Question

我正在尝试使用AWS中的hdfs测试spark 1.6。我正在使用examples文件夹中提供的wordcount python示例。我使用spark-submit提交作业，作业成功完成，并在控制台上打印结果。网络用户界面也说完了。然而，spark-submit永远不会终止。我已经验证了字数统计示例代码中的上下文也已停止。

可能出现什么问题？

这是我在控制台上看到的内容。

6-05-24 14:58:04,749 INFO  [Thread-3] handler.ContextHandler (ContextHandler.java:doStop(843)) - stopped o.s.j.s.ServletContextHandler{/stages/stage,null}
2016-05-24 14:58:04,749 INFO  [Thread-3] handler.ContextHandler (ContextHandler.java:doStop(843)) - stopped o.s.j.s.ServletContextHandler{/stages/json,null}
2016-05-24 14:58:04,749 INFO  [Thread-3] handler.ContextHandler (ContextHandler.java:doStop(843)) - stopped o.s.j.s.ServletContextHandler{/stages,null}
2016-05-24 14:58:04,749 INFO  [Thread-3] handler.ContextHandler (ContextHandler.java:doStop(843)) - stopped o.s.j.s.ServletContextHandler{/jobs/job/json,null}
2016-05-24 14:58:04,750 INFO  [Thread-3] handler.ContextHandler (ContextHandler.java:doStop(843)) - stopped o.s.j.s.ServletContextHandler{/jobs/job,null}
2016-05-24 14:58:04,750 INFO  [Thread-3] handler.ContextHandler (ContextHandler.java:doStop(843)) - stopped o.s.j.s.ServletContextHandler{/jobs/json,null}
2016-05-24 14:58:04,750 INFO  [Thread-3] handler.ContextHandler (ContextHandler.java:doStop(843)) - stopped o.s.j.s.ServletContextHandler{/jobs,null}
2016-05-24 14:58:04,802 INFO  [Thread-3] ui.SparkUI (Logging.scala:logInfo(58)) - Stopped Spark web UI at http://172.30.2.239:4040
2016-05-24 14:58:04,805 INFO  [Thread-3] cluster.SparkDeploySchedulerBackend (Logging.scala:logInfo(58)) - Shutting down all executors
2016-05-24 14:58:04,805 INFO  [dispatcher-event-loop-2] cluster.SparkDeploySchedulerBackend (Logging.scala:logInfo(58)) - Asking each executor to shut down
2016-05-24 14:58:04,814 INFO  [dispatcher-event-loop-5] spark.MapOutputTrackerMasterEndpoint (Logging.scala:logInfo(58)) - MapOutputTrackerMasterEndpoint stopped!
2016-05-24 14:58:04,818 INFO  [Thread-3] storage.MemoryStore (Logging.scala:logInfo(58)) - MemoryStore cleared
2016-05-24 14:58:04,818 INFO  [Thread-3] storage.BlockManager (Logging.scala:logInfo(58)) - BlockManager stopped
2016-05-24 14:58:04,820 INFO  [Thread-3] storage.BlockManagerMaster (Logging.scala:logInfo(58)) - BlockManagerMaster stopped
2016-05-24 14:58:04,821 INFO  [dispatcher-event-loop-3] scheduler.OutputCommitCoordinator$OutputCommitCoordinatorEndpoint (Logging.scala:logInfo(58)) - OutputCommitCoordinator stopped!
2016-05-24 14:58:04,824 INFO  [Thread-3] spark.SparkContext (Logging.scala:logInfo(58)) - Successfully stopped SparkContext
2016-05-24 14:58:04,827 INFO  [sparkDriverActorSystem-akka.actor.default-dispatcher-2] remote.RemoteActorRefProvider$RemotingTerminator (Slf4jLogger.scala:apply$mcV$sp(74)) - Shutting down remote daemon.
2016-05-24 14:58:04,828 INFO  [sparkDriverActorSystem-akka.actor.default-dispatcher-2] remote.RemoteActorRefProvider$RemotingTerminator (Slf4jLogger.scala:apply$mcV$sp(74)) - Remote daemon shut down; proceeding with flushing remote transports.
2016-05-24 14:58:04,843 INFO  [sparkDriverActorSystem-akka.actor.default-dispatcher-2] remote.RemoteActorRefProvider$RemotingTerminator (Slf4jLogger.scala:apply$mcV$sp(74)) - Remoting shut down.

我必须执行ctrl-c来终止spark-submit进程。这真是一个奇怪的问题，我不知道如何解决这个问题。如果有任何我应该查看的日志，或者在这里做不同的事情，请告诉我。

以下是spark-submit进程的jstack输出的pastebin链接： http://pastebin.com/Nfnt4XmT

Answer 1

我的spark作业代码中的自定义线程池存在相同的问题。我发现在您的代码中使用自定义的 non 守护线程池使 spark-submit 挂起。您可以查看ThreadUtils.newDaemonCachedThreadPool()来了解Spark开发人员如何创建线程池，也可以使用此实用程序，但要小心，因为它们是程序包私有的。

Answer 2

对我来说：在本地它停止但在集群上执行时继续发送日志。我认为这是预期的行为。从另一个答案中得到这个并为我工作。

val sc=new SparkContext(conf)
try{
      //code goes here
}
finally{
      sc.stop()
}

这项技术在 Spark 和 PySpark 中都有效。 sample shot

工作完成后，spark-submit继续挂起

2 个答案: