Question

我的本地群集中的spark安装无法正常工作。我下载了spark-1.4.0-bin-hadoop2.6.tgz并将其解压缩到所有节点都可见的目录中（这些节点都可以通过没有密码的ssh访问）。另外，我编辑了conf / slaves，使其包含节点的名称。然后我发出了sbin / start-all.sh。主服务器中的Web UI变为可用，节点出现在工作人员部分中。但是，如果启动一个pyspark部分（使用Web UI中出现的URL连接到master），并尝试运行这个简单的示例：

a=sc.parallelize([0,1,2,3],2)
a.collect()

我收到此错误：

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？提前谢谢。

Answer 1

它似乎是类型转换异常。你可以尝试输入sc.parallelize（List（1,2,3,4,5,6），2）并重新运行

Answer 2

请检查您是否使用了正确的JAVA_HOME。你应该在lauching Spark工作之前设置它。例如：

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

Spark Standalone Mode无法在群集中运行

2 个答案: