Interpreting output from mahout clusterdumper - hadoop

Question

I ran a clustering test on crawled pages (more than 25K docs ; personal data set).
I've done a clusterdump :
$MAHOUT_HOME/bin/mahout clusterdump --seqFileDir output/clusters-1/ --output clusteranalyze.txt
The output after running cluster dumper is shown 25 elements "VL-xxxxx {}" :
VL-24130{n=1312 c=[0:0.017, 10:0.007, 11:0.005, 14:0.017, 31:0.016, 35:0.006, 41:0.010, 43:0.008, 52:0.005, 59:0.010, 68:0.037, 72:0.056, 87:0.028, ... ] r=[0:0.442, 10:0.271, 11:0.198, 14:0.369, 31:0.421, ... ]}
...
VL-24868{n=311 c=[0:0.042, 11:0.016, 17:0.046, 72:0.014, 96:0.044, 118:0.015, 135:0.016, 195:0.017, 318:0.040, 319:0.037, 320:0.036, 330:0.030, ...] ] r=[0:0.740, 11:0.287, 17:0.576, 72:0.239, 96:0.549, 118:0.273, ...]}
How to interpret this output?
In short : I am looking for document ids which belong to a particular cluster.
What is the meaning of :
VL-x ?
n=y c=[z:z', ...]
r=[z'':z''', ...]
Does 0:0.017 means "0" is the document id which belongs to this cluster?
I already have read on mahout wiki-pages what CL, n, c and r means. But can someone please explain them to me better or points to a resource where it is explained a bit more in detail?
Sorry, if i am asking some stupid questions, but i am a newbie wih apache mahout and using it as part of my course assignment for clustering.

Answer 1

By default, kmeans clustering uses WeightedVector which does not include the data point name. So, you would like to make a sequence file yourself using NamedVector. There is a one to one correspondence between the number of seq files and the mapping tasks. So if your mapping capacity is 12, you want to chop your data into 12 pieces when making seqfiles
NamedVecotr:
vector = new NamedVector(new SequentialAccessSparseVector(Cardinality),arrField[0]);
Basically you need to download the clusteredPoints from your HDFS system and write your own code to output the results. Here is the code that I wrote to output the cluster point membership.
import java.io.*;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.TreeMap;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.SequenceFile;
import org.apache.mahout.clustering.WeightedVectorWritable;
import org.apache.mahout.common.Pair;
import org.apache.mahout.common.iterator.sequencefile.PathFilters;
import org.apache.mahout.common.iterator.sequencefile.PathType;
import org.apache.mahout.common.iterator.sequencefile.SequenceFileDirIterable;
import org.apache.mahout.math.NamedVector;
public class ClusterOutput {
/**
* #param args
*/
public static void main(String[] args) {
// TODO Auto-generated method stub
try {
BufferedWriter bw;
Configuration conf = new Configuration();
FileSystem fs = FileSystem.get(conf);
File pointsFolder = new File(args[0]);
File files[] = pointsFolder.listFiles();
bw = new BufferedWriter(new FileWriter(new File(args[1])));
HashMap<String, Integer> clusterIds;
clusterIds = new HashMap<String, Integer>(5000);
for(File file:files){
if(file.getName().indexOf("part-m")<0)
continue;
SequenceFile.Reader reader = new SequenceFile.Reader(fs, new Path(file.getAbsolutePath()), conf);
IntWritable key = new IntWritable();
WeightedVectorWritable value = new WeightedVectorWritable();
while (reader.next(key, value)) {
NamedVector vector = (NamedVector) value.getVector();
String vectorName = vector.getName();
bw.write(vectorName + "\t" + key.toString()+"\n");
if(clusterIds.containsKey(key.toString())){
clusterIds.put(key.toString(), clusterIds.get(key.toString())+1);
}
else
clusterIds.put(key.toString(), 1);
}
bw.flush();
reader.close();
}
bw.flush();
bw.close();
bw = new BufferedWriter(new FileWriter(new File(args[2])));
Set<String> keys=clusterIds.keySet();
for(String key:keys){
bw.write(key+" "+clusterIds.get(key)+"\n");
}
bw.flush();
bw.close();
} catch (IOException e) {
e.printStackTrace();
}
}
}

Answer 2

To complete the answer:
VL-x: is the identifier of the cluster
n=y: is the number of elements in the cluster
c=[z, ...]: is the centroid of the cluster, with the
z's being the weights of the different dimensions
r=[z, ...]: is the radius of the cluster.
More info here:
https://mahout.apache.org/users/clustering/cluster-dumper.html

Answer 3

I think you need to read the source code -- download from http://mahout.apache.org. VL-24130 is just a cluster identifier for a converged cluster.

Answer 4

You can use mahout clusterdump
https://cwiki.apache.org/MAHOUT/cluster-dumper.html