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Shuo Xiang commented on SPARK-1977: ----------------------------------- Hi [~neville], I just run the MovieLens example on my YARN cluster (hadoop-2.0.5-alpha) with kryo enabled and it works. I use the following command: bin/spark-submit --master yarn-cluster --class org.apache.spark.examples.mllib.MovieLensALS --num-executors ** --driver-memory ** --executor-memory ** --executor-cores 1 spark-examples-1.0.0-hadoop2.0.5-alpha.jar --rank 5 --numIterations 20 --lambda 1.0 --kryo /path/to/sample_movielens_data.txt > mutable.BitSet in ALS not serializable with KryoSerializer > ---------------------------------------------------------- > > Key: SPARK-1977 > URL: https://issues.apache.org/jira/browse/SPARK-1977 > Project: Spark > Issue Type: Bug > Components: MLlib > Affects Versions: 1.0.0 > Reporter: Neville Li > Priority: Minor > > OutLinkBlock in ALS.scala has an Array[mutable.BitSet] member. > KryoSerializer uses AllScalaRegistrar from Twitter chill but it doesn't > register mutable.BitSet. > Right now we have to register mutable.BitSet manually. A proper fix would be > using immutable.BitSet in ALS or register mutable.BitSet in upstream chill. > {code} > Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: > Task 1724.0:9 failed 4 times, most recent failure: Exception failure in TID > 68548 on host lon4-hadoopslave-b232.lon4.spotify.net: > com.esotericsoftware.kryo.KryoException: java.lang.ArrayStoreException: > scala.collection.mutable.HashSet > Serialization trace: > shouldSend (org.apache.spark.mllib.recommendation.OutLinkBlock) > > com.esotericsoftware.kryo.serializers.FieldSerializer$ObjectField.read(FieldSerializer.java:626) > > com.esotericsoftware.kryo.serializers.FieldSerializer.read(FieldSerializer.java:221) > com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:732) > com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:43) > com.twitter.chill.Tuple2Serializer.read(TupleSerializers.scala:34) > com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:732) > > org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:115) > > org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:125) > org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71) > > org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39) > > org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$4.apply(CoGroupedRDD.scala:155) > > org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$4.apply(CoGroupedRDD.scala:154) > > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) > org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:154) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.rdd.RDD.iterator(RDD.scala:229) > org.apache.spark.rdd.MappedValuesRDD.compute(MappedValuesRDD.scala:31) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.rdd.RDD.iterator(RDD.scala:229) > > org.apache.spark.rdd.FlatMappedValuesRDD.compute(FlatMappedValuesRDD.scala:31) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.rdd.RDD.iterator(RDD.scala:229) > org.apache.spark.rdd.FlatMappedRDD.compute(FlatMappedRDD.scala:33) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:77) > org.apache.spark.rdd.RDD.iterator(RDD.scala:227) > org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111) > org.apache.spark.scheduler.Task.run(Task.scala:51) > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187) > > java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886) > > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908) > java.lang.Thread.run(Thread.java:662) > Driver stacktrace: > at > org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$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) > {code} -- This message was sent by Atlassian JIRA (v6.2#6252)