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 >>>> >>>
