org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 7, test-cluster-w-0.c.test-project.internal): ExecutorLostFailure (executor 2 exited caused by one of the running tasks) Reason: Container marked as failed: container_1475077182957_0001_01_000005 on host: sun-recommendations-evaluation-w-0.c.test-project.internal. Exit status: 50. Diagnostics: Exception from container-launch. Container id: container_1475077182957_0001_01_000005 Exit code: 50 Stack trace: ExitCodeException exitCode=50:

Stack Overflow | cahen | 2 months ago
  1. 0

    Spark job became incompatible with Google Dataproc

    Stack Overflow | 2 months ago | cahen
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 7, test-cluster-w-0.c.test-project.internal): ExecutorLostFailure (executor 2 exited caused by one of the running tasks) Reason: Container marked as failed: container_1475077182957_0001_01_000005 on host: sun-recommendations-evaluation-w-0.c.test-project.internal. Exit status: 50. Diagnostics: Exception from container-launch. Container id: container_1475077182957_0001_01_000005 Exit code: 50 Stack trace: ExitCodeException exitCode=50:
  2. 0

    Remotely connect to spark on yarn cluster in client mode

    Stack Overflow | 1 year ago | Bamqf
    org.apache.spark.SparkException: Yarn application has already ended! It might have been killed or unable to launch application master. A more detailed error message on hadoop application tracking page is like this: User: blueivy Name: SparkR Application Type: SPARK Application Tags: State: FAILED FinalStatus: FAILED Started: 27-Oct-2015 11:07:09 Elapsed: 4mins, 39sec Tracking URL: History Diagnostics: Application application_1445628650748_0027 failed 2 times due to AM Container for appattempt_1445628650748_0027_000002 exited with exitCode: 10 For more detailed output, check application tracking page:http://master:8088/proxy/application_1445628650748_0027/Then, click on links to logs of each attempt. Diagnostics: Exception from container-launch. Container id: container_1445628650748_0027_02_000001 Exit code: 10 Stack trace: ExitCodeException exitCode=10:
  3. 0

    Container marked as failed with ExitCodeException exitCode=52

    Stack Overflow | 1 month ago | Newbie
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 1618 in stage 12.0 failed 4 times, most recent failure: Lost task 1618.3 in stage 12.0 (TID 6433, ip-172-31-15-52.ec2.internal): ExecutorLostFailure (executor 150 exited caused by one of the running tasks) Reason: Container marked as failed: container_1477092339052_0007_01_000151 on host: ip-172-31-15-52.ec2.internal. Exit status: 52. Diagnostics: Exception from container-launch. Container id: container_1477092339052_0007_01_000151 Exit code: 52 Stack trace: ExitCodeException exitCode=52:
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  5. 0

    Slave lost error in pyspark

    Stack Overflow | 3 weeks ago | newleaf
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 6 in stage 6.0 failed 4 times, most recent failure: Lost task 6.3 in stage 6.0 ExecutorLostFailure (executor 2 exited caused by one of the running tasks) Reason: Slave lost When I did persist, through spark UI I saw the shuffleWrite memory is very high and took a long time and still returned errors. Through some search, I found these might be the out of memory problem. Following this link out of memory error Java I did a repartition up to 1000, still not so helpful. I set up the SparkConf as conf = (SparkConf().set("spark.driver.maxResultSize", "150g").set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")) My server side memory could be up to 200GB Do yo have any good idea to do this or point me to related links. Pyspark will be most helpful Here is the error log from YARN: Application application_1477088172315_0118 failed 2 times due to AM Container for appattempt_1477088172315_0118_000006 exited with exitCode: 10 For more detailed output, check application tracking page: Then, click on links to logs of each attempt. Diagnostics: Exception from container-launch. Container id: container_1477088172315_0118_06_000001 Exit code: 10 Stack trace: ExitCodeException exitCode=10:
  6. 0

    Why does starting my Spark Streaming application give "Container exited with a non-zero exit code 50"?

    Stack Overflow | 2 weeks ago | duckertito
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 51.0 failed 4 times, most recent failure: Lost task 1.3 in stage 51.0 (TID 476, ip-175-33-333-6.eu-east-1.compute.internal): ExecutorLostFailure (executor 2 exited caused by one of the running tasks) Reason: Container marked as failed: container_1479883845484_0065_01_000003 on host: ip-175-33-333-6.eu-east-1.compute.internal. Exit status: 50. Diagnostics: Exception from container-launch. Container id: container_1479883845484_0065_01_000003 Exit code: 50 Stack trace: ExitCodeException exitCode=50:

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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 0.3 in stage 0.0 (TID 7, test-cluster-w-0.c.test-project.internal): ExecutorLostFailure (executor 2 exited caused by one of the running tasks) Reason: Container marked as failed: container_1475077182957_0001_01_000005 on host: sun-recommendations-evaluation-w-0.c.test-project.internal. Exit status: 50. Diagnostics: Exception from container-launch. Container id: container_1475077182957_0001_01_000005 Exit code: 50 Stack trace: ExitCodeException exitCode=50:

      at org.apache.hadoop.util.Shell.runCommand()
    2. Hadoop
      Shell$ShellCommandExecutor.execute
      1. org.apache.hadoop.util.Shell.runCommand(Shell.java:545)
      2. org.apache.hadoop.util.Shell.run(Shell.java:456)
      3. org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:722)
      3 frames
    3. hadoop-yarn-server-nodemanager
      ContainerLaunch.call
      1. org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
      2. org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
      3. org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
      3 frames
    4. Java RT
      Thread.run
      1. java.util.concurrent.FutureTask.run(FutureTask.java:266)
      2. java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
      3. java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
      4. java.lang.Thread.run(Thread.java:745)
      4 frames