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/**
* 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.kmeans;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
import com.google.common.base.Preconditions;
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.common.HadoopUtil;
import org.apache.mahout.common.Pair;
import org.apache.mahout.common.RandomUtils;
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.VectorWritable;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
* Given an Input Path containing a {@link org.apache.hadoop.io.SequenceFile}, randomly 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.
*
* This implementation uses reservoir sampling as described in http://en.wikipedia.org/wiki/Reservoir_sampling
*/
public final class RandomSeedGenerator {
private static final Logger log = LoggerFactory.getLogger(RandomSeedGenerator.class);
public static final String K = "k";
private RandomSeedGenerator() {}
public static Path buildRandom(Configuration conf, Path input, Path output, int k, DistanceMeasure measure)
throws IOException {
return buildRandom(conf, input, output, k, measure, null);
}
public static Path buildRandom(Configuration conf,
Path input,
Path output,
int k,
DistanceMeasure measure,
Long seed) throws IOException {
Preconditions.checkArgument(k > 0, "Must be: k > 0, but k = " + k);
// delete the output directory
FileSystem fs = FileSystem.get(output.toUri(), conf);
HadoopUtil.delete(conf, output);
Path outFile = new Path(output, "part-randomSeed");
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());
Random random = (seed != null) ? RandomUtils.getRandom(seed) : RandomUtils.getRandom();
List chosenTexts = new ArrayList<>(k);
List chosenClusters = new ArrayList<>(k);
int nextClusterId = 0;
int index = 0;
for (FileStatus fileStatus : inputFiles) {
if (!fileStatus.isDir()) {
for (Pair record
: new SequenceFileIterable(fileStatus.getPath(), true, conf)) {
Writable key = record.getFirst();
VectorWritable value = record.getSecond();
Kluster newCluster = new Kluster(value.get(), nextClusterId++, measure);
newCluster.observe(value.get(), 1);
Text newText = new Text(key.toString());
int currentSize = chosenTexts.size();
if (currentSize < k) {
chosenTexts.add(newText);
ClusterWritable clusterWritable = new ClusterWritable();
clusterWritable.setValue(newCluster);
chosenClusters.add(clusterWritable);
} else {
int j = random.nextInt(index);
if (j < k) {
chosenTexts.set(j, newText);
ClusterWritable clusterWritable = new ClusterWritable();
clusterWritable.setValue(newCluster);
chosenClusters.set(j, clusterWritable);
}
}
index++;
}
}
}
try (SequenceFile.Writer writer =
SequenceFile.createWriter(fs, conf, outFile, Text.class, ClusterWritable.class)){
for (int i = 0; i < chosenTexts.size(); i++) {
writer.append(chosenTexts.get(i), chosenClusters.get(i));
}
log.info("Wrote {} Klusters to {}", k, outFile);
}
}
return outFile;
}
}
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