org.apache.mahout.clustering.streaming.mapreduce.StreamingKMeansReducer.java Source code

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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.streaming.mapreduce;

import java.io.IOException;
import java.util.List;

import com.google.common.base.Function;
import com.google.common.base.Preconditions;
import com.google.common.collect.Iterables;
import com.google.common.collect.Lists;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.mahout.clustering.streaming.cluster.BallKMeans;
import org.apache.mahout.common.commandline.DefaultOptionCreator;
import org.apache.mahout.math.Centroid;
import org.apache.mahout.math.Vector;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

public class StreamingKMeansReducer extends Reducer<IntWritable, CentroidWritable, IntWritable, CentroidWritable> {

    private static final Logger log = LoggerFactory.getLogger(StreamingKMeansReducer.class);

    /**
     * Configuration for the MapReduce job.
     */
    private Configuration conf;

    @Override
    public void setup(Context context) {
        // At this point the configuration received from the Driver is assumed to be valid.
        // No other checks are made.
        conf = context.getConfiguration();
    }

    @Override
    public void reduce(IntWritable key, Iterable<CentroidWritable> centroids, Context context)
            throws IOException, InterruptedException {
        List<Centroid> intermediateCentroids;
        // There might be too many intermediate centroids to fit into memory, in which case, we run another pass
        // of StreamingKMeans to collapse the clusters further.
        if (conf.getBoolean(StreamingKMeansDriver.REDUCE_STREAMING_KMEANS, false)) {
            intermediateCentroids = Lists.newArrayList(new StreamingKMeansThread(
                    Iterables.transform(centroids, new Function<CentroidWritable, Centroid>() {
                        @Override
                        public Centroid apply(CentroidWritable input) {
                            Preconditions.checkNotNull(input);
                            return input.getCentroid().clone();
                        }
                    }), conf).call());
        } else {
            intermediateCentroids = centroidWritablesToList(centroids);
        }

        int index = 0;
        for (Vector centroid : getBestCentroids(intermediateCentroids, conf)) {
            context.write(new IntWritable(index), new CentroidWritable((Centroid) centroid));
            ++index;
        }
    }

    public static List<Centroid> centroidWritablesToList(Iterable<CentroidWritable> centroids) {
        // A new list must be created because Hadoop iterators mutate the contents of the Writable in
        // place, without allocating new references when iterating through the centroids Iterable.
        return Lists.newArrayList(Iterables.transform(centroids, new Function<CentroidWritable, Centroid>() {
            @Override
            public Centroid apply(CentroidWritable input) {
                Preconditions.checkNotNull(input);
                return input.getCentroid().clone();
            }
        }));
    }

    public static Iterable<Vector> getBestCentroids(List<Centroid> centroids, Configuration conf) {

        if (log.isInfoEnabled()) {
            log.info("Number of Centroids: {}", centroids.size());
        }

        int numClusters = conf.getInt(DefaultOptionCreator.NUM_CLUSTERS_OPTION, 1);
        int maxNumIterations = conf.getInt(StreamingKMeansDriver.MAX_NUM_ITERATIONS, 10);
        float trimFraction = conf.getFloat(StreamingKMeansDriver.TRIM_FRACTION, 0.9f);
        boolean kMeansPlusPlusInit = !conf.getBoolean(StreamingKMeansDriver.RANDOM_INIT, false);
        boolean correctWeights = !conf.getBoolean(StreamingKMeansDriver.IGNORE_WEIGHTS, false);
        float testProbability = conf.getFloat(StreamingKMeansDriver.TEST_PROBABILITY, 0.1f);
        int numRuns = conf.getInt(StreamingKMeansDriver.NUM_BALLKMEANS_RUNS, 3);

        BallKMeans ballKMeansCluster = new BallKMeans(StreamingKMeansUtilsMR.searcherFromConfiguration(conf),
                numClusters, maxNumIterations, trimFraction, kMeansPlusPlusInit, correctWeights, testProbability,
                numRuns);
        return ballKMeansCluster.cluster(centroids);
    }
}