org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.5 in stage 0.0 (TID 5, ip-172-31-3-140.eu-west-1.compute.internal, executor 13): ExecutorLostFailure (executor 13 exited caused by one of the running tasks) Reason: Executor heartbeat timed out after 164253 ms Driver stacktrace:

Stack Overflow | lelabo_m | 1 month ago
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  1. 0

    Spark unit test fails due to stage failure

    Stack Overflow | 5 months ago | Ian
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 87 in stage 206.0 failed 1 times, most recent failure: Lost task 87.0 in stage 206.0 (TID 4228, localhost): ExecutorLostFailure (executor driver exited caused by one of the running tasks) Reason: Executor heartbeat timed out after 148400 ms Driver stacktrace:
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    Stack Overflow | 5 months ago | sarthak
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 9.0 failed 1 times, most recent failure: Lost task 0.0 in stage 9.0 (TID 98, localhost): ExecutorLostFailure (executor driver exited caused by one of the running tasks) Reason: Executor heartbeat timed out after 247686 ms Driver stacktrace:
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    Stack Overflow | 2 years ago
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 0.0 failed 4 times, most recent failure: Lost task 1.3 in stage 0.0 (TID 6, ip-172-31-36-43.us-west-2.compute.internal): ExecutorLostFailure (executor 6 lost) Driver stacktrace:
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  5. 0

    GitHub comment 287#257026952

    GitHub | 5 months ago | mkaja
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 27.0 failed 4 times, most recent failure: Lost task 0.3 in stage 27.0 (TID 1941, ip- .ec2.internal): ExecutorLostFailure (executor 6 exited caused by one of the running tasks) Reason: Container killed by YARN for exceeding memory limits. 1.4 GB of 1.4 GB physical memory used. Consider boosting spark.yarn.executor.memoryOverhead. Driver stacktrace:

  1. johnxfly 1 times, last 3 days ago
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Root Cause Analysis

  1. org.apache.spark.SparkException

    Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.5 in stage 0.0 (TID 5, ip-172-31-3-140.eu-west-1.compute.internal, executor 13): ExecutorLostFailure (executor 13 exited caused by one of the running tasks) Reason: Executor heartbeat timed out after 164253 ms 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$$failJobAndIndependentStages(DAGScheduler.scala:1435)
    2. org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
    3. org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
    3 frames
  3. Scala
    ArrayBuffer.foreach
    1. scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    2. scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    2 frames
  4. Spark
    DAGScheduler$$anonfun$handleTaskSetFailed$1.apply
    1. org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
    2. org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
    3. org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
    3 frames
  5. Scala
    Option.foreach
    1. scala.Option.foreach(Option.scala:257)
    1 frame
  6. Spark
    PythonRDD.collectAndServe
    1. org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
    2. org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
    3. org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
    4. org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
    5. org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
    6. org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
    7. org.apache.spark.SparkContext.runJob(SparkContext.scala:1918)
    8. org.apache.spark.SparkContext.runJob(SparkContext.scala:1931)
    9. org.apache.spark.SparkContext.runJob(SparkContext.scala:1944)
    10. org.apache.spark.SparkContext.runJob(SparkContext.scala:1958)
    11. org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:935)
    12. org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    13. org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    14. org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
    15. org.apache.spark.rdd.RDD.collect(RDD.scala:934)
    16. org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:453)
    17. org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
    17 frames
  7. Java RT
    Method.invoke
    1. sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    2. sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    3. sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    4. java.lang.reflect.Method.invoke(Method.java:498)
    4 frames
  8. Py4J
    GatewayConnection.run
    1. py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    2. py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    3. py4j.Gateway.invoke(Gateway.java:280)
    4. py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    5. py4j.commands.CallCommand.execute(CallCommand.java:79)
    6. py4j.GatewayConnection.run(GatewayConnection.java:214)
    6 frames
  9. Java RT
    Thread.run
    1. java.lang.Thread.run(Thread.java:745)
    1 frame