OK, it was. Is there a workaround I can try?
On Apr 3, 2015, at 12:22 PM, Dmitriy Lyubimov <dlie...@gmail.com> wrote: Although... i am not aware of one in A'A could be faulty vector length in a matrix if matrix was created by drmWrap with explicit specification of ncol On Fri, Apr 3, 2015 at 12:20 PM, Dmitriy Lyubimov <dlie...@gmail.com> wrote: > it's a bug. There's a number of similar ones in operator A'B. > > On Fri, Apr 3, 2015 at 6:23 AM, Michael Kelly <mich...@onespot.com> wrote: > >> Hi Pat, >> >> I've done some further digging and it looks like the problem is >> occurring when the input files are split up to into parts. The input >> to the item-similarity matrix is the output from a spark job and it >> ends up in about 2000 parts (on the hadoop file system). I have >> reproduced the error locally using a small subset of the rows. >> >> This is a snippet of the file I am using - >> >> ... >> >> 5138353282348067470,1891081885 >> 4417954190713934181,1828065687 >> 133682221673920382,1454844406 >> 133682221673920382,1129053737 >> 133682221673920382,548627241 >> 133682221673920382,1048452021 >> 8547417492653230933,1121310481 >> 7693904559640861382,1333374361 >> 7204049418352603234,606209305 >> 139299176617553863,467181330 >> ... >> >> >> When I run the item-similarity against a single input file which >> contains all the rows, the job succeeds without error. >> >> When I break up the input file into 100 parts, and use the directory >> containing them as input then I get the 'Index outside allowable >> range' exception. >> >> Her are the input files that I used tarred and gzipped - >> >> >> https://s3.amazonaws.com/static.onespot.com/mahout/passing_single_file.tar.gz >> >> https://s3.amazonaws.com/static.onespot.com/mahout/failing_split_into_100_parts.tar.gz >> >> There are 44067 rows in total, 11858 unique userIds and 24166 unique >> itemIds. >> >> This is the exception that I see on the 100 part run - >> 15/04/03 12:07:09 ERROR Executor: Exception in task 0.0 in stage 9.0 (TID >> 707) >> org.apache.mahout.math.IndexException: Index 24190 is outside >> allowable range of [0,24166) >> at org.apache.mahout.math.AbstractVector.viewPart(AbstractVector.java:147) >> at >> org.apache.mahout.math.scalabindings.VectorOps.apply(VectorOps.scala:37) >> at >> org.apache.mahout.sparkbindings.blas.AtA$$anonfun$5$$anonfun$apply$6.apply(AtA.scala:152) >> at >> org.apache.mahout.sparkbindings.blas.AtA$$anonfun$5$$anonfun$apply$6.apply(AtA.scala:149) >> at >> scala.collection.immutable.Stream$$anonfun$map$1.apply(Stream.scala:376) >> at >> scala.collection.immutable.Stream$$anonfun$map$1.apply(Stream.scala:376) >> at scala.collection.immutable.Stream$Cons.tail(Stream.scala:1085) >> at scala.collection.immutable.Stream$Cons.tail(Stream.scala:1077) >> at >> scala.collection.immutable.StreamIterator$$anonfun$next$1.apply(Stream.scala:980) >> at >> scala.collection.immutable.StreamIterator$$anonfun$next$1.apply(Stream.scala:980) >> at >> scala.collection.immutable.StreamIterator$LazyCell.v$lzycompute(Stream.scala:969) >> at scala.collection.immutable.StreamIterator$LazyCell.v(Stream.scala:969) >> at scala.collection.immutable.StreamIterator.hasNext(Stream.scala:974) >> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) >> at >> org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:202) >> at >> org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:56) >> at >> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68) >> at >> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41) >> at org.apache.spark.scheduler.Task.run(Task.scala:56) >> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:200) >> 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) >> >> >> I tried splitting the file up in 10,20 and 50 parts and the job completed. >> Also, should the resulting similarity matrix be the same wether the >> input is split up or not? I passed in the same random seed for the >> spark job, but the matrices were different >> >> Thanks, >> >> Michael >> >> >> >> On Thu, Apr 2, 2015 at 6:56 PM, Pat Ferrel <p...@occamsmachete.com> wrote: >>> The input must be tuples (if not using a filter) so the CLI you have >> expects user and item ids that are >>> >>> user-id1,item-id1 >>> user-id500,item-id3000 >>> … >>> >>> The ids must be tokenized because it doesn’t use a full csv parser, >> only lines of delimited text. >>> >>> If this doesn’t help can you supply a snippet of the input >>> >>> >>> On Apr 2, 2015, at 10:39 AM, Michael Kelly <mich...@onespot.com> wrote: >>> >>> Hi all, >>> >>> I'm running the spark-itemsimilarity job from the cli on an AWS emr >>> cluster, and I'm running into an exception. >>> >>> The input file format is >>> UserId<tab>ItemId1<tab>ItemId2<tab>ItemId3...... >>> >>> There is only one row per user, and a total of 97,000 rows. >>> >>> I also tried input with one row per UserId/ItemId pair, which had >>> about 250,000 rows, but I also saw a similar exception, this time the >>> out of bounds index was around 110,000. >>> >>> The input is stored in hdfs and this is the command I used to start the >> job - >>> >>> mahout spark-itemsimilarity --input userItems --output output --master >>> yarn-client >>> >>> Any idea what the problem might be? >>> >>> Thanks, >>> >>> Michael >>> >>> >>> >>> 15/04/02 16:37:40 WARN TaskSetManager: Lost task 1.0 in stage 10.0 >>> (TID 7631, ip-XX.XX.ec2.internal): >>> org.apache.mahout.math.IndexException: Index 22050 is outside >>> allowable range of [0,21997) >>> >>> >> org.apache.mahout.math.AbstractVector.viewPart(AbstractVector.java:147) >>> >>> >> org.apache.mahout.math.scalabindings.VectorOps.apply(VectorOps.scala:37) >>> >>> >> org.apache.mahout.sparkbindings.blas.AtA$$anonfun$5$$anonfun$apply$6.apply(AtA.scala:152) >>> >>> >> org.apache.mahout.sparkbindings.blas.AtA$$anonfun$5$$anonfun$apply$6.apply(AtA.scala:149) >>> >>> >> scala.collection.immutable.Stream$$anonfun$map$1.apply(Stream.scala:376) >>> >>> >> scala.collection.immutable.Stream$$anonfun$map$1.apply(Stream.scala:376) >>> >>> scala.collection.immutable.Stream$Cons.tail(Stream.scala:1085) >>> >>> scala.collection.immutable.Stream$Cons.tail(Stream.scala:1077) >>> >>> >> scala.collection.immutable.StreamIterator$$anonfun$next$1.apply(Stream.scala:980) >>> >>> >> scala.collection.immutable.StreamIterator$$anonfun$next$1.apply(Stream.scala:980) >>> >>> >> scala.collection.immutable.StreamIterator$LazyCell.v$lzycompute(Stream.scala:969) >>> >>> >> scala.collection.immutable.StreamIterator$LazyCell.v(Stream.scala:969) >>> >>> >> scala.collection.immutable.StreamIterator.hasNext(Stream.scala:974) >>> >>> scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) >>> >>> >> org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:144) >>> >>> >> org.apache.spark.Aggregator.combineValuesByKey(Aggregator.scala:58) >>> >>> >> org.apache.spark.shuffle.hash.HashShuffleWriter.write(HashShuffleWriter.scala:55) >>> >>> >> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68) >>> >>> >> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41) >>> >>> org.apache.spark.scheduler.Task.run(Task.scala:54) >>> >>> >> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:177) >>> >>> >> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) >>> >>> >> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) >>> >>> java.lang.Thread.run(Thread.java:745) >>> >> > >
