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https://issues.apache.org/jira/browse/SYSTEMML-1898?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16273596#comment-16273596
]
Matthias Boehm commented on SYSTEMML-1898:
------------------------------------------
sorry to have missed this issue [~AugustoHan] - could you please provide the
context where you encountered this issue (i.e., are getting this issue when
feeding a data frame as input into MLContext or by explicitly calling our
existing converters)?
> 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
> Labels: starter
>
> 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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