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https://issues.apache.org/jira/browse/SPARK-9089?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14718134#comment-14718134
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Yanbo Liang edited comment on SPARK-9089 at 8/28/15 7:10 AM:
-------------------------------------------------------------
CC [~joshrosen], [~pwendell]
was (Author: yanboliang):
CC [~joshrosen], [~pwendell], [~srowen]
> Failing to run simple job on Spark Standalone Cluster
> -----------------------------------------------------
>
> Key: SPARK-9089
> URL: https://issues.apache.org/jira/browse/SPARK-9089
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.4.0
> Environment: Staging
> Reporter: Amar Goradia
> Priority: Critical
>
> We are trying out Spark and as part of that, we have setup Standalone Spark
> Cluster. As part of testing things out, we simple open PySpark shell and ran
> this simple job: a=sc.parallelize([1,2,3]).count()
> As a result, we are getting errors. We tried googling around this error but
> haven't been able to find exact reasoning behind why we are running into this
> state. Can somebody please help us further look into this issue and advise us
> on what we are missing here?
> Here is full error stack:
> >>> a=sc.parallelize([1,2,3]).count()
> 15/07/16 00:52:15 INFO SparkContext: Starting job: count at <stdin>:1
> 15/07/16 00:52:15 INFO DAGScheduler: Got job 5 (count at <stdin>:1) with 2
> output partitions (allowLocal=false)
> 15/07/16 00:52:15 INFO DAGScheduler: Final stage: ResultStage 5(count at
> <stdin>:1)
> 15/07/16 00:52:15 INFO DAGScheduler: Parents of final stage: List()
> 15/07/16 00:52:15 INFO DAGScheduler: Missing parents: List()
> 15/07/16 00:52:15 INFO DAGScheduler: Submitting ResultStage 5 (PythonRDD[12]
> at count at <stdin>:1), which has no missing parents
> 15/07/16 00:52:15 INFO TaskSchedulerImpl: Cancelling stage 5
> 15/07/16 00:52:15 INFO DAGScheduler: ResultStage 5 (count at <stdin>:1)
> failed in Unknown s
> 15/07/16 00:52:15 INFO DAGScheduler: Job 5 failed: count at <stdin>:1, took
> 0.004963 s
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File "/opt/spark/spark-1.4.0-bin-hadoop2.4/python/pyspark/rdd.py", line
> 972, in count
> return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum()
> File "/opt/spark/spark-1.4.0-bin-hadoop2.4/python/pyspark/rdd.py", line
> 963, in sum
> return self.mapPartitions(lambda x: [sum(x)]).reduce(operator.add)
> File "/opt/spark/spark-1.4.0-bin-hadoop2.4/python/pyspark/rdd.py", line
> 771, in reduce
> vals = self.mapPartitions(func).collect()
> File "/opt/spark/spark-1.4.0-bin-hadoop2.4/python/pyspark/rdd.py", line
> 745, in collect
> port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
> File
> "/opt/spark/spark-1.4.0-bin-hadoop2.4/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py",
> line 538, in __call__
> File
> "/opt/spark/spark-1.4.0-bin-hadoop2.4/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
> serialization failed: java.lang.reflect.InvocationTargetException
> sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
> sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57)
> sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
> java.lang.reflect.Constructor.newInstance(Constructor.java:526)
> org.apache.spark.io.CompressionCodec$.createCodec(CompressionCodec.scala:68)
> org.apache.spark.io.CompressionCodec$.createCodec(CompressionCodec.scala:60)
> org.apache.spark.broadcast.TorrentBroadcast.org$apache$spark$broadcast$TorrentBroadcast$$setConf(TorrentBroadcast.scala:73)
> org.apache.spark.broadcast.TorrentBroadcast.<init>(TorrentBroadcast.scala:80)
> org.apache.spark.broadcast.TorrentBroadcastFactory.newBroadcast(TorrentBroadcastFactory.scala:34)
> org.apache.spark.broadcast.BroadcastManager.newBroadcast(BroadcastManager.scala:62)
> org.apache.spark.SparkContext.broadcast(SparkContext.scala:1289)
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:874)
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:815)
> org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:799)
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1419)
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1411)
> org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> at
> org.apache.spark.scheduler.DAGScheduler.org$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$$anonfun$abortStage$1.apply(DAGScheduler.scala:1256)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1256)
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitMissingTasks(DAGScheduler.scala:884)
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$submitStage(DAGScheduler.scala:815)
> at
> org.apache.spark.scheduler.DAGScheduler.handleJobSubmitted(DAGScheduler.scala:799)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1419)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1411)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
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