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 10% reduce 0% 11/07/22 00:23:42 INFO mapred.JobClient: map 11% reduce 0% 11/07/22 00:23:45 INFO mapred.JobClient: map 12% reduce 0% 11/07/22 00:23:54 INFO mapred.JobClient: map 13% reduce 0% 11/07/22 00:24:03 INFO mapred.JobClient: map 14% reduce 0% 11/07/22 00:24:09 INFO mapred.JobClient: map 15% reduce 0% 11/07/22 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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 >>> >>> >>> >> >> >> > > >
