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From "Xiangrui Meng (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (SPARK-4023) PySpark's stat.Statistics is broken
Date Tue, 21 Oct 2014 16:30:33 GMT

     [ https://issues.apache.org/jira/browse/SPARK-4023?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Xiangrui Meng resolved SPARK-4023.
----------------------------------
       Resolution: Fixed
    Fix Version/s: 1.2.0

Issue resolved by pull request 2870
[https://github.com/apache/spark/pull/2870]

> PySpark's stat.Statistics is broken
> -----------------------------------
>
>                 Key: SPARK-4023
>                 URL: https://issues.apache.org/jira/browse/SPARK-4023
>             Project: Spark
>          Issue Type: Bug
>          Components: MLlib, PySpark
>    Affects Versions: 1.2.0
>            Reporter: Xiangrui Meng
>            Assignee: Davies Liu
>            Priority: Critical
>             Fix For: 1.2.0
>
>
> {code}
> from pyspark.mllib.stat import Statistics
> from pyspark.mllib.random import RandomRDDs
> data = RandomRDDs.uniformVectorRDD(sc, 100000, 10, 10)
> Statistics.colStats(data)
> {code}
> throws 
> {code}
> Py4JJavaError: An error occurred while calling o37.colStats.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage
0.0 failed 1 times, most recent failure: Lost task 2.0 in stage 0.0 (TID 2, localhost): net.razorvine.pickle.PickleException:
expected zero arguments for construction of ClassDict (for numpy.core.multiarray._reconstruct)
>         net.razorvine.pickle.objects.ClassDictConstructor.construct(ClassDictConstructor.java:23)
>         net.razorvine.pickle.Unpickler.load_reduce(Unpickler.java:617)
>         net.razorvine.pickle.Unpickler.dispatch(Unpickler.java:170)
>         net.razorvine.pickle.Unpickler.load(Unpickler.java:84)
>         net.razorvine.pickle.Unpickler.loads(Unpickler.java:97)
>         org.apache.spark.mllib.api.python.SerDe$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(PythonMLLibAPI.scala:695)
>         org.apache.spark.mllib.api.python.SerDe$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(PythonMLLibAPI.scala:694)
>         scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
>         scala.collection.Iterator$class.foreach(Iterator.scala:727)
>         scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
>         scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:144)
>         scala.collection.AbstractIterator.foldLeft(Iterator.scala:1157)
>         scala.collection.TraversableOnce$class.aggregate(TraversableOnce.scala:201)
>         scala.collection.AbstractIterator.aggregate(Iterator.scala:1157)
>         org.apache.spark.mllib.rdd.RDDFunctions$$anonfun$4.apply(RDDFunctions.scala:99)
>         org.apache.spark.mllib.rdd.RDDFunctions$$anonfun$4.apply(RDDFunctions.scala:99)
>         org.apache.spark.mllib.rdd.RDDFunctions$$anonfun$5.apply(RDDFunctions.scala:100)
>         org.apache.spark.mllib.rdd.RDDFunctions$$anonfun$5.apply(RDDFunctions.scala:100)
>         org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:599)
>         org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:599)
>         org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
>         org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
>         org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
>         org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
>         org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
>         org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
>         org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
>         org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
>         org.apache.spark.scheduler.Task.run(Task.scala:56)
>         org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:181)
>         java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>         java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>         java.lang.Thread.run(Thread.java:744)
> {code}



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