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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/06/21 15:56:58 UTC

[jira] [Assigned] (SPARK-16100) Aggregator fails with Tungsten error when complex types are used for results and partial sum

     [ https://issues.apache.org/jira/browse/SPARK-16100?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-16100:
------------------------------------

    Assignee:     (was: Apache Spark)

> Aggregator fails with Tungsten error when complex types are used for results and partial sum
> --------------------------------------------------------------------------------------------
>
>                 Key: SPARK-16100
>                 URL: https://issues.apache.org/jira/browse/SPARK-16100
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.0.0
>            Reporter: Deenar Toraskar
>
> I get a similar error when using complex types in Aggregator. Not sure if this is the same issue or something else.
> {code:Agg.scala}
> import org.apache.spark.sql.functions._
> import org.apache.spark.sql.TypedColumn
> import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder
> import org.apache.spark.sql.expressions.Aggregator
> import org.apache.spark.sql.{Encoder,Row}
> import sqlContext.implicits._
> object CustomSummer extends Aggregator[Valuation, Map[Int, Seq[Double]], Seq[Seq[Double]]] with Serializable  {
>      def zero: Map[Int, Seq[Double]] = Map()
>      def reduce(b: Map[Int, Seq[Double]], a:Valuation): Map[Int, Seq[Double]] = {
>        val timeInterval: Int = a.timeInterval
>        val currentSum: Seq[Double] = b.get(timeInterval).getOrElse(Nil)
>        val currentRow: Seq[Double] = a.pvs
>        b.updated(timeInterval, sumArray(currentSum, currentRow))
>      }     
>     def sumArray(a: Seq[Double], b: Seq[Double]): Seq[Double] = Nil
>      def merge(b1: Map[Int, Seq[Double]], b2: Map[Int, Seq[Double]]): Map[Int, Seq[Double]] = {
>         /* merges two maps together ++ replaces any (k,v) from the map on the left
>         side of ++ (here map1) by (k,v) from the right side map, if (k,_) already
>         exists in the left side map (here map1), e.g. Map(1->1) ++ Map(1->2) results in Map(1->2) */
>         b1 ++ b2.map { case (timeInterval, exposures) =>
>           timeInterval -> sumArray(exposures, b1.getOrElse(timeInterval, Nil))
>         }
>      }
>      def finish(exposures: Map[Int, Seq[Double]]): Seq[Seq[Double]] = 
>       {
>         exposures.size match {
>           case 0 => null
>           case _ => {
>             val range = exposures.keySet.max
>             // convert map to 2 dimensional array, (timeInterval x Seq[expScn1, expScn2, ...]
>             (0 to range).map(x => exposures.getOrElse(x, Nil))
>           }
>         }
>       }
>   override def bufferEncoder: Encoder[Map[Int,Seq[Double]]] = ExpressionEncoder()
>   override def outputEncoder: Encoder[Seq[Seq[Double]]] = ExpressionEncoder()
>    }
> case class Valuation(timeInterval : Int, pvs : Seq[Double])
> val valns = sc.parallelize(Seq(Valuation(0, Seq(1.0,2.0,3.0)),
>   Valuation(2, Seq(1.0,2.0,3.0)),
>   Valuation(1, Seq(1.0,2.0,3.0)),Valuation(2, Seq(1.0,2.0,3.0)),Valuation(0, Seq(1.0,2.0,3.0))
>   )).toDS
> val g_c1 = valns.groupByKey(_.timeInterval).agg(CustomSummer.toColumn).show(false)
> {code}
> I get the following error
> {quote}
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 10.0 failed 1 times, most recent failure: Lost task 1.0 in stage 10.0 (TID 19, localhost): java.lang.IndexOutOfBoundsException: 0
> at scala.collection.mutable.ResizableArray$class.apply(ResizableArray.scala:43)
> at scala.collection.mutable.ArrayBuffer.apply(ArrayBuffer.scala:47)
> at scala.collection.mutable.ArrayBuffer.remove(ArrayBuffer.scala:167)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:244)
> at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:179)
> at org.apache.spark.sql.catalyst.trees.TreeNode.withNewChildren(TreeNode.scala:214)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized$lzycompute(Expression.scala:156)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized(Expression.scala:154)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized$lzycompute(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized(Expression.scala:154)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized$lzycompute(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized(Expression.scala:154)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized$lzycompute(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized(Expression.scala:154)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized$lzycompute(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized(Expression.scala:154)
> at org.apache.spark.sql.catalyst.expressions.Expression.semanticHash(Expression.scala:174)
> at org.apache.spark.sql.catalyst.expressions.EquivalentExpressions$Expr.hashCode(EquivalentExpressions.scala:39)
> at scala.runtime.ScalaRunTime$.hash(ScalaRunTime.scala:210)
> at scala.collection.mutable.HashTable$HashUtils$class.elemHashCode(HashTable.scala:398)
> at scala.collection.mutable.HashMap.elemHashCode(HashMap.scala:39)
> at scala.collection.mutable.HashTable$class.findEntry(HashTable.scala:130)
> at scala.collection.mutable.HashMap.findEntry(HashMap.scala:39)
> at scala.collection.mutable.HashMap.get(HashMap.scala:69)
> at org.apache.spark.sql.catalyst.expressions.EquivalentExpressions.addExpr(EquivalentExpressions.scala:53)
> at org.apache.spark.sql.catalyst.expressions.EquivalentExpressions.addExprTree(EquivalentExpressions.scala:86)
> at org.apache.spark.sql.catalyst.expressions.codegen.CodegenContext$$anonfun$subexpressionElimination$1.apply(CodeGenerator.scala:661)
> at org.apache.spark.sql.catalyst.expressions.codegen.CodegenContext$$anonfun$subexpressionElimination$1.apply(CodeGenerator.scala:661)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at org.apache.spark.sql.catalyst.expressions.codegen.CodegenContext.subexpressionElimination(CodeGenerator.scala:661)
> at org.apache.spark.sql.catalyst.expressions.codegen.CodegenContext.generateExpressions(CodeGenerator.scala:718)
> at org.apache.spark.sql.catalyst.expressions.codegen.GenerateMutableProjection$.create(GenerateMutableProjection.scala:59)
> at org.apache.spark.sql.catalyst.expressions.codegen.GenerateMutableProjection$.generate(GenerateMutableProjection.scala:44)
> at org.apache.spark.sql.execution.SparkPlan.newMutableProjection(SparkPlan.scala:369)
> at org.apache.spark.sql.execution.aggregate.SortAggregateExec$$anonfun$doExecute$1$$anonfun$3$$anonfun$4.apply(SortAggregateExec.scala:93)
> at org.apache.spark.sql.execution.aggregate.SortAggregateExec$$anonfun$doExecute$1$$anonfun$3$$anonfun$4.apply(SortAggregateExec.scala:92)
> at org.apache.spark.sql.execution.aggregate.AggregationIterator.generateProcessRow(AggregationIterator.scala:178)
> at org.apache.spark.sql.execution.aggregate.AggregationIterator.<init>(AggregationIterator.scala:197)
> at org.apache.spark.sql.execution.aggregate.SortBasedAggregationIterator.<init>(SortBasedAggregationIterator.scala:29)
> at org.apache.spark.sql.execution.aggregate.SortAggregateExec$$anonfun$doExecute$1$$anonfun$3.apply(SortAggregateExec.scala:84)
> at org.apache.spark.sql.execution.aggregate.SortAggregateExec$$anonfun$doExecute$1$$anonfun$3.apply(SortAggregateExec.scala:75)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:780)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:780)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
> at org.apache.spark.scheduler.Task.run(Task.scala:85)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
> at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1450)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1438)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1437)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1437)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
> at scala.Option.foreach(Option.scala:236)
> at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1659)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1618)
> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1607)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1872)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1885)
> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1898)
> at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:347)
> at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:39)
> at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2176)
> at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2525)
> at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2175)
> at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2182)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1918)
> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:1917)
> at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2555)
> at org.apache.spark.sql.Dataset.head(Dataset.scala:1917)
> at org.apache.spark.sql.Dataset.take(Dataset.scala:2132)
> at org.apache.spark.sql.Dataset.showString(Dataset.scala:239)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:526)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:506)
> Caused by: java.lang.IndexOutOfBoundsException: 0
> at scala.collection.mutable.ResizableArray$class.apply(ResizableArray.scala:43)
> at scala.collection.mutable.ArrayBuffer.apply(ArrayBuffer.scala:47)
> at scala.collection.mutable.ArrayBuffer.remove(ArrayBuffer.scala:167)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:244)
> at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:179)
> at org.apache.spark.sql.catalyst.trees.TreeNode.withNewChildren(TreeNode.scala:214)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized$lzycompute(Expression.scala:156)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized(Expression.scala:154)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized$lzycompute(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized(Expression.scala:154)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized$lzycompute(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized(Expression.scala:154)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized$lzycompute(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized(Expression.scala:154)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$1.apply(Expression.scala:155)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized$lzycompute(Expression.scala:155)
> at org.apache.spark.sql.catalyst.expressions.Expression.canonicalized(Expression.scala:154)
> at org.apache.spark.sql.catalyst.expressions.Expression.semanticHash(Expression.scala:174)
> at org.apache.spark.sql.catalyst.expressions.EquivalentExpressions$Expr.hashCode(EquivalentExpressions.scala:39)
> at scala.runtime.ScalaRunTime$.hash(ScalaRunTime.scala:210)
> at scala.collection.mutable.HashTable$HashUtils$class.elemHashCode(HashTable.scala:398)
> at scala.collection.mutable.HashMap.elemHashCode(HashMap.scala:39)
> at scala.collection.mutable.HashTable$class.findEntry(HashTable.scala:130)
> at scala.collection.mutable.HashMap.findEntry(HashMap.scala:39)
> at scala.collection.mutable.HashMap.get(HashMap.scala:69)
> at org.apache.spark.sql.catalyst.expressions.EquivalentExpressions.addExpr(EquivalentExpressions.scala:53)
> at org.apache.spark.sql.catalyst.expressions.EquivalentExpressions.addExprTree(EquivalentExpressions.scala:86)
> at org.apache.spark.sql.catalyst.expressions.codegen.CodegenContext$$anonfun$subexpressionElimination$1.apply(CodeGenerator.scala:661)
> at org.apache.spark.sql.catalyst.expressions.codegen.CodegenContext$$anonfun$subexpressionElimination$1.apply(CodeGenerator.scala:661)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at org.apache.spark.sql.catalyst.expressions.codegen.CodegenContext.subexpressionElimination(CodeGenerator.scala:661)
> at org.apache.spark.sql.catalyst.expressions.codegen.CodegenContext.generateExpressions(CodeGenerator.scala:718)
> at org.apache.spark.sql.catalyst.expressions.codegen.GenerateMutableProjection$.create(GenerateMutableProjection.scala:59)
> at org.apache.spark.sql.catalyst.expressions.codegen.GenerateMutableProjection$.generate(GenerateMutableProjection.scala:44)
> at org.apache.spark.sql.execution.SparkPlan.newMutableProjection(SparkPlan.scala:369)
> at org.apache.spark.sql.execution.aggregate.SortAggregateExec$$anonfun$doExecute$1$$anonfun$3$$anonfun$4.apply(SortAggregateExec.scala:93)
> at org.apache.spark.sql.execution.aggregate.SortAggregateExec$$anonfun$doExecute$1$$anonfun$3$$anonfun$4.apply(SortAggregateExec.scala:92)
> at org.apache.spark.sql.execution.aggregate.AggregationIterator.generateProcessRow(AggregationIterator.scala:178)
> at org.apache.spark.sql.execution.aggregate.AggregationIterator.<init>(AggregationIterator.scala:197)
> at org.apache.spark.sql.execution.aggregate.SortBasedAggregationIterator.<init>(SortBasedAggregationIterator.scala:29)
> at org.apache.spark.sql.execution.aggregate.SortAggregateExec$$anonfun$doExecute$1$$anonfun$3.apply(SortAggregateExec.scala:84)
> at org.apache.spark.sql.execution.aggregate.SortAggregateExec$$anonfun$doExecute$1$$anonfun$3.apply(SortAggregateExec.scala:75)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:780)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:780)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
> at org.apache.spark.scheduler.Task.run(Task.scala:85)
> at org.apache.spark.executor.Executor$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)
> {quote}



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