Josiah Samuel Sathiadass created TOREE-424:
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             Summary: ClassCastException on Dataset with case class 
                 Key: TOREE-424
                 URL: https://issues.apache.org/jira/browse/TOREE-424
             Project: TOREE
          Issue Type: Bug
          Components: Kernel
    Affects Versions: 0.2.0
         Environment: ppcle64
            Reporter: Josiah Samuel Sathiadass
         Attachments: Screen Shot 2017-07-14 at 11.39.22 AM.png

When we tried to use Jupyter Notebook with Apache Toree kernel, we couldn't get 
this working for DataSet specially with "case class" as it throws 
*ClassCastException* as follows,

{{Name: org.apache.spark.SparkException
Message: Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, 
most recent failure: Lost task 0.0 in stage 1.0 (TID 1, localhost): 
java.lang.ClassCastException: $line45.$read$$iw$$iw$DataPoint cannot be cast to 
$line45.$read$$iw$$iw$DataPoint
        at 
org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown
 Source)
        at 
org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
        at 
org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
        at 
org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246)
        at 
org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240)
        at 
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803)
        at 
org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803)
        at 
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
        at org.apache.spark.scheduler.Task.run(Task.scala:86)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
        at 
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at 
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)}}

The commands we issued are as follows,

{{import org.apache.spark.sql.SparkSession
val sc = SparkSession.builder.getOrCreate()
import sc.implicits._
import sc.sqlContext.implicits._
case class DataPoint(element: Long)
val ds=spark.range(0,10,1,1).map(x => DataPoint(x))
ds.collect().foreach(println)}}

We were using the latest version of Toree which has the support for Spark 2.0. 

pip install 
https://dist.apache.org/repos/dist/dev/incubator/toree/0.2.0/snapshots/dev1/toree-pip/toree-0.2.0.dev1.tar.gz



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