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 <[email protected]> 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 <[email protected]> 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 <[email protected]> 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) > > >
