Adam,

Pardon my asking again if this has already been answered - Are you running 
against Mahout 0.8?






________________________________
 From: Adam Baron <[email protected]>
To: [email protected]; Suneel Marthi <[email protected]> 
Sent: Tuesday, August 6, 2013 6:56 PM
Subject: Re: How to get human-readable output for large clustering?
 


Suneel,

I was trying -n 25 and -b 100 when I sent my e-mail about it not working for 
me.  Just tried -n 20 and got the same error message.  Any other ideas?

Thanks,
         Adam


On Mon, Aug 5, 2013 at 7:40 PM, Suneel Marthi <[email protected]> wrote:

Adam/Florian,
>
>Could you try running the clusterdump by limiting the number of terms from 
>clusterdump, by specifying -n 20 (outputs the 20 top terms)?
>
>
>
>
>________________________________
> From: Adam Baron <[email protected]>
>To: [email protected]
>Sent: Monday, August 5, 2013 8:03 PM
>Subject: Re: How to get human-readable output for large clustering?
>
>
>
>Florian,
>
>Any luck finding an answer over the past 5 months?  I'm also dealing with
>similar out of memory errors when I run clusterdump.  I'm using 50,000
>features and tried k=500.  The kmeans command ran fine, but then I got the
>dreaded OutOfMemory error on with the clusterdump command:
>
>2013-08-05 18:46:01,686 FATAL org.apache.hadoop.mapred.Child: Error running
>child : java.lang.OutOfMemoryError: Java heap space
>                              at
>org.apache.mahout.math.map.OpenIntDoubleHashMap.rehash(OpenIntDoubleHashMap.java:434)
>                              at
>org.apache.mahout.math.map.OpenIntDoubleHashMap.put(OpenIntDoubleHashMap.java:387)
>                              at
>org.apache.mahout.math.RandomAccessSparseVector.setQuick(RandomAccessSparseVector.java:139)
>                              at
>org.apache.mahout.math.VectorWritable.readFields(VectorWritable.java:118)
>                              at
>org.apache.hadoop.io.SequenceFile$Reader.getCurrentValue(SequenceFile.java:2114)
>                              at
>org.apache.hadoop.io.SequenceFile$Reader.next(SequenceFile.java:2242)
>                              at
>org.apache.mahout.common.iterator.sequencefile.SequenceFileIterator.computeNext(SequenceFileIterator.java:95)
>                              at
>org.apache.mahout.common.iterator.sequencefile.SequenceFileIterator.computeNext(SequenceFileIterator.java:38)
>                              at
>com.google.common.collect.AbstractIterator.tryToComputeNext(AbstractIterator.java:143)
>                              at
>com.google.common.collect.AbstractIterator.hasNext(AbstractIterator.java:138)
>                              at
>com.google.common.collect.Iterators$5.hasNext(Iterators.java:543)
>                              at
>com.google.common.collect.ForwardingIterator.hasNext(ForwardingIterator.java:43)
>                              at
>org.apache.mahout.clustering.evaluation.RepresentativePointsMapper.getRepresentativePoints(RepresentativePointsMapper.java:103)
>                              at
>org.apache.mahout.clustering.evaluation.RepresentativePointsMapper.getRepresentativePoints(RepresentativePointsMapper.java:97)
>                              at
>org.apache.mahout.clustering.evaluation.RepresentativePointsMapper.setup(RepresentativePointsMapper.java:87)
>                              at
>org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:138)
>                              at
>org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:673)
>                              at
>org.apache.hadoop.mapred.MapTask.run(MapTask.java:331)
>                              at
>org.apache.hadoop.mapred.Child$4.run(Child.java:268)
>                              at
>java.security.AccessController.doPrivileged(Native Method)
>                              at
>javax.security.auth.Subject.doAs(Subject.java:396)
>                              at
>org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1408)
>                              at
>org.apache.hadoop.mapred.Child.main(Child.java:262)
>
>Thanks,
>        Adam
>
>On Mon, Mar 11, 2013 at 8:42 AM, Florian Laws <[email protected]>wrote:
>
>> Hi,
>>
>> I have difficulties with clusterdump and clusterpp.
>>
>> Experimenting with Mahout's k-means clusterer, I have successfully
>> obtained kmeans results and clusterdump output for small custom
>> datasets.
>>
>> However, when I try to use a larger dataset with 1M datapoints and
>> 1000 clusters, I start to run into problems with the clusterdump tool.
>> The kmeans step runs fine, but clusterdump fails with with an out of
>> memory error:
>>
>> mahout clusterdump
>>    -i output/lda-vecs-1M-kmeans-k1000-x20/clusters-*-final
>>    -o output/lda-vecs-1M-kmeans-k1000-x20/clusterdump
>>    -dt sequencefile
>>    -dm org.apache.mahout.common.distance.EuclideanDistanceMeasure
>>    --pointsDir output/lda-vecs-1M-kmeans-k1000-x20/clusteredPoints/
>>
>> Running on hadoop, using /Users/issuu/florian/hadoop-1.0.3/bin/hadoop
>> and HADOOP_CONF_DIR=
>> MAHOUT-JOB:
>> /Users/issuu/florian/mahout/mahout-distribution-0.7/mahout-examples-0.7-job.jar
>> 13/03/11 16:21:04 INFO common.AbstractJob: Command line arguments:
>> {--dictionaryType=[sequencefile],
>>
>> --distanceMeasure=[org.apache.mahout.common.distance.EuclideanDistanceMeasure],
>> --endPhase=[2147483647],
>> --input=[output/lda-vecs-1M-kmeans-k1000-x20/clusters-*-final],
>> --output=[output/lda-vecs-1M-kmeans-k1000-x20/clusterdump],
>> --outputFormat=[TEXT],
>> --pointsDir=[output/lda-vecs-1M-kmeans-k1000-x20/clusteredPoints/],
>> --startPhase=[0], --tempDir=[temp]}
>> 2013-03-11 16:21:04.631 java[79418:1203] Unable to load realm info
>> from SCDynamicStore
>>
>> Exception in thread "main" java.lang.OutOfMemoryError: Java heap space
>>         at org.apache.mahout.math.DenseVector.<init>(DenseVector.java:44)
>>         at org.apache.mahout.math.DenseVector.<init>(DenseVector.java:39)
>>         at
>> org.apache.mahout.math.VectorWritable.readFields(VectorWritable.java:99)
>>         at
>> org.apache.mahout.clustering.classify.WeightedVectorWritable.readFields(WeightedVectorWritable.java:56)
>>         at
>> org.apache.hadoop.io.SequenceFile$Reader.getCurrentValue(SequenceFile.java:1809)
>>         at
>> org.apache.hadoop.io.SequenceFile$Reader.next(SequenceFile.java:1937)
>>         at
>> org.apache.mahout.common.iterator.sequencefile.SequenceFileIterator.computeNext(SequenceFileIterator.java:95)
>>         at
>> org.apache.mahout.common.iterator.sequencefile.SequenceFileIterator.computeNext(SequenceFileIterator.java:38)
>>         at
>> com.google.common.collect.AbstractIterator.tryToComputeNext(AbstractIterator.java:141)
>>         at
>> com.google.common.collect.AbstractIterator.hasNext(AbstractIterator.java:136)
>>         at
>> com.google.common.collect.Iterators$5.hasNext(Iterators.java:525)
>>         at
>> com.google.common.collect.ForwardingIterator.hasNext(ForwardingIterator.java:43)
>>         at
>> org.apache.mahout.utils.clustering.ClusterDumper.readPoints(ClusterDumper.java:292)
>>         at
>> org.apache.mahout.utils.clustering.ClusterDumper.init(ClusterDumper.java:245)
>>         at
>> org.apache.mahout.utils.clustering.ClusterDumper.run(ClusterDumper.java:152)
>>         at
>> org.apache.mahout.utils.clustering.ClusterDumper.main(ClusterDumper.java:102)
>>         at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>         at
>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
>>         at
>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
>>         at java.lang.reflect.Method.invoke(Method.java:597)
>>         at
>> org.apache.hadoop.util.ProgramDriver$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)
>>         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.RunJar.main(RunJar.java:156)
>>
>>
>> How do I increase the heap space in a way that the mahout command accepts
>> it?
>> I've set both MAHOUT_HEAPSIZE to 40000 and JAVA_HEAP_MAX to -Xmx40g
>> with no effect.
>>
>>
>> I also read that this is because clusterdump tries to read the whole
>> clustering input into memory,
>> and that one one instead use clusterpp to separate the clusters, so I
>> also tried to use the clusterpp utility as suggested in
>>
>> http://mail-archives.apache.org/mod_mbox/mahout-user/201210.mbox/%3CCAPa28_KPzBzhn5Ug0jQNstbzFOBMhADdfGTrcg2p1HCw5GXWWw%40mail.gmail.com%3E
>>
>> However that fails because it apparently can't determine the number of
>> clusters.
>>
>> $ mahout clusterpp
>>    -i output/lda-vecs-1M-kmeans-k1000-x20/clusters-20-final/
>>    -o  /user/issuu/output/lda-vecs-1M-kmeans-k1000-x20/clusterGroups
>>
>> Running on hadoop, using /Users/issuu/florian/hadoop-1.0.3/bin/hadoop
>> and HADOOP_CONF_DIR=
>> MAHOUT-JOB:
>> /Users/issuu/florian/mahout/mahout-distribution-0.7/mahout-examples-0.7-job.jar
>> 13/03/11 16:34:55 INFO common.AbstractJob: Command line arguments:
>> {--endPhase=[2147483647],
>> --input=[output/lda-vecs-1M-kmeans-k1000-x20/clusters-20-final/],
>> --method=[mapreduce],
>> --output=[/user/issuu/output/lda-vecs-1M-kmeans-k1000-x20/clusterGroups],
>> --startPhase=[0], --tempDir=[temp]}
>> 2013-03-11 16:34:55.925 java[79653:1203] Unable to load realm info
>> from SCDynamicStore
>>
>> Exception in thread "main" java.lang.ArrayIndexOutOfBoundsException: 0
>>         at
>> org.apache.mahout.clustering.topdown.postprocessor.ClusterCountReader.getNumberOfClusters(ClusterCountReader.java:53)
>>         at
>> org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessorDriver.postProcessMR(ClusterOutputPostProcessorDriver.java:150)
>>         at
>> org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessorDriver.run(ClusterOutputPostProcessorDriver.java:104)
>>         at
>> org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessorDriver.run(ClusterOutputPostProcessorDriver.java:70)
>>         at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:65)
>>         at
>> org.apache.mahout.clustering.topdown.postprocessor.ClusterOutputPostProcessorDriver.main(ClusterOutputPostProcessorDriver.java:81)
>>         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)
>>         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.RunJar.main(RunJar.java:156)
>>
>> I'm running Mahout 0.7 on Hadoop 1.0.3 in pseudo-distributed mode.
>>
>> What am I doing wrong?
>> What is the recommended way to get the output of a large(-ish)
>> clustering job into some human-readable format?
>>
>>
>> Thanks,
>>
>> Florian
>>

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