Github user mridulm commented on the pull request:
https://github.com/apache/spark/pull/1499#issuecomment-50115353
Running tests with
export
SPARK_JAVA_OPTS="-Dspark.shuffle.manager=org.apache.spark.shuffle.sort.SortShuffleManager"
causes :
'''
- sorting using mutable pairs *** FAILED ***
org.apache.spark.SparkException: Job aborted due to stage failure: Task
3.0:1 failed 4 times, most recent failure: Exception failure in TID 14 on host
localhost: java.lang.ArrayStoreException: scala.Tuple2
scala.runtime.ScalaRunTime$.array_update(ScalaRunTime.scala:88)
scala.Array$.slowcopy(Array.scala:81)
scala.Array$.copy(Array.scala:107)
scala.collection.mutable.ResizableArray$class.copyToArray(ResizableArray.scala:77)
scala.collection.mutable.ArrayBuffer.copyToArray(ArrayBuffer.scala:47)
scala.collection.TraversableOnce$class.copyToArray(TraversableOnce.scala:241)
scala.collection.AbstractTraversable.copyToArray(Traversable.scala:105)
scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:249)
scala.collection.AbstractTraversable.toArray(Traversable.scala:105)
scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28)
org.apache.spark.rdd.OrderedRDDFunctions$$anonfun$sortByKey$1.apply(OrderedRDDFunctions.scala:62)
org.apache.spark.rdd.OrderedRDDFunctions$$anonfun$sortByKey$1.apply(OrderedRDDFunctions.scala:61)
org.apache.spark.rdd.RDD$$anonfun$12.apply(RDD.scala:581)
org.apache.spark.rdd.RDD$$anonfun$12.apply(RDD.scala:581)
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:112)
org.apache.spark.scheduler.Task.run(Task.scala:51)
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:199)
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$$failJobAndIndependentStages(DAGScheduler.scala:1055)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1039)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1037)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1037)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:641)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:641)
at scala.Option.foreach(Option.scala:236)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:641)
...
'''
The actual classes are :
'''
classes = <[class scala.Tuple2] ;
[class scala.Tuple2,
class scala.Tuple2,
class scala.Tuple2]>
'''
obtained using :
'''
def collect(): Array[T] = {
println("classes = " + sc.runJob(this, (iter: Iterator[T]) =>
iter.map(v => if (v == null) "null" else v.getClass).mkString("[",
",\n\t\t", "]")).
mkString("<", " ; \n\t", ">"))
System.out.flush()
val results = sc.runJob(this, (iter: Iterator[T]) => iter.toArray)
''' in RDD.collect
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