独立火花集群。不能以编程方式提交的工作 - ＆GT; java.io.InvalidClassException [英] Standalone spark cluster. Can't submit job programmatically -> java.io.InvalidClassException
问题描述
星火的家伙，我是很新的火花，这就是为什么我希望你的帮助确实如此。
Spark fellows, I’m quite new to Spark, that’s why I hope for your help indeed.
我想从我的笔记本电脑计划的火花群集上的相当简单的工作。尽管它的工作原理，当我与提交./火花提交，它抛出一个异常，当我尝试以编程方式做到这一点。
I’m trying to schedule the quite simple job on spark cluster from my laptop. Despite it works, when I submit it with ./spark-submit, it throws an exception, when I try to do it programmatically.
环境：
- 星火 - 1主节点和2个工作节点（独立运行模式）。星火未编译，但二进制文件下载。星火版本 - 1.0.2
- Java版本1.7.0_45
- 应用程序JAR位于无处不在（在客户端和在同一个地方工作节点）;
- README.md文件被复制到每个节点，以及;
Environment: - Spark - 1 master node and 2 worker nodes (standalone mode). Spark was not compiled, but the binaries were downloaded. Spark version - 1.0.2 - java version "1.7.0_45" - Application jar is located everywhere (on client and on worker nodes in the same place); - README.md file is copied to every node as well;
我想要的应用程序来运行：
The application I'm trying to run:
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，这个应用程序上运行的集群成功，当我这样做：
So the problem is, that this application runs on cluster successfully, when I do:
./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
但它不工作，当我试图通过调用编程方式做同样的 SBT运行
下面是堆栈跟踪，我得到主节点上：
Here is the stacktrace, that I get on master node:
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)
有什么能解决这个？
谢谢你在前进。
What could be the solution to this? Thank you in advance.
推荐答案
浪费了大量的时间后，我发现这个问题。
尽管我没有在我的应用程序，Hadoop的客户事务而使用的Hadoop / HDFS。问题是在Hadoop的客户端版本，它比的Hadoop版本不同，火花是专为。
星火公司的Hadoop版本1.2.1，但在我的应用程序，为2.4。
After wasting a lot of time, I've found the problem. Despite I haven't used hadoop/hdfs in my application, hadoop client matters. The problem was in hadoop-client version, it was different than the version of hadoop, spark was built for. Spark's hadoop version 1.2.1, but in my application that was 2.4.
当我在我的应用程序改变的Hadoop客户端的版本1.2.1，我能够在集群执行火花code。
When I changed the version of hadoop client to 1.2.1 in my app, I'm able to execute spark code on cluster.
这篇关于独立火花集群。不能以编程方式提交的工作 - ＆GT; java.io.InvalidClassException的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
