[ https://issues.apache.org/jira/browse/SPARK-16100?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15341847#comment-15341847 ]
Deenar Toraskar commented on SPARK-16100: ----------------------------------------- similar issue > 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} -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org