org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 15.0 failed 1 times, most recent failure: Lost task 0.0 in stage 15.0 (TID 13, localhost): java.lang.ArrayStoreException: java.lang.Long

Stack Overflow | LearningSlowly | 7 months ago
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  1. 0

    Inspecting GraphX Graph Object

    Stack Overflow | 7 months ago | LearningSlowly
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 15.0 failed 1 times, most recent failure: Lost task 0.0 in stage 15.0 (TID 13, localhost): java.lang.ArrayStoreException: java.lang.Long
  2. 0

    adam bizarre behavior

    Google Groups | 2 years ago | Sungwook Yoon
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 4 times, most recent failure: Lost task 0.3 in stage 1.0 (TID 7, aday3): java.lang.ArrayStoreException: org.apache.avro.generic.GenericData$Record
  3. 0

    GraphX pregel with Java

    Stack Overflow | 1 week ago | DaliMidou
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 28.0 failed 1 times, most recent failure: Lost task 0.0 in stage 28.0 (TID 46, localhost): java.lang.ArrayStoreException: scala.collection.mutable.MutableList
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  5. 0

    RE: Not Serializable exception when integrating SQL and Spark Streaming

    apache.org | 1 year ago
    org.apache.spark.SparkException: Task not serializable at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:166) at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:158) at org.apache.spark.SparkContext.clean(SparkContext.scala:1435) at org.apache.spark.rdd.RDD.map(RDD.scala:271) at org.apache.spark.api.java.JavaRDDLike$class.map(JavaRDDLike.scala:78) at org.apache.spark.sql.api.java.JavaSchemaRDD.map(JavaSchemaRDD.scala:42) at com.basic.spark.NumberCount$2.call(NumberCount.java:79) at com.basic.spark.NumberCount$2.call(NumberCount.java:67) at org.apache.spark.streaming.api.java.JavaDStreamLike$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:274) at org.apache.spark.streaming.api.java.JavaDStreamLike$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:274) at org.apache.spark.streaming.dstream.DStream$anonfun$foreachRDD$1.apply(DStream.scala:529) at org.apache.spark.streaming.dstream.DStream$anonfun$foreachRDD$1.apply(DStream.scala:529) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply$mcV$sp(ForEachDStream.scala:42) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply(ForEachDStream.scala:40) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply(ForEachDStream.scala:40) at scala.util.Try$.apply(Try.scala:161) at org.apache.spark.streaming.scheduler.Job.run(Job.scala:32) at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:171) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
  6. 0

    RE: Not Serializable exception when integrating SQL and Spark Streaming

    apache.org | 1 year ago
    org.apache.spark.SparkException: Task not serializable at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:166) at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:158) at org.apache.spark.SparkContext.clean(SparkContext.scala:1435) at org.apache.spark.rdd.RDD.map(RDD.scala:271) at org.apache.spark.api.java.JavaRDDLike$class.map(JavaRDDLike.scala:78) at org.apache.spark.sql.api.java.JavaSchemaRDD.map(JavaSchemaRDD.scala:42) at com.basic.spark.NumberCount$2.call(NumberCount.java:79) at com.basic.spark.NumberCount$2.call(NumberCount.java:67) at org.apache.spark.streaming.api.java.JavaDStreamLike$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:274) at org.apache.spark.streaming.api.java.JavaDStreamLike$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:274) at org.apache.spark.streaming.dstream.DStream$anonfun$foreachRDD$1.apply(DStream.scala:529) at org.apache.spark.streaming.dstream.DStream$anonfun$foreachRDD$1.apply(DStream.scala:529) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply$mcV$sp(ForEachDStream.scala:42) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply(ForEachDStream.scala:40) at org.apache.spark.streaming.dstream.ForEachDStream$anonfun$1.apply(ForEachDStream.scala:40) at scala.util.Try$.apply(Try.scala:161) at org.apache.spark.streaming.scheduler.Job.run(Job.scala:32) at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:171) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)

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    Root Cause Analysis

    1. org.apache.spark.SparkException

      Job aborted due to stage failure: Task 0 in stage 15.0 failed 1 times, most recent failure: Lost task 0.0 in stage 15.0 (TID 13, localhost): java.lang.ArrayStoreException: java.lang.Long

      at scala.runtime.ScalaRunTime$.array_update()
    2. Scala
      ScalaRunTime$.array_update
      1. scala.runtime.ScalaRunTime$.array_update(ScalaRunTime.scala:88)
      1 frame
    3. Spark Project GraphX
      ShippableVertexPartition$$anonfun$apply$5.apply
      1. org.apache.spark.graphx.util.collection.GraphXPrimitiveKeyOpenHashMap.setMerge(GraphXPrimitiveKeyOpenHashMap.scala:87)
      2. org.apache.spark.graphx.impl.ShippableVertexPartition$$anonfun$apply$5.apply(ShippableVertexPartition.scala:61)
      3. org.apache.spark.graphx.impl.ShippableVertexPartition$$anonfun$apply$5.apply(ShippableVertexPartition.scala:60)
      3 frames
    4. Scala
      Iterator$class.foreach
      1. scala.collection.Iterator$class.foreach(Iterator.scala:727)
      1 frame
    5. Spark
      InterruptibleIterator.foreach
      1. org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
      1 frame
    6. Spark Project GraphX
      VertexRDD$$anonfun$2.apply
      1. org.apache.spark.graphx.impl.ShippableVertexPartition$.apply(ShippableVertexPartition.scala:60)
      2. org.apache.spark.graphx.VertexRDD$$anonfun$2.apply(VertexRDD.scala:328)
      3. org.apache.spark.graphx.VertexRDD$$anonfun$2.apply(VertexRDD.scala:325)
      3 frames
    7. Spark
      RDD.iterator
      1. org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:88)
      2. org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
      3. org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:69)
      4. org.apache.spark.rdd.RDD.iterator(RDD.scala:268)
      4 frames
    8. Spark Project GraphX
      VertexRDD.compute
      1. org.apache.spark.graphx.VertexRDD.compute(VertexRDD.scala:71)
      1 frame
    9. Spark
      Executor$TaskRunner.run
      1. org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
      2. org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
      3. org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
      4. org.apache.spark.scheduler.Task.run(Task.scala:89)
      5. org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
      5 frames
    10. Java RT
      Thread.run
      1. java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
      2. java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
      3. java.lang.Thread.run(Thread.java:745)
      3 frames