spark-shell无法连接到远程主站

时间：2017-04-18 09:35:45

标签： hadoop apache-spark bigdata

我有两个相同版本的火花。 192.168.2.230为主人，192.168.2.5为奴隶 我在./spark-submit --version和2.5上尝试了2.230：

Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 2.1.0
      /_/

Using Scala version 2.11.8, OpenJDK 64-Bit Server VM, 1.8.0_121
Branch
Compiled by user jenkins on 2016-12-16T02:04:48Z
Revision
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Type --help for more information.

他们的火花版本是一样的。
然后我更改了主配置（2.230）conf/spark-env.sh设置：

SPARK_LOCAL_IP=192.168.2.230 
SPARK_MASTER_HOST=192.168.2.230

并运行master（2.230）：

sbin/start-all.sh

我可以在端口http://192.168.2.230:8080上看到主管理ui。

然后我尝试在2.5上使用spark shell：

./spark-shell --master=spark://192.168.2.230:7077

发生了一些错误，无法连接到2.230，它喜欢版本不兼容，但这两个火花副本来自同一个tar.gz，这里是错误：

[root@localhost bin]# ./spark-shell --master=spark://192.168.2.230:7077
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
17/04/19 03:04:20 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
17/04/19 03:04:20 WARN Utils: Your hostname, localhost.localdomain resolves to a loopback address: 127.0.0.1; using 192.168.2.5 instead (on interface enp3s0)
17/04/19 03:04:20 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
17/04/19 03:04:20 WARN StandaloneAppClient$ClientEndpoint: Failed to connect to master 192.168.2.230:7077
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.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:100)
    at org.apache.spark.rpc.RpcEnv.setupEndpointRef(RpcEnv.scala:108)
    at org.apache.spark.deploy.client.StandaloneAppClient$ClientEndpoint$$anonfun$tryRegisterAllMasters$1$$anon$1.run(StandaloneAppClient.scala:106)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
    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.lang.RuntimeException: java.io.InvalidClassException: org.apache.spark.rpc.netty.RequestMessage; local class incompatible: stream classdesc serialVersionUID = -5447855329526097695, local class serialVersionUID = -2221986757032131007
    at java.io.ObjectStreamClass.initNonProxy(ObjectStreamClass.java:616)
    at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1630)
    at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1521)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1781)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1353)
    at java.io.ObjectInputStream.readObject(ObjectInputStream.java:373)
    at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:76)
    at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:109)
    at org.apache.spark.rpc.netty.NettyRpcEnv$$anonfun$deserialize$1$$anonfun$apply$1.apply(NettyRpcEnv.scala:258)
    at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
    at org.apache.spark.rpc.netty.NettyRpcEnv.deserialize(NettyRpcEnv.scala:310)
    at org.apache.spark.rpc.netty.NettyRpcEnv$$anonfun$deserialize$1.apply(NettyRpcEnv.scala:257)
    at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
    at org.apache.spark.rpc.netty.NettyRpcEnv.deserialize(NettyRpcEnv.scala:256)
    at org.apache.spark.rpc.netty.NettyRpcHandler.internalReceive(NettyRpcEnv.scala:588)
    at org.apache.spark.rpc.netty.NettyRpcHandler.receive(NettyRpcEnv.scala:570)
    at org.apache.spark.network.server.TransportRequestHandler.processRpcRequest(TransportRequestHandler.java:149)
    at org.apache.spark.network.server.TransportRequestHandler.handle(TransportRequestHandler.java:102)
    at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:104)
    at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:51)
    at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
    at io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:266)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
    at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:103)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
    at org.apache.spark.network.util.TransportFrameDecoder.channelRead(TransportFrameDecoder.java:86)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
    at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:846)
    at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131)
    at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:511)
    at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
    at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
    at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)
    at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111)
    at java.lang.Thread.run(Thread.java:745)

    at org.apache.spark.network.client.TransportResponseHandler.handle(TransportResponseHandler.java:189)
    at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:121)
    at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:51)
    at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353)
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346)
    at io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:266)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353)
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346)
    at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:102)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353)
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346)
    at org.apache.spark.network.util.TransportFrameDecoder.channelRead(TransportFrameDecoder.java:85)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353)
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346)
    at io.netty.channel.DefaultChannelPipeline$HeadContext.channelRead(DefaultChannelPipeline.java:1294)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367)
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353)
    at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:911)
    at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131)
    at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:652)
    at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:575)
    at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:489)
    at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:451)
    at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:140)
    at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144)
    ... 1 more
17/04/19 03:04:40 ERROR StandaloneSchedulerBackend: Application has been killed. Reason: All masters are unresponsive! Giving up.
17/04/19 03:04:40 WARN StandaloneSchedulerBackend: Application ID is not initialized yet.
17/04/19 03:04:40 WARN StandaloneAppClient$ClientEndpoint: Drop UnregisterApplication(null) because has not yet connected to master
17/04/19 03:04:40 ERROR SparkContext: Error initializing SparkContext.
java.lang.IllegalArgumentException: requirement failed: Can only call getServletHandlers on a running MetricsSystem
    at scala.Predef$.require(Predef.scala:224)
    at org.apache.spark.metrics.MetricsSystem.getServletHandlers(MetricsSystem.scala:91)
    at org.apache.spark.SparkContext.<init>(SparkContext.scala:524)
    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$.main(SparkSubmit.scala:126)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
java.lang.IllegalArgumentException: requirement failed: Can only call getServletHandlers on a running MetricsSystem
  at scala.Predef$.require(Predef.scala:224)
  at org.apache.spark.metrics.MetricsSystem.getServletHandlers(MetricsSystem.scala:91)
  at org.apache.spark.SparkContext.<init>(SparkContext.scala:524)
  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.

scala>

2.5无法连接到2.230的原因使得类不兼容：
Caused by: java.lang.RuntimeException: java.io.InvalidClassException: org.apache.spark.rpc.netty.RequestMessage; local class incompatible: stream classdesc serialVersionUID = -5447855329526097695, local class serialVersionUID = -2221986757032131007

但我在2.230本地尝试：./spark-shell --master spark://192.168.2.230:7077它成功了......

为什么我不能使用远程spark-shell（2.5）来连接master（2.230）？

2 个答案:

答案 0 :(得分：2)

对不起，这是我的错 我在192.168.2.230上运行了一个码头火花，其版本为1.6 当192.168.2.5连接192.168.2.230时，docker会将7077端口转发到1.6版本的spark，这样就会出现不兼容的错误。

现在我更改了版本2.1 spark的端口7777，./spark-shell --master spark://192.168.2.230:7777它可以工作。

答案 1 :(得分：0)

谢谢，兹尔。

因为我是从另一个容器访问它，所以通过找到合适的容器的IP地址（172.18.0.1而不是127.0.0.1）解决了同样的问题。

可以使用ifconfig命令找到该IP地址

仅补充说，在某些情况下，导致此问题的原因可能是IP甚至根本没有服务或无法访问。很奇怪。

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