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Posted to issues@spark.apache.org by "Ohad Zadok (JIRA)" <ji...@apache.org> on 2015/07/08 21:21:05 UTC

[jira] [Created] (SPARK-8904) When using LDA DAGScheduler throws exception

Ohad Zadok created SPARK-8904:
---------------------------------

             Summary: When using LDA DAGScheduler throws exception
                 Key: SPARK-8904
                 URL: https://issues.apache.org/jira/browse/SPARK-8904
             Project: Spark
          Issue Type: Bug
          Components: ML, MLlib
    Affects Versions: 1.4.0
         Environment: Amazon EC2 using ubuntu
            Reporter: Ohad Zadok


When using the LDA algorithm, DAGscheduler throws an exeption, this is the stack trace:

        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)

Driver stacktrace:
        at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1266)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1257)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1256)
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
        at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1256)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730)
        at scala.Option.foreach(Option.scala:236)
        at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:730)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1450)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1411)
        at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)




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