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From Reynold Xin <r...@databricks.com>
Subject Re: tpcds q1 - java.lang.NegativeArraySizeException
Date Mon, 13 Jun 2016 19:25:33 GMT
Did you try this on master?


On Mon, Jun 13, 2016 at 11:26 AM, Ovidiu-Cristian MARCU <
ovidiu-cristian.marcu@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)
>
>

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