/**
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.mahout.clustering.spectral.kmeans;
import java.io.IOException;
import java.util.Map;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileStatus;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.SequenceFile;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
import org.apache.mahout.clustering.iterator.ClusterWritable;
import org.apache.mahout.clustering.kmeans.Kluster;
import org.apache.mahout.common.HadoopUtil;
import org.apache.mahout.common.Pair;
import org.apache.mahout.common.distance.DistanceMeasure;
import org.apache.mahout.common.iterator.sequencefile.PathFilters;
import org.apache.mahout.common.iterator.sequencefile.SequenceFileIterable;
import org.apache.mahout.math.Vector;
import org.apache.mahout.math.VectorWritable;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.google.common.collect.Maps;
import com.google.common.io.Closeables;
/**
* Given an Input Path containing a {@link org.apache.hadoop.io.SequenceFile}, select k vectors and write them to the
* output file as a {@link org.apache.mahout.clustering.kmeans.Kluster} representing the initial centroid to use. The
* selection criterion is the rows with max value in that respective column
*/
public final class EigenSeedGenerator {
private static final Logger log = LoggerFactory.getLogger(EigenSeedGenerator.class);
public static final String K = "k";
private EigenSeedGenerator() {}
public static Path buildFromEigens(Configuration conf, Path input, Path output, int k, DistanceMeasure measure)
throws IOException {
// delete the output directory
FileSystem fs = FileSystem.get(output.toUri(), conf);
HadoopUtil.delete(conf, output);
Path outFile = new Path(output, "part-eigenSeed");
boolean newFile = fs.createNewFile(outFile);
if (newFile) {
Path inputPathPattern;
if (fs.getFileStatus(input).isDir()) {
inputPathPattern = new Path(input, "*");
} else {
inputPathPattern = input;
}
FileStatus[] inputFiles = fs.globStatus(inputPathPattern, PathFilters.logsCRCFilter());
SequenceFile.Writer writer = SequenceFile.createWriter(fs, conf, outFile, Text.class, ClusterWritable.class);
Map<Integer,Double> maxEigens = Maps.newHashMapWithExpectedSize(k); // store
// max
// value
// of
// each
// column
Map<Integer,Text> chosenTexts = Maps.newHashMapWithExpectedSize(k);
Map<Integer,ClusterWritable> chosenClusters = Maps.newHashMapWithExpectedSize(k);
for (FileStatus fileStatus : inputFiles) {
if (!fileStatus.isDir()) {
for (Pair<Writable,VectorWritable> record : new SequenceFileIterable<Writable,VectorWritable>(
fileStatus.getPath(), true, conf)) {
Writable key = record.getFirst();
VectorWritable value = record.getSecond();
for (Vector.Element e : value.get().nonZeroes()) {
int index = e.index();
double v = Math.abs(e.get());
if (!maxEigens.containsKey(index) || v > maxEigens.get(index)) {
maxEigens.put(index, v);
Text newText = new Text(key.toString());
chosenTexts.put(index, newText);
Kluster newCluster = new Kluster(value.get(), index, measure);
newCluster.observe(value.get(), 1);
ClusterWritable clusterWritable = new ClusterWritable();
clusterWritable.setValue(newCluster);
chosenClusters.put(index, clusterWritable);
}
}
}
}
}
try {
for (Integer key : maxEigens.keySet()) {
writer.append(chosenTexts.get(key), chosenClusters.get(key));
}
log.info("EigenSeedGenerator:: Wrote {} Klusters to {}", chosenTexts.size(), outFile);
} finally {
Closeables.close(writer, false);
}
}
return outFile;
}
}