com.alimama.quanjingmonitor.kmeans.KMeansClusterMapper.java Source code

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Here is the source code for com.alimama.quanjingmonitor.kmeans.KMeansClusterMapper.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 com.alimama.quanjingmonitor.kmeans;

import java.io.IOException;
import java.util.ArrayList;
import java.util.Collection;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.WritableComparable;
import org.apache.hadoop.mapreduce.Mapper;

public class KMeansClusterMapper extends Mapper<WritableComparable<?>, Text, Text, Text> {

    ParseVector parse = new ParseVector();

    @Override
    protected void map(WritableComparable<?> key, Text point, Context context)
            throws IOException, InterruptedException {

        Cluster nearestCluster = null;
        double nearestDistance = Integer.MAX_VALUE;
        Vector pointv = parse.parseVector(point.toString());
        if (pointv == null) {
            return;
        }
        pointv.setNumPoints(1);
        for (Cluster cluster : clusters) {
            Vector clusterCenter = cluster.getCenter();
            boolean isDeny = clusterCenter.Deny(pointv);
            if (isDeny) {
                continue;
            }
            double distance = clusterCenter.distiance(pointv);
            context.getCounter("Clustering", "similar").increment(1);

            if (distance <= nearestDistance || nearestCluster == null) {
                nearestCluster = cluster;
                nearestDistance = distance;
            }
        }
        if (nearestCluster != null) {
            context.write(new Text(String.valueOf(nearestCluster.getId())),
                    new Text(String.valueOf(nearestDistance) + "@abtest@" + point.toString()));
        }

    }

    private final Collection<Cluster> clusters = new ArrayList<Cluster>();

    @Override
    protected void setup(Context context) throws IOException, InterruptedException {
        super.setup(context);
        this.clusters.clear();

        Configuration conf = context.getConfiguration();
        parse.setup(conf);

        try {

            String clusterPath = conf.get(KMeansDriver.CLUSTER_PATH_KEY);
            if (clusterPath != null && clusterPath.length() > 0) {
                KmeansPublic.configureWithClusterInfo(conf, new Path(clusterPath), clusters);
                if (clusters.isEmpty()) {
                    throw new IllegalStateException("No clusters found. Check your -c path.");
                }
            }
        } catch (Throwable e) {
            throw new IllegalStateException(e);
        }
    }

}