You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@systemml.apache.org by "Glenn Weidner (JIRA)" <ji...@apache.org> on 2016/09/13 00:23:20 UTC

[jira] [Commented] (SYSTEMML-911) GC overhead limit exceeded running LinearRegressionCG from MLContext

    [ https://issues.apache.org/jira/browse/SYSTEMML-911?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15485751#comment-15485751 ] 

Glenn Weidner commented on SYSTEMML-911:
----------------------------------------

Note the example runs with lower number of cols, e.g, 10.  The stack trace in descriptions was using 0.10 against Spark 1.6.1.

> GC overhead limit exceeded running LinearRegressionCG from MLContext
> --------------------------------------------------------------------
>
>                 Key: SYSTEMML-911
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-911
>             Project: SystemML
>          Issue Type: Bug
>          Components: APIs
>            Reporter: Glenn Weidner
>         Attachments: LinearRegrCG.0.10.scala
>
>
> Running attached scala from spark-shell using original MLContext against Spark 1.6 (or 2.0) encountered out-of-memory GC overhead limit exceeded:
> uncaught exception during compilation: java.lang.AssertionError
> org.apache.sysml.runtime.DMLRuntimeException: org.apache.sysml.runtime.DMLRuntimeException: ERROR: Runtime error in program block generated from statement block between lines 3 and 9 -- Error evaluating instruction: SPARK°rblk°X·MATRIX·DOUBLE°_mVar2·MATRIX·DOUBLE°1000°1000°true
> 	at org.apache.sysml.runtime.controlprogram.Program.execute(Program.java:152)
> 	at org.apache.sysml.api.MLContext.executeUsingSimplifiedCompilationChain(MLContext.java:1398)
> 	at org.apache.sysml.api.MLContext.compileAndExecuteScript(MLContext.java:1257)
> 	at org.apache.sysml.api.MLContext.executeScript(MLContext.java:1146)
> 	at org.apache.sysml.api.MLContext.executeScript(MLContext.java:1136)
> 	at org.apache.sysml.api.MLContext.executeScript(MLContext.java:1131)
> 	at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:32)
> 	at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:37)
> 	at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:39)
> 	at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:41)
> 	at $iwC$$iwC$$iwC$$iwC.<init>(<console>:43)
> 	at $iwC$$iwC$$iwC.<init>(<console>:45)
> 	at $iwC$$iwC.<init>(<console>:47)
> 	at $iwC.<init>(<console>:49)
> 	at <init>(<console>:51)
> 	at .<init>(<console>:55)
> 	at .<clinit>(<console>)
> 	at .<init>(<console>:7)
> 	at .<clinit>(<console>)
> 	at $print(<console>)
> 	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> 	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> 	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> 	at java.lang.reflect.Method.invoke(Method.java:498)
> 	at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
> 	at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1346)
> 	at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
> 	at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
> 	at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
> 	at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
> 	at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
> 	at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
> 	at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:657)
> 	at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:665)
> 	at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:670)
> 	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:997)
> 	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
> 	at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
> 	at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
> 	at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
> 	at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
> 	at org.apache.spark.repl.Main$.main(Main.scala:31)
> 	at org.apache.spark.repl.Main.main(Main.scala)
> 	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> 	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> 	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> 	at java.lang.reflect.Method.invoke(Method.java:498)
> 	at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
> 	at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
> 	at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
> 	at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
> 	at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
> Caused by: org.apache.sysml.runtime.DMLRuntimeException: ERROR: Runtime error in program block generated from statement block between lines 3 and 9 -- Error evaluating instruction: SPARK°rblk°X·MATRIX·DOUBLE°_mVar2·MATRIX·DOUBLE°1000°1000°true
> 	at org.apache.sysml.runtime.controlprogram.ProgramBlock.executeSingleInstruction(ProgramBlock.java:333)
> 	at org.apache.sysml.runtime.controlprogram.ProgramBlock.executeInstructions(ProgramBlock.java:222)
> 	at org.apache.sysml.runtime.controlprogram.ProgramBlock.execute(ProgramBlock.java:166)
> 	at org.apache.sysml.runtime.controlprogram.Program.execute(Program.java:145)
> 	... 51 more
> Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 6.0 failed 1 times, most recent failure: Lost task 0.0 in stage 6.0 (TID 10, localhost): java.lang.OutOfMemoryError: GC overhead limit exceeded
> 	at org.apache.sysml.runtime.instructions.spark.utils.RDDConverterUtilsExt$RowToBinaryBlockFunctionHelper.flushBlocksToList(RDDConverterUtilsExt.java:800)
> 	at org.apache.sysml.runtime.instructions.spark.utils.RDDConverterUtilsExt$RowToBinaryBlockFunctionHelper.convertToBinaryBlock(RDDConverterUtilsExt.java:736)
> 	at org.apache.sysml.runtime.instructions.spark.utils.RDDConverterUtilsExt$DataFrameToBinaryBlockFunction.call(RDDConverterUtilsExt.java:463)
> 	at org.apache.sysml.runtime.instructions.spark.utils.RDDConverterUtilsExt$DataFrameToBinaryBlockFunction.call(RDDConverterUtilsExt.java:448)
> 	at org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:192)
> 	at org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:192)
> 	at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710)
> 	at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
> 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
> 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> 	at org.apache.spark.scheduler.Task.run(Task.scala:89)
> 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> 	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> 	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> 	at java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
> 	at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
> 	at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
> 	at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
> 	at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> 	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> 	at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
> 	at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
> 	at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
> 	at scala.Option.foreach(Option.scala:236)
> 	at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
> 	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
> 	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
> 	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
> 	at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> 	at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
> 	at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
> 	at org.apache.spark.SparkContext.runJob(SparkContext.scala:1952)
> 	at org.apache.spark.rdd.RDD$$anonfun$aggregate$1.apply(RDD.scala:1114)
> 	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
> 	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
> 	at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
> 	at org.apache.spark.rdd.RDD.aggregate(RDD.scala:1107)
> 	at org.apache.spark.api.java.JavaRDDLike$class.aggregate(JavaRDDLike.scala:411)
> 	at org.apache.spark.api.java.AbstractJavaRDDLike.aggregate(JavaRDDLike.scala:46)
> 	at org.apache.sysml.runtime.instructions.spark.utils.SparkUtils.computeNNZFromBlocks(SparkUtils.java:458)
> 	at org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext.writeRDDtoHDFS(SparkExecutionContext.java:802)
> 	at org.apache.sysml.runtime.controlprogram.caching.MatrixObject.readBlobFromRDD(MatrixObject.java:612)
> 	at org.apache.sysml.runtime.controlprogram.caching.MatrixObject.readBlobFromRDD(MatrixObject.java:62)
> 	at org.apache.sysml.runtime.controlprogram.caching.CacheableData.acquireRead(CacheableData.java:440)
> 	at org.apache.sysml.hops.recompile.Recompiler.executeInMemoryReblock(Recompiler.java:2067)
> 	at org.apache.sysml.runtime.instructions.spark.ReblockSPInstruction.processInstruction(ReblockSPInstruction.java:100)
> 	at org.apache.sysml.runtime.controlprogram.ProgramBlock.executeSingleInstruction(ProgramBlock.java:303)
> 	... 54 more
> Caused by: java.lang.OutOfMemoryError: GC overhead limit exceeded
> 	at org.apache.sysml.runtime.instructions.spark.utils.RDDConverterUtilsExt$RowToBinaryBlockFunctionHelper.flushBlocksToList(RDDConverterUtilsExt.java:800)
> 	at org.apache.sysml.runtime.instructions.spark.utils.RDDConverterUtilsExt$RowToBinaryBlockFunctionHelper.convertToBinaryBlock(RDDConverterUtilsExt.java:736)
> 	at org.apache.sysml.runtime.instructions.spark.utils.RDDConverterUtilsExt$DataFrameToBinaryBlockFunction.call(RDDConverterUtilsExt.java:463)
> 	at org.apache.sysml.runtime.instructions.spark.utils.RDDConverterUtilsExt$DataFrameToBinaryBlockFunction.call(RDDConverterUtilsExt.java:448)
> 	at org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:192)
> 	at org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:192)
> 	at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710)
> 	at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$20.apply(RDD.scala:710)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
> 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
> 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> 	at org.apache.spark.scheduler.Task.run(Task.scala:89)
> 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> 	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)



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)