如何知道在 YARN 客户端模式下使用 spark-shell 导致 ClosedChannelExceptions 的原因是什么？
[英]How to know what is the reason for ClosedChannelExceptions with spark-shell in YARN client mode?
问题描述
我一直在尝试在 YARN client模式下运行spark-shell ，但是我收到了很多ClosedChannelException错误。 我正在为 Hadoop 2.6 使用 spark 2.0.0 版本。
以下是例外情况：
$ 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
^
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.0.0
/_/
Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_101)
Type in expressions to have them evaluated.
Type :help for more information.
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
4 个解决方案
解决方案1
27 已采纳 2016-09-14 06:20:01
原因是由于 Java 8 过多的内存分配问题，可能会丢失与纱线集群的关联： https : //issues.apache.org/jira/browse/YARN-4714
您可以通过在 yarn-site.xml 中设置以下属性来强制 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>
感谢 simplejack，参考来自带有 Yarn 的集群模式下的 Spark Pi 示例：关联丢失
解决方案2
3 2017-09-18 22:31:33
我个人通过按照Akira Ajisaka的Jira 票证中的建议增加yarn.nodemanager.vmem-pmem-ratio解决了这个问题：
<property>
<name>yarn.nodemanager.vmem-pmem-ratio</name>
<value>5</value>
</property>
解决方案3
3 2018-12-21 16:23:14
我已经建立了另一个答案，这取决于您使用的是 Spark 客户端还是集群模式。
- 在集群模式下，当我指定Driver Memory --driver-memory 为 512m 时它失败了。 （默认设置要求 2GB 的 am 资源（这包括驱动程序内存 + 为 Application Master 请求的开销）就足够了）
- 在客户端模式下，重要的设置是 spark.yarn.am.memory 因为默认情况下这仅为 AM 请求 1024m，这太少了，因为 Java 8 需要大量虚拟内存。 > 1024m 似乎有效。
答案在此处描述
解决方案4
0 2020-01-07 07:36:28
我收到了带有不同消息的 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，我正在对记录进行批处理并进行 HTTP 调用来处理这些记录，这可能需要几分钟时间。 可能是 Spark 假设分区已死，因为它很长时间没有获取更多记录，因此我们得到了这个异常。
使用更长的值设置网络超时有效。
spark.network.timeout=500s
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