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https://issues.apache.org/jira/browse/TOREE-424?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Josiah Samuel Sathiadass updated TOREE-424:
-------------------------------------------
Priority: Minor (was: Major)
> 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
> Priority: Minor
> 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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