of >> val recordingData = >> Array.fill[Byte](recordingBytes.map(_.length).sum)(0) >> >> I attach a screenshot of Java Mission Control >> >> >> >> On Fri, Jul 3, 2020 at 7:24 AM Xintong Song <tonysong...@gmail.com> >> wrote: >> >>> I agree with Roman's suggestion for increasing heap size. >>> >>> It seems that the heap grows faster than freed. Thus eventually the Full >>> GC is triggered, taking more than 50s and causing the timeout. However, >>> even the full GC frees only 2GB space out of the 28GB max size. That >>> probably suggests that the max heap size is not sufficient. >>> >>>> 2020-07-01T10:15:12.869+0000: [Full GC (Allocation Failure) >>>> 28944M->26018M(28960M), 51.5256128 secs] >>>> [Eden: 0.0B(1448.0M)->0.0B(1448.0M) Survivors: 0.0B->0.0B Heap: >>>> 28944.6M(28960.0M)->26018.9M(28960.0M)], [Metaspace: >>>> 113556K->112729K(1150976K)] >>>> [Times: user=91.08 sys=0.06, real=51.53 secs] >>> >>> >>> I would not be so sure about the memory leak. I think it could be a >>> normal pattern that memory keeps growing as more data is processed. E.g., >>> from the provided log, I see window operation tasks executed in the task >>> manager. Such operation might accumulate data until the window is emitted. >>> >>> Maybe Ori you can also take a look at the task manager log when the job >>> runs with Flink 1.9 without this problem, see how the heap size changed. As >>> I mentioned before, it is possible that, with the same configurations Flink >>> 1.10 has less heap size compared to Flink 1.9, due to the memory model >>> changes. >>> >>> Thank you~ >>> >>> Xintong Song >>> >>> >>> >>> On Thu, Jul 2, 2020 at 8:58 PM Ori Popowski <ori....@gmail.com> wrote: >>> >>>> Thank you very much for your analysis. >>>> >>>> When I said there was no memory leak - I meant that from the specific >>>> TaskManager I monitored in real-time using JProfiler. >>>> Unfortunately, this problem occurs only in 1 of the TaskManager and you >>>> cannot anticipate which. So when you pick a TM to profile at random - >>>> everything looks fine. >>>> >>>> I'm running the job again with Java FlightRecorder now, and I hope I'll >>>> find the reason for the memory leak. >>>> >>>> Thanks! >>>> >>>> On Thu, Jul 2, 2020 at 3:42 PM Khachatryan Roman < >>>> khachatryan.ro...@gmail.com> wrote: >>>> >>>>> Thanks, Ori >>>>> >>>>> From the log, it looks like there IS a memory leak. >>>>> >>>>> At 10:12:53 there was the last "successfull" gc when 13Gb freed in >>>>> 0.4653809 secs: >>>>> [Eden: 17336.0M(17336.0M)->0.0B(2544.0M) Survivors: 40960.0K->2176.0M >>>>> Heap: 23280.3M(28960.0M)->10047.0M(28960.0M)] >>>>> >>>>> Then the heap grew from 10G to 28G with GC not being able to free up >>>>> enough space: >>>>> [Eden: 2544.0M(2544.0M)->0.0B(856.0M) Survivors: 2176.0M->592.0M Heap: >>>>> 12591.0M(28960.0M)->11247.0M(28960.0M)] >>>>> [Eden: 856.0M(856.0M)->0.0B(1264.0M) Survivors: 592.0M->184.0M Heap: >>>>> 12103.0M(28960.0M)->11655.0M(28960.0M)] >>>>> [Eden: 1264.0M(1264.0M)->0.0B(1264.0M) Survivors: 184.0M->184.0M Heap: >>>>> 12929.0M(28960.0M)->12467.0M(28960.0M)] >>>>> ... ... >>>>> [Eden: 1264.0M(1264.0M)->0.0B(1264.0M) Survivors: 184.0M->184.0M Heap: >>>>> 28042.6M(28960.0M)->27220.6M(28960.0M)] >>>>> [Eden: 1264.0M(1264.0M)->0.0B(1264.0M) Survivors: 184.0M->184.0M Heap: >>>>> 28494.5M(28960.0M)->28720.6M(28960.0M)] >>>>> [Eden: 224.0M(1264.0M)->0.0B(1448.0M) Survivors: 184.0M->0.0B Heap: >>>>> 28944.6M(28960.0M)->28944.6M(28960.0M)] >>>>> >>>>> Until 10:15:12 when GC freed almost 4G - but it took 51 seconds and >>>>> heartbeat timed out: >>>>> 2020-07-01T10:15:12.869+0000: [Full GC (Allocation Failure) >>>>> 28944M->26018M(28960M), 51.5256128 secs] >>>>> [Eden: 0.0B(1448.0M)->0.0B(1448.0M) Survivors: 0.0B->0.0B Heap: >>>>> 28944.6M(28960.0M)->26018.9M(28960.0M)], [Metaspace: >>>>> 113556K->112729K(1150976K)] >>>>> [Times: user=91.08 sys=0.06, real=51.53 secs] >>>>> 2020-07-01T10:16:04.395+0000: [GC concurrent-mark-abort] >>>>> 10:16:04.398 [flink-akka.actor.default-dispatcher-21] INFO >>>>> org.apache.flink.runtime.taskexecutor.TaskExecutor - The heartbeat of >>>>> JobManager with id bc59ba6a >>>>> >>>>> No substantial amount memory was freed after that. >>>>> >>>>> If this memory usage pattern is expected, I'd suggest to: >>>>> 1. increase heap size >>>>> 2. play with PrintStringDeduplicationStatistics and >>>>> UseStringDeduplication flags - probably string deduplication is making G1 >>>>> slower then CMS >>>>> >>>>> Regards, >>>>> Roman >>>>> >>>>> >>>>> On Thu, Jul 2, 2020 at 10:11 AM Ori Popowski <ori....@gmail.com> >>>>> wrote: >>>>> >>>>>> Hi, >>>>>> >>>>>> I'd be happy to :) Attached is a TaskManager log which timed out. >>>>>> >>>>>> >>>>>> Thanks! >>>>>> >>>>>> On Thu, Jul 2, 2020 at 4:21 AM Xintong Song <tonysong...@gmail.com> >>>>>> wrote: >>>>>> >>>>>>> Maybe you can share the log and gc-log of the problematic >>>>>>> TaskManager? See if we can find any clue. >>>>>>> >>>>>>> Thank you~ >>>>>>> >>>>>>> Xintong Song >>>>>>> >>>>>>> >>>>>>> >>>>>>> On Wed, Jul 1, 2020 at 8:11 PM Ori Popowski <ori....@gmail.com> >>>>>>> wrote: >>>>>>> >>>>>>>> I've found out that sometimes one of my TaskManagers experiences a >>>>>>>> GC pause of 40-50 seconds and I have no idea why. >>>>>>>> I profiled one of the machines using JProfiler and everything looks >>>>>>>> fine. No memory leaks, memory is low. >>>>>>>> However, I cannot anticipate which of the machines will get the >>>>>>>> 40-50 seconds pause and I also cannot profile all of them all the time. >>>>>>>> >>>>>>>> Any suggestions? >>>>>>>> >>>>>>>> On Mon, Jun 29, 2020 at 4:44 AM Xintong Song <tonysong...@gmail.com> >>>>>>>> wrote: >>>>>>>> >>>>>>>>> In Flink 1.10, there's a huge change in the memory management >>>>>>>>> compared to previous versions. This could be related to your >>>>>>>>> observations, >>>>>>>>> because with the same configurations, it is possible that there's >>>>>>>>> less JVM >>>>>>>>> heap space (with more off-heap memory). Please take a look at this >>>>>>>>> migration guide [1]. >>>>>>>>> >>>>>>>>> Thank you~ >>>>>>>>> >>>>>>>>> Xintong Song >>>>>>>>> >>>>>>>>> >>>>>>>>> [1] >>>>>>>>> https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_migration.html >>>>>>>>> >>>>>>>>> On Sun, Jun 28, 2020 at 10:12 PM Ori Popowski <ori....@gmail.com> >>>>>>>>> wrote: >>>>>>>>> >>>>>>>>>> Thanks for the suggestions! >>>>>>>>>> >>>>>>>>>> > i recently tried 1.10 and see this error frequently. and i dont >>>>>>>>>> have the same issue when running with 1.9.1 >>>>>>>>>> I did downgrade to Flink 1.9 and there's certainly no change in >>>>>>>>>> the occurrences in the heartbeat timeout >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> > >>>>>>>>>> >>>>>>>>>> - Probably the most straightforward way is to try increasing >>>>>>>>>> the timeout to see if that helps. You can leverage the >>>>>>>>>> configuration option >>>>>>>>>> `heartbeat.timeout`[1]. The default is 50s. >>>>>>>>>> - It might be helpful to share your configuration setups >>>>>>>>>> (e.g., the TM resources, JVM parameters, timeout, etc.). Maybe >>>>>>>>>> the easiest >>>>>>>>>> way is to share the beginning part of your JM/TM logs, including >>>>>>>>>> the JVM >>>>>>>>>> parameters and all the loaded configurations. >>>>>>>>>> - You may want to look into the GC logs in addition to the >>>>>>>>>> metrics. In case of a CMS GC stop-the-world, you may not be able >>>>>>>>>> to see the >>>>>>>>>> most recent metrics due to the process not responding to the >>>>>>>>>> metric >>>>>>>>>> querying services. >>>>>>>>>> - You may also look into the status of the JM process. If JM >>>>>>>>>> is under significant GC pressure, it could also happen that the >>>>>>>>>> heartbeat >>>>>>>>>> message from TM is not timely handled before the timeout check. >>>>>>>>>> - Is there any metrics monitoring the network condition >>>>>>>>>> between the JM and timeouted TM? Possibly any jitters? >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> Weirdly enough, I did manage to find a problem with the timed out >>>>>>>>>> TaskManagers, which slipped away the last time I checked: The timed >>>>>>>>>> out >>>>>>>>>> TaskManager is always the one with the max. GC time (young >>>>>>>>>> generation). I >>>>>>>>>> see it only now that I run with G1GC, but with the previous GC it >>>>>>>>>> wasn't >>>>>>>>>> the case. >>>>>>>>>> >>>>>>>>>> Does anyone know what can cause high GC time and how to mitigate >>>>>>>>>> this? >>>>>>>>>> >>>>>>>>>> On Sun, Jun 28, 2020 at 5:04 AM Xintong Song < >>>>>>>>>> tonysong...@gmail.com> wrote: >>>>>>>>>> >>>>>>>>>>> Hi Ori, >>>>>>>>>>> >>>>>>>>>>> Here are some suggestions from my side. >>>>>>>>>>> >>>>>>>>>>> - Probably the most straightforward way is to try increasing >>>>>>>>>>> the timeout to see if that helps. You can leverage the >>>>>>>>>>> configuration option >>>>>>>>>>> `heartbeat.timeout`[1]. The default is 50s. >>>>>>>>>>> - It might be helpful to share your configuration setups >>>>>>>>>>> (e.g., the TM resources, JVM parameters, timeout, etc.). Maybe >>>>>>>>>>> the easiest >>>>>>>>>>> way is to share the beginning part of your JM/TM logs, including >>>>>>>>>>> the JVM >>>>>>>>>>> parameters and all the loaded configurations. >>>>>>>>>>> - You may want to look into the GC logs in addition to the >>>>>>>>>>> metrics. In case of a CMS GC stop-the-world, you may not be able >>>>>>>>>>> to see the >>>>>>>>>>> most recent metrics due to the process not responding to the >>>>>>>>>>> metric >>>>>>>>>>> querying services. >>>>>>>>>>> - You may also look into the status of the JM process. If JM >>>>>>>>>>> is under significant GC pressure, it could also happen that the >>>>>>>>>>> heartbeat >>>>>>>>>>> message from TM is not timely handled before the timeout check. >>>>>>>>>>> - Is there any metrics monitoring the network condition >>>>>>>>>>> between the JM and timeouted TM? Possibly any jitters? >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Thank you~ >>>>>>>>>>> >>>>>>>>>>> Xintong Song >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> [1] >>>>>>>>>>> https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/config.html#heartbeat-timeout >>>>>>>>>>> >>>>>>>>>>> On Thu, Jun 25, 2020 at 11:15 PM Ori Popowski <ori....@gmail.com> >>>>>>>>>>> wrote: >>>>>>>>>>> >>>>>>>>>>>> Hello, >>>>>>>>>>>> >>>>>>>>>>>> I'm running Flink 1.10 on EMR and reading from Kafka with 189 >>>>>>>>>>>> partitions and I have parallelism of 189. >>>>>>>>>>>> >>>>>>>>>>>> Currently running with RocksDB, with checkpointing disabled. My >>>>>>>>>>>> state size is appx. 500gb. >>>>>>>>>>>> >>>>>>>>>>>> I'm getting sporadic "Heartbeat of TaskManager timed out" >>>>>>>>>>>> errors with no apparent reason. >>>>>>>>>>>> >>>>>>>>>>>> I check the container that gets the timeout for GC pauses, heap >>>>>>>>>>>> memory, direct memory, mapped memory, offheap memory, CPU load, >>>>>>>>>>>> network >>>>>>>>>>>> load, total out-records, total in-records, backpressure, and >>>>>>>>>>>> everything I >>>>>>>>>>>> can think of. But all those metrics show that there's nothing >>>>>>>>>>>> unusual, and >>>>>>>>>>>> it has around average values for all those metrics. There are a >>>>>>>>>>>> lot of >>>>>>>>>>>> other containers which score higher. >>>>>>>>>>>> >>>>>>>>>>>> All the metrics are very low because every TaskManager runs on >>>>>>>>>>>> a r5.2xlarge machine alone. >>>>>>>>>>>> >>>>>>>>>>>> I'm trying to debug this for days and I cannot find any >>>>>>>>>>>> explanation for it. >>>>>>>>>>>> >>>>>>>>>>>> Can someone explain why it's happening? >>>>>>>>>>>> >>>>>>>>>>>> java.util.concurrent.TimeoutException: Heartbeat of TaskManager >>>>>>>>>>>> with id container_1593074931633_0011_01_000127 timed out. >>>>>>>>>>>> at org.apache.flink.runtime.jobmaster. >>>>>>>>>>>> JobMaster$TaskManagerHeartbeatListener.notifyHeartbeatTimeout( >>>>>>>>>>>> JobMaster.java:1147) >>>>>>>>>>>> at org.apache.flink.runtime.heartbeat.HeartbeatMonitorImpl >>>>>>>>>>>> .run(HeartbeatMonitorImpl.java:109) >>>>>>>>>>>> at java.util.concurrent.Executors$RunnableAdapter.call( >>>>>>>>>>>> Executors.java:511) >>>>>>>>>>>> at java.util.concurrent.FutureTask.run(FutureTask.java:266) >>>>>>>>>>>> at org.apache.flink.runtime.rpc.akka.AkkaRpcActor >>>>>>>>>>>> .handleRunAsync(AkkaRpcActor.java:397) >>>>>>>>>>>> at org.apache.flink.runtime.rpc.akka.AkkaRpcActor >>>>>>>>>>>> .handleRpcMessage(AkkaRpcActor.java:190) >>>>>>>>>>>> at org.apache.flink.runtime.rpc.akka.FencedAkkaRpcActor >>>>>>>>>>>> .handleRpcMessage(FencedAkkaRpcActor.java:74) >>>>>>>>>>>> at org.apache.flink.runtime.rpc.akka.AkkaRpcActor >>>>>>>>>>>> .handleMessage(AkkaRpcActor.java:152) >>>>>>>>>>>> at akka.japi.pf.UnitCaseStatement.apply(CaseStatements >>>>>>>>>>>> .scala:26) >>>>>>>>>>>> at akka.japi.pf.UnitCaseStatement.apply(CaseStatements >>>>>>>>>>>> .scala:21) >>>>>>>>>>>> at scala.PartialFunction$class.applyOrElse(PartialFunction >>>>>>>>>>>> .scala:123) >>>>>>>>>>>> at akka.japi.pf.UnitCaseStatement.applyOrElse( >>>>>>>>>>>> CaseStatements.scala:21) >>>>>>>>>>>> at scala.PartialFunction$OrElse.applyOrElse(PartialFunction >>>>>>>>>>>> .scala:170) >>>>>>>>>>>> at scala.PartialFunction$OrElse.applyOrElse(PartialFunction >>>>>>>>>>>> .scala:171) >>>>>>>>>>>> at scala.PartialFunction$OrElse.applyOrElse(PartialFunction >>>>>>>>>>>> .scala:171) >>>>>>>>>>>> at akka.actor.Actor$class.aroundReceive(Actor.scala:517) >>>>>>>>>>>> at akka.actor.AbstractActor.aroundReceive(AbstractActor >>>>>>>>>>>> .scala:225) >>>>>>>>>>>> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:592) >>>>>>>>>>>> at akka.actor.ActorCell.invoke(ActorCell.scala:561) >>>>>>>>>>>> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:258) >>>>>>>>>>>> at akka.dispatch.Mailbox.run(Mailbox.scala:225) >>>>>>>>>>>> at akka.dispatch.Mailbox.exec(Mailbox.scala:235) >>>>>>>>>>>> at akka.dispatch.forkjoin.ForkJoinTask.doExec(ForkJoinTask >>>>>>>>>>>> .java:260) >>>>>>>>>>>> at akka.dispatch.forkjoin.ForkJoinPool$WorkQueue.runTask( >>>>>>>>>>>> ForkJoinPool.java:1339) >>>>>>>>>>>> at akka.dispatch.forkjoin.ForkJoinPool.runWorker( >>>>>>>>>>>> ForkJoinPool.java:1979) >>>>>>>>>>>> at akka.dispatch.forkjoin.ForkJoinWorkerThread.run( >>>>>>>>>>>> ForkJoinWorkerThread.java:107) >>>>>>>>>>>> >>>>>>>>>>>> Thanks >>>>>>>>>>>> >>>>>>>>>>>
