[ 
https://issues.apache.org/jira/browse/FLINK-10672?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16940226#comment-16940226
 ] 

Yun Gao commented on FLINK-10672:
---------------------------------

Hi [~mxm], very thanks for the explanation. Besides, is it possible to also 
provide the topology of the underlying Flink Job and the status of each job 
vertex when the job get stuck? I think with these information, we may be able 
to analyze if there are cyclic dependency among tasks. 

> Task stuck while writing output to flink
> ----------------------------------------
>
>                 Key: FLINK-10672
>                 URL: https://issues.apache.org/jira/browse/FLINK-10672
>             Project: Flink
>          Issue Type: Bug
>          Components: Runtime / Coordination
>    Affects Versions: 1.5.4
>         Environment: OS: Debuan rodente 4.17
> Flink version: 1.5.4
> ||Key||Value||
> |jobmanager.heap.mb|1024|
> |jobmanager.rpc.address|localhost|
> |jobmanager.rpc.port|6123|
> |metrics.reporter.jmx.class|org.apache.flink.metrics.jmx.JMXReporter|
> |metrics.reporter.jmx.port|9250-9260|
> |metrics.reporters|jmx|
> |parallelism.default|1|
> |rest.port|8081|
> |taskmanager.heap.mb|1024|
> |taskmanager.numberOfTaskSlots|1|
> |web.tmpdir|/tmp/flink-web-bdb73d6c-5b9e-47b5-9ebf-eed0a7c82c26|
>  
> h1. Overview
> ||Data Port||All Slots||Free Slots||CPU Cores||Physical Memory||JVM Heap 
> Size||Flink Managed Memory||
> |43501|1|0|12|62.9 GB|922 MB|642 MB|
> h1. Memory
> h2. JVM (Heap/Non-Heap)
> ||Type||Committed||Used||Maximum||
> |Heap|922 MB|575 MB|922 MB|
> |Non-Heap|68.8 MB|64.3 MB|-1 B|
> |Total|991 MB|639 MB|922 MB|
> h2. Outside JVM
> ||Type||Count||Used||Capacity||
> |Direct|3,292|105 MB|105 MB|
> |Mapped|0|0 B|0 B|
> h1. Network
> h2. Memory Segments
> ||Type||Count||
> |Available|3,194|
> |Total|3,278|
> h1. Garbage Collection
> ||Collector||Count||Time||
> |G1_Young_Generation|13|336|
> |G1_Old_Generation|1|21|
>            Reporter: Ankur Goenka
>            Assignee: Yun Gao
>            Priority: Major
>              Labels: beam
>         Attachments: 1uruvakHxBu.png, 3aDKQ24WvKk.png, Po89UGDn58V.png, 
> jmx_dump.json, jmx_dump_detailed.json, jstack_129827.log, jstack_163822.log, 
> jstack_66985.log
>
>
> I am running a fairly complex pipleline with 200+ task.
> The pipeline works fine with small data (order of 10kb input) but gets stuck 
> with a slightly larger data (300kb input).
>  
> The task gets stuck while writing the output toFlink, more specifically it 
> gets stuck while requesting memory segment in local buffer pool. The Task 
> manager UI shows that it has enough memory and memory segments to work with.
> The relevant stack trace is 
> {quote}"grpc-default-executor-0" #138 daemon prio=5 os_prio=0 
> tid=0x00007fedb0163800 nid=0x30b7f in Object.wait() [0x00007fedb4f90000]
>  java.lang.Thread.State: TIMED_WAITING (on object monitor)
>  at (C/C++) 0x00007fef201c7dae (Unknown Source)
>  at (C/C++) 0x00007fef1f2aea07 (Unknown Source)
>  at (C/C++) 0x00007fef1f241cd3 (Unknown Source)
>  at java.lang.Object.wait(Native Method)
>  - waiting on <0x00000000f6d56450> (a java.util.ArrayDeque)
>  at 
> org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestMemorySegment(LocalBufferPool.java:247)
>  - locked <0x00000000f6d56450> (a java.util.ArrayDeque)
>  at 
> org.apache.flink.runtime.io.network.buffer.LocalBufferPool.requestBufferBuilderBlocking(LocalBufferPool.java:204)
>  at 
> org.apache.flink.runtime.io.network.api.writer.RecordWriter.requestNewBufferBuilder(RecordWriter.java:213)
>  at 
> org.apache.flink.runtime.io.network.api.writer.RecordWriter.sendToTarget(RecordWriter.java:144)
>  at 
> org.apache.flink.runtime.io.network.api.writer.RecordWriter.emit(RecordWriter.java:107)
>  at 
> org.apache.flink.runtime.operators.shipping.OutputCollector.collect(OutputCollector.java:65)
>  at 
> org.apache.flink.runtime.operators.util.metrics.CountingCollector.collect(CountingCollector.java:35)
>  at 
> org.apache.beam.runners.flink.translation.functions.FlinkExecutableStagePruningFunction.flatMap(FlinkExecutableStagePruningFunction.java:42)
>  at 
> org.apache.beam.runners.flink.translation.functions.FlinkExecutableStagePruningFunction.flatMap(FlinkExecutableStagePruningFunction.java:26)
>  at 
> org.apache.flink.runtime.operators.chaining.ChainedFlatMapDriver.collect(ChainedFlatMapDriver.java:80)
>  at 
> org.apache.flink.runtime.operators.util.metrics.CountingCollector.collect(CountingCollector.java:35)
>  at 
> org.apache.beam.runners.flink.translation.functions.FlinkExecutableStageFunction$MyDataReceiver.accept(FlinkExecutableStageFunction.java:230)
>  - locked <0x00000000f6a60bd0> (a java.lang.Object)
>  at 
> org.apache.beam.sdk.fn.data.BeamFnDataInboundObserver.accept(BeamFnDataInboundObserver.java:81)
>  at 
> org.apache.beam.sdk.fn.data.BeamFnDataInboundObserver.accept(BeamFnDataInboundObserver.java:32)
>  at 
> org.apache.beam.sdk.fn.data.BeamFnDataGrpcMultiplexer$InboundObserver.onNext(BeamFnDataGrpcMultiplexer.java:139)
>  at 
> org.apache.beam.sdk.fn.data.BeamFnDataGrpcMultiplexer$InboundObserver.onNext(BeamFnDataGrpcMultiplexer.java:125)
>  at 
> org.apache.beam.vendor.grpc.v1.io.grpc.stub.ServerCalls$StreamingServerCallHandler$StreamingServerCallListener.onMessage(ServerCalls.java:248)
>  at 
> org.apache.beam.vendor.grpc.v1.io.grpc.ForwardingServerCallListener.onMessage(ForwardingServerCallListener.java:33)
>  at 
> org.apache.beam.vendor.grpc.v1.io.grpc.Contexts$ContextualizedServerCallListener.onMessage(Contexts.java:76)
>  at 
> org.apache.beam.vendor.grpc.v1.io.grpc.internal.ServerCallImpl$ServerStreamListenerImpl.messagesAvailable(ServerCallImpl.java:263)
>  at 
> org.apache.beam.vendor.grpc.v1.io.grpc.internal.ServerImpl$JumpToApplicationThreadServerStreamListener$1MessagesAvailable.runInContext(ServerImpl.java:683)
>  at 
> org.apache.beam.vendor.grpc.v1.io.grpc.internal.ContextRunnable.run(ContextRunnable.java:37)
>  at 
> org.apache.beam.vendor.grpc.v1.io.grpc.internal.SerializingExecutor.run(SerializingExecutor.java:123)
>  at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
>  at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
>  at java.lang.Thread.run(Thread.java:748){quote}
>  
> The full stack trace and logs are attached.
>  Please take a look and let me know if more information is needed.



--
This message was sent by Atlassian Jira
(v8.3.4#803005)

Reply via email to