How many slots do you have on each task manager? Flink uses ChildFirstClassLoader for loading user codes, to avoid dependency conflicts between user codes and Flink's framework. Ideally, after a slot is freed and reassigned to a new job, the user class loaders of the previous job should be unloaded. 33 instances of them does not sound right. It might be worth looking into where the references that keep these instances alive come from.
Flink 1.10.3 is not released yet. If you want to try the unreleased version, you would need to download the sources [1], build the flink distribution [2] and build your custom image (from the 1.0.2 image and replace the flink distribution with the one you built). Thank you~ Xintong Song [1] https://github.com/apache/flink/tree/release-1.10 [2] https://ci.apache.org/projects/flink/flink-docs-release-1.10/flinkDev/building.html On Wed, Sep 23, 2020 at 8:29 PM Claude M <claudemur...@gmail.com> wrote: > It was mentioned that this issue may be fixed in 1.10.3 but there is no > 1.10.3 docker image here: https://hub.docker.com/_/flink > > > On Wed, Sep 23, 2020 at 7:14 AM Claude M <claudemur...@gmail.com> wrote: > >> In regards to the metaspace memory issue, I was able to get a heap dump >> and the following is the output: >> >> Problem Suspect 1 >> One instance of *"java.lang.ref.Finalizer"* loaded by *"<system class >> loader>"* occupies *4,112,624 (11.67%)* bytes. The instance is >> referenced by *sun.misc.Cleaner @ 0xb5d6b520* , loaded by *"<system >> class loader>"*. The memory is accumulated in one instance of >> *"java.lang.Object[]"* loaded by *"<system class loader>"*. >> >> Problem Suspect 2 >> 33 instances of *"org.apache.flink.util.ChildFirstClassLoader"*, loaded >> by *"sun.misc.Launcher$AppClassLoader @ 0xb4068680"* occupy *6,615,416 >> (18.76%)*bytes. >> >> Based on this, I'm not clear on what needs to be done to solve this. >> >> >> On Tue, Sep 22, 2020 at 3:10 PM Claude M <claudemur...@gmail.com> wrote: >> >>> Thanks for your responses. >>> 1. There were no job re-starts prior to the metaspace OEM. >>> 2. I tried increasing the CPU request and still encountered the >>> problem. Any configuration change I make to the job manager, whether it's >>> in the flink-conf.yaml or increasing the pod's CPU/memory request, results >>> with this problem. >>> >>> >>> On Tue, Sep 22, 2020 at 12:04 AM Xintong Song <tonysong...@gmail.com> >>> wrote: >>> >>>> Thanks for the input, Brain. >>>> >>>> This looks like what we are looking for. The issue is fixed in 1.10.3, >>>> which also matches this problem occurred in 1.10.2. >>>> >>>> Maybe Claude can further confirm it. >>>> >>>> Thank you~ >>>> >>>> Xintong Song >>>> >>>> >>>> >>>> On Tue, Sep 22, 2020 at 10:57 AM Zhou, Brian <b.z...@dell.com> wrote: >>>> >>>>> Hi Xintong and Claude, >>>>> >>>>> >>>>> >>>>> In our internal tests, we also encounter these two issues and we spent >>>>> much time debugging them. There are two points I need to confirm if we >>>>> share the same problem. >>>>> >>>>> 1. Your job is using default restart strategy, which is per-second >>>>> restart. >>>>> 2. Your CPU resource on jobmanager might be small >>>>> >>>>> >>>>> >>>>> Here is some findings I want to share. >>>>> >>>>> ## Metaspace OOM >>>>> >>>>> Due to https://issues.apache.org/jira/browse/FLINK-15467 , when we >>>>> have some job restarts, there will be some threads from the sourceFunction >>>>> hanging, cause the class loader cannot close. New restarts would load new >>>>> classes, then expand the metaspace, and finally OOM happens. >>>>> >>>>> >>>>> >>>>> ## Leader retrieving >>>>> >>>>> Constant restarts may be heavy for jobmanager, if JM CPU resources are >>>>> not enough, the thread for leader retrieving may be stuck. >>>>> >>>>> >>>>> >>>>> Best Regards, >>>>> >>>>> Brian >>>>> >>>>> >>>>> >>>>> *From:* Xintong Song <tonysong...@gmail.com> >>>>> *Sent:* Tuesday, September 22, 2020 10:16 >>>>> *To:* Claude M; user >>>>> *Subject:* Re: metaspace out-of-memory & error while retrieving the >>>>> leader gateway >>>>> >>>>> >>>>> >>>>> ## Metaspace OOM >>>>> >>>>> As the error message already suggested, the metaspace OOM you >>>>> encountered is likely caused by a class loading leak. I think you are on >>>>> the right direction trying to look into the heap dump and find out where >>>>> the leak comes from. IIUC, after removing the ZK folder, you are now able >>>>> to run Flink with the heap dump options. >>>>> >>>>> >>>>> >>>>> The problem does not occur in previous versions because Flink starts >>>>> to set the metaspace limit since the 1.10 release. The class loading leak >>>>> might have already been there, but is never discovered. This could lead to >>>>> unpredictable stability and performance issues. That's why Flink updated >>>>> its memory model and explicitly set the metaspace limit in the 1.10 >>>>> release. >>>>> >>>>> >>>>> >>>>> ## Leader retrieving >>>>> >>>>> The command looks good to me. If this problem happens only once, it >>>>> could be irrelevant to adding the options. If that does not block you from >>>>> getting the heap dump, we can look into it later. >>>>> >>>>> >>>>> Thank you~ >>>>> >>>>> Xintong Song >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> On Mon, Sep 21, 2020 at 9:37 PM Claude M <claudemur...@gmail.com> >>>>> wrote: >>>>> >>>>> Hi Xintong, >>>>> >>>>> >>>>> >>>>> Thanks for your reply. Here is the command output w/ the java.opts: >>>>> >>>>> >>>>> >>>>> /usr/local/openjdk-8/bin/java -Xms768m -Xmx768m -XX:+UseG1GC >>>>> -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/opt/flink/log >>>>> -Dlog4j.configuration=file:/opt/flink/conf/log4j-console.properties >>>>> -Dlogback.configurationFile=file:/opt/flink/conf/logback-console.xml >>>>> -classpath >>>>> /opt/flink/lib/flink-metrics-datadog-statsd-2.11-0.1.jar:/opt/flink/lib/flink-shaded-hadoop-2-uber-2.7.5-10.0.jar:/opt/flink/lib/flink-table-blink_2.11-1.10.2.jar:/opt/flink/lib/flink-table_2.11-1.10.2.jar:/opt/flink/lib/log4j-1.2.17.jar:/opt/flink/lib/slf4j-log4j12-1.7.15.jar:/opt/flink/lib/flink-dist_2.11-1.10.2.jar::/etc/hadoop/conf: >>>>> org.apache.flink.runtime.entrypoint.StandaloneSessionClusterEntrypoint >>>>> --configDir /opt/flink/conf --executionMode cluster >>>>> >>>>> >>>>> >>>>> To answer your questions: >>>>> >>>>> - Correct, in order for the pod to start up, I have to remove the >>>>> flink app folder from zookeeper. I only have to delete once after >>>>> applying >>>>> the java.opts arguments. It doesn't make sense though that I should >>>>> have >>>>> to do this just from adding a parameter. >>>>> - I'm using the standalone deployment. >>>>> - I'm using job cluster mode. >>>>> >>>>> A higher priority issue I'm trying to solve is this metaspace out of >>>>> memory that is occuring in task managers. This was not happening before I >>>>> upgraded to Flink 1.10.2. Even after increasing the memory, I'm still >>>>> encountering the problem. That is when I added the java.opts argument to >>>>> see if I can get more information about the problem. That is when I ran >>>>> across the second issue w/ the job manager pod not starting up. >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> Thanks >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> On Sun, Sep 20, 2020 at 10:23 PM Xintong Song <tonysong...@gmail.com> >>>>> wrote: >>>>> >>>>> Hi Claude, >>>>> >>>>> >>>>> >>>>> IIUC, in your case the leader retrieving problem is triggered by >>>>> adding the `java.opts`? Then could you try to find and post the complete >>>>> command for launching the JVM process? You can try log into the pod and >>>>> execute `ps -ef | grep <PID>`. >>>>> >>>>> >>>>> >>>>> A few more questions: >>>>> >>>>> - What do you mean by "resolve this"? Does the jobmanager pod get >>>>> stuck there, and recover when you remove the folder from ZK? Do you have >>>>> to >>>>> do the removal for everytime submitting the Kubernetes? >>>>> >>>>> The only way I can resolve this is to delete the folder from zookeeper >>>>> which I shouldn't have to do. >>>>> >>>>> - Which Flink's kubernetes deployment are you using? The standalone or >>>>> native Kubernetes? >>>>> >>>>> - Which cluster mode are you using? Job cluster, session cluster, or >>>>> the application mode? >>>>> >>>>> >>>>> >>>>> Thank you~ >>>>> >>>>> Xintong Song >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> On Sat, Sep 19, 2020 at 1:22 AM Claude M <claudemur...@gmail.com> >>>>> wrote: >>>>> >>>>> Hello, >>>>> >>>>> >>>>> >>>>> I upgraded from Flink 1.7.2 to 1.10.2. One of the jobs running on the >>>>> task managers is periodically crashing w/ the following error: >>>>> >>>>> >>>>> >>>>> java.lang.OutOfMemoryError: Metaspace. The metaspace out-of-memory >>>>> error has occurred. This can mean two things: either the job requires a >>>>> larger size of JVM metaspace to load classes or there is a class loading >>>>> leak. In the first case 'taskmanager.memory.jvm-metaspace.size' >>>>> configuration option should be increased. If the error persists (usually >>>>> in >>>>> cluster after several job (re-)submissions) then there is probably a class >>>>> loading leak which has to be investigated and fixed. The task executor has >>>>> to be shutdown. >>>>> >>>>> >>>>> >>>>> I found this issue regarding it: >>>>> >>>>> https://issues.apache.org/jira/browse/FLINK-16406 >>>>> >>>>> >>>>> >>>>> I have tried increasing the taskmanager.memory.jvm-metaspace.size to >>>>> 256M & 512M and still was having the problem. >>>>> >>>>> >>>>> >>>>> I then added the following to the flink.conf to try to get more >>>>> information about the error: >>>>> >>>>> env.java.opts: -XX:+UseG1GC -XX:+HeapDumpOnOutOfMemoryError >>>>> -XX:HeapDumpPath=/opt/flink/log >>>>> >>>>> >>>>> >>>>> When I deployed the change which is in a Kubernetes cluster, the >>>>> jobmanager pod fails to start up and the following message shows >>>>> repeatedly: >>>>> >>>>> >>>>> >>>>> 2020-09-18 17:03:46,255 WARN >>>>> org.apache.flink.runtime.webmonitor.retriever.impl.RpcGatewayRetriever - >>>>> Error while retrieving the leader gateway. Retrying to connect to >>>>> akka.tcp://flink@flink-jobmanager:50010/user/dispatcher. >>>>> >>>>> >>>>> >>>>> The only way I can resolve this is to delete the folder from zookeeper >>>>> which I shouldn't have to do. >>>>> >>>>> >>>>> >>>>> Any ideas on these issues? >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> >>>>>
