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From Liquan Pei <liquan...@gmail.com>
Subject Re: MLUtils.loadLibSVMFile error
Date Wed, 24 Sep 2014 22:47:23 GMT
Hi Sameer,

This seems to be a file format issue. Can you make sure that your data
satisfies the format?


Each line of libsvm format is as follows:

<label> <index1>:<value1> <index2>:<value2> ...

Thanks,

Liquan

On Wed, Sep 24, 2014 at 3:02 PM, Sameer Tilak <sstilak@live.com> wrote:

>  Hi All,
>
>
> When I try to load dataset using MLUtils.loadLibSVMFile, I have the
> following problem. Any help will be greatly appreciated!
>
>
>
> Code snippet:
>
>
> import org.apache.spark.mllib.regression.LabeledPoint
>
> import org.apache.spark.mllib.util.MLUtils
>
> import org.apache.spark.rdd.RDD
>
> import org.apache.spark.mllib.regression.LinearRegressionWithSGD
>
>
> val examples: RDD[LabeledPoint] = MLUtils.loadLibSVMFile(sc
> ,"structured/results/data.txt")
>
>
> stacktrace:
>
>
> 14/09/24 15:00:49 ERROR Executor: Exception in task ID 0
> java.lang.ArrayIndexOutOfBoundsException: 1
> at
> org.apache.spark.mllib.util.MLUtils$$anonfun$4$$anonfun$5.apply(MLUtils.scala:82)
> at
> org.apache.spark.mllib.util.MLUtils$$anonfun$4$$anonfun$5.apply(MLUtils.scala:79)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
> at org.apache.spark.mllib.util.MLUtils$$anonfun$4.apply(MLUtils.scala:79)
> at org.apache.spark.mllib.util.MLUtils$$anonfun$4.apply(MLUtils.scala:76)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:107)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:227)
> at org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
> at org.apache.spark.scheduler.Task.run(Task.scala:51)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:744)
> 14/09/24 15:00:49 ERROR Executor: Exception in task ID 1
> java.lang.ArrayIndexOutOfBoundsException: 1
> at
> org.apache.spark.mllib.util.MLUtils$$anonfun$4$$anonfun$5.apply(MLUtils.scala:82)
> at
> org.apache.spark.mllib.util.MLUtils$$anonfun$4$$anonfun$5.apply(MLUtils.scala:79)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
> at org.apache.spark.mllib.util.MLUtils$$anonfun$4.apply(MLUtils.scala:79)
> at org.apache.spark.mllib.util.MLUtils$$anonfun$4.apply(MLUtils.scala:76)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:107)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:227)
> at org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
> at org.apache.spark.scheduler.Task.run(Task.scala:51)
> at org.apache.spark.executor.Executor$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:744)
> 14/09/24 15:00:49 WARN TaskSetManager: Lost TID 0 (task 0.0:0)
> 14/09/24 15:00:49 WARN TaskSetManager: Loss was due to
> java.lang.ArrayIndexOutOfBoundsException
> java.lang.ArrayIndexOutOfBoundsException: 1
> at
> org.apache.spark.mllib.util.MLUtils$$anonfun$4$$anonfun$5.apply(MLUtils.scala:82)
> at
> org.apache.spark.mllib.util.MLUtils$$anonfun$4$$anonfun$5.apply(MLUtils.scala:79)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
> at org.apache.spark.mllib.util.MLUtils$$anonfun$4.apply(MLUtils.scala:79)
> at org.apache.spark.mllib.util.MLUtils$$anonfun$4.apply(MLUtils.scala:76)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:107)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:227)
> at org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
> at org.apache.spark.scheduler.Task.run(Task.scala:51)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:744)
> 14/09/24 15:00:49 ERROR TaskSetManager: Task 0.0:0 failed 1 times;
> aborting job
> 14/09/24 15:00:49 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks
> have all completed, from pool
> 14/09/24 15:00:49 INFO DAGScheduler: Failed to run reduce at
> MLUtils.scala:95
> 14/09/24 15:00:49 INFO TaskSchedulerImpl: Cancelling stage 0
> 14/09/24 15:00:49 INFO TaskSetManager: Loss was due to
> java.lang.ArrayIndexOutOfBoundsException: 1 [duplicate 1]
> 14/09/24 15:00:49 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks
> have all completed, from pool
> org.apache.spark.SparkException: Job aborted due to stage failure: Task
> 0.0:0 failed 1 times, most recent failure: Exception failure in TID 0 on
> host localhost: java.lang.ArrayIndexOutOfBoundsException: 1
>
> org.apache.spark.mllib.util.MLUtils$$anonfun$4$$anonfun$5.apply(MLUtils.scala:82)
>
> org.apache.spark.mllib.util.MLUtils$$anonfun$4$$anonfun$5.apply(MLUtils.scala:79)
>
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
>
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
>
> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
>         scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
>
> scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
>         scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
>
> org.apache.spark.mllib.util.MLUtils$$anonfun$4.apply(MLUtils.scala:79)
>
> org.apache.spark.mllib.util.MLUtils$$anonfun$4.apply(MLUtils.scala:76)
>         scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
>         scala.collection.Iterator$class.foreach(Iterator.scala:727)
>         scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
>
> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
>
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
>         org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:107)
>         org.apache.spark.rdd.RDD.iterator(RDD.scala:227)
>         org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31)
>         org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
>         org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
>         org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
>         org.apache.spark.scheduler.Task.run(Task.scala:51)
>
> org.apache.spark.executor.Executor$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:744)
> 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)
>



-- 
Liquan Pei
Department of Physics
University of Massachusetts Amherst

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