[ https://issues.apache.org/jira/browse/SYSTEMML-1283?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15874106#comment-15874106 ]
Matthias Boehm edited comment on SYSTEMML-1283 at 2/20/17 6:36 AM: ------------------------------------------------------------------- It is not related - the issue is that we enter the branch of converting the input to a frame instead of matrix (see FrameRDDConverterUtils). Furthermore, it's just the GC limit - probably due to converting doubles - to double objects - to strings (default, given the unspecified frame schema). Anyway, if it would not crash with OOM it would fail on the first operation that is not supported over frames - this needs to be fixed at API level. was (Author: mboehm7): it is not related - the issue is that we enter the branch of converting the input to a frame instead of matrix (see FrameRDDConverterUtils). > Out of memory error > ------------------- > > Key: SYSTEMML-1283 > URL: https://issues.apache.org/jira/browse/SYSTEMML-1283 > Project: SystemML > Issue Type: Bug > Reporter: Brendan Dwyer > > Possibly related to [SYSTEMML-1281] > When a matrix X containing ~13,000 rows and ~30 unique values are passed into > the following DML scripts it errors out on my laptop but passes in my 5 node > cluster. > {code} > # # encode dml function for one hot encoding > encode_onehot = function(matrix[double] X) return(matrix[double] Y) { > N = nrow(X) > Y = table(seq(1, N, 1), X) > } > # a dummy read, which allows sysML to attach variables > X = read("") > > col_idx = $onehot_index > > nc = ncol(X) > if (col_idx < 1 | col_idx > nc) { > stop("one hot index out of range") > } > Y = matrix(0, rows=1, cols=1) > oneHot = encode_onehot(X[,col_idx:col_idx]) > if (col_idx == 1) { > if (col_idx < nc) { > X_tmp = X[, col_idx+1:nc] > Y = append(oneHot, X_tmp) > } else { > Y = oneHot > } > } else if (1 < col_idx & col_idx < nc) { > Y = append(append(X[,1:col_idx-1], oneHot), X[, col_idx+1:nc]) > } else { # col_idx == nc > Y = append(X[,1:col_idx-1], oneHot) > } > # a dummy write, which allows sysML to attach varibles > write(Y, "") > {code} > Error: > {code} > 17/02/17 16:57:35 ERROR Executor: Exception in task 0.0 in stage 63.0 (TID > 1739) > java.lang.OutOfMemoryError: GC overhead limit exceeded > at java.lang.Double.valueOf(Double.java:519) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificSafeProjection.apply_853$(Unknown > Source) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificSafeProjection.apply(Unknown > Source) > at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) > at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) > at org.apache.spark.util.Utils$$anon$4.next(Utils.scala:1778) > at org.apache.spark.util.Utils$$anon$4.next(Utils.scala:1772) > at > scala.collection.convert.Wrappers$IteratorWrapper.next(Wrappers.scala:31) > at > org.apache.sysml.runtime.instructions.spark.utils.FrameRDDConverterUtils$DataFrameToBinaryBlockFunction.call(FrameRDDConverterUtils.java:748) > at > org.apache.sysml.runtime.instructions.spark.utils.FrameRDDConverterUtils$DataFrameToBinaryBlockFunction.call(FrameRDDConverterUtils.java:715) > at > org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:186) > at > org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:186) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) > at > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96) > at > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) > at org.apache.spark.scheduler.Task.run(Task.scala:99) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > at java.lang.Thread.run(Thread.java:745) > 17/02/17 16:57:35 ERROR TaskSetManager: Task 0 in stage 63.0 failed 1 times; > aborting job > 17/02/17 16:57:36 ERROR SparkUncaughtExceptionHandler: Uncaught exception in > thread Thread[Executor task launch worker-20,5,main] > java.lang.OutOfMemoryError: GC overhead limit exceeded > at java.lang.Double.valueOf(Double.java:519) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificSafeProjection.apply_853$(Unknown > Source) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificSafeProjection.apply(Unknown > Source) > at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) > at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) > at org.apache.spark.util.Utils$$anon$4.next(Utils.scala:1778) > at org.apache.spark.util.Utils$$anon$4.next(Utils.scala:1772) > at > scala.collection.convert.Wrappers$IteratorWrapper.next(Wrappers.scala:31) > at > org.apache.sysml.runtime.instructions.spark.utils.FrameRDDConverterUtils$DataFrameToBinaryBlockFunction.call(FrameRDDConverterUtils.java:748) > at > org.apache.sysml.runtime.instructions.spark.utils.FrameRDDConverterUtils$DataFrameToBinaryBlockFunction.call(FrameRDDConverterUtils.java:715) > at > org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:186) > at > org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:186) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) > at > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96) > at > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) > at org.apache.spark.scheduler.Task.run(Task.scala:99) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282) > 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) > 17/02/17 16:57:36 ERROR RBackendHandler: executeScript on 117277 failed > java.lang.reflect.InvocationTargetException > 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.api.r.RBackendHandler.handleMethodCall(RBackendHandler.scala:167) > at > org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:108) > at > org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:40) > at > io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) > at > io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:266) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) > at > io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:102) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) > at > io.netty.handler.codec.ByteToMessageDecoder.fireChannelRead(ByteToMessageDecoder.java:293) > at > io.netty.handler.codec.ByteToMessageDecoder.channelRead(ByteToMessageDecoder.java:267) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) > at > io.netty.channel.DefaultChannelPipeline$HeadContext.channelRead(DefaultChannelPipeline.java:1294) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:911) > at > io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131) > at > io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:652) > at > io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:575) > at > io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:489) > at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:451) > at > io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:140) > at > io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144) > at java.lang.Thread.run(Thread.java:745) > Caused by: org.apache.sysml.runtime.DMLRuntimeException: > org.apache.sysml.runtime.DMLRuntimeException: ERROR: Runtime error in program > block generated from statement block between lines 16 and 17 -- Error > evaluating instruction: SPARK°rangeReIndex°X- MATRIX- DOUBLE°1- SCALAR- INT- > true°_Var178- SCALAR- INT- false°9- SCALAR- INT- true°9- SCALAR- INT- > true°_mVar179- MATRIX- DOUBLE°MULTI_BLOCK > at > org.apache.sysml.runtime.controlprogram.Program.execute(Program.java:130) > at > org.apache.sysml.api.MLContext.executeUsingSimplifiedCompilationChain(MLContext.java:1655) > at > org.apache.sysml.api.MLContext.compileAndExecuteScript(MLContext.java:1520) > at org.apache.sysml.api.MLContext.executeScript(MLContext.java:1469) > at org.apache.sysml.api.MLContext.executeScript(MLContext.java:1455) > at org.apache.sysml.api.MLContext.executeScript(MLContext.java:1413) > at org.apache.sysml.api.MLContext.executeScript(MLContext.java:1419) > ... 36 more > Caused by: org.apache.sysml.runtime.DMLRuntimeException: ERROR: Runtime error > in program block generated from statement block between lines 16 and 17 -- > Error evaluating instruction: SPARK°rangeReIndex°X- MATRIX- DOUBLE°1- SCALAR- > INT- true°_Var178- SCALAR- INT- false°9- SCALAR- INT- true°9- SCALAR- INT- > true°_mVar179- MATRIX- DOUBLE°MULTI_BLOCK > at > org.apache.sysml.runtime.controlprogram.ProgramBlock.executeSingleInstruction(ProgramBlock.java:320) > at > org.apache.sysml.runtime.controlprogram.ProgramBlock.executeInstructions(ProgramBlock.java:221) > at > org.apache.sysml.runtime.controlprogram.ProgramBlock.execute(ProgramBlock.java:168) > at > org.apache.sysml.runtime.controlprogram.Program.execute(Program.java:123) > ... 42 more > Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: > Task 0 in stage 63.0 failed 1 times, most recent failure: Lost task 0.0 in > stage 63.0 (TID 1739, localhost, executor driver): > java.lang.OutOfMemoryError: GC overhead limit exceeded > at java.lang.Double.valueOf(Double.java:519) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificSafeProjection.apply_853$(Unknown > Source) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificSafeProjection.apply(Unknown > Source) > at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) > at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) > at org.apache.spark.util.Utils$$anon$4.next(Utils.scala:1778) > at org.apache.spark.util.Utils$$anon$4.next(Utils.scala:1772) > at > scala.collection.convert.Wrappers$IteratorWrapper.next(Wrappers.scala:31) > at > org.apache.sysml.runtime.instructions.spark.utils.FrameRDDConverterUtils$DataFrameToBinaryBlockFunction.call(FrameRDDConverterUtils.java:748) > at > org.apache.sysml.runtime.instructions.spark.utils.FrameRDDConverterUtils$DataFrameToBinaryBlockFunction.call(FrameRDDConverterUtils.java:715) > at > org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:186) > at > org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:186) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) > at > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96) > at > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) > at org.apache.spark.scheduler.Task.run(Task.scala:99) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282) > 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$$failJobAndIndependentStages(DAGScheduler.scala:1435) > at > org.apache.spark.scheduler.DAGScheduler$$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:802) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802) > at scala.Option.foreach(Option.scala:257) > at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > at > org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1958) > at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:935) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) > at org.apache.spark.rdd.RDD.withScope(RDD.scala:362) > at org.apache.spark.rdd.RDD.collect(RDD.scala:934) > at > org.apache.spark.api.java.JavaRDDLike$class.collect(JavaRDDLike.scala:361) > at > org.apache.spark.api.java.AbstractJavaRDDLike.collect(JavaRDDLike.scala:45) > at > org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext.toMatrixBlock(SparkExecutionContext.java:783) > at > org.apache.sysml.runtime.instructions.spark.MatrixIndexingSPInstruction.processInstruction(MatrixIndexingSPInstruction.java:151) > at > org.apache.sysml.runtime.controlprogram.ProgramBlock.executeSingleInstruction(ProgramBlock.java:290) > ... 45 more > Caused by: java.lang.OutOfMemoryError: GC overhead limit exceeded > at java.lang.Double.valueOf(Double.java:519) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificSafeProjection.apply_853$(Unknown > Source) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificSafeProjection.apply(Unknown > Source) > at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) > at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) > at org.apache.spark.util.Utils$$anon$4.next(Utils.scala:1778) > at org.apache.spark.util.Utils$$anon$4.next(Utils.scala:1772) > at > scala.collection.convert.Wrappers$IteratorWrapper.next(Wrappers.scala:31) > at > org.apache.sysml.runtime.instructions.spark.utils.FrameRDDConverterUtils$DataFrameToBinaryBlockFunction.call(FrameRDDConverterUtils.java:748) > at > org.apache.sysml.runtime.instructions.spark.utils.FrameRDDConverterUtils$DataFrameToBinaryBlockFunction.call(FrameRDDConverterUtils.java:715) > at > org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:186) > at > org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:186) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) > at > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96) > at > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) > at org.apache.spark.scheduler.Task.run(Task.scala:99) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > ... 1 more > Show Traceback > > Rerun with Debug > Error: HydraR[sysml.execute]: DML returned error: Error in > handleErrors(returnStatus, conn): > org.apache.sysml.runtime.DMLRuntimeException: > org.apache.sysml.runtime.DMLRuntimeException: ERROR: Runtime error in program > block generated from statement block between lines 16 and 17 -- Error > evaluating instruction: SPARK°rangeReIndex°X- MATRIX- DOUBLE°1- SCALAR- INT- > true°_Var178- SCALAR- INT- false°9- SCALAR- INT- true°9- SCALAR- INT- > true°_mVar179- MATRIX- DOUBLE°MULTI_BLOCK > at > org.apache.sysml.runtime.controlprogram.Program.execute(Program.java:130) > at > org.apache.sysml.api.MLContext.executeUsingSimplifiedCompilationChain(MLContext.java:1655) > at > org.apache.sysml.api.MLContext.compileAndExecuteScript(MLContext.java:1520) > at org.apache.sysml.api.MLContext.executeScript(MLContext.java:1469) > at org.apache.sysml.api.MLContext.executeScript(MLContext.java:1455) > at org.apache.sysml.api.MLContext.executeScript(MLContext.java:1413) > at org.apache.sysml.api.MLContext.executeScript(MLContext.java:1419) > 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.api.r.RBackendHandler.handleMethodCall(RBackendHandler.scala:167) > at > org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:108) > at > org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:40) > at > io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) > at > io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:266) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) > at > io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:102) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) > at > io.netty.handler.codec.ByteToMessageDecoder.fireChannelRead(ByteToMessageDecoder.java:293) > at > io.netty.handler.codec.ByteToMessageDecoder.channelRead(ByteToMessageDecoder.java:267) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) > at > io.netty.channel.DefaultChannelPipeline$HeadContext.channelRead(DefaultChannelPipeline.java:1294) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) > at > io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:911) > at > io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131) > at > io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:652) > at > io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:575) > at > io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:489) > at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:451) > at > io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:140) > at > io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144) > at java.lang.Thread.run(Thread.java:745) > Caused by: org.apache.sysml.runtime.DMLRuntimeException: ERROR: Runtime error > in program block generated from statement block between lines 16 and 17 -- > Error evaluating instruction: SPARK°rangeReIndex°X- MATRIX- DOUBLE°1- SCALAR- > INT- true°_Var178- SCALAR- INT- false°9- SCALAR- INT- true°9- SCALAR- INT- > true°_mVar179- MATRIX- DOUBLE°MULTI_BLOCK > at > org.apache.sysml.runtime.controlprogram.ProgramBlock.executeSingleInstruction(ProgramBlock.java:320) > at > org.apache.sysml.runtime.controlprogram.ProgramBlock.executeInstructions(ProgramBlock.java:221) > at > org.apache.sysml.runtime.controlprogram.ProgramBlock.execute(ProgramBlock.java:168) > at > org.apache.sysml.runtime.controlprogram.Program.execute(Program.java:123) > ... 42 more > Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: > Task 0 in stage 63.0 failed 1 times, most recent failure: Lost task 0.0 in > stage 63.0 (TID 1739, localhost, executor driver): > java.lang.OutOfMemoryError: GC overhead limit exceeded > at java.lang.Double.valueOf(Double.java:519) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificSafeProjection.apply_853$(Unknown > Source) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificSafeProjection.apply(Unknown > Source) > at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) > at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) > at org.apache.spark.util.Utils$$anon$4.next(Utils.scala:1778) > at org.apache.spark.util.Utils$$anon$4.next(Utils.scala:1772) > at > scala.collection.convert.Wrappers$IteratorWrapper.next(Wrappers.scala:31) > at > org.apache.sysml.runtime.instructions.spark.utils.FrameRDDConverterUtils$DataFrameToBinaryBlockFunction.call(FrameRDDConverterUtils.java:748) > at > org.apache.sysml.runtime.instructions.spark.utils.FrameRDDConverterUtils$DataFrameToBinaryBlockFunction.call(FrameRDDConverterUtils.java:715) > at > org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:186) > at > org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$7$1.apply(JavaRDDLike.scala:186) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796) > at > org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:796) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) > at > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96) > at > org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) > at org.apache.spark.scheduler.Task.run(Task.scala:99) > at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > at java.lang.Thread.run(Thread.java:745) > Driver stacktrace: > at > org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala: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.DAGSchedul > {code} -- This message was sent by Atlassian JIRA (v6.3.15#6346)