Skip to content
This repository was archived by the owner on Jul 16, 2020. It is now read-only.
This repository was archived by the owner on Jul 16, 2020. It is now read-only.

Training: ExceptionFailure #85

Description

@liuandy-good

2020-05-30 19:33:31 WARN TaskSetManager:66 - Lost task 0.0 in stage 0.0 (TID 0, 192.168.1.200, executor 0): java.lang.UnsatisfiedLinkError: ai.rapids.cudf.Table.gdfReadCSV([Ljava/lang/String;[Ljava/lang/String;[Ljava/lang/String;Ljava/lang/String;JJIBBB[Ljava/lang/String;[Ljava/lang/String;[Ljava/lang/String;)[J
at ai.rapids.cudf.Table.gdfReadCSV(Native Method)
at ai.rapids.cudf.Table.readCSV(Table.java:314)
at ml.dmlc.xgboost4j.scala.spark.rapids.CSVPartitionReader.readToTable(GpuCSVScan.scala:214)
at ml.dmlc.xgboost4j.scala.spark.rapids.CSVPartitionReader.readBatch(GpuCSVScan.scala:194)
at ml.dmlc.xgboost4j.scala.spark.rapids.CSVPartitionReader.next(GpuCSVScan.scala:230)
at ml.dmlc.xgboost4j.scala.spark.rapids.PartitionedFileReader.next(FilePartitionReaderFactory.scala:41)
at ml.dmlc.xgboost4j.scala.spark.rapids.FilePartitionReader.next(FilePartitionReader.scala:69)
at ml.dmlc.xgboost4j.scala.spark.rapids.GpuDatasetRDD$$anon$1.hasNext(GpuDatasetRDD.scala:51)
at ml.dmlc.xgboost4j.scala.spark.Watches$.ml$dmlc$xgboost4j$scala$spark$Watches$$buildDMatrixIncrementally(XGBoost.scala:966)
at ml.dmlc.xgboost4j.scala.spark.Watches$$anonfun$42.apply(XGBoost.scala:1026)
at ml.dmlc.xgboost4j.scala.spark.Watches$$anonfun$42.apply(XGBoost.scala:1026)
at ml.dmlc.xgboost4j.scala.spark.rapids.GpuDataset$.time(GpuDataset.scala:508)
at ml.dmlc.xgboost4j.scala.spark.Watches$.buildWatches(XGBoost.scala:1025)
at ml.dmlc.xgboost4j.scala.spark.XGBoost$$anonfun$ml$dmlc$xgboost4j$scala$spark$XGBoost$$trainForGpuDataset$1.apply(XGBoost.scala:628)
at ml.dmlc.xgboost4j.scala.spark.XGBoost$$anonfun$ml$dmlc$xgboost4j$scala$spark$XGBoost$$trainForGpuDataset$1.apply(XGBoost.scala:625)
at ml.dmlc.xgboost4j.scala.spark.rapids.GpuDataset$$anonfun$ml$dmlc$xgboost4j$scala$spark$rapids$GpuDataset$$getBatchMapper$1.apply(GpuDataset.scala:516)
at ml.dmlc.xgboost4j.scala.spark.rapids.GpuDataset$$anonfun$ml$dmlc$xgboost4j$scala$spark$rapids$GpuDataset$$getBatchMapper$1.apply(GpuDataset.scala:515)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:801)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:801)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD$$anonfun$7.apply(RDD.scala:337)
at org.apache.spark.rdd.RDD$$anonfun$7.apply(RDD.scala:335)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1094)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1085)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:1020)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1085)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:811)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:335)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:286)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)

2020-05-30 19:33:31 INFO TaskSetManager:54 - Starting task 0.1 in stage 0.0 (TID 1, 192.168.1.200, executor 0, partition 0, ANY, 8496 bytes)
2020-05-30 19:33:31 ERROR XGBoostTaskFailedListener:178 - Training Task Failed during XGBoost Training: ExceptionFailure(java.lang.UnsatisfiedLinkError,ai.rapids.cudf.Table.gdfReadCSV([Ljava/lang/String;[Ljava/lang/String;[Ljava/lang/String;Ljava/lang/String;JJIBBB[Ljava/lang/String;[Ljava/lang/String;[Ljava/lang/String;)[J,[Ljava.lang.StackTraceElement;@6c432b9b,java.lang.UnsatisfiedLinkError: ai.rapids.cudf.Table.gdfReadCSV([Ljava/lang/String;[Ljava/lang/String;[Ljava/lang/String;Ljava/lang/String;JJIBBB[Ljava/lang/String;[Ljava/lang/String;[Ljava/lang/String;)[J
at ai.rapids.cudf.Table.gdfReadCSV(Native Method)
at ai.rapids.cudf.Table.readCSV(Table.java:314)
at ml.dmlc.xgboost4j.scala.spark.rapids.CSVPartitionReader.readToTable(GpuCSVScan.scala:214)
at ml.dmlc.xgboost4j.scala.spark.rapids.CSVPartitionReader.readBatch(GpuCSVScan.scala:194)
at ml.dmlc.xgboost4j.scala.spark.rapids.CSVPartitionReader.next(GpuCSVScan.scala:230)
at ml.dmlc.xgboost4j.scala.spark.rapids.PartitionedFileReader.next(FilePartitionReaderFactory.scala:41)
at ml.dmlc.xgboost4j.scala.spark.rapids.FilePartitionReader.next(FilePartitionReader.scala:69)
at ml.dmlc.xgboost4j.scala.spark.rapids.GpuDatasetRDD$$anon$1.hasNext(GpuDatasetRDD.scala:51)
at ml.dmlc.xgboost4j.scala.spark.Watches$.ml$dmlc$xgboost4j$scala$spark$Watches$$buildDMatrixIncrementally(XGBoost.scala:966)
at ml.dmlc.xgboost4j.scala.spark.Watches$$anonfun$42.apply(XGBoost.scala:1026)
at ml.dmlc.xgboost4j.scala.spark.Watches$$anonfun$42.apply(XGBoost.scala:1026)
at ml.dmlc.xgboost4j.scala.spark.rapids.GpuDataset$.time(GpuDataset.scala:508)
at ml.dmlc.xgboost4j.scala.spark.Watches$.buildWatches(XGBoost.scala:1025)
at ml.dmlc.xgboost4j.scala.spark.XGBoost$$anonfun$ml$dmlc$xgboost4j$scala$spark$XGBoost$$trainForGpuDataset$1.apply(XGBoost.scala:628)
at ml.dmlc.xgboost4j.scala.spark.XGBoost$$anonfun$ml$dmlc$xgboost4j$scala$spark$XGBoost$$trainForGpuDataset$1.apply(XGBoost.scala:625)
at ml.dmlc.xgboost4j.scala.spark.rapids.GpuDataset$$anonfun$ml$dmlc$xgboost4j$scala$spark$rapids$GpuDataset$$getBatchMapper$1.apply(GpuDataset.scala:516)
at ml.dmlc.xgboost4j.scala.spark.rapids.GpuDataset$$anonfun$ml$dmlc$xgboost4j$scala$spark$rapids$GpuDataset$$getBatchMapper$1.apply(GpuDataset.scala:515)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:801)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:801)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD$$anonfun$7.apply(RDD.scala:337)
at org.apache.spark.rdd.RDD$$anonfun$7.apply(RDD.scala:335)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1094)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1085)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:1020)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1085)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:811)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:335)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:286)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
,Some(org.apache.spark.ThrowableSerializationWrapper@6284c863),Vector(AccumulableInfo(3,None,Some(5960),None,false,true,None), AccumulableInfo(5,None,Some(0),None,false,true,None), AccumulableInfo(6,None,Some(57),None,false,true,None)),Vector(LongAccumulator(id: 3, name: Some(internal.metrics.executorRunTime), value: 5960), LongAccumulator(id: 5, name: Some(internal.metrics.resultSize), value: 0), LongAccumulator(id: 6, name: Some(internal.metrics.jvmGCTime), value: 57))), stopping SparkContext
2020-05-30 19:33:31 INFO AbstractConnector:318 - Stopped Spark@541733dc{HTTP/1.1,[http/1.1]}{0.0.0.0:4040}
2020-05-30 19:33:31 INFO SparkUI:54 - Stopped Spark web UI at http://ecs-gpu-dl:4040
2020-05-30 19:33:31 INFO DAGScheduler:54 - Job 0 failed: foreachPartition at XGBoost.scala:686, took 7.389169 s
2020-05-30 19:33:31 INFO DAGScheduler:54 - ResultStage 0 (foreachPartition at XGBoost.scala:686) failed in 7.356 s due to Stage cancelled because SparkContext was shut down
2020-05-30 19:33:31 ERROR RabitTracker:91 - Uncaught exception thrown by worker:
org.apache.spark.SparkException: Job 0 cancelled because SparkContext was shut down
at org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:837)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:835)
at scala.collection.mutable.HashSet.foreach(HashSet.scala:78)
at org.apache.spark.scheduler.DAGScheduler.cleanUpAfterSchedulerStop(DAGScheduler.scala:835)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onStop(DAGScheduler.scala:1900)
at org.apache.spark.util.EventLoop.stop(EventLoop.scala:83)
at org.apache.spark.scheduler.DAGScheduler.stop(DAGScheduler.scala:1813)
at org.apache.spark.SparkContext$$anonfun$stop$8.apply$mcV$sp(SparkContext.scala:1931)
at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1361)
at org.apache.spark.SparkContext.stop(SparkContext.scala:1930)
at org.apache.spark.TaskFailedListener$$anon$1$$anonfun$run$1.apply$mcV$sp(SparkParallelismTracker.scala:197)
at org.apache.spark.TaskFailedListener$$anon$1$$anonfun$run$1.apply(SparkParallelismTracker.scala:197)
at org.apache.spark.TaskFailedListener$$anon$1$$anonfun$run$1.apply(SparkParallelismTracker.scala:197)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at org.apache.spark.TaskFailedListener$$anon$1.run(SparkParallelismTracker.scala:196)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:935)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:933)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:933)
at ml.dmlc.xgboost4j.scala.spark.XGBoost$$anonfun$trainDistributedForGpuDataset$1$$anon$1.run(XGBoost.scala:686)
2020-05-30 19:33:31 INFO StandaloneSchedulerBackend:54 - Shutting down all executors
2020-05-30 19:33:31 INFO CoarseGrainedSchedu

Activity

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Projects

    No projects

      Milestone

      No milestone

      Relationships

      None yet

      Development

      No branches or pull requests

      Issue actions