Is this the wrong list to be asking this question? I'm not even sure where to start troubleshooting.
On Tue, Jan 20, 2015 at 9:48 AM, Dave <[email protected]> wrote: > 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 <[email protected]> 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 >> >>
