Details
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Bug
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Status: Resolved
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Minor
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Resolution: Fixed
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1.0.0
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OS: Fedora Linux
Spark Version: 1.0.0. Git clone from the Spark Repository
Description
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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