[ https://issues.apache.org/jira/browse/SYSTEMML-2013?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Matthias Boehm resolved SYSTEMML-2013. -------------------------------------- Resolution: Fixed Assignee: Matthias Boehm Fix Version/s: SystemML 1.0 > Perftest genStratStatsData failed for 80GB > ------------------------------------------ > > Key: SYSTEMML-2013 > URL: https://issues.apache.org/jira/browse/SYSTEMML-2013 > Project: SystemML > Issue Type: Bug > Reporter: Matthias Boehm > Assignee: Matthias Boehm > Fix For: SystemML 1.0 > > > {code} > Caused by: org.apache.sysml.runtime.DMLRuntimeException: ERROR: Runtime error > in program block generated from statement block between lines 107 and 0 -- > Error evaluating instruction: > SPARK°write°_mVar123·MATRIX·DOUBLE°mbperftest/stratstats/A_10M/data·SCALAR·STRING·true°binaryblock·SCALAR·STRING·true°·SCALAR·STRING·true > at > org.apache.sysml.runtime.controlprogram.ProgramBlock.executeSingleInstruction(ProgramBlock.java:294) > at > org.apache.sysml.runtime.controlprogram.ProgramBlock.executeInstructions(ProgramBlock.java:218) > at > org.apache.sysml.runtime.controlprogram.ProgramBlock.execute(ProgramBlock.java:163) > at > org.apache.sysml.runtime.controlprogram.Program.execute(Program.java:118) > ... 13 more > Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: > Serialized task 15:2 was 323397641 bytes, which exceeds max allowed: > spark.rpc.message.maxSize (134217728 bytes). Consider increasing > spark.rpc.message.maxSize or using broadcast variables for large values. > 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:1951) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1.apply$mcV$sp(PairRDDFunctions.scala:1226) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1.apply(PairRDDFunctions.scala:1168) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1.apply(PairRDDFunctions.scala:1168) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) > at org.apache.spark.rdd.RDD.withScope(RDD.scala:362) > at > org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopDataset(PairRDDFunctions.scala:1168) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$4.apply$mcV$sp(PairRDDFunctions.scala:1071) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$4.apply(PairRDDFunctions.scala:1037) > at > org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopFile$4.apply(PairRDDFunctions.scala:1037) > at > org.apache.spark.rdd.RDDOperationScope$.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.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:1037) > at > org.apache.spark.api.java.JavaPairRDD.saveAsHadoopFile(JavaPairRDD.scala:803) > at > org.apache.sysml.runtime.instructions.spark.WriteSPInstruction.processMatrixWriteInstruction(WriteSPInstruction.java:218) > at > org.apache.sysml.runtime.instructions.spark.WriteSPInstruction.processInstruction(WriteSPInstruction.java:144) > at > org.apache.sysml.runtime.controlprogram.ProgramBlock.executeSingleInstruction(ProgramBlock.java:264) > {code} -- This message was sent by Atlassian JIRA (v6.4.14#64029)