Not sure if anyone who can help has seen this. Any suggestions would be
appreciated, thanks!
On Mon Jan 19 2015 at 1:50:43 PM Dave <dla...@gmail.com> wrote:
> Hi,
>
> I've setup my first spark cluster (1 master, 2 workers) and an iPython
> notebook server that I'm trying to setup to access the cluster. I'm running
> the workers from Anaconda to make sure the python setup is correct on each
> box. The iPy notebook server appears to have everything setup correctly,
> and I'm able to initialize Spark and push a job out. However, the job is
> failing, and I'm not sure how to troubleshoot. Here's the code:
>
> from pyspark import SparkContext
> CLUSTER_URL = 'spark://192.168.1.20:7077'
> sc = SparkContext( CLUSTER_URL, 'pyspark')
> def sample(p):
> x, y = random(), random()
> return 1 if x*x + y*y < 1 else 0
>
> count = sc.parallelize(xrange(0, 20)).map(sample).reduce(lambda a, b: a +
> b)
> print "Pi is roughly %f" % (4.0 * count / 20)
>
>
> And here's the error:
>
> Py4JJavaError Traceback (most recent call
> last)<ipython-input-4-e8dce94b43bb> in <module>() 3 return 1 if x*x
> + y*y < 1 else 0 4 ----> 5 count = sc.parallelize(xrange(0,
> 20)).map(sample).reduce(lambda a, b: a + b) 6 print "Pi is roughly %f" %
> (4.0 * count / 20)
> /opt/spark-1.2.0/python/pyspark/rdd.pyc in reduce(self, f) 713
> yield reduce(f, iterator, initial) 714 --> 715 vals =
> self.mapPartitions(func).collect() 716 if vals: 717
> return reduce(f, vals)
> /opt/spark-1.2.0/python/pyspark/rdd.pyc in collect(self) 674 """
> 675 with SCCallSiteSync(self.context) as css:--> 676
> bytesInJava = self._jrdd.collect().iterator() 677 return
> list(self._collect_iterator_through_file(bytesInJava)) 678
> /opt/spark-1.2.0/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py in
> __call__(self, *args) 536 answer =
> self.gateway_client.send_command(command) 537 return_value =
> get_return_value(answer, self.gateway_client,--> 538
> self.target_id, self.name) 539 540 for temp_arg in temp_args:
> /opt/spark-1.2.0/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py in
> get_return_value(answer, gateway_client, target_id, name) 298
> raise Py4JJavaError( 299 'An error occurred while
> calling {0}{1}{2}.\n'.--> 300 format(target_id, '.',
> name), value) 301 else: 302 raise Py4JError(
> Py4JJavaError: An error occurred while calling o28.collect.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 31
> in stage 0.0 failed 4 times, most recent failure: Lost task 31.3 in stage 0.0
> (TID 72, 192.168.1.21): org.apache.spark.api.python.PythonException:
> Traceback (most recent call last):
> File "/opt/spark-1.2.0/python/pyspark/worker.py", line 107, in main
> process()
> File "/opt/spark-1.2.0/python/pyspark/worker.py", line 98, in process
> serializer.dump_stream(func(split_index, iterator), outfile)
> File "/opt/spark-1.2.0/python/pyspark/serializers.py", line 227, in
> dump_stream
> vs = list(itertools.islice(iterator, batch))
> File "/opt/spark-1.2.0/python/pyspark/rdd.py", line 710, in func
> initial = next(iterator)
> File "<ipython-input-4-e8dce94b43bb>", line 2, in sample
> TypeError: 'module' object is not callable
>
> at
> org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:137)
> at
> org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:174)
> at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:96)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:745)
>
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1214)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1203)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1202)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1202)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
> at scala.Option.foreach(Option.scala:236)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:696)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1420)
> at akka.actor.Actor$class.aroundReceive(Actor.scala:465)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessActor.aroundReceive(DAGScheduler.scala:1375)
> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
> at akka.actor.ActorCell.invoke(ActorCell.scala:487)
> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
> at akka.dispatch.Mailbox.run(Mailbox.scala:220)
> at
> akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393)
> at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
> at
> scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
> at
> scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
> at
> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
>
>
>
>
> I'm happy to send out more logs if that's helpful.
>
> Thanks for any help!
> Dave
>
>
