Mapper Reduce核心模块代码（此版本无法直接运行，完善代码结构与调用+配置环境后可运行）

 KMeansMapper.java

public class KMeansMapper extends Mapper<LongWritable, Text,Text,Text> {
    String centerArray[] = null; //质心坐标字符串,坐标用",“分割
    double centers[][] = new double[Center.k][]; //每个质心每一维度的坐标

    //获得初始质心
    @Override
    protected void setup(Context context) 
        throws IOException, InterruptedException {
        String centerSource = context.getConfiguration().get(Main.FLAG);
        //为到所有质心字符串数组,centerArray.Length为质心个数
        centerArray = centerSource.split("\t");
        for (int i = 0; i < centerArray.length; i++) {
            //centerArray.Length为质心个数
            String center[] = centerArray[i].split(",");
            centers[i] = new double[center.length];
            for (int j = 0; j < center.length; j++) {
                centers[i][j] = Double.parseDouble(center[j]);
            }
        }
    }

    @Override
    protected void map(LongWritable key, Text value, Context context) 
        throws IOException, InterruptedException {
        String line = value.toString();
        String vector[] = line.split(",");
        double sample[]=new double[vector.length];   //质心维度数量
        for(int i=0; i < vector.length; i++){
            sample[i] = Double.parseDouble(vector[i]);
        }
        double min = Double.MAX_VALUE; //最小距离
        int index = 0;  //索引
        for(int i = 0; i < centers.length; i++){
            double distance = culDistance(sample, centers[i]);
            // 找到最小距离质心
            if(min > distance){
                min = distance;
                index = i;
                System.out.println(distance);
            }
        }
        //<质心, 其他数据点>
        context.write(new Text(centerArray[index]), value);
    }
}

KMeansCombiner.java

public class KMeansCombiner extends Reducer<Text, Text, Text, Text>{
    @Override
    protected void reduce(Text key, Iterable<Text> values, Context context) 
        throws IOException, InterruptedException {
        int length = key.toString().split(",").length;
        double center[] = new double[length];
        int size = 0;

        //迭代读取
        Iterator<Text> iterator = values.iterator();
        while(iterator.hasNext()){
            String centers[] = iterator.next().toString().split(",");
            for(int i = 0; i< length; i++){
                center[i] += Double.parseDouble(centers[i]);
            }
            size++;
        }
        
        StringBuffer stringBuffer = new StringBuffer();
        for(int i=0; i < center.length; i++){
            center[i] /= size;
            stringBuffer.append(center);
            stringBuffer.append(",");
        }
        stringBuffer.deleteCharAt(stringBuffer.toString().length() - 1);

        //更新
        context.write(key, new Text(stringBuffer.toString()));
    }
}

KMeansReducer.java

public class KMeansReducer extends Reducer<Text, Text, Text, NullWritable>{
    //引入计数器
    Counter counter = null;

    @Override
    protected void reduce(Text key, Iterable<Text> values, Context context) 
        throws IOException, InterruptedException {
        int length = key.toString().split(",").length;
        //保存新生成的簇中心
        double newCenter[] = new double[length];
        int size = 0; //向量数
        for(Text value : values){
            String centers[] = value.toString().split(",");
            for(int i = 0; i < centers.length; i++){
                //累加 
                newCenter[i] += Double.parseDouble(centers[i]);
            }
            size++;
        }

        StringBuffer stringBuffer = new StringBuffer();
        for(int i=0; i< newCenter.length; i++){
            newCenter[i] /= size; //均值
            stringBuffer.append(newCenter[i]);
            stringBuffer.append(",");
        }
        stringBuffer.deleteCharAt(stringBuffer.toString().length() - 1);

        //接收旧坐标
        String oldCenterStr[] = key.toString.split(",");
        double oldCenter[] = new double[oldCenterStr.length];
        for(int i=0; i<oldCenterStr.length; i++){
            oldCenter[i] = Double.parseDouble(oldCenterStr[i]);
        }
        //查看是否收敛
        boolean flag = isConverged(oldCenter, newCenter);

        //若收敛，即可确定质心
        if(flag){
            counter = context.getCounter("myCounter", "kmeansCounter");
            counter.increment(1l);
        }
        context.write(new Text(stringBuffer.toString().trim()), NullWritable.get());
    }
}