Description
I get a similar error when using complex types in Aggregator. Not sure if this is the same issue or something else.
Unable to find source-code formatter for language: agg.scala. Available languages are: actionscript, ada, applescript, bash, c, c#, c++, cpp, css, erlang, go, groovy, haskell, html, java, javascript, js, json, lua, none, nyan, objc, perl, php, python, r, rainbow, ruby, scala, sh, sql, swift, visualbasic, xml, yaml
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)
I get the following error
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)
Attachments
Issue Links
- is related to
-
SPARK-15704 TungstenAggregate crashes
-
- Resolved
-
- links to
