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 <jeast...@narus.com> >To: "user@mahout.apache.org" <user@mahout.apache.org>; Jeffrey ><mycyber...@yahoo.com> >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:mycyber...@yahoo.com] >Sent: Wednesday, July 20, 2011 2:41 AM >To: user@mahout.apache.org >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 > > >
