Did you try this on master?
On Mon, Jun 13, 2016 at 11:26 AM, Ovidiu-Cristian MARCU < ovidiu-cristian.ma...@inria.fr> wrote: > Hi, > > Running the first query of tpcds on a standalone setup (4 nodes, tpcds2 > generated for scale 10 and transformed in parquet under hdfs) it results > in one exception [1]. > Close to this problem I found this issue > https://issues.apache.org/jira/browse/SPARK-12089 but it seems to be > solved. > > Running the second query is successful. > > OpenJDK 64-Bit Server VM 1.7.0_101-b00 on Linux 3.2.0-4-amd64 > Intel(R) Xeon(R) CPU E5-2630 v3 @ 2.40GHz > TPCDS Snappy: Best/Avg Time(ms) Rate(M/s) > Per Row(ns) Relative > > ------------------------------------------------------------------------------------------------ > q2 4512 / 8142 0.0 > 61769.4 1.0X > > Best, > Ovidiu > > [1] > WARN TaskSetManager: Lost task 17.0 in stage 80.0 (TID 4469, > 172.16.96.70): java.lang.NegativeArraySizeException > at > org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder.grow(BufferHolder.java:61) > at > org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter.write(UnsafeRowWriter.java:214) > 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$$anonfun$doExecute$3$$anon$2.hasNext(WholeStageCodegenExec.scala:386) > at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) > at > scala.collection.convert.Wrappers$IteratorWrapper.hasNext(Wrappers.scala:30) > at org.spark_project.guava.collect.Ordering.leastOf(Ordering.java:628) > at org.apache.spark.util.collection.Utils$.takeOrdered(Utils.scala:37) > at > org.apache.spark.rdd.RDD$$anonfun$takeOrdered$1$$anonfun$30.apply(RDD.scala:1365) > at > org.apache.spark.rdd.RDD$$anonfun$takeOrdered$1$$anonfun$30.apply(RDD.scala:1362) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:757) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:757) > at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:318) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:282) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) > at org.apache.spark.scheduler.Task.run(Task.scala:85) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) > at java.lang.Thread.run(Thread.java:745) > > ERROR TaskSetManager: Task 17 in stage 80.0 failed 4 times; aborting job > > Driver stacktrace: > at org.apache.spark.scheduler.DAGScheduler.org > $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422) > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:806) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:806) > at scala.Option.foreach(Option.scala:257) > at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:806) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1644) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1603) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1592) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1872) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1935) > at org.apache.spark.rdd.RDD$$anonfun$reduce$1.apply(RDD.scala:974) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) > at org.apache.spark.rdd.RDD.withScope(RDD.scala:357) > at org.apache.spark.rdd.RDD.reduce(RDD.scala:956) > at org.apache.spark.rdd.RDD$$anonfun$takeOrdered$1.apply(RDD.scala:1371) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) > at org.apache.spark.rdd.RDD.withScope(RDD.scala:357) > at org.apache.spark.rdd.RDD.takeOrdered(RDD.scala:1358) > at > org.apache.spark.sql.execution.TakeOrderedAndProjectExec.executeCollect(limit.scala:128) > at > org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2163) > at > org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57) > at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2489) > at org.apache.spark.sql.Dataset.org > $apache$spark$sql$Dataset$$execute$1(Dataset.scala:2162) > at > org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$collect$1.apply(Dataset.scala:2167) > at > org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$collect$1.apply(Dataset.scala:2167) > at org.apache.spark.sql.Dataset.withCallback(Dataset.scala:2502) > at org.apache.spark.sql.Dataset.org > $apache$spark$sql$Dataset$$collect(Dataset.scala:2167) > at org.apache.spark.sql.Dataset.collect(Dataset.scala:2143) > at > org.apache.spark.sql.execution.benchmark.TPCDSQueryBenchmark$$anonfun$tpcdsAll$2$$anonfun$apply$2.apply$mcVI$sp(TPCDSQueryBenchmark.scala:88) > at > org.apache.spark.util.Benchmark$$anonfun$addCase$1.apply(Benchmark.scala:75) > at > org.apache.spark.util.Benchmark$$anonfun$addCase$1.apply(Benchmark.scala:73) > at org.apache.spark.util.Benchmark.measure(Benchmark.scala:135) > at org.apache.spark.util.Benchmark$$anonfun$1.apply(Benchmark.scala:104) > at org.apache.spark.util.Benchmark$$anonfun$1.apply(Benchmark.scala:102) > at > scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) > at > scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) > at scala.collection.TraversableLike$class.map(TraversableLike.scala:234) > at scala.collection.AbstractTraversable.map(Traversable.scala:104) > at org.apache.spark.util.Benchmark.run(Benchmark.scala:102) > at > org.apache.spark.sql.execution.benchmark.TPCDSQueryBenchmark$$anonfun$tpcdsAll$2.apply(TPCDSQueryBenchmark.scala:90) > at > org.apache.spark.sql.execution.benchmark.TPCDSQueryBenchmark$$anonfun$tpcdsAll$2.apply(TPCDSQueryBenchmark.scala:57) > at > scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33) > at scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:35) > at > org.apache.spark.sql.execution.benchmark.TPCDSQueryBenchmark$.tpcdsAll(TPCDSQueryBenchmark.scala:57) > at > org.apache.spark.sql.execution.benchmark.TPCDSQueryBenchmark$.main(TPCDSQueryBenchmark.scala:135) > at > org.apache.spark.sql.execution.benchmark.TPCDSQueryBenchmark.main(TPCDSQueryBenchmark.scala) > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) > at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) > at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) > at java.lang.reflect.Method.invoke(Method.java:606) > at > org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:729) > at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:185) > at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:210) > at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:124) > at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) > Caused by: java.lang.NegativeArraySizeException > at > org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder.grow(BufferHolder.java:61) > at > org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter.write(UnsafeRowWriter.java:214) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown > Source) > at > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > at > org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$doExecute$3$$anon$2.hasNext(WholeStageCodegenExec.scala:386) > at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408) > at > scala.collection.convert.Wrappers$IteratorWrapper.hasNext(Wrappers.scala:30) > at org.spark_project.guava.collect.Ordering.leastOf(Ordering.java:664) > at org.apache.spark.util.collection.Utils$.takeOrdered(Utils.scala:37) > at > org.apache.spark.rdd.RDD$$anonfun$takeOrdered$1$$anonfun$30.apply(RDD.scala:1365) > at > org.apache.spark.rdd.RDD$$anonfun$takeOrdered$1$$anonfun$30.apply(RDD.scala:1362) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:757) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:757) > at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:318) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:282) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) > at org.apache.spark.scheduler.Task.run(Task.scala:85) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) > at java.lang.Thread.run(Thread.java:745) > >
