Just make sure you are having the same installation of spark-1.4.0-bin-hadoop2.6 everywhere. (including the slaves, master, and from where you start the spark-shell).
Thanks Best Regards On Mon, Jul 13, 2015 at 4:34 AM, Eduardo <erocha....@gmail.com> wrote: > My installation of spark is not working correctly in my local cluster. I > downloaded spark-1.4.0-bin-hadoop2.6.tgz and untar it in a directory > visible to all nodes (these nodes are all accessible by ssh without > password). In addition, I edited conf/slaves so that it contains the names > of the nodes. Then I issued a sbin/start-all.sh . The Web UI in the master > became available and the nodes appeared in the workers sections. However, > if a start a pyspark section (connecting to the master using the URL that > appeared in the Web UI), and try to run this simple example: > > a=sc.parallelize([0,1,2,3],2) > a.collect() > > I get this error: > > 15/07/12 19:52:58 ERROR TaskSetManager: Task 1 in stage 0.0 failed 4 times; > aborting job > Traceback (most recent call last): > File "<stdin>", line 1, in <module> > File "/home/myuser/spark-1.4.0-bin-hadoop2.6/python/pyspark/rdd.py", line > 745, in collect > port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd()) > File > "/home/myuser/spark-1.4.0-bin-hadoop2.6/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py", > line 538, in __call__ > File > "/home/myuser/spark-1.4.0-bin-hadoop2.6/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", > line 300, in get_return_value > py4j.protocol.Py4JJavaError: An error occurred while calling > z:org.apache.spark.api.python.PythonRDD.collectAndServe. > : org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 > in stage 0.0 failed 4 times, most recent failure: Lost task 1.3 in stage 0.0 > (TID 6, 172.16.1.1): java.io.InvalidClassException: > scala.reflect.ClassTag$$anon$1; local class incompatible: stream classdesc > serialVersionUID = -4937928798201944954, local class serialVersionUID = > -8102093212602380348 > at java.io.ObjectStreamClass.initNonProxy(ObjectStreamClass.java:604) > at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1601) > at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1514) > at > java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1750) > at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1347) > at > java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1964) > at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1888) > at > java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1771) > at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1347) > at > java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1964) > at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1888) > at > java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1771) > at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1347) > at java.io.ObjectInputStream.readObject(ObjectInputStream.java:369) > at > org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:69) > at > org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:95) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:194) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603) > at java.lang.Thread.run(Thread.java:722) > > Driver stacktrace: > at > org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1266) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1257) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1256) > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1256) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730) > at scala.Option.foreach(Option.scala:236) > at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:730) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1450) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1411) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > > Has anyone experienced this issue? Thanks in advance. >
