org.ankus.mapreduce.algorithms.clustering.kmeans.KMeansClusterAssignFinalMapper.java Source code

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Here is the source code for org.ankus.mapreduce.algorithms.clustering.kmeans.KMeansClusterAssignFinalMapper.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.ankus.mapreduce.algorithms.clustering.kmeans;

import java.io.IOException;

import org.ankus.util.CommonMethods;
import org.ankus.util.ArgumentsConstants;
import org.ankus.util.ConfigurationVariable;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

/**
 * KMeansClusterAssignFinalMapper
 * @desc final mapper class for k-means mr job
 *
 * @version 0.0.1
 * @date : 2013.08.22
 * @author Moonie
 */
public class KMeansClusterAssignFinalMapper extends Mapper<Object, Text, NullWritable, Text> {

    String mDelimiter; // delimiter for attribute separation

    int mIndexArr[]; // index array used as clustering feature
    int mNominalIndexArr[]; // index array of nominal attributes used as clustering features
    int mExceptionIndexArr[]; // index array do not used as clustering features

    int mClusterCnt; // cluster count
    KMeansClusterInfoMgr mClusters[]; // clusters

    @Override
    protected void cleanup(Context context) throws IOException, InterruptedException {

    }

    @Override
    protected void map(Object key, Text value, Context context) throws IOException, InterruptedException {
        String[] columns = value.toString().split(mDelimiter);
        int clusterIndex = -1;

        String writeValueStr = "";
        /**
         * cluster index get
         */
        double distMin = 99999999;
        for (int k = 0; k < mClusterCnt; k++) {
            double attrDistanceSum = 0;
            double attrCnt = 0;

            for (int i = 0; i < columns.length; i++) {
                double distAttr = 0;

                if (CommonMethods.isContainIndex(mIndexArr, i, true)
                        && !CommonMethods.isContainIndex(mExceptionIndexArr, i, false)) {
                    attrCnt++;
                    if (CommonMethods.isContainIndex(mNominalIndexArr, i, false)) {
                        distAttr = mClusters[k].getAttributeDistance(i, columns[i],
                                ConfigurationVariable.NOMINAL_ATTRIBUTE);
                    } else
                        distAttr = mClusters[k].getAttributeDistance(i, columns[i],
                                ConfigurationVariable.NUMERIC_ATTRIBUTE);

                    attrDistanceSum += Math.pow(distAttr, 2);

                    if (k == 0)
                        writeValueStr += columns[i] + mDelimiter;
                }

            }

            double dist = Math.sqrt(attrDistanceSum);
            if (dist < distMin) {
                distMin = dist;
                clusterIndex = k;
            }
        }

        //      context.write(NullWritable.get(), new Text(value + mDelimiter + clusterIndex + mDelimiter + distMin));
        context.write(NullWritable.get(), new Text(writeValueStr + clusterIndex + mDelimiter + distMin));
    }

    @Override
    protected void setup(Context context) throws IOException, InterruptedException {
        Configuration conf = context.getConfiguration();

        mDelimiter = conf.get(ArgumentsConstants.DELIMITER, "\t");

        mIndexArr = CommonMethods.convertIndexStr2IntArr(conf.get(ArgumentsConstants.TARGET_INDEX, "-1"));
        mNominalIndexArr = CommonMethods.convertIndexStr2IntArr(conf.get(ArgumentsConstants.NOMINAL_INDEX, "-1"));
        mExceptionIndexArr = CommonMethods
                .convertIndexStr2IntArr(conf.get(ArgumentsConstants.EXCEPTION_INDEX, "-1"));

        mClusterCnt = Integer.parseInt(conf.get(ArgumentsConstants.CLUSTER_COUNT, "1"));

        // cluster load and setting
        Path clusterPath = new Path(conf.get(ArgumentsConstants.CLUSTER_PATH, null));
        mClusters = KMeansClusterInfoMgr.loadClusterInfoFile(conf, clusterPath, mClusterCnt, mDelimiter);
    }

}