org.apache.spark.SparkException: Job aborted due to stage failure: Task 1.0:8 failed 1 times, most recent failure: Exception failure in TID 8 on host localhost: java.lang.ArrayIndexOutOfBoundsException: 1 $iwC$$iwC$$iwC$$iwC$$anonfun$2.apply(<console>:21) $iwC$$iwC$$iwC$$iwC$$anonfun$2.apply(<console>:21) scala.collection.Iterator$$anon$11.next(Iterator.scala:328) scala.collection.Iterator$$anon$1.next(Iterator.scala:853) scala.collection.Iterator$$anon$11.next(Iterator.scala:328) scala.collection.Iterator$$anon$11.next(Iterator.scala:328) scala.collection.Iterator$$anon$11.next(Iterator.scala:328) scala.collection.Iterator$class.foreach(Iterator.scala:727) scala.collection.AbstractIterator.foreach(Iterator.scala:1157) org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:158) org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) 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:745) Driver stacktrace:

nabble.com | 4 months ago
  1. 0

    Apache Spark User List - spark-shell -- running into ArrayIndexOutOfBoundsException

    nabble.com | 4 months ago
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 1.0:8 failed 1 times, most recent failure: Exception failure in TID 8 on host localhost: java.lang.ArrayIndexOutOfBoundsException: 1 $iwC$$iwC$$iwC$$iwC$$anonfun$2.apply(<console>:21) $iwC$$iwC$$iwC$$iwC$$anonfun$2.apply(<console>:21) scala.collection.Iterator$$anon$11.next(Iterator.scala:328) scala.collection.Iterator$$anon$1.next(Iterator.scala:853) scala.collection.Iterator$$anon$11.next(Iterator.scala:328) scala.collection.Iterator$$anon$11.next(Iterator.scala:328) scala.collection.Iterator$$anon$11.next(Iterator.scala:328) scala.collection.Iterator$class.foreach(Iterator.scala:727) scala.collection.AbstractIterator.foreach(Iterator.scala:1157) org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:158) org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) 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:745) Driver stacktrace:
  2. 0

    How to use foreach (each record add to solr) in foreachRDD to spark streaming?

    Stack Overflow | 2 years ago | user1976546
    org.apache.spark.SparkException: Job aborted due to stage failure: All masters are unresponsive! Giving up.
  3. 0

    Apache Spark: A Task failed with java.lang.ArrayIndexOutOfBoundsException at com.ning.compress.lzf.impl.UnsafeChunkDecoder.copyOverlappingLong

    Stack Overflow | 2 years ago | zeodtr
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0.0:359 failed 4 times, most recent failure: Exception failure in TID 1622 on host cluster02: java.lang.ArrayIndexOutOfBoundsException: 65535 com.ning.compress.lzf.impl.UnsafeChunkDecoder.copyOverlappingLong(UnsafeChunkDecoder.java:221) com.ning.compress.lzf.impl.UnsafeChunkDecoder.decodeChunk(UnsafeChunkDecoder.java:117) com.ning.compress.lzf.impl.UnsafeChunkDecoder.decodeChunk(UnsafeChunkDecoder.java:66) com.ning.compress.lzf.LZFInputStream.readyBuffer(LZFInputStream.java:339) com.ning.compress.lzf.LZFInputStream.read(LZFInputStream.java:169) java.io.ObjectInputStream$PeekInputStream.read(ObjectInputStream.java:2310) java.io.ObjectInputStream$PeekInputStream.readFully(ObjectInputStream.java:2323) java.io.ObjectInputStream$BlockDataInputStream.readUTFBody(ObjectInputStream.java:3063) java.io.ObjectInputStream$BlockDataInputStream.readUTF(ObjectInputStream.java:2864) java.io.ObjectInputStream.readString(ObjectInputStream.java:1638) java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1341) java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1990) java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1915) java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798) java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) java.io.ObjectInputStream.readObject(ObjectInputStream.java:370) org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:63) org.apache.spark.serializer.DeserializationStream$$anon$1.getNext(Serializer.scala:125) org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71) scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:30) org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39) org.apache.spark.Aggregator.combineValuesByKey(Aggregator.scala:58) org.apache.spark.rdd.PairRDDFunctions$$anonfun$combineByKey$4.apply(PairRDDFunctions.scala:107) org.apache.spark.rdd.PairRDDFunctions$$anonfun$combineByKey$4.apply(PairRDDFunctions.scala:106) org.apache.spark.rdd.RDD$$anonfun$14.apply(RDD.scala:582) org.apache.spark.rdd.RDD$$anonfun$14.apply(RDD.scala:582) org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35) org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) org.apache.spark.rdd.RDD.iterator(RDD.scala:229) org.apache.spark.rdd.MappedValuesRDD.compute(MappedValuesRDD.scala:31) org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) org.apache.spark.rdd.RDD.iterator(RDD.scala:229) org.apache.spark.rdd.MappedValuesRDD.compute(MappedValuesRDD.scala:31) org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) org.apache.spark.rdd.RDD.iterator(RDD.scala:229) org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111) org.apache.spark.scheduler.Task.run(Task.scala:51) org.apache.spark.executor.Executor$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:
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  5. 0

    SparkException: Job aborted due to stage failure

    Stack Overflow | 2 years ago | manjunath k
    org.apache.spark.SparkException: Job aborted due to stage failure: Master removed our application: FAILED
  6. 0

    simple mapping partitions job in (py)spark

    Stack Overflow | 2 years ago | lollercoaster
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 2.0:0 failed 1 times, most recent failure: Exception failure in TID 0 on host localhost: org.apache.spark.api.python.PythonException: Traceback (most recent call last): File "/usr/bin/spark-1.0.0-bin-hadoop2/python/pyspark/worker.py", line 77, in main serializer.dump_stream(func(split_index, iterator), outfile) File "/usr/bin/spark-1.0.0-bin-hadoop2/python/pyspark/serializers.py", line 191, in dump_stream self.serializer.dump_stream(self._batched(iterator), stream) File "/usr/bin/spark-1.0.0-bin-hadoop2/python/pyspark/serializers.py", line 123, in dump_stream for obj in iterator: File "/usr/bin/spark-1.0.0-bin-hadoop2/python/pyspark/serializers.py", line 180, in _batched for item in iterator: TypeError: 'NoneType' object is not iterable org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:115) org.apache.spark.api.python.PythonRDD$$anon$1.&lt;init&gt;(PythonRDD.scala:145) org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:78) org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) org.apache.spark.rdd.RDD.iterator(RDD.scala:229) org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111) org.apache.spark.scheduler.Task.run(Task.scala:51) org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187) java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) java.lang.Thread.run(Thread.java:745) Driver stacktrace:

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Root Cause Analysis

  1. org.apache.spark.SparkException

    Job aborted due to stage failure: Task 1.0:8 failed 1 times, most recent failure: Exception failure in TID 8 on host localhost: java.lang.ArrayIndexOutOfBoundsException: 1 $iwC$$iwC$$iwC$$iwC$$anonfun$2.apply(<console>:21) $iwC$$iwC$$iwC$$iwC$$anonfun$2.apply(<console>:21) scala.collection.Iterator$$anon$11.next(Iterator.scala:328) scala.collection.Iterator$$anon$1.next(Iterator.scala:853) scala.collection.Iterator$$anon$11.next(Iterator.scala:328) scala.collection.Iterator$$anon$11.next(Iterator.scala:328) scala.collection.Iterator$$anon$11.next(Iterator.scala:328) scala.collection.Iterator$class.foreach(Iterator.scala:727) scala.collection.AbstractIterator.foreach(Iterator.scala:1157) org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:158) org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) 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:745) Driver stacktrace:

    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages()
  2. Spark
    DAGScheduler$$anonfun$abortStage$1.apply
    1. org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1033)
    2. org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1017)
    3. org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1015)
    3 frames
  3. Scala
    ArrayBuffer.foreach
    1. scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    2. scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
    2 frames
  4. Spark
    DAGScheduler$$anonfun$handleTaskSetFailed$1.apply
    1. org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1015)
    2. org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:633)
    3. org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:633)
    3 frames
  5. Scala
    Option.foreach
    1. scala.Option.foreach(Option.scala:236)
    1 frame
  6. Spark
    DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse
    1. org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:633)
    2. org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1207)
    2 frames
  7. Akka Actor
    ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec
    1. akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
    2. akka.actor.ActorCell.invoke(ActorCell.scala:456)
    3. akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
    4. akka.dispatch.Mailbox.run(Mailbox.scala:219)
    5. akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
    5 frames
  8. Scala
    ForkJoinWorkerThread.run
    1. scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
    2. scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
    3. scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
    4. scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
    4 frames