org.apache.mahout.clustering.kmeans.RandomSeedGenerator.java Source code

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Here is the source code for org.apache.mahout.clustering.kmeans.RandomSeedGenerator.java

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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<Text> chosenTexts = new ArrayList<>(k);
            List<ClusterWritable> chosenClusters = new ArrayList<>(k);
            int nextClusterId = 0;

            int index = 0;
            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();
                        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;
    }

}