hi, thanks for the quick answer -- I suppose this is possible, though I don't understand how it could come about. The largest individual RDD elements are ~ 1 Mb in size (most are smaller) and the RDD is composed of 800k of them. The file is saved in 134 parts, but is being read in using some 1916+ partitions (I don't know why actually -- how does this number come about?). How can I check if any objects/batches are exceeding 2Gb?
Thanks, Rok On Tue, Jan 27, 2015 at 7:55 PM, Davies Liu <[email protected]> wrote: > Maybe it's caused by integer overflow, is it possible that one object > or batch bigger than 2G (after pickling)? > > On Tue, Jan 27, 2015 at 7:59 AM, rok <[email protected]> wrote: > > I've got an dataset saved with saveAsPickleFile using pyspark -- it saves > > without problems. When I try to read it back in, it fails with: > > > > Job aborted due to stage failure: Task 401 in stage 0.0 failed 4 times, > most > > recent failure: Lost task 401.3 in stage 0.0 (TID 449, > > e1326.hpc-lca.ethz.ch): java.lang.NegativeArraySizeException: > > > > org.apache.hadoop.io.BytesWritable.setCapacity(BytesWritable.java:119) > > org.apache.hadoop.io.BytesWritable.setSize(BytesWritable.java:98) > > > > org.apache.hadoop.io.BytesWritable.readFields(BytesWritable.java:153) > > > > > org.apache.hadoop.io.serializer.WritableSerialization$WritableDeserializer.deserialize(WritableSerialization.java:67) > > > > > org.apache.hadoop.io.serializer.WritableSerialization$WritableDeserializer.deserialize(WritableSerialization.java:40) > > > > > org.apache.hadoop.io.SequenceFile$Reader.deserializeValue(SequenceFile.java:1875) > > > > > org.apache.hadoop.io.SequenceFile$Reader.getCurrentValue(SequenceFile.java:1848) > > > > > org.apache.hadoop.mapred.SequenceFileRecordReader.getCurrentValue(SequenceFileRecordReader.java:103) > > > > > org.apache.hadoop.mapred.SequenceFileRecordReader.next(SequenceFileRecordReader.java:78) > > > org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:219) > > > org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:188) > > org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:71) > > > > > org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39) > > scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) > > > > > org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:330) > > > > > org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply$mcV$sp(PythonRDD.scala:209) > > > > > org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:184) > > > > > org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:184) > > > org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1311) > > > > > org.apache.spark.api.python.PythonRDD$WriterThread.run(PythonRDD.scala:183) > > > > > > Not really sure where to start looking for the culprit -- any suggestions > > most welcome. Thanks! > > > > Rok > > > > > > > > > > -- > > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/NegativeArraySizeException-in-pyspark-when-loading-an-RDD-pickleFile-tp21395.html > > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > > > --------------------------------------------------------------------- > > To unsubscribe, e-mail: [email protected] > > For additional commands, e-mail: [email protected] > > >
