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https://issues.apache.org/jira/browse/SPARK-19814?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Simon King updated SPARK-19814:
-------------------------------
Attachment: SparkHistoryCPUandRAM.png
Graph showing CPU usage (top) and RSS RAM (bottom). Note the one run of SHS in
the middle with lower max heap setting eventually spent much more CPU time on
garbage collection.
> Spark History Server Out Of Memory / Extreme GC
> -----------------------------------------------
>
> Key: SPARK-19814
> URL: https://issues.apache.org/jira/browse/SPARK-19814
> Project: Spark
> Issue Type: Bug
> Components: Web UI
> Affects Versions: 1.6.1, 2.0.0, 2.1.0
> Environment: Spark History Server (we've run it on several different
> Hadoop distributions)
> Reporter: Simon King
> Attachments: SparkHistoryCPUandRAM.png
>
>
> Spark History Server runs out of memory, gets into GC thrash and eventually
> becomes unresponsive. This seems to happen more quickly with heavy use of the
> REST API. We've seen this with several versions of Spark.
> Running with the following settings (spark 2.1):
> spark.history.fs.cleaner.enabled true
> spark.history.fs.cleaner.interval 1d
> spark.history.fs.cleaner.maxAge 7d
> spark.history.retainedApplications 500
> We will eventually get errors like:
> 17/02/25 05:02:19 WARN ServletHandler:ยท
> javax.servlet.ServletException: scala.MatchError: java.lang.OutOfMemoryError:
> GC overhead limit exceeded (of class java.lang.OutOfMemoryError)
> at
> org.glassfish.jersey.servlet.WebComponent.serviceImpl(WebComponent.java:489)
> at org.glassfish.jersey.servlet.WebComponent.service(WebComponent.java:427)
> at
> org.glassfish.jersey.servlet.ServletContainer.service(ServletContainer.java:388)
> at
> org.glassfish.jersey.servlet.ServletContainer.service(ServletContainer.java:341)
> at
> org.glassfish.jersey.servlet.ServletContainer.service(ServletContainer.java:228)
> at
> org.spark_project.jetty.servlet.ServletHolder.handle(ServletHolder.java:812)
> at
> org.spark_project.jetty.servlet.ServletHandler.doHandle(ServletHandler.java:587)
> at
> org.spark_project.jetty.server.handler.ContextHandler.doHandle(ContextHandler.java:1127)
> at
> org.spark_project.jetty.servlet.ServletHandler.doScope(ServletHandler.java:515)
> at
> org.spark_project.jetty.server.handler.ContextHandler.doScope(ContextHandler.java:1061)
> at
> org.spark_project.jetty.server.handler.ScopedHandler.handle(ScopedHandler.java:141)
> at
> org.spark_project.jetty.servlets.gzip.GzipHandler.handle(GzipHandler.java:529)
> at
> org.spark_project.jetty.server.handler.ContextHandlerCollection.handle(ContextHandlerCollection.java:215)
> at
> org.spark_project.jetty.server.handler.HandlerWrapper.handle(HandlerWrapper.java:97)
> at org.spark_project.jetty.server.Server.handle(Server.java:499)
> at org.spark_project.jetty.server.HttpChannel.handle(HttpChannel.java:311)
> at
> org.spark_project.jetty.server.HttpConnection.onFillable(HttpConnection.java:257)
> at
> org.spark_project.jetty.io.AbstractConnection$2.run(AbstractConnection.java:544)
> at
> org.spark_project.jetty.util.thread.QueuedThreadPool.runJob(QueuedThreadPool.java:635)
> at
> org.spark_project.jetty.util.thread.QueuedThreadPool$3.run(QueuedThreadPool.java:555)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: scala.MatchError: java.lang.OutOfMemoryError: GC overhead limit
> exceeded (of class java.lang.OutOfMemoryError)
> at
> org.apache.spark.deploy.history.ApplicationCache.getSparkUI(ApplicationCache.scala:148)
> at
> org.apache.spark.deploy.history.HistoryServer.getSparkUI(HistoryServer.scala:110)
> at
> org.apache.spark.status.api.v1.UIRoot$class.withSparkUI(ApiRootResource.scala:244)
> at
> org.apache.spark.deploy.history.HistoryServer.withSparkUI(HistoryServer.scala:49)
> at
> org.apache.spark.status.api.v1.ApiRootResource.getJobs(ApiRootResource.scala:66)
> at sun.reflect.GeneratedMethodAccessor102.invoke(Unknown Source)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at
> org.glassfish.jersey.server.internal.routing.SubResourceLocatorRouter$1.run(SubResourceLocatorRouter.java:158)
> at
> org.glassfish.jersey.server.internal.routing.SubResourceLocatorRouter.getResource(SubResourceLocatorRouter.java:178)
> at
> org.glassfish.jersey.server.internal.routing.SubResourceLocatorRouter.apply(SubResourceLocatorRouter.java:109)
> at
> org.glassfish.jersey.server.internal.routing.RoutingStage._apply(RoutingStage.java:109)
> at
> org.glassfish.jersey.server.internal.routing.RoutingStage._apply(RoutingStage.java:112)
> at
> org.glassfish.jersey.server.internal.routing.RoutingStage._apply(RoutingStage.java:112)
> at
> org.glassfish.jersey.server.internal.routing.RoutingStage._apply(RoutingStage.java:112)
> at
> org.glassfish.jersey.server.internal.routing.RoutingStage._apply(RoutingStage.java:112)
> at
> org.glassfish.jersey.server.internal.routing.RoutingStage.apply(RoutingStage.java:92)
> at
> org.glassfish.jersey.server.internal.routing.RoutingStage.apply(RoutingStage.java:61)
> at org.glassfish.jersey.process.internal.Stages.process(Stages.java:197)
> at org.glassfish.jersey.server.ServerRuntime$2.run(ServerRuntime.java:318)
> at org.glassfish.jersey.internal.Errors$1.call(Errors.java:271)
> at org.glassfish.jersey.internal.Errors$1.call(Errors.java:267)
> at org.glassfish.jersey.internal.Errors.process(Errors.java:315)
> at org.glassfish.jersey.internal.Errors.process(Errors.java:297)
> at org.glassfish.jersey.internal.Errors.process(Errors.java:267)
> at
> org.glassfish.jersey.process.internal.RequestScope.runInScope(RequestScope.java:317)
> at org.glassfish.jersey.server.ServerRuntime.process(ServerRuntime.java:305)
> at
> org.glassfish.jersey.server.ApplicationHandler.handle(ApplicationHandler.java:1154)
> at
> org.glassfish.jersey.servlet.WebComponent.serviceImpl(WebComponent.java:473)
> In our case we see memory usage gradually increase over perhaps 2 days, then
> level off near max heap size (4G in our case), then often within 12-24 hours
> GC activity will start to increase, and will result in more and more frequent
> errors, as in the stack trace above.
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