[
https://issues.apache.org/jira/browse/SPARK-2172?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Xiangrui Meng resolved SPARK-2172.
----------------------------------
Resolution: Fixed
Fixed in https://github.com/apache/spark/pull/1223 by [~piotrszul] .
> PySpark cannot import mllib modules in YARN-client mode
> -------------------------------------------------------
>
> Key: SPARK-2172
> URL: https://issues.apache.org/jira/browse/SPARK-2172
> Project: Spark
> Issue Type: Bug
> Components: MLlib, PySpark, Spark Core, YARN
> Affects Versions: 1.0.0, 1.1.0
> Environment: Ubuntu 14.04
> Java 7
> Python 2.7
> CDH 5.0.2 (Hadoop 2.3.0): HDFS, YARN
> Spark 1.0.0 and git master
> Reporter: Vlad Frolov
> Labels: mllib, python
> Fix For: 1.0.1, 1.1.0
>
>
> Here is the simple reproduce code:
> {noformat}
> $ HADOOP_CONF_DIR=/etc/hadoop/conf MASTER=yarn-client ./bin/pyspark
> {noformat}
> {code:title=issue.py|borderStyle=solid}
> >>> from pyspark.mllib.regression import LabeledPoint
> >>> sc.parallelize([1,2,3]).map(lambda x: LabeledPoint(1, [2])).count()
> {code}
> Note: The same issue occurs with .collect() instead of .count()
> {code:title=TraceBack|borderStyle=solid}
> Py4JJavaError: An error occurred while calling o110.collect.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task
> 8.0:0 failed 4 times, most recent failure: Exception failure in TID 52 on
> host ares: org.apache.spark.api.python.PythonException: Traceback (most
> recent call last):
> File
> "/mnt/storage/bigisle/yarn/1/yarn/local/usercache/blb/filecache/18/spark-assembly-1.0.0-hadoop2.2.0.jar/pyspark/worker.py",
> line 73, in main
> command = pickleSer._read_with_length(infile)
> File
> "/mnt/storage/bigisle/yarn/1/yarn/local/usercache/blb/filecache/18/spark-assembly-1.0.0-hadoop2.2.0.jar/pyspark/serializers.py",
> line 146, in _read_with_length
> return self.loads(obj)
> ImportError: No module named mllib.regression
>
> org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:115)
>
> org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:145)
> org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:78)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
> org.apache.spark.scheduler.Task.run(Task.scala:51)
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
>
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1033)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1017)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1015)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1015)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:633)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:633)
> at scala.Option.foreach(Option.scala:236)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:633)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1207)
> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
> at akka.actor.ActorCell.invoke(ActorCell.scala:456)
> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
> at akka.dispatch.Mailbox.run(Mailbox.scala:219)
> at
> akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
> 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)
> {code}
> However, this code works as expected:
> {code:title=noissue.py|borderStyle=solid}
> >>> from pyspark.mllib.regression import LabeledPoint
> >>> sc.parallelize([1,2,3]).map(lambda x: LabeledPoint(1, [2])).first()
> >>> sc.parallelize([1,2,3]).map(lambda x: LabeledPoint(1, [2])).take(3)
> {code}
--
This message was sent by Atlassian JIRA
(v6.2#6252)
