DataFrame to MatrixBlock Out of Bounds

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?