Apache Spark running spark-shell on YARN error
17,505
Solution 1
I found the solution from another Stackoverflow question. It was not about configuring Apache Spark, it was about configuring Hadoop YARN:
Running yarn with spark not working with Java 8
Make sure your yarn-site.xml, from your Hadoop configuration folder, has these properties:
<property>
<name>yarn.nodemanager.pmem-check-enabled</name>
<value>false</value>
</property>
<property>
<name>yarn.nodemanager.vmem-check-enabled</name>
<value>false</value>
</property>
Solution 2
I met the same problem with you. When I check the NodeManager log，I find this warn:
2017-10-26 19:43:21,787 WARN org.apache.hadoop.yarn.server.nodemanager.containermanager.monitor.ContainersMonitorImpl: Container [pid=3820,containerID=container_1509016963775_0001_02_000001] is running beyond virtual memory limits. Current usage: 339.0 MB of 1 GB physical memory used; 2.2 GB of 2.1 GB virtual memory used. Killing container.
So I set a bigger virtual memory(yarn.nodemanager.vmem-pmem-ratio in yarn-site.xml, which default value is 2.1). Then it really worked.
Author by
Dobob
Updated on August 04, 2022Comments
-
Dobob over 1 year
I downloaded:
spark-2.1.0-bin-hadoop2.7.tgzfrom http://spark.apache.org/downloads.html. I have Hadoop HDFS and YARN started with$ start-dfs.shand$ start-yarn.sh. But running$ spark-shell --master yarn --deploy-mode clientgives me the error below:$ spark-shell --master yarn --deploy-mode client Setting default log level to "WARN". To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel). 17/04/08 23:04:54 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 17/04/08 23:04:54 WARN util.Utils: Your hostname, Pandora resolves to a loopback address: 127.0.1.1; using 192.168.1.11 instead (on interface wlp3s0) 17/04/08 23:04:54 WARN util.Utils: Set SPARK_LOCAL_IP if you need to bind to another address 17/04/08 23:04:56 WARN yarn.Client: Neither spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading libraries under SPARK_HOME. 17/04/08 23:05:15 ERROR cluster.YarnClientSchedulerBackend: Yarn application has already exited with state FINISHED! 17/04/08 23:05:15 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:614) at org.apache.spark.scheduler.TaskSchedulerImpl.postStartHook(TaskSchedulerImpl.scala:169) at org.apache.spark.SparkContext.<init>(SparkContext.scala:567) at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2313) at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:868) at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:860) at scala.Option.getOrElse(Option.scala:121) at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:860) at org.apache.spark.repl.Main$.createSparkSession(Main.scala:95) at $line3.$read$$iw$$iw.<init>(<console>:15) at $line3.$read$$iw.<init>(<console>:42) at $line3.$read.<init>(<console>:44) at $line3.$read$.<init>(<console>:48) at $line3.$read$.<clinit>(<console>) at $line3.$eval$.$print$lzycompute(<console>:7) at $line3.$eval$.$print(<console>:6) at $line3.$eval.$print(<console>) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:786) at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:1047) at scala.tools.nsc.interpreter.IMain$WrappedRequest$$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:105) 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:738) at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187) at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126) at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) 17/04/08 23:05:15 ERROR client.TransportClient: Failed to send RPC 7918328175210939600 to /192.168.1.11:56186: java.nio.channels.ClosedChannelException java.nio.channels.ClosedChannelException at io.netty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source) 17/04/08 23:05:15 ERROR cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Sending RequestExecutors(0,0,Map()) to AM was unsuccessful java.io.IOException: Failed to send RPC 7918328175210939600 to /192.168.1.11:56186: java.nio.channels.ClosedChannelException at org.apache.spark.network.client.TransportClient$3.operationComplete(TransportClient.java:249) at org.apache.spark.network.client.TransportClient$3.operationComplete(TransportClient.java:233) at io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:514) at io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:488) at io.netty.util.concurrent.DefaultPromise.access$000(DefaultPromise.java:34) at io.netty.util.concurrent.DefaultPromise$1.run(DefaultPromise.java:438) at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:408) at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:455) at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:140) at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144) at java.lang.Thread.run(Thread.java:745) Caused by: java.nio.channels.ClosedChannelException at io.netty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source) 17/04/08 23:05:15 ERROR util.Utils: Uncaught exception in thread Yarn application state monitor 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.scheduler.cluster.CoarseGrainedSchedulerBackend.requestTotalExecutors(CoarseGrainedSchedulerBackend.scala:512) at org.apache.spark.scheduler.cluster.YarnSchedulerBackend.stop(YarnSchedulerBackend.scala:93) at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.stop(YarnClientSchedulerBackend.scala:151) at org.apache.spark.scheduler.TaskSchedulerImpl.stop(TaskSchedulerImpl.scala:467) at org.apache.spark.scheduler.DAGScheduler.stop(DAGScheduler.scala:1588) at org.apache.spark.SparkContext$$anonfun$stop$8.apply$mcV$sp(SparkContext.scala:1826) at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1283) at org.apache.spark.SparkContext.stop(SparkContext.scala:1825) at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend$MonitorThread.run(YarnClientSchedulerBackend.scala:108) Caused by: java.io.IOException: Failed to send RPC 7918328175210939600 to /192.168.1.11:56186: java.nio.channels.ClosedChannelException at org.apache.spark.network.client.TransportClient$3.operationComplete(TransportClient.java:249) at org.apache.spark.network.client.TransportClient$3.operationComplete(TransportClient.java:233) at io.netty.util.concurrent.DefaultPromise.notifyListener0(DefaultPromise.java:514) at io.netty.util.concurrent.DefaultPromise.notifyListenersNow(DefaultPromise.java:488) at io.netty.util.concurrent.DefaultPromise.access$000(DefaultPromise.java:34) at io.netty.util.concurrent.DefaultPromise$1.run(DefaultPromise.java:438) at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:408) at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:455) at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:140) at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144) at java.lang.Thread.run(Thread.java:745) Caused by: java.nio.channels.ClosedChannelException at io.netty.channel.AbstractChannel$AbstractUnsafe.write(...)(Unknown Source) java.lang.IllegalStateException: Spark context stopped while waiting for backend at org.apache.spark.scheduler.TaskSchedulerImpl.waitBackendReady(TaskSchedulerImpl.scala:614) at org.apache.spark.scheduler.TaskSchedulerImpl.postStartHook(TaskSchedulerImpl.scala:169) at org.apache.spark.SparkContext.<init>(SparkContext.scala:567) at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2313) at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:868) at org.apache.spark.sql.SparkSession$Builder$$anonfun$6.apply(SparkSession.scala:860) at scala.Option.getOrElse(Option.scala:121) at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:860) 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 2.1.0 /_/ Using Scala version 2.11.8 (OpenJDK 64-Bit Server VM, Java 1.8.0_121) Type in expressions to have them evaluated. Type :help for more information.YARN detects Spark is running with it, but the error is causing Spark to exit with undefined status.
