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 >>>>>>> >>>>>>
