独立火花星团.无法以编程方式提交作业 - > java.io.InvalidClassException

Question

Spark家伙,我对Spark很新,这就是为什么我希望你的帮助确实如此.

我正试图从我的笔记本电脑上安排火花集群上相当简单的工作.尽管它有效,但当我提交它时./spark-submit,它会抛出异常,当我尝试以编程方式进行时.

环境: - Spark - 1个主节点和2个工作节点(独立模式).Spark没有编译,但下载了二进制文件.Spark版本 - 1.0.2 - java版本"1.7.0_45" - 应用程序jar位于任何地方(在客户端和工作节点上的同一位置); - README.md文件也被复制到每个节点;

我正在尝试运行的应用程序:

val logFile = "/user/vagrant/README.md"

val conf = new SparkConf()
conf.setMaster("spark://192.168.33.50:7077")
conf.setAppName("Simple App")
conf.setJars(List("file:///user/vagrant/spark-1.0.2-bin-hadoop1/bin/hello-apache-spark_2.10-1.0.0-SNAPSHOT.jar"))
conf.setSparkHome("/user/vagrant/spark-1.0.2-bin-hadoop1")

val sc = new SparkContext(conf)

val logData = sc.textFile(logFile, 2).cache()

...

所以问题是,当我这样做时,这个应用程序在集群上成功运行:

./spark-submit --class com.paycasso.SimpleApp --master spark://192.168.33.50:7077 --deploy-mode client file:///home/vagrant/spark-1.0.2-bin-hadoop1/bin/hello-apache-spark_2.10-1.0.0-SNAPSHOT.jar

但是当我尝试通过调用以编程方式执行相同操作时,它不起作用 sbt run

这是堆栈跟踪,我在主节点上得到:

14/09/04 15:09:44 ERROR Remoting: org.apache.spark.deploy.ApplicationDescription; local class incompatible: stream classdesc serialVersionUID = -6451051318873184044, local class serialVersionUID = 583745679236071411
java.io.InvalidClassException: org.apache.spark.deploy.ApplicationDescription; local class incompatible: stream classdesc serialVersionUID = -6451051318873184044, local class serialVersionUID = 583745679236071411
    at java.io.ObjectStreamClass.initNonProxy(ObjectStreamClass.java:617)
    at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1622)
    at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1517)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1771)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
    at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1990)
    at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1915)
    at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)
    at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
    at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
    at akka.serialization.JavaSerializer$$anonfun$1.apply(Serializer.scala:136)
    at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
    at akka.serialization.JavaSerializer.fromBinary(Serializer.scala:136)
    at akka.serialization.Serialization$$anonfun$deserialize$1.apply(Serialization.scala:104)
    at scala.util.Try$.apply(Try.scala:161)
    at akka.serialization.Serialization.deserialize(Serialization.scala:98)
    at akka.remote.serialization.MessageContainerSerializer.fromBinary(MessageContainerSerializer.scala:58)
    at akka.serialization.Serialization$$anonfun$deserialize$1.apply(Serialization.scala:104)
    at scala.util.Try$.apply(Try.scala:161)
    at akka.serialization.Serialization.deserialize(Serialization.scala:98)
    at akka.remote.MessageSerializer$.deserialize(MessageSerializer.scala:23)
    at akka.remote.DefaultMessageDispatcher.payload$lzycompute$1(Endpoint.scala:55)
    at akka.remote.DefaultMessageDispatcher.payload$1(Endpoint.scala:55)
    at akka.remote.DefaultMessageDispatcher.dispatch(Endpoint.scala:73)
    at akka.remote.EndpointReader$$anonfun$receive$2.applyOrElse(Endpoint.scala:764)
    at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
    at akka.actor.ActorCell.invoke(ActorCell.scala:456)
    at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
    at akka.dispatch.Mailbox.run(Mailbox.scala:219)
    at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
    at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
    at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
    at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
    at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)

有什么可以解决这个问题？先感谢您.

Answer 1

浪费了很多时间后,我发现了问题.尽管我没有在我的应用程序中使用hadoop/hdfs,但hadoop客户端很重要.问题出在hadoop-client版本,它与hadoop的版本不同,spark是为其构建的.Spark的hadoop版本为1.2.1,但在我的应用程序中为2.4.

当我在我的应用程序中将hadoop客户端的版本更改为1.2.1时,我能够在群集上执行spark代码.