如何知道在 YARN 客戶端模式下使用 spark-shell 導致 ClosedChannelExceptions 的原因是什么？

Question

我一直在嘗試在 YARN client模式下運行spark-shell ，但是我收到了很多ClosedChannelException錯誤。 我正在為 Hadoop 2.6 使用 spark 2.0.0 版本。

以下是例外情況：

$ spark-2.0.0-bin-hadoop2.6/bin/spark-shell --master yarn --deploy-mode client
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel).
16/09/13 14:12:36 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
16/09/13 14:12:38 WARN yarn.Client: Neither spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading libraries under SPARK_HOME.
16/09/13 14:12:55 ERROR cluster.YarnClientSchedulerBackend: Yarn application has already exited with state FINISHED!
16/09/13 14:12:55 ERROR client.TransportClient: Failed to send RPC 7920194824462016141 to /172.27.1.63:41034: java.nio.channels.ClosedChannelException
java.nio.channels.ClosedChannelException
16/09/13 14:12:55 ERROR spark.SparkContext: Error initializing SparkContext.
java.lang.IllegalStateException: Spark context stopped while waiting for backend
    at org.apache.spark.scheduler.TaskSchedulerImpl.waitBackendReady(TaskSchedulerImpl.scala:581)
    at org.apache.spark.scheduler.TaskSchedulerImpl.postStartHook(TaskSchedulerImpl.scala:162)
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:549)
    at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2256)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$8.apply(SparkSession.scala:831)
    at org.apache.spark.sql.SparkSession$Builder$$anonfun$8.apply(SparkSession.scala:823)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:823)
    at org.apache.spark.repl.Main$.createSparkSession(Main.scala:95)
    at $line3.$read$$iw$$iw.<init>(<console>:15)
    at $line3.$read$$iw.<init>(<console>:31)
    at $line3.$read.<init>(<console>:33)
    at $line3.$read$.<init>(<console>:37)
    at $line3.$read$.<clinit>(<console>)
    at $line3.$eval$.$print$lzycompute(<console>:7)
    at $line3.$eval$.$print(<console>:6)
    at $line3.$eval.$print(<console>)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:786)
    at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:1047)
    at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:638)
    at scala.tools.nsc.interpreter.IMain$WrappedRequest$$anonfun$loadAndRunReq$1.apply(IMain.scala:637)
    at scala.reflect.internal.util.ScalaClassLoader$class.asContext(ScalaClassLoader.scala:31)
    at scala.reflect.internal.util.AbstractFileClassLoader.asContext(AbstractFileClassLoader.scala:19)
    at scala.tools.nsc.interpreter.IMain$WrappedRequest.loadAndRunReq(IMain.scala:637)
    at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:569)
    at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:565)
    at scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:807)
    at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:681)
    at scala.tools.nsc.interpreter.ILoop.processLine(ILoop.scala:395)
    at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply$mcV$sp(SparkILoop.scala:38)
    at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:37)
    at org.apache.spark.repl.SparkILoop$$anonfun$initializeSpark$1.apply(SparkILoop.scala:37)
    at scala.tools.nsc.interpreter.IMain.beQuietDuring(IMain.scala:214)
    at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:37)
    at org.apache.spark.repl.SparkILoop.loadFiles(SparkILoop.scala:94)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply$mcZ$sp(ILoop.scala:920)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:909)
    at scala.tools.nsc.interpreter.ILoop$$anonfun$process$1.apply(ILoop.scala:909)
    at scala.reflect.internal.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:97)
    at scala.tools.nsc.interpreter.ILoop.process(ILoop.scala:909)
    at org.apache.spark.repl.Main$.doMain(Main.scala:68)
    at org.apache.spark.repl.Main$.main(Main.scala:51)
    at org.apache.spark.repl.Main.main(Main.scala)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:729)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:185)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:210)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:124)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
16/09/13 14:12:55 WARN netty.NettyRpcEndpointRef: Error sending message [message = RequestExecutors(0,0,Map())] in 1 attempts
org.apache.spark.SparkException: Exception thrown in awaitResult
    at org.apache.spark.rpc.RpcTimeout$$anonfun$1.applyOrElse(RpcTimeout.scala:77)
    at org.apache.spark.rpc.RpcTimeout$$anonfun$1.applyOrElse(RpcTimeout.scala:75)
    at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36)
    at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
    at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
    at scala.PartialFunction$OrElse.apply(PartialFunction.scala:167)
    at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:83)
    at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:102)
    at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:78)
    at org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint$$anonfun$receiveAndReply$1$$anonfun$applyOrElse$1.apply$mcV$sp(YarnSchedulerBackend.scala:271)
    at org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint$$anonfun$receiveAndReply$1$$anonfun$applyOrElse$1.apply(YarnSchedulerBackend.scala:271)
    at org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint$$anonfun$receiveAndReply$1$$anonfun$applyOrElse$1.apply(YarnSchedulerBackend.scala:271)
    at scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
    at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.IOException: Failed to send RPC 7920194824462016141 to /172.27.1.63:41034: java.nio.channels.ClosedChannelException
    at org.apache.spark.network.client.TransportClient$3.operationComplete(TransportClient.java:239)
    at org.apache.spark.network.client.TransportClient$3.operationComplete(TransportClient.java:226)
    at io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:680)
    at io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:567)
    at io.netty.util.concurrent.DefaultPromise.tryFailure(DefaultPromise.java:424)
    at io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetFailure(AbstractChannel.java:801)
    at io.netty.channel.AbstractChannel$AbstractUnsafe.write(AbstractChannel.java:699)
    at io.netty.channel.DefaultChannelPipeline$HeadContext.write(DefaultChannelPipeline.java:1122)
    at io.netty.channel.AbstractChannelHandlerContext.invokeWrite(AbstractChannelHandlerContext.java:633)
    at io.netty.channel.AbstractChannelHandlerContext.access$1900(AbstractChannelHandlerContext.java:32)
    at io.netty.channel.AbstractChannelHandlerContext$AbstractWriteTask.write(AbstractChannelHandlerContext.java:908)
    at io.netty.channel.AbstractChannelHandlerContext$WriteAndFlushTask.write(AbstractChannelHandlerContext.java:960)
    at io.netty.channel.AbstractChannelHandlerContext$AbstractWriteTask.run(AbstractChannelHandlerContext.java:893)
    at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:357)
    at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:357)
    at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111)
    ... 1 more
Caused by: java.nio.channels.ClosedChannelException
java.lang.IllegalStateException: Spark context stopped while waiting for backend
  at org.apache.spark.scheduler.TaskSchedulerImpl.waitBackendReady(TaskSchedulerImpl.scala:581)
  at org.apache.spark.scheduler.TaskSchedulerImpl.postStartHook(TaskSchedulerImpl.scala:162)
  at org.apache.spark.SparkContext.<init>(SparkContext.scala:549)
  at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2256)
  at org.apache.spark.sql.SparkSession$Builder$$anonfun$8.apply(SparkSession.scala:831)
  at org.apache.spark.sql.SparkSession$Builder$$anonfun$8.apply(SparkSession.scala:823)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:823)
  at org.apache.spark.repl.Main$.createSparkSession(Main.scala:95)
  ... 47 elided
<console>:14: error: not found: value spark
       import spark.implicits._
              ^
<console>:14: error: not found: value spark
       import spark.sql
              ^
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Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_101)
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scala> 16/09/13 14:12:59 ERROR client.TransportClient: Failed to send RPC 5797372389565173518 to /172.27.1.63:41034: java.nio.channels.ClosedChannelException
16/09/13 14:12:59 WARN netty.NettyRpcEndpointRef: Error sending message [message = RequestExecutors(0,0,Map())] in 2 attempts
org.apache.spark.SparkException: Exception thrown in awaitResult
    at org.apache.spark.rpc.RpcTimeout$$anonfun$1.applyOrElse(RpcTimeout.scala:77)
    at org.apache.spark.rpc.RpcTimeout$$anonfun$1.applyOrElse(RpcTimeout.scala:75)
    at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:36)
    at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
    at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
    at scala.PartialFunction$OrElse.apply(PartialFunction.scala:167)
    at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:83)
    at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:102)
    at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:78)
    at org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint$$anonfun$receiveAndReply$1$$anonfun$applyOrElse$1.apply$mcV$sp(YarnSchedulerBackend.scala:271)
    at org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint$$anonfun$receiveAndReply$1$$anonfun$applyOrElse$1.apply(YarnSchedulerBackend.scala:271)
    at org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint$$anonfun$receiveAndReply$1$$anonfun$applyOrElse$1.apply(YarnSchedulerBackend.scala:271)
    at scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
    at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.IOException: Failed to send RPC 5797372389565173518 to /172.27.1.63:41034: java.nio.channels.ClosedChannelException
    at org.apache.spark.network.client.TransportClient$3.operationComplete(TransportClient.java:239)
    at org.apache.spark.network.client.TransportClient$3.operationComplete(TransportClient.java:226)
    at io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:680)
    at io.netty.util.concurrent.DefaultPromise.notifyListeners(DefaultPromise.java:567)
    at io.netty.util.concurrent.DefaultPromise.tryFailure(DefaultPromise.java:424)
    at io.netty.channel.AbstractChannel$AbstractUnsafe.safeSetFailure(AbstractChannel.java:801)
    at io.netty.channel.AbstractChannel$AbstractUnsafe.write(AbstractChannel.java:699)
    at io.netty.channel.DefaultChannelPipeline$HeadContext.write(DefaultChannelPipeline.java:1122)
    at io.netty.channel.AbstractChannelHandlerContext.invokeWrite(AbstractChannelHandlerContext.java:633)
    at io.netty.channel.AbstractChannelHandlerContext.access$1900(AbstractChannelHandlerContext.java:32)
    at io.netty.channel.AbstractChannelHandlerContext$AbstractWriteTask.write(AbstractChannelHandlerContext.java:908)
    at io.netty.channel.AbstractChannelHandlerContext$WriteAndFlushTask.write(AbstractChannelHandlerContext.java:960)
    at io.netty.channel.AbstractChannelHandlerContext$AbstractWriteTask.run(AbstractChannelHandlerContext.java:893)
    at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:357)
    at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:357)
    at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111)
    ... 1 more
Caused by: java.nio.channels.ClosedChannelException

Answer 1

原因是由於 Java 8 過多的內存分配問題，可能會丟失與紗線集群的關聯： https : //issues.apache.org/jira/browse/YARN-4714

您可以通過在 yarn-site.xml 中設置以下屬性來強制 YARN 忽略它

<property>
    <name>yarn.nodemanager.pmem-check-enabled</name>
    <value>false</value>
</property>

<property>
    <name>yarn.nodemanager.vmem-check-enabled</name>
    <value>false</value>
</property>

感謝 simplejack，參考來自帶有 Yarn 的集群模式下的 Spark Pi 示例：關聯丟失

Answer 2

我個人通過按照Akira Ajisaka的Jira 票證中的建議增加yarn.nodemanager.vmem-pmem-ratio解決了這個問題：

<property>
    <name>yarn.nodemanager.vmem-pmem-ratio</name>
    <value>5</value>
</property>

Answer 3

我已經建立了另一個答案，這取決於您使用的是 Spark 客戶端還是集群模式。

• 在集群模式下，當我指定Driver Memory --driver-memory 為 512m 時它失敗了。 （默認設置要求 2GB 的 am 資源（這包括驅動程序內存 + 為 Application Master 請求的開銷）就足夠了）
• 在客戶端模式下，重要的設置是 spark.yarn.am.memory 因為默認情況下這僅為 AM 請求 1024m，這太少了，因為 Java 8 需要大量虛擬內存。 > 1024m 似乎有效。

答案在此處描述

Answer 4

我收到了帶有不同消息的 ClosedChannelException：

20/01/07 06:31:54 ERROR server.TransportChannelHandler: Connection to ip-10-0-202-150.ec2.internal/10.0.202.150:37801 has been quiet for 120000 ms while there are outstanding requests. Assuming connection is dead; please adjust spark.network.timeout if this is wrong.
20/01/07 06:31:54 ERROR executor.Executor: Exception in task 556.0 in stage 1.0 (TID 556)
java.nio.channels.ClosedChannelException
...

在 mapPartition 中，我正在對記錄進行批處理並進行 HTTP 調用來處理這些記錄，這可能需要幾分鍾時間。 可能是 Spark 假設分區已死，因為它很長時間沒有獲取更多記錄，因此我們得到了這個異常。

使用更長的值設置網絡超時有效。

spark.network.timeout=500s