PySpark cannot import mllib modules in YARN-client mode

>>> from pyspark.mllib.regression import LabeledPoint

>>> sc.parallelize([1,2,3]).map(lambda x: LabeledPoint(1, [2])).count()

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)

>>> 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)