[
https://issues.apache.org/jira/browse/SPARK-15704?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15341478#comment-15341478
]
Deenar Toraskar commented on SPARK-15704:
-----------------------------------------
Hi guys
I get a similar error when using complex types in Aggregator. Not sure if this
is the same issue or something else.
{code:title=Agg.scala|borderStyle=solid}
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$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
{quote}
> TungstenAggregate crashes
> --------------------------
>
> Key: SPARK-15704
> URL: https://issues.apache.org/jira/browse/SPARK-15704
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.0
> Reporter: Hiroshi Inoue
> Assignee: Hiroshi Inoue
> Fix For: 2.0.0
>
>
> When I run DatasetBenchmark, the JVM crashes while executing "Dataset complex
> Aggregator" test case due to IndexOutOfBoundsException.
> The error happens in TungstenAggregate; the mappings between bufferSerializer
> and bufferDeserializer are broken due to unresolved attribute.
> {quote}
> 16/06/02 01:41:05 ERROR Executor: Exception in task 0.0 in stage 67.0 (TID
> 232)
> java.lang.IndexOutOfBoundsException: -1
> at
> scala.collection.LinearSeqOptimized$class.apply(LinearSeqOptimized.scala:65)
> at scala.collection.immutable.List.apply(List.scala:84)
> at
> org.apache.spark.sql.catalyst.expressions.aggregate.DeclarativeAggregate$RichAttribute.right(interfaces.scala:389)
> at
> org.apache.spark.sql.execution.aggregate.TypedAggregateExpression$$anonfun$3.applyOrElse(TypedAggregateExpression.scala:110)
> at
> org.apache.spark.sql.execution.aggregate.TypedAggregateExpression$$anonfun$3.applyOrElse(TypedAggregateExpression.scala:109)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:265)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:265)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:68)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:264)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:270)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:270)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:307)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
> at scala.collection.Iterator$class.foreach(Iterator.scala:893)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> at
> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
> at scala.collection.AbstractIterator.to(Iterator.scala:1336)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1336)
> at
> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1336)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:356)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:270)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:270)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:270)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5$$anonfun$apply$11.apply(TreeNode.scala:336)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> at scala.collection.immutable.List.map(List.scala:285)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:334)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
> at scala.collection.Iterator$class.foreach(Iterator.scala:893)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
> at
> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
> at scala.collection.AbstractIterator.to(Iterator.scala:1336)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1336)
> at
> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1336)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:356)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:270)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:254)
> at
> org.apache.spark.sql.execution.aggregate.TypedAggregateExpression.mergeExpressions$lzycompute(TypedAggregateExpression.scala:109)
> at
> org.apache.spark.sql.execution.aggregate.TypedAggregateExpression.mergeExpressions(TypedAggregateExpression.scala:105)
> at
> org.apache.spark.sql.execution.aggregate.AggregationIterator$$anonfun$7.apply(AggregationIterator.scala:162)
> at
> org.apache.spark.sql.execution.aggregate.AggregationIterator$$anonfun$7.apply(AggregationIterator.scala:158)
> at
> scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
> at
> scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at
> scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
> at scala.collection.AbstractTraversable.flatMap(Traversable.scala:104)
> at
> org.apache.spark.sql.execution.aggregate.AggregationIterator.generateProcessRow(AggregationIterator.scala:158)
> at
> org.apache.spark.sql.execution.aggregate.AggregationIterator.<init>(AggregationIterator.scala:197)
> at
> org.apache.spark.sql.execution.aggregate.SortBasedAggregationIterator.<init>(SortBasedAggregationIterator.scala:39)
> at
> org.apache.spark.sql.execution.aggregate.SortBasedAggregateExec$$anonfun$doExecute$1$$anonfun$3.apply(SortBasedAggregateExec.scala:80)
> at
> org.apache.spark.sql.execution.aggregate.SortBasedAggregateExec$$anonfun$doExecute$1$$anonfun$3.apply(SortBasedAggregateExec.scala:71)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:775)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:775)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:318)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:282)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
> at org.apache.spark.scheduler.Task.run(Task.scala:85)
> at org.apache.spark.executor.Executor$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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