Jun Xie created SPARK-2251:
------------------------------
Summary: MLLib Naive Bayes Example SparkException: Can only zip
RDDs with same number of elements in each partition
Key: SPARK-2251
URL: https://issues.apache.org/jira/browse/SPARK-2251
Project: Spark
Issue Type: Bug
Components: MLlib
Affects Versions: 1.0.0
Environment: OS: Fedora Linux
Spark Version: 1.0.0. Git clone from the Spark Repository
Reporter: Jun Xie
Priority: Minor
I follow the exact code from Naive Bayes Example
(http://spark.apache.org/docs/latest/mllib-naive-bayes.html) of MLLib.
When I executed the final command:
val accuracy = 1.0 * predictionAndLabel.filter(x => x._1 == x._2).count() /
test.count()
It complains "Can only zip RDDs with same number of elements in each partition".
I got the following exception:
14/06/23 19:39:23 INFO SparkContext: Starting job: count at <console>:31
14/06/23 19:39:23 INFO DAGScheduler: Got job 3 (count at <console>:31) with 2
output partitions (allowLocal=false)
14/06/23 19:39:23 INFO DAGScheduler: Final stage: Stage 4(count at <console>:31)
14/06/23 19:39:23 INFO DAGScheduler: Parents of final stage: List()
14/06/23 19:39:23 INFO DAGScheduler: Missing parents: List()
14/06/23 19:39:23 INFO DAGScheduler: Submitting Stage 4 (FilteredRDD[14] at
filter at <console>:31), which has no missing parents
14/06/23 19:39:23 INFO DAGScheduler: Submitting 2 missing tasks from Stage 4
(FilteredRDD[14] at filter at <console>:31)
14/06/23 19:39:23 INFO TaskSchedulerImpl: Adding task set 4.0 with 2 tasks
14/06/23 19:39:23 INFO TaskSetManager: Starting task 4.0:0 as TID 8 on executor
localhost: localhost (PROCESS_LOCAL)
14/06/23 19:39:23 INFO TaskSetManager: Serialized task 4.0:0 as 3410 bytes in 0
ms
14/06/23 19:39:23 INFO TaskSetManager: Starting task 4.0:1 as TID 9 on executor
localhost: localhost (PROCESS_LOCAL)
14/06/23 19:39:23 INFO TaskSetManager: Serialized task 4.0:1 as 3410 bytes in 1
ms
14/06/23 19:39:23 INFO Executor: Running task ID 8
14/06/23 19:39:23 INFO Executor: Running task ID 9
14/06/23 19:39:23 INFO BlockManager: Found block broadcast_0 locally
14/06/23 19:39:23 INFO BlockManager: Found block broadcast_0 locally
14/06/23 19:39:23 INFO HadoopRDD: Input split:
file:/home/jun/open_source/spark/mllib/data/sample_naive_bayes_data.txt:0+24
14/06/23 19:39:23 INFO HadoopRDD: Input split:
file:/home/jun/open_source/spark/mllib/data/sample_naive_bayes_data.txt:24+24
14/06/23 19:39:23 INFO HadoopRDD: Input split:
file:/home/jun/open_source/spark/mllib/data/sample_naive_bayes_data.txt:0+24
14/06/23 19:39:23 INFO HadoopRDD: Input split:
file:/home/jun/open_source/spark/mllib/data/sample_naive_bayes_data.txt:24+24
14/06/23 19:39:23 ERROR Executor: Exception in task ID 9
org.apache.spark.SparkException: Can only zip RDDs with same number of elements
in each partition
at
org.apache.spark.rdd.RDD$$anonfun$zip$1$$anon$1.hasNext(RDD.scala:663)
at scala.collection.Iterator$$anon$14.hasNext(Iterator.scala:388)
at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1067)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:858)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:858)
at
org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1079)
at
org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1079)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
at org.apache.spark.scheduler.Task.run(Task.scala:51)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:724)
14/06/23 19:39:23 ERROR Executor: Exception in task ID 8
org.apache.spark.SparkException: Can only zip RDDs with same number of elements
in each partition
at
org.apache.spark.rdd.RDD$$anonfun$zip$1$$anon$1.hasNext(RDD.scala:663)
at scala.collection.Iterator$$anon$14.hasNext(Iterator.scala:388)
at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1067)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:858)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:858)
at
org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1079)
at
org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1079)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
at org.apache.spark.scheduler.Task.run(Task.scala:51)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
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:724)
14/06/23 19:39:23 WARN TaskSetManager: Lost TID 8 (task 4.0:0)
14/06/23 19:39:23 WARN TaskSetManager: Loss was due to
org.apache.spark.SparkException
org.apache.spark.SparkException: Can only zip RDDs with same number of elements
in each partition
at
org.apache.spark.rdd.RDD$$anonfun$zip$1$$anon$1.hasNext(RDD.scala:663)
at scala.collection.Iterator$$anon$14.hasNext(Iterator.scala:388)
at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1067)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:858)
at org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:858)
at
org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1079)
at
org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1079)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
at org.apache.spark.scheduler.Task.run(Task.scala:51)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:724)
14/06/23 19:39:23 ERROR TaskSetManager: Task 4.0:0 failed 1 times; aborting job
14/06/23 19:39:23 INFO TaskSchedulerImpl: Removed TaskSet 4.0, whose tasks have
all completed, from pool
14/06/23 19:39:23 INFO DAGScheduler: Failed to run count at <console>:31
14/06/23 19:39:23 INFO TaskSetManager: Loss was due to
org.apache.spark.SparkException: Can only zip RDDs with same number of elements
in each partition [duplicate 1]
14/06/23 19:39:23 INFO TaskSchedulerImpl: Removed TaskSet 4.0, whose tasks have
all completed, from pool
14/06/23 19:39:23 INFO TaskSchedulerImpl: Cancelling stage 4
org.apache.spark.SparkException: Job aborted due to stage failure: Task 4.0:0
failed 1 times, most recent failure: Exception failure in TID 8 on host
localhost: org.apache.spark.SparkException: Can only zip RDDs with same number
of elements in each partition
org.apache.spark.rdd.RDD$$anonfun$zip$1$$anon$1.hasNext(RDD.scala:663)
scala.collection.Iterator$$anon$14.hasNext(Iterator.scala:388)
org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1067)
org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:858)
org.apache.spark.rdd.RDD$$anonfun$count$1.apply(RDD.scala:858)
org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1079)
org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1079)
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
org.apache.spark.scheduler.Task.run(Task.scala:51)
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
java.lang.Thread.run(Thread.java:724)
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1038)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1022)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1020)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1020)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:638)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:638)
at scala.Option.foreach(Option.scala:236)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:638)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1212)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at
akka.dispatch.ForkJoinExecutorConfigurator$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)
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