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我的本地群集中安装的spark没有正常工作。我下载了spark-1.4.0-bin-hadoop2.6.tgz并将其解压到所有节点可见的目录中（这些节点都可以通过ssh无密码访问）。另外，我编辑了conf/slaves，以便它包含节点的名称。然后我发布了一个sbin/start-all.sh。主站中的Web UI变为可用，并且节点出现在工作人员部分中。但是，如果开始pyspark部分（使用出现在Web UI的URL连接到主机），并尝试运行这个简单的例子：Spark独立模式在群集中不起作用
a=sc.parallelize([0,1,2,3],2)
a.collect()
我得到这个错误：
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)
有没有人遇到过这个问题？提前致谢。
这不是一个强制性异常。我的例子并行化的第一个参数已经是一个列表。不管怎么说，还是要谢谢你。 – Eduardo