Return-Path: X-Original-To: archive-asf-public-internal@cust-asf2.ponee.io Delivered-To: archive-asf-public-internal@cust-asf2.ponee.io Received: from cust-asf.ponee.io (cust-asf.ponee.io [163.172.22.183]) by cust-asf2.ponee.io (Postfix) with ESMTP id F22A4200D47 for ; Sat, 11 Nov 2017 03:47:20 +0100 (CET) Received: by cust-asf.ponee.io (Postfix) id EBDD1160BF2; Sat, 11 Nov 2017 02:47:20 +0000 (UTC) Delivered-To: archive-asf-public@cust-asf.ponee.io Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by cust-asf.ponee.io (Postfix) with SMTP id 6F28E160BEE for ; Sat, 11 Nov 2017 03:46:18 +0100 (CET) Received: (qmail 40162 invoked by uid 500); 10 Nov 2017 14:09:20 -0000 Mailing-List: contact user-help@flink.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Delivered-To: mailing list user@flink.apache.org Received: (qmail 40132 invoked by uid 99); 10 Nov 2017 14:09:19 -0000 Received: from pnap-us-west-generic-nat.apache.org (HELO spamd3-us-west.apache.org) (209.188.14.142) by apache.org (qpsmtpd/0.29) with ESMTP; Fri, 10 Nov 2017 14:09:19 +0000 Received: from localhost (localhost [127.0.0.1]) by spamd3-us-west.apache.org (ASF Mail Server at spamd3-us-west.apache.org) with ESMTP id 9A179182EC4; Fri, 10 Nov 2017 14:09:13 +0000 (UTC) X-Virus-Scanned: Debian amavisd-new at spamd3-us-west.apache.org X-Spam-Flag: NO X-Spam-Score: -2.403 X-Spam-Level: X-Spam-Status: No, score=-2.403 tagged_above=-999 required=6.31 tests=[DKIM_SIGNED=0.1, DKIM_VALID=-0.1, DKIM_VALID_AU=-0.1, RCVD_IN_DNSWL_MED=-2.3, RP_MATCHES_RCVD=-0.001, SPF_HELO_PASS=-0.001, SPF_PASS=-0.001] autolearn=disabled Authentication-Results: spamd3-us-west.apache.org (amavisd-new); dkim=pass (1024-bit key) header.d=cs.hacettepe.edu.tr Received: from mx1-lw-us.apache.org ([10.40.0.8]) by localhost (spamd3-us-west.apache.org [10.40.0.10]) (amavisd-new, port 10024) with ESMTP id cUXWo_9FJiiC; Fri, 10 Nov 2017 14:09:05 +0000 (UTC) Received: from cs.hacettepe.edu.tr (email.cs.hacettepe.edu.tr [193.140.236.18]) by mx1-lw-us.apache.org (ASF Mail Server at mx1-lw-us.apache.org) with ESMTPS id 8F0D361125; Fri, 10 Nov 2017 14:09:03 +0000 (UTC) DKIM-Signature: v=1; a=rsa-sha256; q=dns/txt; c=relaxed/relaxed; d=cs.hacettepe.edu.tr; s=cs; h=Message-ID:References:In-Reply-To:Subject:Cc: To:From:Date:Content-Type:MIME-Version:Sender:Reply-To: Content-Transfer-Encoding:Content-ID:Content-Description:Resent-Date: Resent-From:Resent-Sender:Resent-To:Resent-Cc:Resent-Message-ID:List-Id: List-Help:List-Unsubscribe:List-Subscribe:List-Post:List-Owner:List-Archive; bh=FTlXNMWqnkNwOnaDTarfH4eFWw9qEgWqsYHKPHuRnXc=; b=V9d+OgJEmMPbgo4rG/71uOHTP nXdbFvN3q03EIoAhcux8rTZFYY1abazng6XXBKw2qlUsKqRbhorbaIIskiiW3L236761NGx7iDkGA bb6SvEMFXm8BIyAIrESqiRc4qp8CHYVvUtM6nboMO+ThmrrVgf3vKdbD38KcoWzGWnvxs=; Received: from [127.0.0.1] (helo=webmail.cs.hacettepe.edu.tr) by cs.hacettepe.edu.tr with esmtpsa (TLSv1.2:ECDHE-RSA-AES128-GCM-SHA256:128) (Exim 4.89) (envelope-from ) id 1eD9zB-0008J0-Bh; Fri, 10 Nov 2017 17:09:01 +0300 MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="=_fc96efdb53e3ded96e7ded732e05f80d" Date: Fri, 10 Nov 2017 17:08:44 +0300 From: =?UTF-8?Q?=C3=87ET=C4=B0NKAYA_EBRU_=C3=87ET=C4=B0NKAYA_EBRU?= To: Piotr Nowojski Cc: Javier Lopez , Aljoscha Krettek , Nico Kruber , Ufuk Celebi , user Subject: Re: Flink memory leak In-Reply-To: <633C1FF0-9221-4689-9401-B3708DA305F4@data-artisans.com> References: <58D3AB1E-821D-46A2-8F04-8BB708037C2B@cs.hacettepe.edu.tr> <30C290C1-3FFD-479D-A926-861B110638BD@cs.hacettepe.edu.tr> <8c5facf8eda9ed6197c9e1c36099f8bb@cs.hacettepe.edu.tr> <14DD60D2-6E14-4DF3-836C-0A712F68B8C2@data-artisans.com> <95582EE2-9F90-43B8-8B3A-71A027A5DB1B@data-artisans.com> <972D0323-A628-45C6-AD1B-654EBD95AD96@data-artisans.com> <0019c4f2caf07e0fbde7a73ab7361002@cs.hacettepe.edu.tr> <9021B6B4-8A8D-4DBF-9C24-AC1F06956A4C@data-artisans.com> <57a785fab1f98ee12060d42adad186ff@cs.hacettepe.edu.tr> <633C1FF0-9221-4689-9401-B3708DA305F4@data-artisans.com> Message-ID: X-Sender: b20926247@cs.hacettepe.edu.tr User-Agent: Roundcube Webmail/1.1.9 X-Spam-Note: SpamAssassin run bypassed due to message size archived-at: Sat, 11 Nov 2017 02:47:21 -0000 --=_fc96efdb53e3ded96e7ded732e05f80d Content-Transfer-Encoding: 8bit Content-Type: text/plain; charset=UTF-8; format=flowed On 2017-11-10 13:14, Piotr Nowojski wrote: > jobmanager1.log and taskmanager2.log are the same. Can you also submit > files containing std output? > > Piotrek > >> On 10 Nov 2017, at 09:35, ÇETİNKAYA EBRU ÇETİNKAYA EBRU >> wrote: >> >> On 2017-11-10 11:04, Piotr Nowojski wrote: >>> Hi, >>> Thanks for the logs, however I do not see before mentioned exceptions >>> in it. It ends with java.lang.InterruptedException >>> Is it the correct log file? Also, could you attach the std output >>> file >>> of the failing TaskManager? >>> Piotrek >>>> On 10 Nov 2017, at 08:42, ÇETİNKAYA EBRU ÇETİNKAYA EBRU >>>> wrote: >>>> On 2017-11-09 20:08, Piotr Nowojski wrote: >>>>> Hi, >>>>> Could you attach full logs from those task managers? At first >>>>> glance I >>>>> don’t see a connection between those exceptions and any memory >>>>> issue >>>>> that you might had. It looks like a dependency issue in one (some? >>>>> All?) of your jobs. >>>>> Did you build your jars with -Pbuild-jar profile as described here: >>>>> https://ci.apache.org/projects/flink/flink-docs-release-1.3/quickstart/java_api_quickstart.html#build-project >>>>> ? >>>>> If that doesn’t help. Can you binary search which job is causing >>>>> the >>>>> problem? There might be some Flink incompatibility between >>>>> different >>>>> versions and rebuilding a job’s jar with a version matching to the >>>>> cluster version might help. >>>>> Piotrek >>>>>> On 9 Nov 2017, at 17:36, ÇETİNKAYA EBRU ÇETİNKAYA EBRU >>>>>> wrote: >>>>>> On 2017-11-08 18:30, Piotr Nowojski wrote: >>>>>> Btw, Ebru: >>>>>> I don’t agree that the main suspect is NetworkBufferPool. On your >>>>>> screenshots it’s memory consumption was reasonable and stable: >>>>>> 596MB >>>>>> -> 602MB -> 597MB. >>>>>> PoolThreadCache memory usage ~120MB is also reasonable. >>>>>> Do you experience any problems, like Out Of Memory >>>>>> errors/crashes/long >>>>>> GC pauses? Or just JVM process is using more memory over time? You >>>>>> are >>>>>> aware that JVM doesn’t like to release memory back to OS once it >>>>>> was >>>>>> used? So increasing memory usage until hitting some limit (for >>>>>> example >>>>>> JVM max heap size) is expected behaviour. >>>>>> Piotrek >>>>>> On 8 Nov 2017, at 15:48, Piotr Nowojski >>>>>> wrote: >>>>>> I don’t know if this is relevant to this issue, but I was >>>>>> constantly getting failures trying to reproduce this leak using >>>>>> your >>>>>> Job, because you were using non deterministic getKey function: >>>>>> @Override >>>>>> public Integer getKey(Integer event) { >>>>>> Random randomGen = new Random((new Date()).getTime()); >>>>>> return randomGen.nextInt() % 8; >>>>>> } >>>>>> And quoting Java doc of KeySelector: >>>>>> "If invoked multiple times on the same object, the returned key >>>>>> must >>>>>> be the same.” >>>>>> I’m trying to reproduce this issue with following job: >>>>>> https://gist.github.com/pnowojski/b80f725c1af7668051c773438637e0d3 >>>>>> Where IntegerSource is just an infinite source, DisardingSink is >>>>>> well just discarding incoming data. I’m cancelling the job every 5 >>>>>> seconds and so far (after ~15 minutes) my memory consumption is >>>>>> stable, well below maximum java heap size. >>>>>> Piotrek >>>>>> On 8 Nov 2017, at 15:28, Javier Lopez >>>>>> wrote: >>>>>> Yes, I tested with just printing the stream. But it could take a >>>>>> lot of time to fail. >>>>>> On Wednesday, 8 November 2017, Piotr Nowojski >>>>>> wrote: >>>>>> Thanks for quick answer. >>>>>> So it will also fail after some time with `fromElements` source >>>>>> instead of Kafka, right? >>>>>> Did you try it also without a Kafka producer? >>>>>> Piotrek >>>>>> On 8 Nov 2017, at 14:57, Javier Lopez >>>>>> wrote: >>>>>> Hi, >>>>>> You don't need data. With data it will die faster. I tested as >>>>>> well with a small data set, using the fromElements source, but it >>>>>> will take some time to die. It's better with some data. >>>>>> On 8 November 2017 at 14:54, Piotr Nowojski >>>>>> wrote: >>>>>> Hi, >>>>>> Thanks for sharing this job. >>>>>> Do I need to feed some data to the Kafka to reproduce this >>>>> issue with your script? >>>>>>> Does this OOM issue also happen when you are not using the >>>>> Kafka source/sink? >>>>>>> Piotrek >>>>>>> On 8 Nov 2017, at 14:08, Javier Lopez >>>>> wrote: >>>>>>> Hi, >>>>>>> This is the test flink job we created to trigger this leak >>>>> https://gist.github.com/javieredo/c6052404dbe6cc602e99f4669a09f7d6 >>>>>>> And this is the python script we are using to execute the job >>>>> thousands of times to get the OOM problem >>>>> https://gist.github.com/javieredo/4825324d5d5f504e27ca6c004396a107 >>>>>>> The cluster we used for this has this configuration: >>>>>>> Instance type: t2.large >>>>>>> Number of workers: 2 >>>>>>> HeapMemory: 5500 >>>>>>> Number of task slots per node: 4 >>>>>>> TaskMangMemFraction: 0.5 >>>>>>> NumberOfNetworkBuffers: 2000 >>>>>>> We have tried several things, increasing the heap, reducing the >>>>> heap, more memory fraction, changes this value in the >>>>> taskmanager.sh "TM_MAX_OFFHEAP_SIZE="2G"; and nothing seems to >>>>> work. >>>>>>> Thanks for your help. >>>>>>> On 8 November 2017 at 13:26, ÇETİNKAYA EBRU ÇETİNKAYA EBRU >>>>> wrote: >>>>>> On 2017-11-08 15:20, Piotr Nowojski wrote: >>>>>> Hi Ebru and Javier, >>>>>> Yes, if you could share this example job it would be helpful. >>>>>> Ebru: could you explain in a little more details how does >>>>> your Job(s) >>>>>> look like? Could you post some code? If you are just using >>>>> maps and >>>>>> filters there shouldn’t be any network transfers involved, >>>>> aside >>>>>> from Source and Sink functions. >>>>>> Piotrek >>>>>> On 8 Nov 2017, at 12:54, ebru >>>>> wrote: >>>>>> Hi Javier, >>>>>> It would be helpful if you share your test job with us. >>>>>> Which configurations did you try? >>>>>> -Ebru >>>>>> On 8 Nov 2017, at 14:43, Javier Lopez >>>>> >>>>>> wrote: >>>>>> Hi, >>>>>> We have been facing a similar problem. We have tried some >>>>> different >>>>>> configurations, as proposed in other email thread by Flavio >>>>> and >>>>>> Kien, but it didn't work. We have a workaround similar to >>>>> the one >>>>>> that Flavio has, we restart the taskmanagers once they reach >>>>> a >>>>>> memory threshold. We created a small test to remove all of >>>>> our >>>>>> dependencies and leave only flink native libraries. This >>>>> test reads >>>>>> data from a Kafka topic and writes it back to another topic >>>>> in >>>>>> Kafka. We cancel the job and start another every 5 seconds. >>>>> After >>>>>> ~30 minutes of doing this process, the cluster reaches the >>>>> OS memory >>>>>> limit and dies. >>>>>> Currently, we have a test cluster with 8 workers and 8 task >>>>> slots >>>>>> per node. We have one job that uses 56 slots, and we cannot >>>>> execute >>>>>> that job 5 times in a row because the whole cluster dies. If >>>>> you >>>>>> want, we can publish our test job. >>>>>> Regards, >>>>>> On 8 November 2017 at 11:20, Aljoscha Krettek >>>>> >>>>>> wrote: >>>>>> @Nico & @Piotr Could you please have a look at this? You >>>>> both >>>>>> recently worked on the network stack and might be most >>>>> familiar with >>>>>> this. >>>>>> On 8. Nov 2017, at 10:25, Flavio Pompermaier >>>>> >>>>>> wrote: >>>>>> We also have the same problem in production. At the moment >>>>> the >>>>>> solution is to restart the entire Flink cluster after every >>>>> job.. >>>>>> We've tried to reproduce this problem with a test (see >>>>>> https://issues.apache.org/jira/browse/FLINK-7845 [1]) but we >>>>> don't >>>>>> know whether the error produced by the test and the leak are >>>>>> correlated.. >>>>>> Best, >>>>>> Flavio >>>>>> On Wed, Nov 8, 2017 at 9:51 AM, ÇETİNKAYA EBRU ÇETİNKAYA >>>>> EBRU >>>>>> wrote: >>>>>> On 2017-11-07 16:53, Ufuk Celebi wrote: >>>>>> Do you use any windowing? If yes, could you please share >>>>> that code? >>>>>> If >>>>>> there is no stateful operation at all, it's strange where >>>>> the list >>>>>> state instances are coming from. >>>>>> On Tue, Nov 7, 2017 at 2:35 PM, ebru >>>>> >>>>>> wrote: >>>>>> Hi Ufuk, >>>>>> We don’t explicitly define any state descriptor. We only >>>>> use map >>>>>> and filters >>>>>> operator. We thought that gc handle clearing the flink’s >>>>> internal >>>>>> states. >>>>>> So how can we manage the memory if it is always increasing? >>>>>> - Ebru >>>>>> On 7 Nov 2017, at 16:23, Ufuk Celebi wrote: >>>>>> Hey Ebru, the memory usage might be increasing as long as a >>>>> job is >>>>>> running. >>>>>> This is expected (also in the case of multiple running >>>>> jobs). The >>>>>> screenshots are not helpful in that regard. :-( >>>>>> What kind of stateful operations are you using? Depending on >>>>> your >>>>>> use case, >>>>>> you have to manually call `clear()` on the state instance in >>>>> order >>>>>> to >>>>>> release the managed state. >>>>>> Best, >>>>>> Ufuk >>>>>> On Tue, Nov 7, 2017 at 12:43 PM, ebru >>>>>> wrote: >>>>>> Begin forwarded message: >>>>>> From: ebru >>>>>> Subject: Re: Flink memory leak >>>>>> Date: 7 November 2017 at 14:09:17 GMT+3 >>>>>> To: Ufuk Celebi >>>>>> Hi Ufuk, >>>>>> There are there snapshots of htop output. >>>>>> 1. snapshot is initial state. >>>>>> 2. snapshot is after submitted one job. >>>>>> 3. Snapshot is the output of the one job with 15000 EPS. And >>>>> the >>>>>> memory >>>>>> usage is always increasing over time. >>>>>> <1.png><2.png><3.png> >>>>>> On 7 Nov 2017, at 13:34, Ufuk Celebi wrote: >>>>>> Hey Ebru, >>>>>> let me pull in Aljoscha (CC'd) who might have an idea what's >>>>> causing >>>>>> this. >>>>>> Since multiple jobs are running, it will be hard to >>>>> understand to >>>>>> which job the state descriptors from the heap snapshot >>>>> belong to. >>>>>> - Is it possible to isolate the problem and reproduce the >>>>> behaviour >>>>>> with only a single job? >>>>>> – Ufuk >>>>>> On Tue, Nov 7, 2017 at 10:27 AM, ÇETİNKAYA EBRU >>>>> ÇETİNKAYA EBRU >>>>>> wrote: >>>>>> Hi, >>>>>> We are using Flink 1.3.1 in production, we have one job >>>>> manager and >>>>>> 3 task >>>>>> managers in standalone mode. Recently, we've noticed that we >>>>> have >>>>>> memory >>>>>> related problems. We use docker container to serve Flink >>>>> cluster. We >>>>>> have >>>>>> 300 slots and 20 jobs are running with parallelism of 10. >>>>> Also the >>>>>> job >>>>>> count >>>>>> may be change over time. Taskmanager memory usage always >>>>> increases. >>>>>> After >>>>>> job cancelation this memory usage doesn't decrease. We've >>>>> tried to >>>>>> investigate the problem and we've got the task manager jvm >>>>> heap >>>>>> snapshot. >>>>>> According to the jam heap analysis, possible memory leak was >>>>> Flink >>>>>> list >>>>>> state descriptor. But we are not sure that is the cause of >>>>> our >>>>>> memory >>>>>> problem. How can we solve the problem? >>>>>> We have two types of Flink job. One has no state full >>>>> operator >>>>>> contains only maps and filters and the other has time window >>>>> with >>>>>> count trigger. >>>>>> * We've analysed the jvm heaps again in different >>>>> conditions. First >>>>>> we analysed the snapshot when no flink jobs running on >>>>> cluster. (image >>>>>> 1) >>>>>> * Then, we analysed the jvm heap snapshot when the flink job >>>>> that has >>>>>> no state full operator is running. And according to the >>>>> results, leak >>>>>> suspect was NetworkBufferPool (image 2) >>>>>> * Last analys, there were both two types of jobs running >>>>> and leak >>>>>> suspect was again NetworkBufferPool. (image 3) >>>>>> In our system jobs are regularly cancelled and resubmitted so >>>>> we >>>>>> noticed that when job is submitted some amount of memory >>>>> allocated and >>>>>> after cancelation this allocated memory never freed. So over >>>>> time >>>>>> memory usage is always increasing and exceeded the limits. >>>>> Links: >>>>> ------ >>>>> [1] https://issues.apache.org/jira/browse/FLINK-7845 >>>>> Hi Piotr, >>>>> There are two types of jobs. >>>>> In first, we use Kafka source and Kafka sink, there isn't any >>>>> window operator. >>>>>> In second job, we use Kafka source, filesystem sink and >>>>> elastic search sink and window operator for buffering. >>>>> Hi Piotrek, >>>>> Thanks for your reply. >>>>> We've tested our link cluster again. We have 360 slots, and our >>>>> cluster configuration is like this; >>>>> jobmanager.rpc.address: %JOBMANAGER% >>>>> jobmanager.rpc.port: 6123 >>>>> jobmanager.heap.mb: 1536 >>>>> taskmanager.heap.mb: 1536 >>>>> taskmanager.numberOfTaskSlots: 120 >>>>> taskmanager.memory.preallocate: false >>>>> parallelism.default: 1 >>>>> jobmanager.web.port: 8081 >>>>> state.backend: filesystem >>>>> state.backend.fs.checkpointdir: file:///storage/%CHECKPOINTDIR% >>>>> state.checkpoints.dir: file:///storage/%CHECKPOINTDIR% >>>>> taskmanager.network.numberOfBuffers: 5000 >>>>> We are using docker based Flink cluster. >>>>> WE submitted 36 jobs with the parallelism of 10. After all slots >>>>> became full. Memory usage were increasing by the time and one by >>>>> one >>>>> task managers start to die. And the exception was like this; >>>>> Taskmanager1 log: >>>>> Uncaught error from thread [flink-akka.actor.default-dispatcher-17] >>>>> shutting down JVM since 'akka.jvm-exit-on-fatal-error' is enabled >>>>> for >>>>> ActorSystem[flink] >>>>> java.lang.NoClassDefFoundError: >>>>> org/apache/kafka/common/metrics/stats/Rate$1 >>>>>   at >>>>> org.apache.kafka.common.metrics.stats.Rate.convert(Rate.java:93) >>>>>   at >>>>> org.apache.kafka.common.metrics.stats.Rate.measure(Rate.java:62) >>>>>   at >>>>> org.apache.kafka.common.metrics.KafkaMetric.value(KafkaMetric.java:61) >>>>>   at >>>>> org.apache.kafka.common.metrics.KafkaMetric.value(KafkaMetric.java:52) >>>>>   at >>>>> org.apache.flink.streaming.connectors.kafka.internals.metrics.KafkaMetricWrapper.getValue(KafkaMetricWrapper.java:35) >>>>>   at >>>>> org.apache.flink.streaming.connectors.kafka.internals.metrics.KafkaMetricWrapper.getValue(KafkaMetricWrapper.java:26) >>>>>   at >>>>> org.apache.flink.runtime.metrics.dump.MetricDumpSerialization.serializeGauge(MetricDumpSerialization.java:213) >>>>>   at >>>>> org.apache.flink.runtime.metrics.dump.MetricDumpSerialization.access$200(MetricDumpSerialization.java:50) >>>>>   at >>>>> org.apache.flink.runtime.metrics.dump.MetricDumpSerialization$MetricDumpSerializer.serialize(MetricDumpSerialization.java:138) >>>>>   at >>>>> org.apache.flink.runtime.metrics.dump.MetricQueryService.onReceive(MetricQueryService.java:109) >>>>>   at >>>>> akka.actor.UntypedActor$$anonfun$receive$1.applyOrElse(UntypedActor.scala:167) >>>>>   at akka.actor.Actor$class.aroundReceive(Actor.scala:467) >>>>>   at akka.actor.UntypedActor.aroundReceive(UntypedActor.scala:97) >>>>>   at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516) >>>>>   at akka.actor.ActorCell.invoke(ActorCell.scala:487) >>>>>   at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238) >>>>>   at akka.dispatch.Mailbox.run(Mailbox.scala:220) >>>>>   at >>>>> akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:397) >>>>>   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) >>>>> Caused by: java.lang.ClassNotFoundException: >>>>> org.apache.kafka.common.metrics.stats.Rate$1 >>>>>   at java.net.URLClassLoader.findClass(URLClassLoader.java:381) >>>>>   at java.lang.ClassLoader.loadClass(ClassLoader.java:424) >>>>>   at java.lang.ClassLoader.loadClass(ClassLoader.java:357) >>>>>   ... 22 more >>>>> Taskmanager2 log: >>>>> Uncaught error from thread [flink-akka.actor.default-dispatcher-17] >>>>> shutting down JVM since 'akka.jvm-exit-on-fatal-error' is enabled >>>>> for >>>>> ActorSystem[flink] >>>>> Java.lang.NoClassDefFoundError: >>>>> org/apache/flink/streaming/connectors/kafka/internals/AbstractFetcher$1 >>>>>   at >>>>> org.apache.flink.streaming.connectors.kafka.internals.AbstractFetcher$OffsetGauge.getValue(AbstractFetcher.java:492) >>>>>   at >>>>> org.apache.flink.streaming.connectors.kafka.internals.AbstractFetcher$OffsetGauge.getValue(AbstractFetcher.java:480) >>>>>   at >>>>> org.apache.flink.runtime.metrics.dump.MetricDumpSerialization.serializeGauge(MetricDumpSerialization.java:213) >>>>>   at >>>>> org.apache.flink.runtime.metrics.dump.MetricDumpSerialization.access$200(MetricDumpSerialization.java:50) >>>>>   at >>>>> org.apache.flink.runtime.metrics.dump.MetricDumpSerialization$MetricDumpSerializer.serialize(MetricDumpSerialization.java:138) >>>>>   at >>>>> org.apache.flink.runtime.metrics.dump.MetricQueryService.onReceive(MetricQueryService.java:109) >>>>>   at >>>>> akka.actor.UntypedActor$$anonfun$receive$1.applyOrElse(UntypedActor.scala:167) >>>>>   at akka.actor.Actor$class.aroundReceive(Actor.scala:467) >>>>>   at akka.actor.UntypedActor.aroundReceive(UntypedActor.scala:97) >>>>>   at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516) >>>>>   at akka.actor.ActorCell.invoke(ActorCell.scala:487) >>>>>   at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238) >>>>>   at akka.dispatch.Mailbox.run(Mailbox.scala:220) >>>>>   at >>>>> akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:397) >>>>>   at >>>>> scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260) >>>>>   at >>>>> scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339) >>>>>   at >>>>> scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979) >>>>>   at >>>>> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107) >>>>> Caused by: java.lang.ClassNotFoundException: >>>>> org.apache.flink.streaming.connectors.kafka.internals.AbstractFetcher$1 >>>>>   at java.net.URLClassLoader.findClass(URLClassLoader.java:381) >>>>>   at java.lang.ClassLoader.loadClass(ClassLoader.java:424) >>>>>   at java.lang.ClassLoader.loadClass(ClassLoader.java:357) >>>>>   ... 18 more >>>>> -Ebru >>>> Hi Piotrek, >>>> We attached the full log of the taskmanager1. >>>> This may not be a dependency issue because until all of the task >>>> slots is full, we didn't get any No Class Def Found exception, when >>>> there is available memory jobs can run without exception for days. >>>> Also there is Kafka Instance Already Exist exception in full log, >>>> but this not relevant and doesn't effect jobs or task managers. >>>> -Ebru >> Hi, >> >> Sorry we attached wrong log file. I've attached all task managers and >> job manager's log. All task managers and job manager was >> killed. We' ve lost stdout files so we reproduced the problem. Also after some time, it start using swap. 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