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From "Tathagata Das (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-11932) trackStateByKey throws java.lang.IllegalArgumentException: requirement failed on restarting from checkpoint
Date Mon, 23 Nov 2015 22:01:11 GMT

     [ https://issues.apache.org/jira/browse/SPARK-11932?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Tathagata Das updated SPARK-11932:
----------------------------------
    Description: 
Code 
{code}
  StreamingContext.getOrCreate(".", () => createContext(args))
  ...

  def createContext(args: Array[String]) : StreamingContext = {

    val sparkConf = new SparkConf().setAppName("StatefulNetworkWordCount")
    // Create the context with a 1 second batch size
    val ssc = new StreamingContext(sparkConf, Seconds(1))
    
    ssc.checkpoint(".")

    // Initial RDD input to trackStateByKey
    val initialRDD = ssc.sparkContext.parallelize(List(("hello", 1), ("world", 1)))

    // Create a ReceiverInputDStream on target ip:port and count the
    // words in input stream of \n delimited test (eg. generated by 'nc')
    val lines = ssc.socketTextStream(args(0), args(1).toInt)
    val words = lines.flatMap(_.split(" "))
    val wordDstream = words.map(x => (x, 1))

    // Update the cumulative count using updateStateByKey
    // This will give a DStream made of state (which is the cumulative count of the words)
    val trackStateFunc = (batchTime: Time, word: String, one: Option[Int], state: State[Int])
=> {
      val sum = one.getOrElse(0) + state.getOption.getOrElse(0)
      val output = (word, sum)
      state.update(sum)
      Some(output)
    }

    val stateDstream = wordDstream.trackStateByKey(
      StateSpec.function(trackStateFunc).initialState(initialRDD))
    stateDstream.print()
    
    ssc
  
  }
{code}

Error 
{code}
15/11/23 10:55:07 ERROR StreamingContext: Error starting the context, marking it as stopped
java.lang.IllegalArgumentException: requirement failed
at scala.Predef$.require(Predef.scala:221)
at org.apache.spark.streaming.rdd.TrackStateRDD.<init>(TrackStateRDD.scala:133)
at org.apache.spark.streaming.dstream.InternalTrackStateDStream$$anonfun$compute$2.apply(TrackStateDStream.scala:148)
at org.apache.spark.streaming.dstream.InternalTrackStateDStream$$anonfun$compute$2.apply(TrackStateDStream.scala:143)
at scala.Option.map(Option.scala:145)
at org.apache.spark.streaming.dstream.InternalTrackStateDStream.compute(TrackStateDStream.scala:143)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)
at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:424)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342)
at scala.Option.orElse(Option.scala:257)
at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339)
at org.apache.spark.streaming.dstream.TrackStateDStreamImpl.compute(TrackStateDStream.scala:66)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)
at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:424)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344)
at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342)
at scala.Option.orElse(Option.scala:257)
at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339)
at org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scla:47)
at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:115)
at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:114)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:251)
at scala.collection.AbstractTraversable.flatMap(Traversable.scala:105)
at org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:114)
at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$restart$4.apply(JobGenerator.scala:231)
at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$restart$4.apply(JobGenerator.scala:226)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
at org.apache.spark.streaming.scheduler.JobGenerator.restart(JobGenerator.scala:226
at org.apache.spark.streaming.scheduler.JobGenerator.start(JobGenerator.scala:96)
at org.apache.spark.streaming.scheduler.JobScheduler.start(JobScheduler.scala:83)
at org.apache.spark.streaming.StreamingContext$$anonfun$liftedTree1$1$1.apply$mcV$sp(StreamingContext.scala:609)
at org.apache.spark.streaming.StreamingContext$$anonfun$liftedTree1$1$1.apply(StreamingContext.scala:605)
at org.apache.spark.streaming.StreamingContext$$anonfun$liftedTree1$1$1.apply(StreamingContext.scala:605)
at ... run in separate thread using org.apache.spark.util.ThreadUtils ... ()
at org.apache.spark.streaming.StreamingContext.liftedTree1$1(StreamingContext.scala:605)
at org.apache.spark.streaming.StreamingContext.start(StreamingContext.scala:599)
at org.apache.spark.examples.streaming.StatefulNetworkWordCount$.main(StatefulNetworkWordCount.scala:48)
at org.apache.spark.examples.streaming.StatefulNetworkWordCount.main(StatefulNetworkWordCount.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:483)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:727)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
{code}


  was:
Code 
{{{
  StreamingContext.getOrCreate(".", () => createContext(args))
  ...

  def createContext(args: Array[String]) : StreamingContext = {

    val sparkConf = new SparkConf().setAppName("StatefulNetworkWordCount")
    // Create the context with a 1 second batch size
    val ssc = new StreamingContext(sparkConf, Seconds(1))
    
    ssc.checkpoint(".")

    // Initial RDD input to trackStateByKey
    val initialRDD = ssc.sparkContext.parallelize(List(("hello", 1), ("world", 1)))

    // Create a ReceiverInputDStream on target ip:port and count the
    // words in input stream of \n delimited test (eg. generated by 'nc')
    val lines = ssc.socketTextStream(args(0), args(1).toInt)
    val words = lines.flatMap(_.split(" "))
    val wordDstream = words.map(x => (x, 1))

    // Update the cumulative count using updateStateByKey
    // This will give a DStream made of state (which is the cumulative count of the words)
    val trackStateFunc = (batchTime: Time, word: String, one: Option[Int], state: State[Int])
=> {
      val sum = one.getOrElse(0) + state.getOption.getOrElse(0)
      val output = (word, sum)
      state.update(sum)
      Some(output)
    }

    val stateDstream = wordDstream.trackStateByKey(
      StateSpec.function(trackStateFunc).initialState(initialRDD))
    stateDstream.print()
    
    ssc
  
  }
}}}


Error 
{{
15/11/23 10:55:07 ERROR StreamingContext: Error starting the context, marking it as stopped

java.lang.IllegalArgumentException: requirement failed

at scala.Predef$.require(Predef.scala:221)

at org.apache.spark.streaming.rdd.TrackStateRDD.<init>(TrackStateRDD.scala:133)

at org.apache.spark.streaming.dstream.InternalTrackStateDStream$$anonfun$compute$2.apply(TrackStateDStream.scala:148)

at org.apache.spark.streaming.dstream.InternalTrackStateDStream$$anonfun$compute$2.apply(TrackStateDStream.scala:143)

at scala.Option.map(Option.scala:145)

at org.apache.spark.streaming.dstream.InternalTrackStateDStream.compute(TrackStateDStream.scala:143)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)

at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)

at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:424)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342)

at scala.Option.orElse(Option.scala:257)

at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339)

at org.apache.spark.streaming.dstream.TrackStateDStreamImpl.compute(TrackStateDStream.scala:66)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)

at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)

at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:424)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342)

at scala.Option.orElse(Option.scala:257)

at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339)

at org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:47)

at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:115)

at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:114)

at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)

at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)

at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)

at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)

at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:251)

at scala.collection.AbstractTraversable.flatMap(Traversable.scala:105)

at org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:114)

at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$restart$4.apply(JobGenerator.scala:231)

at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$restart$4.apply(JobGenerator.scala:226)

at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)

at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)

at org.apache.spark.streaming.scheduler.JobGenerator.restart(JobGenerator.scala:226)

at org.apache.spark.streaming.scheduler.JobGenerator.start(JobGenerator.scala:96)

at org.apache.spark.streaming.scheduler.JobScheduler.start(JobScheduler.scala:83)

at org.apache.spark.streaming.StreamingContext$$anonfun$liftedTree1$1$1.apply$mcV$sp(StreamingContext.scala:609)

at org.apache.spark.streaming.StreamingContext$$anonfun$liftedTree1$1$1.apply(StreamingContext.scala:605)

at org.apache.spark.streaming.StreamingContext$$anonfun$liftedTree1$1$1.apply(StreamingContext.scala:605)

at ... run in separate thread using org.apache.spark.util.ThreadUtils ... ()

at org.apache.spark.streaming.StreamingContext.liftedTree1$1(StreamingContext.scala:605)

at org.apache.spark.streaming.StreamingContext.start(StreamingContext.scala:599)

at org.apache.spark.examples.streaming.StatefulNetworkWordCount$.main(StatefulNetworkWordCount.scala:48)

at org.apache.spark.examples.streaming.StatefulNetworkWordCount.main(StatefulNetworkWordCount.scala)

at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)

at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)

at java.lang.reflect.Method.invoke(Method.java:483)

at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:727)

at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)

at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)

at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)

at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
}}



> trackStateByKey throws java.lang.IllegalArgumentException: requirement failed on restarting
from checkpoint
> -----------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-11932
>                 URL: https://issues.apache.org/jira/browse/SPARK-11932
>             Project: Spark
>          Issue Type: Bug
>          Components: Streaming
>            Reporter: Tathagata Das
>            Assignee: Tathagata Das
>            Priority: Blocker
>
> Code 
> {code}
>   StreamingContext.getOrCreate(".", () => createContext(args))
>   ...
>   def createContext(args: Array[String]) : StreamingContext = {
>     val sparkConf = new SparkConf().setAppName("StatefulNetworkWordCount")
>     // Create the context with a 1 second batch size
>     val ssc = new StreamingContext(sparkConf, Seconds(1))
>     
>     ssc.checkpoint(".")
>     // Initial RDD input to trackStateByKey
>     val initialRDD = ssc.sparkContext.parallelize(List(("hello", 1), ("world", 1)))
>     // Create a ReceiverInputDStream on target ip:port and count the
>     // words in input stream of \n delimited test (eg. generated by 'nc')
>     val lines = ssc.socketTextStream(args(0), args(1).toInt)
>     val words = lines.flatMap(_.split(" "))
>     val wordDstream = words.map(x => (x, 1))
>     // Update the cumulative count using updateStateByKey
>     // This will give a DStream made of state (which is the cumulative count of the words)
>     val trackStateFunc = (batchTime: Time, word: String, one: Option[Int], state: State[Int])
=> {
>       val sum = one.getOrElse(0) + state.getOption.getOrElse(0)
>       val output = (word, sum)
>       state.update(sum)
>       Some(output)
>     }
>     val stateDstream = wordDstream.trackStateByKey(
>       StateSpec.function(trackStateFunc).initialState(initialRDD))
>     stateDstream.print()
>     
>     ssc
>   
>   }
> {code}
> Error 
> {code}
> 15/11/23 10:55:07 ERROR StreamingContext: Error starting the context, marking it as stopped
> java.lang.IllegalArgumentException: requirement failed
> at scala.Predef$.require(Predef.scala:221)
> at org.apache.spark.streaming.rdd.TrackStateRDD.<init>(TrackStateRDD.scala:133)
> at org.apache.spark.streaming.dstream.InternalTrackStateDStream$$anonfun$compute$2.apply(TrackStateDStream.scala:148)
> at org.apache.spark.streaming.dstream.InternalTrackStateDStream$$anonfun$compute$2.apply(TrackStateDStream.scala:143)
> at scala.Option.map(Option.scala:145)
> at org.apache.spark.streaming.dstream.InternalTrackStateDStream.compute(TrackStateDStream.scala:143)
> at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)
> at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)
> at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
> at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)
> at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)
> at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:424)
> at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344)
> at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342)
> at scala.Option.orElse(Option.scala:257)
> at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339)
> at org.apache.spark.streaming.dstream.TrackStateDStreamImpl.compute(TrackStateDStream.scala:66)
> at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)
> at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)
> at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
> at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349
> at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)
> at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:424)
> at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344)
> at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342)
> at scala.Option.orElse(Option.scala:257)
> at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339)
> at org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scla:47)
> at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:115)
> at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:114)
> at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)
> at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:251)
> at scala.collection.AbstractTraversable.flatMap(Traversable.scala:105)
> at org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:114)
> at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$restart$4.apply(JobGenerator.scala:231)
> at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$restart$4.apply(JobGenerator.scala:226)
> at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
> at org.apache.spark.streaming.scheduler.JobGenerator.restart(JobGenerator.scala:226
> at org.apache.spark.streaming.scheduler.JobGenerator.start(JobGenerator.scala:96)
> at org.apache.spark.streaming.scheduler.JobScheduler.start(JobScheduler.scala:83)
> at org.apache.spark.streaming.StreamingContext$$anonfun$liftedTree1$1$1.apply$mcV$sp(StreamingContext.scala:609)
> at org.apache.spark.streaming.StreamingContext$$anonfun$liftedTree1$1$1.apply(StreamingContext.scala:605)
> at org.apache.spark.streaming.StreamingContext$$anonfun$liftedTree1$1$1.apply(StreamingContext.scala:605)
> at ... run in separate thread using org.apache.spark.util.ThreadUtils ... ()
> at org.apache.spark.streaming.StreamingContext.liftedTree1$1(StreamingContext.scala:605)
> at org.apache.spark.streaming.StreamingContext.start(StreamingContext.scala:599)
> at org.apache.spark.examples.streaming.StatefulNetworkWordCount$.main(StatefulNetworkWordCount.scala:48)
> at org.apache.spark.examples.streaming.StatefulNetworkWordCount.main(StatefulNetworkWordCount.scala)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:483)
> at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:727)
> at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
> at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
> at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
> at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
> {code}



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