erm, is there any workaround to the problem?
----- Original Message ----- > From: Jeff Eastman <[email protected]> > To: "[email protected]" <[email protected]> > Cc: > Sent: Tuesday, July 26, 2011 1:12 PM > Subject: RE: fkmeans or Cluster Dumper not working? > > Also makes sense that fuzzyk centroids would be completely dense, since every > point is a member of every cluster. My reducer heaps are 4G. > > -----Original Message----- > From: Jeff Eastman [mailto:[email protected]] > Sent: Monday, July 25, 2011 2:32 PM > To: [email protected]; Jeffrey > Subject: RE: fkmeans or Cluster Dumper not working? > > I'm able to run fuzzyk on your data set with k=10 and k=50 without problems. > I also ran it fine with k=100 just to push it a bit harder. Runs took longer > as > k increased as expected (39s, 2m50s, 5m57s) as did the clustering (11s, 45s, > 1m11s). The cluster dumper is throwing an OME with your data points and > probably > also with the larger cluster volumes, suggesting it needs a larger -Xmx value > since it is running locally and not influenced by the cluster vm parameters. > > I will try some more and keep you updated. > > The cluster dumper is throwing an OME trying to inhale all your data points. > It > is running locally > > -----Original Message----- > From: Jeffrey [mailto:[email protected]] > Sent: Sunday, July 24, 2011 12:51 AM > To: [email protected] > Subject: Re: fkmeans or Cluster Dumper not working? > > Erm, is there any update? is the problem reproducible? > > Best wishes, > Jeffrey04 > > > >> ________________________________ >> From: Jeffrey <[email protected]> >> To: Jeff Eastman <[email protected]>; > "[email protected]" <[email protected]> >> Sent: Friday, July 22, 2011 12:40 AM >> Subject: Re: fkmeans or Cluster Dumper not working? >> >> >> Hi Jeff, >> >> >> lol, this is probably my last reply before i fall asleep (GMT+8 here). >> >> >> First thing first, data file is here: http://coolsilon.com/image-tag.mvc >> >> >> Q: What is the cardinality of your vector data? >> about 1000+ rows (resources) * 14 000+ columns (tags) >> Q: Is it sparse or dense? >> sparse (assuming sparse = each vector contains mostly 0) >> Q: How many vectors are you trying to cluster? >> all of them? (1000+ rows) >> Q: What is the exact error you see when fkmeans fails with k=10? With k=50? >> i think i posted the exception when k=50, but will post them again here >> >> >> k=10, fkmeans actually works, but cluster dumper returns exception, however, > if i take out --pointsDir, then it would work (output looks ok, but without > all > the points) >> >> >> $ bin/mahout fkmeans --input sensei/image-tag.arff.mvc --output > sensei/clusters --clusters sensei/clusters/clusters-0 --clustering > --overwrite > --emitMostLikely false --numClusters 10 --maxIter 10 --m 5 >> ... >> $ bin/mahout clusterdump --seqFileDir sensei/clusters/clusters-1 > --pointsDir sensei/clusters/clusteredPoints --output image-tag-clusters.txt > Running on hadoop, using > HADOOP_HOME=/home/jeffrey04/Applications/hadoop-0.20.203.0 >> HADOOP_CONF_DIR=/home/jeffrey04/Applications/hadoop-0.20.203.0/conf >> MAHOUT-JOB: > /home/jeffrey04/Applications/mahout/examples/target/mahout-examples-0.6-SNAPSHOT-job.jar >> 11/07/22 00:14:50 INFO common.AbstractJob: Command line arguments: > {--dictionaryType=text, --endPhase=2147483647, > --output=image-tag-clusters.txt, > --pointsDir=sensei/clusters/clusteredPoints, > --seqFileDir=sensei/clusters/clusters-1, --startPhase=0, --tempDir=temp} >> Exception in thread "main" java.lang.OutOfMemoryError: Java > heap space >> at java.lang.Object.clone(Native Method) >> 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:94) >> at > org.apache.mahout.clustering.WeightedVectorWritable.readFields(WeightedVectorWritable.java:55) >> at > org.apache.hadoop.io.SequenceFile$Reader.getCurrentValue(SequenceFile.java:1751) >> at > org.apache.hadoop.io.SequenceFile$Reader.next(SequenceFile.java:1879) >> 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$5.hasNext(Iterators.java:525) >> at > com.google.common.collect.ForwardingIterator.hasNext(ForwardingIterator.java:43) >> at > org.apache.mahout.utils.clustering.ClusterDumper.readPoints(ClusterDumper.java:255) >> at > org.apache.mahout.utils.clustering.ClusterDumper.init(ClusterDumper.java:209) >> at > org.apache.mahout.utils.clustering.ClusterDumper.run(ClusterDumper.java:123) >> at > org.apache.mahout.utils.clustering.ClusterDumper.main(ClusterDumper.java:89) >> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >> at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) >> at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) >> at java.lang.reflect.Method.invoke(Method.java:616) >> at > org.apache.hadoop.util.ProgramDriver$ProgramDescription.invoke(ProgramDriver.java:68) >> at > org.apache.hadoop.util.ProgramDriver.driver(ProgramDriver.java:139) >> at > org.apache.mahout.driver.MahoutDriver.main(MahoutDriver.java:188) >> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >> at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) >> at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) >> at java.lang.reflect.Method.invoke(Method.java:616) >> at org.apache.hadoop.util.RunJar.main(RunJar.java:156) >> $ bin/mahout clusterdump --seqFileDir sensei/clusters/clusters-1 > --output image-tag-clusters.txt Running on hadoop, using > HADOOP_HOME=/home/jeffrey04/Applications/hadoop-0.20.203.0 >> HADOOP_CONF_DIR=/home/jeffrey04/Applications/hadoop-0.20.203.0/conf >> MAHOUT-JOB: > /home/jeffrey04/Applications/mahout/examples/target/mahout-examples-0.6-SNAPSHOT-job.jar >> 11/07/22 00:19:04 INFO common.AbstractJob: Command line arguments: > {--dictionaryType=text, --endPhase=2147483647, > --output=image-tag-clusters.txt, > --seqFileDir=sensei/clusters/clusters-1, --startPhase=0, --tempDir=temp} >> 11/07/22 00:19:13 INFO driver.MahoutDriver: Program took 9504 ms >> >> >> k=50, fkmeans shows exception after map 100% reduce 0%, and would retry (map > 0% reduce 0%) after the exception >> >> >> $ bin/mahout fkmeans --input sensei/image-tag.arff.mvc --output > sensei/clusters --clusters sensei/clusters/clusters-0 --clustering > --overwrite > --emitMostLikely false --numClusters 50 --maxIter 10 --m 5 >> Running on hadoop, using > HADOOP_HOME=/home/jeffrey04/Applications/hadoop-0.20.203.0 >> HADOOP_CONF_DIR=/home/jeffrey04/Applications/hadoop-0.20.203.0/conf >> MAHOUT-JOB: > /home/jeffrey04/Applications/mahout/examples/target/mahout-examples-0.6-SNAPSHOT-job.jar >> 11/07/22 00:21:07 INFO common.AbstractJob: Command line arguments: > {--clustering=null, --clusters=sensei/clusters/clusters-0, > --convergenceDelta=0.5, > --distanceMeasure=org.apache.mahout.common.distance.SquaredEuclideanDistanceMeasure, > > --emitMostLikely=false, --endPhase=2147483647, > --input=sensei/image-tag.arff.mvc, --m=5, --maxIter=10, --method=mapreduce, > --numClusters=50, --output=sensei/clusters, --overwrite=null, --startPhase=0, > --tempDir=temp, --threshold=0} >> 11/07/22 00:21:09 INFO common.HadoopUtil: Deleting sensei/clusters >> 11/07/22 00:21:09 INFO util.NativeCodeLoader: Loaded the native-hadoop > library >> 11/07/22 00:21:09 INFO zlib.ZlibFactory: Successfully loaded & > initialized native-zlib library >> 11/07/22 00:21:09 INFO compress.CodecPool: Got brand-new compressor >> 11/07/22 00:21:10 INFO compress.CodecPool: Got brand-new decompressor >> 11/07/22 00:21:21 INFO kmeans.RandomSeedGenerator: Wrote 50 vectors to > sensei/clusters/clusters-0/part-randomSeed >> 11/07/22 00:21:24 INFO fuzzykmeans.FuzzyKMeansDriver: Fuzzy K-Means > Iteration 1 >> 11/07/22 00:21:25 INFO input.FileInputFormat: Total input paths to > process : 1 >> 11/07/22 00:21:26 INFO mapred.JobClient: Running job: > job_201107211512_0029 >> 11/07/22 00:21:27 INFO mapred.JobClient: map 0% reduce 0% >> 11/07/22 00:22:08 INFO mapred.JobClient: map 1% reduce 0% >> 11/07/22 00:22:20 INFO mapred.JobClient: map 2% reduce 0% >> 11/07/22 00:22:33 INFO mapred.JobClient: map 3% reduce 0% >> 11/07/22 00:22:42 INFO mapred.JobClient: map 4% reduce 0% >> 11/07/22 00:22:50 INFO mapred.JobClient: map 5% reduce 0% >> 11/07/22 00:23:00 INFO mapred.JobClient: map 6% reduce 0% >> 11/07/22 00:23:09 INFO mapred.JobClient: map 7% reduce 0% >> 11/07/22 00:23:18 INFO mapred.JobClient: map 8% reduce 0% >> 11/07/22 00:23:27 INFO mapred.JobClient: map 9% reduce 0% >> 11/07/22 00:23:33 INFO mapred.JobClient: map 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INFO mapred.JobClient: map 91% reduce 0% >> 11/07/22 00:34:01 INFO mapred.JobClient: map 92% reduce 0% >> 11/07/22 00:34:10 INFO mapred.JobClient: map 93% reduce 0% >> 11/07/22 00:34:13 INFO mapred.JobClient: map 94% reduce 0% >> 11/07/22 00:34:25 INFO mapred.JobClient: map 95% reduce 0% >> 11/07/22 00:34:31 INFO mapred.JobClient: map 96% reduce 0% >> 11/07/22 00:34:40 INFO mapred.JobClient: map 97% reduce 0% >> 11/07/22 00:34:47 INFO mapred.JobClient: map 98% reduce 0% >> 11/07/22 00:34:56 INFO mapred.JobClient: map 99% reduce 0% >> 11/07/22 00:35:02 INFO mapred.JobClient: map 100% reduce 0% >> 11/07/22 00:35:07 INFO mapred.JobClient: Task Id : > attempt_201107211512_0029_m_000000_0, Status : FAILED >> org.apache.hadoop.util.DiskChecker$DiskErrorException: Could not find > any valid local directory for output/file.out >> at > org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.getLocalPathForWrite(LocalDirAllocator.java:381) >> at > org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:146) >> at > org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:127) >> at > org.apache.hadoop.mapred.MapOutputFile.getOutputFileForWrite(MapOutputFile.java:69) >> at > org.apache.hadoop.mapred.MapTask$MapOutputBuffer.mergeParts(MapTask.java:1639) >> at > org.apache.hadoop.mapred.MapTask$MapOutputBuffer.flush(MapTask.java:1322) >> at > org.apache.hadoop.mapred.MapTask$NewOutputCollector.close(MapTask.java:698) >> at > org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:765) >> at org.apache.hadoop.mapred.MapTask.run(MapTask.java:369) >> at org.apache.hadoop.mapred.Child$4.run(Child.java:259) >> at java.security.AccessController.doPrivileged(Native Method) >> at javax.security.auth.Subject.doAs(Subject.java:416) >> at > org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1059) >> at org.apache.hadoop.mapred.Child.main(Child.java:253) >> >> >> 11/07/22 00:35:09 INFO mapred.JobClient: map 0% reduce 0% >> ... >> >> >> Q: What are the Hadoop heap settings you are using for your job? >> I am new to hadoop, not sure where to get those, but got these from > localhost:50070, is it right? >> 147 files and directories, 60 blocks = 207 total. Heap Size is 31.57 MB / > 966.69 MB (3%) >> >> >> p/s: i keep forgetting to include my operating environment, sorry. I > basically run this in a guest operating system (in a virtualbox virtual > machine), assigned 1 CPU core, and 1.5GB of memory. Then the host operating > system is OS X 10.6.8 running on alubook (macbook late 2008 model) with 4GB > of > memory. >> >> >> $ cat /etc/*-release >> DISTRIB_ID=Ubuntu >> DISTRIB_RELEASE=11.04 >> DISTRIB_CODENAME=natty >> DISTRIB_DESCRIPTION="Ubuntu 11.04" >> $ uname -a >> Linux sensei 2.6.38-10-generic #46-Ubuntu SMP Tue Jun 28 15:05:41 UTC > 2011 i686 i686 i386 GNU/Linux >> >> >> Best wishes, >> Jeffrey04 >> >>> ________________________________ >>> From: Jeff Eastman <[email protected]> >>> To: "[email protected]" <[email protected]>; > Jeffrey <[email protected]> >>> Sent: Thursday, July 21, 2011 11:54 PM >>> Subject: RE: fkmeans or Cluster Dumper not working? >>> >>> Excellent, so this appears to be localized to fuzzyk. Unfortunately, the > Apache mail server strips off attachments so you'd need another mechanism (a > JIRA?) to upload your data if it is not too large. Some more questions in the > interim: >>> >>> - What is the cardinality of your vector data? >>> - Is it sparse or dense? >>> - How many vectors are you trying to cluster? >>> - What is the exact error you see when fkmeans fails with k=10? With > k=50? >>> - What are the Hadoop heap settings you are using for your job? >>> >>> -----Original Message----- >>> From: Jeffrey [mailto:[email protected]] >>> Sent: Thursday, July 21, 2011 11:21 AM >>> To: [email protected] >>> Subject: Re: fkmeans or Cluster Dumper not > working? >>> >>> Hi Jeff, >>> >>> Q: Did you change your invocation to specify a different -c directory > (e.g. clusters-0)? >>> A: Yes :) >>> >>> Q: Did you add the -cl argument? >>> A: Yes :) >>> >>> $ bin/mahout fkmeans --input sensei/image-tag.arff.mvc --output > sensei/clusters --clusters sensei/clusters/clusters-0 --clustering > --overwrite > --emitMostLikely false --numClusters 5 --maxIter 10 --m 5 >>> $ bin/mahout fkmeans --input sensei/image-tag.arff.mvc --output > sensei/clusters --clusters sensei/clusters/clusters-0 --clustering > --overwrite > --emitMostLikely false --numClusters 10 --maxIter 10 --m 5 >>> $ bin/mahout fkmeans --input sensei/image-tag.arff.mvc --output > sensei/clusters --clusters sensei/clusters/clusters-0 --clustering > --overwrite > --emitMostLikely false --numClusters 50 --maxIter 10 --m 5 >>> >>> Q: What is the new CLI invocation for clusterdump? >>> A: >>> $ bin/mahout clusterdump --seqFileDir sensei/clusters/clusters-4 > --pointsDir > sensei/clusters/clusteredPoints --output image-tag-clusters.txt >>> >>> >>> Q: Did this work for -k 10? What happens with -k 50? >>> A: works for k=5 (but i don't see the points), but not k=10, fkmeans > fails when k=50, so i can't dump when k=50 >>> >>> Q: Have you tried kmeans? >>> A: Yes (all tested on 0.6-snapshot) >>> >>> k=5: no problem :) >>> k=10: no problem :) >>> k=50: no problem :) >>> >>> p/s: attached with the test data i used (in mvc format), let me know if > you guys prefer raw data in arff format >>> >>> Best wishes, >>> Jeffrey04 >>> >>> >>> >>>> ________________________________ >>>> From: Jeff Eastman <[email protected]> >>>> To: "[email protected]" > <[email protected]>; Jeffrey <[email protected]> >>>> Sent: Thursday, July 21, 2011 9:36 PM >>>> Subject: RE: fkmeans or Cluster Dumper not working? >>>> >>>> You are correct, the wiki for fkmeans did not mention the -cl > argument. I've added that just now. I think this is what Frank means in his > comment but you do *not* have to write any custom code to get the cluster > dumper > to do what you want, just use the -cl argument and specify clusteredPoints as > the -p input to clusterdump. >>>> >>>> Check out TestClusterDumper.testKmeans and .testFuzzyKmeans. These > show how to invoke the clustering and cluster dumper from Java at least. >>>> >>>> Did you change your invocation to specify a different -c directory > (e.g. clusters-0)? >>>> Did you add the -cl argument? >>>> What is the new CLI invocation for clusterdump? >>>> Did this work for -k 10? What happens with -k > 50? >>>> Have you tried kmeans? >>>> >>>> I can help you better if you will give me answers to my questions >>>> >>>> -----Original Message----- >>>> From: Jeffrey [mailto:[email protected]] >>>> Sent: Thursday, July 21, 2011 4:30 AM >>>> To: [email protected] >>>> Subject: Re: fkmeans or Cluster Dumper not working? >>>> >>>> Hi again, >>>> >>>> Let me update on what's working and what's not working. >>>> >>>> Works: >>>> fkmeans clustering (10 clusters) - thanks Jeff for the --cl tip >>>> fkmeans clustering (5 clusters) >>>> clusterdump (5 clusters) - so points are not included in the > clusterdump and I need to write a program for it? >>>> >>>> Not Working: >>>> fkmeans clustering (50 clusters) - same error >>>> clusterdump (10 > clusters) - same error >>>> >>>> >>>> so it seems to attach points to the cluster dumper output like the > synthetic control example does, i would have to write some code as pointed by > @Frank_Scholten ? > https://twitter.com/#!/Frank_Scholten/status/93617269296472064 >>>> >>>> Best wishes, >>>> Jeffrey04 >>>> >>>>> ________________________________ >>>>> From: Jeff Eastman <[email protected]> >>>>> To: "[email protected]" > <[email protected]>; Jeffrey <[email protected]> >>>>> Sent: Wednesday, July 20, 2011 11:53 PM >>>>> Subject: RE: fkmeans or Cluster Dumper not working? >>>>> >>>>> Hi Jeffrey, >>>>> >>>>> It is always difficult to debug remotely, but here are some > suggestions: >>>>> - First, you are specifying both an input clusters directory > --clusters and --numClusters clusters so the job is sampling 10 points from > your > input data set and writing them to clusteredPoints as the prior clusters for > the > first iteration. You should pick a different name for this directory, as the > clusteredPoints directory is used by the -cl (--clustering) option (which you > did not supply) to write out the clustered (classified) input vectors. When > you > subsequently supplied clusteredPoints to the clusterdumper it was expecting a > different format and that caused the exception you saw. Change your > --clusters > directory (clusters-0 is good) > and add a -cl argument and things should go more smoothly. The -cl option is > not > the default and so no clustering of the input points is performed without > this > (Many people get caught by this and perhaps the default should be changed, > but > clustering can be expensive and so it is not performed without request). >>>>> - If you still have problems, try again with k-means. The > similarity to fkmeans is good and it will eliminate fkmeans itself if you see > the same problems with k-means >>>>> - I don't see why changing the -k argument from 10 to 50 > should cause any problems, unless your vectors are very large and you are > getting an OME in the reducer. Since the reducer is calculating centroid > vectors > for the next iteration these will become more dense and memory will increase > substantially. >>>>> - I can't figure out what might be causing your second > exception. It is bombing inside of Hadoop file IO and this causes me to > suspect > command argument > problems. >>>>> >>>>> Hope this helps, >>>>> Jeff >>>>> >>>>> >>>>> -----Original Message----- >>>>> From: Jeffrey [mailto:[email protected]] >>>>> Sent: Wednesday, July 20, 2011 2:41 AM >>>>> To: [email protected] >>>>> Subject: fkmeans or Cluster Dumper not working? >>>>> >>>>> Hi, >>>>> >>>>> I am trying to generate clusters using the fkmeans command line > tool from my test data. Not sure if this is correct, as it only runs one > iteration (output from 0.6-snapshot, gotta use some workaround to some weird > bug > - > http://search.lucidimagination.com/search/document/d95ff0c29ac4a8a7/bug_in_fkmeans > > ) >>>>> >>>>> $ bin/mahout fkmeans --input sensei/image-tag.arff.mvc --output > sensei/clusters --clusters sensei/clusteredPoints --maxIter 10 --numClusters > 10 > --overwrite --m 5 >>>>> Running on hadoop, using > HADOOP_HOME=/home/jeffrey04/Applications/hadoop-0.20.203.0HADOOP_CONF_DIR=/home/jeffrey04/Applications/hadoop-0.20.203.0/confMAHOUT-JOB: > > /home/jeffrey04/Applications/mahout/examples/target/mahout-examples-0.6-SNAPSHOT-job.jar11/07/20 > > 14:05:18 INFO common.AbstractJob: Command line arguments: > {--clusters=sensei/clusteredPoints, --convergenceDelta=0.5, > --distanceMeasure=org.apache.mahout.common.distance.SquaredEuclideanDistanceMeasure, > > --emitMostLikely=true, --endPhase=2147483647, > --input=sensei/image-tag.arff.mvc, > --m=5, --maxIter=10, --method=mapreduce, --numClusters=10, > --output=sensei/clusters, --overwrite=null, --startPhase=0, --tempDir=temp, > --threshold=0}11/07/20 14:05:20 INFO common.HadoopUtil: Deleting > sensei/clusters11/07/20 > 14:05:20 INFO common.HadoopUtil: Deleting sensei/clusteredPoints11/07/20 > 14:05:20 INFO util.NativeCodeLoader: Loaded the native-hadoop library11/07/20 > 14:05:20 INFO zlib.ZlibFactory: Successfully >>>>> loaded & initialized native-zlib library11/07/20 14:05:20 > INFO compress.CodecPool: Got brand-new compressor11/07/20 14:05:20 INFO > compress.CodecPool: Got brand-new decompressor >>>>> 11/07/20 14:05:29 INFO kmeans.RandomSeedGenerator: Wrote 10 > vectors to sensei/clusteredPoints/part-randomSeed >>>>> 11/07/20 14:05:29 INFO fuzzykmeans.FuzzyKMeansDriver: Fuzzy > K-Means Iteration 1 >>>>> 11/07/20 14:05:30 INFO input.FileInputFormat: Total input paths > to process : 1 >>>>> 11/07/20 14:05:30 INFO mapred.JobClient: Running job: > job_201107201152_0021 >>>>> 11/07/20 14:05:31 INFO mapred.JobClient: map 0% reduce 0% >>>>> 11/07/20 14:05:54 INFO mapred.JobClient: map 2% reduce 0% >>>>> 11/07/20 14:05:57 INFO > mapred.JobClient: map 5% reduce 0% >>>>> 11/07/20 14:06:00 INFO mapred.JobClient: map 6% reduce 0% >>>>> 11/07/20 14:06:03 INFO mapred.JobClient: map 7% reduce 0% >>>>> 11/07/20 14:06:07 INFO mapred.JobClient: map 10% reduce 0% >>>>> 11/07/20 14:06:10 INFO mapred.JobClient: map 13% reduce 0% >>>>> 11/07/20 14:06:13 INFO mapred.JobClient: map 15% reduce 0% >>>>> 11/07/20 14:06:16 INFO mapred.JobClient: map 17% reduce 0% >>>>> 11/07/20 14:06:19 INFO mapred.JobClient: map 19% reduce 0% >>>>> 11/07/20 14:06:22 INFO mapred.JobClient: map 23% reduce 0% >>>>> 11/07/20 14:06:25 INFO mapred.JobClient: map 25% reduce 0% >>>>> 11/07/20 14:06:28 INFO mapred.JobClient: map 27% reduce 0% >>>>> 11/07/20 14:06:31 INFO mapred.JobClient: map 30% reduce 0% >>>>> 11/07/20 14:06:34 INFO mapred.JobClient: map 33% reduce > 0% >>>>> 11/07/20 14:06:37 INFO mapred.JobClient: map 36% reduce 0% >>>>> 11/07/20 14:06:40 INFO mapred.JobClient: map 37% reduce 0% >>>>> 11/07/20 14:06:43 INFO mapred.JobClient: map 40% reduce 0% >>>>> 11/07/20 14:06:46 INFO mapred.JobClient: map 43% reduce 0% >>>>> 11/07/20 14:06:49 INFO mapred.JobClient: map 46% reduce 0% >>>>> 11/07/20 14:06:52 INFO mapred.JobClient: map 48% reduce 0% >>>>> 11/07/20 14:06:55 INFO mapred.JobClient: map 50% reduce 0% >>>>> 11/07/20 14:06:57 INFO mapred.JobClient: map 53% reduce 0% >>>>> 11/07/20 14:07:00 INFO mapred.JobClient: map 56% reduce 0% >>>>> 11/07/20 14:07:03 INFO mapred.JobClient: map 58% reduce 0% >>>>> 11/07/20 14:07:06 INFO mapred.JobClient: map 60% reduce 0% >>>>> 11/07/20 14:07:09 INFO mapred.JobClient: map 63% reduce 0% >>>>> 11/07/20 14:07:13 INFO > mapred.JobClient: map 65% reduce 0% >>>>> 11/07/20 14:07:16 INFO mapred.JobClient: map 67% reduce 0% >>>>> 11/07/20 14:07:19 INFO mapred.JobClient: map 70% reduce 0% >>>>> 11/07/20 14:07:22 INFO mapred.JobClient: map 73% reduce 0% >>>>> 11/07/20 14:07:25 INFO mapred.JobClient: map 75% reduce 0% >>>>> 11/07/20 14:07:28 INFO mapred.JobClient: map 77% reduce 0% >>>>> 11/07/20 14:07:31 INFO mapred.JobClient: map 80% reduce 0% >>>>> 11/07/20 14:07:34 INFO mapred.JobClient: map 83% reduce 0% >>>>> 11/07/20 14:07:37 INFO mapred.JobClient: map 85% reduce 0% >>>>> 11/07/20 14:07:40 INFO mapred.JobClient: map 87% reduce 0% >>>>> 11/07/20 14:07:43 INFO mapred.JobClient: map 89% reduce 0% >>>>> 11/07/20 14:07:46 INFO mapred.JobClient: map 92% reduce 0% >>>>> 11/07/20 14:07:49 INFO mapred.JobClient: map 95% reduce > 0% >>>>> 11/07/20 14:07:55 INFO mapred.JobClient: map 98% reduce 0% >>>>> 11/07/20 14:07:59 INFO mapred.JobClient: map 99% reduce 0% >>>>> 11/07/20 14:08:02 INFO mapred.JobClient: map 100% reduce 0% >>>>> 11/07/20 14:08:23 INFO mapred.JobClient: map 100% reduce 100% >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Job complete: > job_201107201152_0021 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Counters: 26 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Job Counters >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Launched reduce > tasks=1 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: > SLOTS_MILLIS_MAPS=149314 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Total time spent by > all reduces waiting after reserving slots (ms)=0 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Total time spent by > all maps waiting after > reserving slots (ms)=0 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Launched map > tasks=1 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Data-local map > tasks=1 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: > SLOTS_MILLIS_REDUCES=15618 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: File Output Format > Counters >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Bytes > Written=2247222 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Clustering >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Converged > Clusters=10 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: FileSystemCounters >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: > FILE_BYTES_READ=130281382 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: > HDFS_BYTES_READ=254494 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: > FILE_BYTES_WRITTEN=132572666 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: > HDFS_BYTES_WRITTEN=2247222 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: File Input Format > Counters >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Bytes Read=247443 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Map-Reduce Framework >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Reduce input > groups=10 >>>>> 11/07/20 14:08:31 INFO mapred.JobClient: Map output > materialized bytes=2246233 >>>>> 11/07/20 14:08:32 INFO mapred.JobClient: Combine output > records=330 >>>>> 11/07/20 14:08:32 INFO mapred.JobClient: Map input > records=1113 >>>>> 11/07/20 14:08:32 INFO mapred.JobClient: Reduce shuffle > bytes=2246233 >>>>> 11/07/20 14:08:32 INFO mapred.JobClient: Reduce output > records=10 >>>>> 11/07/20 14:08:32 INFO > mapred.JobClient: Spilled Records=590 >>>>> 11/07/20 14:08:32 INFO mapred.JobClient: Map output > bytes=2499995001 >>>>> 11/07/20 14:08:32 INFO mapred.JobClient: Combine input > records=11450 >>>>> 11/07/20 14:08:32 INFO mapred.JobClient: Map output > records=11130 >>>>> 11/07/20 14:08:32 INFO mapred.JobClient: SPLIT_RAW_BYTES=127 >>>>> 11/07/20 14:08:32 INFO mapred.JobClient: Reduce input > records=10 >>>>> 11/07/20 14:08:32 INFO driver.MahoutDriver: Program took 194096 > ms >>>>> >>>>> if I increase the --numClusters argument (e.g. 50), then it will > return exception after >>>>> 11/07/20 14:08:02 INFO mapred.JobClient: map 100% reduce 0% >>>>> >>>>> and would retry again (also reproducible using 0.6-snapshot) >>>>> >>>>> ... >>>>> 11/07/20 14:22:25 INFO mapred.JobClient: map 100% reduce > 0% >>>>> 11/07/20 14:22:30 INFO mapred.JobClient: Task Id : > attempt_201107201152_0022_m_000000_0, Status : FAILED >>>>> org.apache.hadoop.util.DiskChecker$DiskErrorException: Could not > find any valid local directory for output/file.out >>>>> at > org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.getLocalPathForWrite(LocalDirAllocator.java:381) >>>>> at > org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:146) >>>>> at > org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:127) >>>>> at > org.apache.hadoop.mapred.MapOutputFile.getOutputFileForWrite(MapOutputFile.java:69) >>>>> at > org.apache.hadoop.mapred.MapTask$MapOutputBuffer.mergeParts(MapTask.java:1639) >>>>> at > org.apache.hadoop.mapred.MapTask$MapOutputBuffer.flush(MapTask.java:1322) >>>>> at > org.apache.hadoop.mapred.MapTask$NewOutputCollector.close(MapTask.java:698) >>>>> at > org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:765) >>>>> at > org.apache.hadoop.mapred.MapTask.run(MapTask.java:369) >>>>> at org.apache.hadoop.mapred.Child$4.run(Child.java:259) >>>>> at java.security.AccessController.doPrivileged(Native > Method) >>>>> at javax.security.auth.Subject.doAs(Subject.java:416) >>>>> at > org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1059) >>>>> at org.apache.hadoop.mapred.Child.main(Child.java:253) >>>>> >>>>> 11/07/20 14:22:32 INFO > mapred.JobClient: map 0% reduce 0% >>>>> ... >>>>> >>>>> Then I ran cluster dumper to dump information about the > clusters, this command would work if I only care about the cluster centroids > (both 0.5 release and 0.6-snapshot) >>>>> >>>>> $ bin/mahout clusterdump --seqFileDir sensei/clusters/clusters-1 > --output image-tag-clusters.txt >>>>> Running on hadoop, using > HADOOP_HOME=/home/jeffrey04/Applications/hadoop-0.20.203.0 >>>>> HADOOP_CONF_DIR=/home/jeffrey04/Applications/hadoop-0.20.203.0/conf >>>>> MAHOUT-JOB: > /home/jeffrey04/Applications/mahout/examples/target/mahout-examples-0.6-SNAPSHOT-job.jar >>>>> 11/07/20 14:33:45 INFO common.AbstractJob: Command line > arguments: {--dictionaryType=text, --endPhase=2147483647, > --output=image-tag-clusters.txt, --seqFileDir=sensei/clusters/clusters-1, > --startPhase=0, --tempDir=temp} >>>>> 11/07/20 14:33:56 INFO driver.MahoutDriver: Program took 11761 > ms >>>>> >>>>> but if I want to see the degree of membership of each points, I > get another exception (yes, reproducible for both 0.5 release and > 0.6-snapshot) >>>>> >>>>> $ bin/mahout clusterdump --seqFileDir sensei/clusters/clusters-1 > --output image-tag-clusters.txt --pointsDir sensei/clusteredPoints >>>>> Running on hadoop, using > HADOOP_HOME=/home/jeffrey04/Applications/hadoop-0.20.203.0 >>>>> HADOOP_CONF_DIR=/home/jeffrey04/Applications/hadoop-0.20.203.0/conf >>>>> MAHOUT-JOB: > /home/jeffrey04/Applications/mahout/examples/target/mahout-examples-0.6-SNAPSHOT-job.jar >>>>> 11/07/20 14:35:08 INFO common.AbstractJob: Command line > arguments: {--dictionaryType=text, --endPhase=2147483647, > --output=image-tag-clusters.txt, --pointsDir=sensei/clusteredPoints, > --seqFileDir=sensei/clusters/clusters-1, --startPhase=0, --tempDir=temp} >>>>> 11/07/20 14:35:10 INFO util.NativeCodeLoader: Loaded the > native-hadoop > library >>>>> 11/07/20 14:35:10 INFO zlib.ZlibFactory: Successfully loaded > & initialized native-zlib library >>>>> 11/07/20 14:35:10 INFO compress.CodecPool: Got brand-new > decompressor >>>>> Exception in thread "main" > java.lang.ClassCastException: org.apache.hadoop.io.Text cannot be cast to > org.apache.hadoop.io.IntWritable >>>>> at > org.apache.mahout.utils.clustering.ClusterDumper.readPoints(ClusterDumper.java:261) >>>>> at > org.apache.mahout.utils.clustering.ClusterDumper.init(ClusterDumper.java:209) >>>>> at > org.apache.mahout.utils.clustering.ClusterDumper.run(ClusterDumper.java:123) >>>>> at > org.apache.mahout.utils.clustering.ClusterDumper.main(ClusterDumper.java:89) >>>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native > Method) >>>>> > at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) >>>>> at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) >>>>> at java.lang.reflect.Method.invoke(Method.java:616) >>>>> 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:188) >>>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native > Method) >>>>> at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) >>>>> at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) >>>>> at java.lang.reflect.Method.invoke(Method.java:616) >>>>> at org.apache.hadoop.util.RunJar.main(RunJar.java:156) >>>>> >>>>> erm, would writing a short program to call the API (btw, > can't seem to find the latest API doc?) be a better choice here? Or did I do > anything wrong here (yes, Java is not my main language, and I am very new to > Mahout.. and h)? >>>>> >>>>> the data is converted from an arff file with about 1000 rows > (resource) and 14k columns (tag), and it is just a subset of my data. > (actually > made a mistake so it is now generating resource clusters instead of tag > clusters, but I am just doing this as a proof of concept whether mahout is > good > enough for the task) >>>>> >>>>> Best > wishes, >>>>> Jeffrey04 >>>>> >>>>> >>>>> >>>> >>>> >>>> >>> >>> >>> >> >> >
