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 >
