org.apache.spark.SparkException: Yarn application has already ended! It might have been killed or unable to launch application master.

GitHub | mbuccini | 6 months ago
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  1. 0

    SparkException when trying to create a context with a non-existing or unauthorized queue

    GitHub | 6 months ago | mbuccini
    org.apache.spark.SparkException: Yarn application has already ended! It might have been killed or unable to launch application master.
  2. 0
    samebug tip
    Change the queue name to hadoop
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    Stack Overflow | 1 year ago | iboss
    org.apache.spark.SparkException: Yarn application has already ended! It might have been killed or unable to launch application master.
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  5. 0

    Spark Config Files

    Stack Overflow | 12 months ago | Ashesh Nair
    org.apache.spark.SparkException: Yarn application has already ended! It might have been killed or unable to launch application master.
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    Stack Overflow | 8 months ago | Sai Krishna
    org.apache.spark.SparkException: Yarn application has already ended! It might have been killed or unable to launch application master.
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Root Cause Analysis

  1. org.apache.spark.SparkException

    Yarn application has already ended! It might have been killed or unable to launch application master.

    at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication()
  2. Spark
    SparkContext.<init>
    1. org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:124)
    2. org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:64)
    3. org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:144)
    4. org.apache.spark.SparkContext.<init>(SparkContext.scala:530)
    4 frames
  3. Spark Project Streaming
    StreamingContext.<init>
    1. org.apache.spark.streaming.StreamingContext$.createNewSparkContext(StreamingContext.scala:874)
    2. org.apache.spark.streaming.StreamingContext.<init>(StreamingContext.scala:81)
    2 frames
  4. spark.jobserver.context
    StreamingContextFactory.makeContext
    1. spark.jobserver.context.StreamingContextFactory$$anon$1.<init>(StreamingContextFactory.scala:16)
    2. spark.jobserver.context.StreamingContextFactory.makeContext(StreamingContextFactory.scala:16)
    3. spark.jobserver.context.StreamingContextFactory.makeContext(StreamingContextFactory.scala:8)
    4. spark.jobserver.context.SparkContextFactory$class.makeContext(SparkContextFactory.scala:37)
    5. spark.jobserver.context.StreamingContextFactory.makeContext(StreamingContextFactory.scala:8)
    5 frames
  5. spark.jobserver
    JobManagerActor$$anonfun$wrappedReceive$1.applyOrElse
    1. spark.jobserver.JobManagerActor.createContextFromConfig(JobManagerActor.scala:378)
    2. spark.jobserver.JobManagerActor$$anonfun$wrappedReceive$1.applyOrElse(JobManagerActor.scala:122)
    2 frames
  6. Scala
    AbstractPartialFunction$mcVL$sp.apply
    1. scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33)
    2. scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33)
    3. scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25)
    3 frames
  7. ooyala.common.akka
    ActorStack$$anonfun$receive$1.applyOrElse
    1. ooyala.common.akka.ActorStack$$anonfun$receive$1.applyOrElse(ActorStack.scala:33)
    1 frame
  8. Scala
    AbstractPartialFunction$mcVL$sp.apply
    1. scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33)
    2. scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33)
    3. scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25)
    3 frames
  9. ooyala.common.akka
    Slf4jLogging$$anonfun$receive$1.applyOrElse
    1. ooyala.common.akka.Slf4jLogging$$anonfun$receive$1$$anonfun$applyOrElse$1.apply$mcV$sp(Slf4jLogging.scala:26)
    2. ooyala.common.akka.Slf4jLogging$class.ooyala$common$akka$Slf4jLogging$$withAkkaSourceLogging(Slf4jLogging.scala:35)
    3. ooyala.common.akka.Slf4jLogging$$anonfun$receive$1.applyOrElse(Slf4jLogging.scala:25)
    3 frames
  10. Scala
    AbstractPartialFunction$mcVL$sp.apply
    1. scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33)
    2. scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33)
    3. scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25)
    3 frames
  11. ooyala.common.akka
    ActorMetrics$$anonfun$receive$1.applyOrElse
    1. ooyala.common.akka.ActorMetrics$$anonfun$receive$1.applyOrElse(ActorMetrics.scala:24)
    1 frame
  12. Akka Actor
    Actor$class.aroundReceive
    1. akka.actor.Actor$class.aroundReceive(Actor.scala:467)
    1 frame
  13. ooyala.common.akka
    InstrumentedActor.aroundReceive
    1. ooyala.common.akka.InstrumentedActor.aroundReceive(InstrumentedActor.scala:8)
    1 frame
  14. Akka Actor
    ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec
    1. akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
    2. akka.actor.ActorCell.invoke(ActorCell.scala:487)
    3. akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
    4. akka.dispatch.Mailbox.run(Mailbox.scala:220)
    5. akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:397)
    5 frames
  15. Scala
    ForkJoinWorkerThread.run
    1. scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
    2. scala.concurrent.forkjoin.ForkJoinPool$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