You are viewing a plain text version of this content. The canonical link for it is here.
Posted to user@spark.apache.org by Srikrishna S <sr...@gmail.com> on 2014/07/11 21:01:54 UTC

Job getting killed

I am trying to run Logistic Regression on the url dataset (from
libsvm) using the exact same code
as the example on a 5 node Yarn-Cluster.

I get a pretty cryptic error that says

"Killed"

Nothing more

Settings:

  --master yarn-client"
  --verbose"
  --driver-memory 24G
  --executor-memory 24G
  --executor-cores 8
  --num-executors 5

I set the akka.frame_size to 200MB.


Script:

ef main(args: Array[String]) {

    val conf = new SparkConf()
             .setMaster("yarn-client")
             .setAppName("Logistic regression SGD fixed")
             .set("spark.akka.frameSize", "200")
    var sc = new SparkContext(conf)

    // Load and parse the data
    val dataset = args(0)
    val maxIterations = 100
    val start_time = System.nanoTime()
    val data = MLUtils.loadLibSVMFile(sc, dataset)

    // Building the model
    var solver = new LogisticRegressionWithSGD()
    solver.optimizer.setNumIterations(maxIterations)
    solver.optimizer.setRegParam(0.01)
    val model = solver.run(data)

   // Measure the accuracy. Don't measure the time taken to do this.
   val preditionsAndLabels = data.map { point =>
     val prediction = model.predict(point.features)
     (prediction, point.label)
   }

   val accuracy = (preditionsAndLabels.filter(r => r._1 ==
r._2).count.toDouble) / data.count
   val elapsed_time = (System.nanoTime() - start_time) / 1e9

   // User the last known accuracy
   println(dataset + ",spark-sgd," + maxIterations + ","  +
elapsed_time + "," + accuracy)
   System.exit(0)
  }

Re: Job getting killed

Posted by akhandeshi <am...@gmail.com>.
Where you able to resolve this issue.  I am seeing similar problem!  It seems
to be connected to using OFF_PEAK persist.

Thanks,

Ami



--
View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Job-getting-killed-tp9437p21123.html
Sent from the Apache Spark User List mailing list archive at Nabble.com.

---------------------------------------------------------------------
To unsubscribe, e-mail: user-unsubscribe@spark.apache.org
For additional commands, e-mail: user-help@spark.apache.org