Spark Standalone Mode not working in a cluster

Question

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.

Answer 1

It's seems like it type cast exception. Can you try input as sc.parallelize(List(1,2,3,4,5,6), 2) and re-run

Answer 2

Please, check that you use the proper JAVA_HOME. you should set it before lauching the Spark job. For example:

export JAVA_HOME=/usr/java/jdk1.7.0_67-cloudera
export PATH=$JAVA_HOME/bin:$JAVA_HOME/jre/bin:$PATH