org.apache.spark.SparkException: Job aborted due to stage failure: Task 21 in stage 1.0 failed 1 times, most recent failure: Lost task 21.0 in stage 1.0 (TID 245, localhost): java.lang.OutOfMemoryError: GC overhead limit exceeded

GitHub | car2008 | 2 months ago
  1. 0

    GitHub comment 572#249369489

    GitHub | 2 months ago | car2008
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 21 in stage 1.0 failed 1 times, most recent failure: Lost task 21.0 in stage 1.0 (TID 245, localhost): java.lang.OutOfMemoryError: GC overhead limit exceeded
  2. 0

    Running Spark inside Web Application may throw “java.lang.OutOfMemoryError: GC overhead limit exceeded”

    Stack Overflow | 5 months ago | CHellegaard
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 3.0 failed 1 times, most recent failure: Lost task 0.0 in stage 3.0 (TID 18, localhost): java.lang.OutOfMemoryError: GC overhead limit exceeded
  3. 0

    GitHub comment 173#243313005

    GitHub | 3 months ago | car2008
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 9 in stage 2.0 failed 1 times, most recent failure: Lost task 9.0 in stage 2.0 (TID 201, localhost): java.lang.OutOfMemoryError: GC overhead limit exceeded
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  5. 0

    SparkException caused by GC overhead limit exceeded - Hortonworks

    hortonworks.com | 2 months ago
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 4.0 failed 1 times, most recent failure: Lost task 0.0 in stage 4.0 (TID 40, localhost): java.lang.OutOfMemoryError: GC overhead limit exceeded
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    Read, sort and count 20GB CSV file stored in HDFS by using pyspark RDD

    Stack Overflow | 2 months ago | sourabh pandey
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost): java.lang.OutOfMemoryError: GC overhead limit exceeded

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    Root Cause Analysis

    1. org.apache.spark.SparkException

      Job aborted due to stage failure: Task 21 in stage 1.0 failed 1 times, most recent failure: Lost task 21.0 in stage 1.0 (TID 245, localhost): java.lang.OutOfMemoryError: GC overhead limit exceeded

      at org.apache.spark.serializer.DeserializationStream$$anon$2.getNext()
    2. Spark
      NextIterator.hasNext
      1. org.apache.spark.serializer.DeserializationStream$$anon$2.getNext(Serializer.scala:201)
      2. org.apache.spark.serializer.DeserializationStream$$anon$2.getNext(Serializer.scala:198)
      3. org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
      3 frames
    3. Scala
      Iterator$$anon$11.hasNext
      1. scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
      2. scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
      2 frames
    4. Spark
      Executor$TaskRunner.run
      1. org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:32)
      2. org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
      3. org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:152)
      4. org.apache.spark.Aggregator.combineCombinersByKey(Aggregator.scala:58)
      5. org.apache.spark.shuffle.BlockStoreShuffleReader.read(BlockStoreShuffleReader.scala:83)
      6. org.apache.spark.rdd.ShuffledRDD.compute(ShuffledRDD.scala:98)
      7. org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
      8. org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
      9. org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
      10. org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
      11. org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
      12. org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
      13. org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
      14. org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
      15. org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
      16. org.apache.spark.scheduler.Task.run(Task.scala:89)
      17. org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
      17 frames
    5. Java RT
      Thread.run
      1. java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
      2. java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
      3. java.lang.Thread.run(Thread.java:745)
      3 frames