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Posted to user-zh@flink.apache.org by 胡松 <hs...@qq.com> on 2020/08/18 12:05:22 UTC
回复： flink 1.10.1 跑批任务 OutOfMemoryError: Metaspace
@Xintong Song
我们dump文件 这个driver是由ParentFirstClassloader加载的，存在DriverManager的registeredDrivers里，存在对ParentFirstClassloader的强引用。我们初始化mysql的代码如下，难道需要手动卸载下driver，然后各位有知道怎样手动卸载么或者有使用HikariDataSource没问题的么，而且我们用的是批处理，每10分钟执行次？
this.config = new HikariConfig();
this.config.setDriverClassName("com.mysql.jdbc.Driver");
this.config.setJdbcUrl(config.getConnectString());
this.config.setUsername(config.getUsername());
this.config.setPassword(config.getPassword());
this.config.setMinimumIdle(config.getCpMinimumIdle());
this.config.setMaximumPoolSize(config.getCpMaximumPoolSize());
this.config.setIdleTimeout(config.getCpIdleTimeout());
this.config.setMaxLifetime(config.getCpMaxLifetime());
this.config.setAutoCommit(false);
this.source = new HikariDataSource(this.config);
return true;
------------------ 原始邮件 ------------------
发件人: "user-zh" <tonysong820@gmail.com>;
发送时间: 2020年8月18日(星期二) 下午5:04
收件人: "user-zh"<user-zh@flink.apache.org>;
主题: Re: flink 1.10.1 跑批任务 OutOfMemoryError: Metaspace
按你的描述，应该是存在类加载泄露的问题。也就是说，由于某些原因，导致之前作业加载的类，没能被释放掉，致使类元数据积累越来越多，metaspace
空间不足。
具体泄露的原因还是需要根据 dump 分析，通常是作业用到的第三方依赖导致的，这种情况 flink 是没法强行清除加载类的。
Thank you~
Xintong Song
On Mon, Aug 17, 2020 at 6:38 PM 胡松 <hs-cs@qq.com> wrote:
> hi all
> &nbsp; &nbsp;使用flink 1.10.1 每10分钟跑一个批任务，但是跑一天后重复复现报错
> 2020-08-15 19:32:59
> org.apache.flink.runtime.JobException: Recovery is suppressed by
> NoRestartBackoffTimeStrategy
> at
> org.apache.flink.runtime.executiongraph.failover.flip1.ExecutionFailureHandler.handleFailure(ExecutionFailureHandler.java:110)
> at
> org.apache.flink.runtime.executiongraph.failover.flip1.ExecutionFailureHandler.getFailureHandlingResult(ExecutionFailureHandler.java:76)
> at
> org.apache.flink.runtime.scheduler.DefaultScheduler.handleTaskFailure(DefaultScheduler.java:192)
> at
> org.apache.flink.runtime.scheduler.DefaultScheduler.maybeHandleTaskFailure(DefaultScheduler.java:186)
> at
> org.apache.flink.runtime.scheduler.DefaultScheduler.updateTaskExecutionStateInternal(DefaultScheduler.java:180)
> at
> org.apache.flink.runtime.scheduler.SchedulerBase.updateTaskExecutionState(SchedulerBase.java:498)
> at
> org.apache.flink.runtime.jobmaster.JobMaster.updateTaskExecutionState(JobMaster.java:384)
> at sun.reflect.GeneratedMethodAccessor250.invoke(Unknown Source)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at
> org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleRpcInvocation(AkkaRpcActor.java:282)
> at
> org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleRpcMessage(AkkaRpcActor.java:197)
> at
> org.apache.flink.runtime.rpc.akka.FencedAkkaRpcActor.handleRpcMessage(FencedAkkaRpcActor.java:74)
> at
> org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleMessage(AkkaRpcActor.java:150)
> at akka.japi.pf.UnitCaseStatement.apply(CaseStatements.scala:26)
> at akka.japi.pf.UnitCaseStatement.apply(CaseStatements.scala:21)
> at
> scala.PartialFunction$class.applyOrElse(PartialFunction.scala:123)
> at akka.japi.pf
> .UnitCaseStatement.applyOrElse(CaseStatements.scala:21)
> at
> scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:170)
> at
> scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:171)
> at
> scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:171)
> at akka.actor.Actor$class.aroundReceive(Actor.scala:517)
> at akka.actor.AbstractActor.aroundReceive(AbstractActor.scala:225)
> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:592)
> at akka.actor.ActorCell.invoke(ActorCell.scala:561)
> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:258)
> at akka.dispatch.Mailbox.run(Mailbox.scala:225)
> at akka.dispatch.Mailbox.exec(Mailbox.scala:235)
> at
> akka.dispatch.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
> at
> akka.dispatch.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
> at
> akka.dispatch.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
> at
> akka.dispatch.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
> Caused by: 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...
>
> 使用MemoryAnalyzer分析，dump 700m 的文件就70多m，没定位到原因。
>
>
> 请问各位有碰到批任务这种问题的么？