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Posted to issues@systemml.apache.org by "Janardhan (JIRA)" <ji...@apache.org> on 2019/04/13 08:00:00 UTC

[jira] [Resolved] (SYSTEMML-1898) DataFrame to MatrixBlock Out of Bounds

     [ https://issues.apache.org/jira/browse/SYSTEMML-1898?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Janardhan resolved SYSTEMML-1898.
---------------------------------
       Resolution: Fixed
    Fix Version/s: SystemML 1.2

> DataFrame to MatrixBlock Out of Bounds 
> ---------------------------------------
>
>                 Key: SYSTEMML-1898
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-1898
>             Project: SystemML
>          Issue Type: Question
>         Environment: spark 2.1.0 with systemml-0.14.0
>            Reporter: Augusto
>            Assignee: Matthias Boehm
>            Priority: Major
>              Labels: starter
>             Fix For: SystemML 1.2
>
>
> When I'm running systemml, with data set about 1000 instances, 30000 features(actually only 15 not zero feature per instance), the task always failed with output below :
> [Stage 28:>                                                       (0 + 12) / 12]17/09/08 10:21:33 WARN scheduler.TaskSetManager: Lost task 2.0 in stage 28.0 (TID 225, sd002021.skydata.com, executor 6): java.lang.ArrayIndexOutOfBoundsException: 0
> 	at org.apache.sysml.runtime.matrix.data.SparseRow.append(SparseRow.java:215)
> 	at org.apache.sysml.runtime.matrix.data.SparseBlockMCSR.append(SparseBlockMCSR.java:253)
> 	at org.apache.sysml.runtime.matrix.data.MatrixBlock.appendValue(MatrixBlock.java:663)
> 	at org.apache.sysml.runtime.instructions.spark.utils.RDDConverterUtils$DataFrameToBinaryBlockFunction.call(RDDConverterUtils.java:1076)
> 	at org.apache.sysml.runtime.instructions.spark.utils.RDDConverterUtils$DataFrameToBinaryBlockFunction.call(RDDConverterUtils.java:1008)
> 	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$23.apply(RDD.scala:796)
> 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
> 	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
> 	at org.apache.spark.scheduler.Task.run(Task.scala:99)
> 	at org.apache.spark.executor.Executor$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)
> Can someone help, please? 



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