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From Pat Ferrel <...@occamsmachete.com>
Subject Re: Problem using SNAPSHOT kmeans
Date Tue, 05 Jun 2012 19:12:07 GMT
I think I found the root but not sure what needs fixing.

I took out n-gram generation and the vector now looks like this:
Key: https://farfetchers.com/category/collections/source/brice-berard:
Value: 
https://farfetchers.com/category/collections/source/brice-berard:{701:0.5484552974788475,1876:0.6020428878306935,3620:0.5802940184767269}

This works in clustering.

It doesn't seem like a malformed vector should crash clustering (it 
apparently doesn't in mahout 0.6) but it looks like something in 
seq2sparse's n-gram weighting does cause a malformed vector.

I'll file a JIRA

On 6/5/12 11:48 AM, Pat Ferrel wrote:
> Using seqdumper on the TFIDF vectors, that vector is indeed in the list
> Key: https://farfetchers.com/category/collections/source/brice-berard:
> Value: https://farfetchers.com/category/collections/source/brice-berard:{
>
> Looking in the seqfiles we find the document in part-00005 of 10 in no 
> particular part of the file.
> Key: https://farfetchers.com/category/collections/source/brice-berard:
> Value: ::Title::
> Brice Berard | FarFetchers.com
> Blog Posts
>
> On the chance that this originates in seq2sparse I'll try changing 
> options until the vector looks different. and try clustering again.
>
> On 6/5/12 10:43 AM, Pat Ferrel wrote:
>> I'm not completely sure what I'm looking at but...
>>
>> In iterateSeq on iteration #1  of processing vectors/tfidf-vectors it 
>> reads
>> vector = 
>> "https://farfetchers.com/category/collections/source/brice-berard:{"
>>
>> it's a named vector where the  url is the name, the value is "{", 
>> which looks wrong and when that is classified to get a probability it 
>> gets
>>
>> probabilities = 
>> "{0:NaN,1:NaN,2:NaN,3:NaN,4:NaN,5:NaN,6:NaN,7:NaN,8:NaN,9:NaN,10:NaN,11:NaN,12:NaN,13:NaN,14:NaN,15:NaN,16:NaN,17:NaN,18:NaN,19:NaN}"
>>
>> That causes the probabilities.maxValueIndex() = -1 and everything dies.
>>
>> vector looks wrong, doesn't it? Truncated?
>>
>> I went back to try the same on mahout 0.6 but iterateSeq does not get 
>> called though I used -xm sequential on both runs. I can't see 
>> kmeans-clusters/clusters-0 being created on mahout 0.6 either. Is 
>> that part of the refactoring?
>>
>> On 6/4/12 3:07 PM, Pat Ferrel wrote:
>>> Some things to try:
>>> - Have you verified the contents of your input vectors actually have 
>>> data in them?
>>> * YES, from the other email you know that the data works fine in 0.6
>>> - Can you run the cluster dumper on the 
>>> b3/kmeans-clusters/clusters-0 contents?
>>> * YES, It is attached from trunk's clusterdump after the failure of 
>>> kmeans, of course. A simple data set fortunately.
>>> - Is it possible to run the sequential version (-xm sequential)? If 
>>> it is you could run it in a debugger to gain more insight.
>>> * YES, will report back.
>>>
>>> On 6/4/12 2:19 PM, Jeff Eastman wrote:
>>>> It looks like the probabilities vector returned by 
>>>> AbstractClusteringPolicy.classify() has no non-zero elements. In 
>>>> this case, AbstractClusteringPolicy.select()'s call to 
>>>> AbstractVector.maxValueIndex() is returning -1 and that is causing 
>>>> the exception.
>>>>
>>>> How could this happen? I'm not exactly sure, but consider that the 
>>>> probabilities vector is calculated in 
>>>> AbstractClusteringPolicy.classify() by calling 
>>>> DistanceMeasureCluster.pdf() on each of the prior clusters in 
>>>> b3/kmeans-clusters/clusters-0. With a CosineDistanceMeasure I don't 
>>>> see how this could ever return zero. Certainly, some of your 
>>>> vectors will match the prior cluster centers exactly (they were 
>>>> sampled from the input) and those values would return pdf==1. Even 
>>>> if the cosine distance was 1 the pdf would be 0.5.
>>>>
>>>> Some things to try:
>>>> - Have you verified the contents of your input vectors actually 
>>>> have data in them?
>>>> - Can you run the cluster dumper on the 
>>>> b3/kmeans-clusters/clusters-0 contents?
>>>> - Is it possible to run the sequential version (-xm sequential)? If 
>>>> it is you could run it in a debugger to gain more insight.
>>>>
>>>> Jeff
>>>>
>>>> On 6/4/12 12:05 PM, Pat Ferrel wrote:
>>>>> Using the CLI to kmeans from several trunk versions I get an error 
>>>>> I don't understand.  When the job died the 
>>>>> b3/canopy-centroids/clusters-0-final contained the random-seeds 
>>>>> file generated by the kmeans driver and the 
>>>>> b3/kmeans-clusters/clusters-0 had several part files but 
>>>>> b3/kmeans-clusters/clusters-1 was empty. When I look through the 
>>>>> code from the trace it doesn't make much sense.
>>>>>
>>>>> Command line:
>>>>> mahout kmeans
>>>>>   -i b3/vectors/tfidf-vectors/
>>>>>   -k 20
>>>>>   -c b3/canopy-centroids/clusters-0-final
>>>>>   -cl
>>>>>   -o b3/kmeans-clusters
>>>>>   -ow
>>>>>   -cd 0.01
>>>>>   -x 30
>>>>>   -dm org.apache.mahout.common.distance.CosineDistanceMeasure
>>>>>
>>>>> Error:
>>>>> 12/06/04 07:55:03 INFO common.AbstractJob: Command line arguments: 
>>>>> {--clustering=null, 
>>>>> --clusters=[b3/canopy-centroids/clusters-0-final], 
>>>>> --convergenceDelta=[0.01], 
>>>>> --distanceMeasure=[org.apache.mahout.common.distance.CosineDistanceMeasure],

>>>>> --endPhase=[2147483647], --input=[b3/vectors/tfidf-vectors/], 
>>>>> --maxIter=[30], --method=[mapreduce], --numClusters=[20], 
>>>>> --output=[b3/kmeans-clusters], --overwrite=null, --startPhase=[0], 
>>>>> --tempDir=[temp]}
>>>>> 2012-06-04 07:55:03.752 java[67308:1903] Unable to load realm info 
>>>>> from SCDynamicStore
>>>>> 12/06/04 07:55:03 INFO common.HadoopUtil: Deleting 
>>>>> b3/canopy-centroids/clusters-0-final
>>>>> 12/06/04 07:55:04 WARN util.NativeCodeLoader: Unable to load 
>>>>> native-hadoop library for your platform... using builtin-java 
>>>>> classes where applicable
>>>>> 12/06/04 07:55:04 INFO compress.CodecPool: Got brand-new compressor
>>>>> 12/06/04 07:55:04 INFO kmeans.RandomSeedGenerator: Wrote 20 
>>>>> vectors to b3/canopy-centroids/clusters-0-final/part-randomSeed
>>>>> 12/06/04 07:55:04 INFO kmeans.KMeansDriver: Input: 
>>>>> b3/vectors/tfidf-vectors Clusters In: 
>>>>> b3/canopy-centroids/clusters-0-final/part-randomSeed Out: 
>>>>> b3/kmeans-clusters Distance: 
>>>>> org.apache.mahout.common.distance.CosineDistanceMeasure
>>>>> 12/06/04 07:55:04 INFO kmeans.KMeansDriver: convergence: 0.01 max 
>>>>> Iterations: 30 num Reduce Tasks: 
>>>>> org.apache.mahout.math.VectorWritable Input Vectors: {}
>>>>> 12/06/04 07:55:04 INFO compress.CodecPool: Got brand-new decompressor
>>>>> Cluster Iterator running iteration 1 over priorPath: 
>>>>> b3/kmeans-clusters/clusters-0
>>>>> 12/06/04 07:55:05 INFO input.FileInputFormat: Total input paths to 
>>>>> process : 1
>>>>> 12/06/04 07:55:05 INFO mapred.JobClient: Running job: job_local_0001
>>>>> 12/06/04 07:55:06 INFO mapred.MapTask: io.sort.mb = 100
>>>>> 12/06/04 07:55:08 INFO mapred.MapTask: data buffer = 
>>>>> 79691776/99614720
>>>>> 12/06/04 07:55:08 INFO mapred.MapTask: record buffer = 262144/327680
>>>>> 12/06/04 07:55:08 INFO mapred.JobClient:  map 0% reduce 0%
>>>>> 12/06/04 07:55:09 WARN mapred.LocalJobRunner: job_local_0001
>>>>> org.apache.mahout.math.IndexException: Index -1 is outside 
>>>>> allowable range of [0,20)
>>>>>     at 
>>>>> org.apache.mahout.math.AbstractVector.set(AbstractVector.java:439)
>>>>>     at 
>>>>> org.apache.mahout.clustering.iterator.AbstractClusteringPolicy.select(AbstractClusteringPolicy.java:44)
>>>>>     at 
>>>>> org.apache.mahout.clustering.iterator.CIMapper.map(CIMapper.java:52)
>>>>>     at 
>>>>> org.apache.mahout.clustering.iterator.CIMapper.map(CIMapper.java:18)
>>>>>     at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:144)
>>>>>     at 
>>>>> org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:764)
>>>>>     at org.apache.hadoop.mapred.MapTask.run(MapTask.java:370)
>>>>>     at 
>>>>> org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:212)

>>>>>
>>>>> 12/06/04 07:55:09 INFO mapred.JobClient: Job complete: job_local_0001
>>>>> 12/06/04 07:55:09 INFO mapred.JobClient: Counters: 0
>>>>> Exception in thread "main" java.lang.InterruptedException: Cluster 
>>>>> Iteration 1 failed processing b3/kmeans-clusters/clusters-1
>>>>>     at 
>>>>> org.apache.mahout.clustering.iterator.ClusterIterator.iterateMR(ClusterIterator.java:186)
>>>>>     at 
>>>>> org.apache.mahout.clustering.kmeans.KMeansDriver.buildClusters(KMeansDriver.java:229)
>>>>>     at 
>>>>> org.apache.mahout.clustering.kmeans.KMeansDriver.run(KMeansDriver.java:149)
>>>>>     at 
>>>>> org.apache.mahout.clustering.kmeans.KMeansDriver.run(KMeansDriver.java:108)
>>>>>     at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:65)
>>>>>     at 
>>>>> org.apache.mahout.clustering.kmeans.KMeansDriver.main(KMeansDriver.java:49)
>>>>>     at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>>>>     at 
>>>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
>>>>>     at 
>>>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
>>>>>     at java.lang.reflect.Method.invoke(Method.java:597)
>>>>>     at 
>>>>> org.apache.hadoop.util.ProgramDriver$ProgramDescription.invoke(ProgramDriver.java:68)
>>>>>     at 
>>>>> org.apache.hadoop.util.ProgramDriver.driver(ProgramDriver.java:139)
>>>>>     at 
>>>>> org.apache.mahout.driver.MahoutDriver.main(MahoutDriver.java:195)
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>

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