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Posted to issues@spark.apache.org by "Kohki Nishio (Jira)" <ji...@apache.org> on 2021/09/22 17:48:00 UTC

[jira] [Commented] (SPARK-36827) Task/Stage/Job data remain in memory leads memory leak

    [ https://issues.apache.org/jira/browse/SPARK-36827?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17418742#comment-17418742 ] 

Kohki Nishio commented on SPARK-36827:
--------------------------------------

one thread shows slightly different codepoint
{code}
"element-tracking-store-worker" #355 daemon prio=5 os_prio=0 tid=0x00007f31b0014800 nid=0x409 runnable [0x00007f2f25783000]
   java.lang.Thread.State: RUNNABLE
	at java.util.concurrent.ConcurrentHashMap$Traverser.advance(ConcurrentHashMap.java:3318)
	at java.util.concurrent.ConcurrentHashMap$ValueIterator.next(ConcurrentHashMap.java:3439)
	at java.util.concurrent.ConcurrentHashMap$CollectionView.toArray(ConcurrentHashMap.java:4417)
	at java.util.ArrayList.<init>(ArrayList.java:178)
	at org.apache.spark.util.kvstore.InMemoryStore$InMemoryView.copyElements(InMemoryStore.java:428)
	at org.apache.spark.util.kvstore.InMemoryStore$InMemoryView.iterator(InMemoryStore.java:374)
	at org.apache.spark.util.kvstore.KVStoreView.closeableIterator(KVStoreView.java:117)
{code}

this loop seems to be very expensive if there are millions of entries
{code}
stages.map .. (AppStatusListener - N)
        final List<T> sorted = copyElements();  (InMemoryStore)
        sorted.sort((e1, e2) -> modifier * compare(e1, e2, getter)); (InMemoryStore)
{code}

so it gets out of control quickly

> Task/Stage/Job data remain in memory leads memory leak
> ------------------------------------------------------
>
>                 Key: SPARK-36827
>                 URL: https://issues.apache.org/jira/browse/SPARK-36827
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 3.1.2
>            Reporter: Kohki Nishio
>            Priority: Major
>         Attachments: mem1.txt, worker.txt
>
>
> Noticing memory-leak like behavior, steady increase of heap after GC and eventually it leads to a service failure. 
> The GC histogram shows very high number of Task/Data/Job data
> {code}
>  num     #instances         #bytes  class name 
> ---------------------------------------------- 
>    6:       7835346     2444627952  org.apache.spark.status.TaskDataWrapper 
>   25:       3765152      180727296  org.apache.spark.status.StageDataWrapper 
>   88:        232255        9290200  org.apache.spark.status.JobDataWrapper 
> {code}
> Thread dumps show clearly the clean up thread is doing infinite loop
> {code}
> "element-tracking-store-worker" #355 daemon prio=5 os_prio=0 tid=0x00007f31b0014800 nid=0x409 runnable [0x00007f2f25783000]
>    java.lang.Thread.State: RUNNABLE
> 	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> 	at java.lang.reflect.Method.invoke(Method.java:498)
> 	at org.apache.spark.util.kvstore.KVTypeInfo$MethodAccessor.get(KVTypeInfo.java:162)
> 	at org.apache.spark.util.kvstore.InMemoryStore$InMemoryView.compare(InMemoryStore.java:434)
> 	at org.apache.spark.util.kvstore.InMemoryStore$InMemoryView.lambda$iterator$0(InMemoryStore.java:375)
> 	at org.apache.spark.util.kvstore.InMemoryStore$InMemoryView$$Lambda$9000/574018760.compare(Unknown Source)
> 	at java.util.TimSort.gallopLeft(TimSort.java:542)
> 	at java.util.TimSort.mergeLo(TimSort.java:752)
> 	at java.util.TimSort.mergeAt(TimSort.java:514)
> 	at java.util.TimSort.mergeCollapse(TimSort.java:439)
> 	at java.util.TimSort.sort(TimSort.java:245)
> 	at java.util.Arrays.sort(Arrays.java:1512)
> 	at java.util.ArrayList.sort(ArrayList.java:1464)
> 	at org.apache.spark.util.kvstore.InMemoryStore$InMemoryView.iterator(InMemoryStore.java:375)
> 	at org.apache.spark.util.kvstore.KVStoreView.closeableIterator(KVStoreView.java:117)
> 	at org.apache.spark.status.AppStatusListener.$anonfun$cleanupStages$2(AppStatusListener.scala:1269)
> 	at org.apache.spark.status.AppStatusListener$$Lambda$9126/608388595.apply(Unknown Source)
> 	at scala.collection.immutable.List.map(List.scala:297)
> 	at org.apache.spark.status.AppStatusListener.cleanupStages(AppStatusListener.scala:1260)
> 	at org.apache.spark.status.AppStatusListener.$anonfun$new$3(AppStatusListener.scala:98)
> 	at org.apache.spark.status.AppStatusListener$$Lambda$646/596139882.apply$mcVJ$sp(Unknown Source)
> 	at org.apache.spark.status.ElementTrackingStore.$anonfun$write$3(ElementTrackingStore.scala:135)
> 	at org.apache.spark.status.ElementTrackingStore.$anonfun$write$3$adapted(ElementTrackingStore.scala:133)
> 	at org.apache.spark.status.ElementTrackingStore$$Lambda$986/162337848.apply(Unknown Source)
> 	at scala.collection.immutable.List.foreach(List.scala:431)
> 	at org.apache.spark.status.ElementTrackingStore.$anonfun$write$2(ElementTrackingStore.scala:133)
> 	at org.apache.spark.status.ElementTrackingStore.$anonfun$write$2$adapted(ElementTrackingStore.scala:131)
> 	at org.apache.spark.status.ElementTrackingStore$$Lambda$984/600376389.apply(Unknown Source)
> 	at org.apache.spark.status.ElementTrackingStore$LatchedTriggers.$anonfun$fireOnce$1(ElementTrackingStore.scala:58)
> 	at org.apache.spark.status.ElementTrackingStore$LatchedTriggers$$Lambda$985/1187323214.apply$mcV$sp(Unknown Source)
> 	at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
> 	at org.apache.spark.util.Utils$.tryLog(Utils.scala:2013)
> 	at org.apache.spark.status.ElementTrackingStore$$anon$1.run(ElementTrackingStore.scala:117)
> 	at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
> 	at java.util.concurrent.FutureTask.run(FutureTask.java:266)
> 	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)
> {code}
> Even after taking off all the incoming traffic, this thread continues to stay in AppStatusListener.cleanupStages, so I'm certain that it's doing infinite loop.



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