Hadoop编写矩阵相乘

Hadoop编写矩阵相乘可以采用MapReduce模型。具体步骤如下：

1. Map阶段：将矩阵分块并读入到Map函数中，同时将矩阵中的非零元素作为键值对传递给Reducer函数。

2. Reduce阶段：将Map阶段得到的键值对传递给Reducer函数，进行矩阵相乘操作，并将结果输出。

下面是代码示例：

Map阶段：

public static class MatrixMapper extends Mapper<LongWritable, Text, Text, Text> {

    private Text outKey = new Text();
    private Text outValue = new Text();

    public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        String[] values = value.toString().split(",");
        int row = Integer.parseInt(values[0]);
        int col = Integer.parseInt(values[1]);
        int val = Integer.parseInt(values[2]);
        if (col == 0) {
            // 第一个矩阵
            outKey.set(row + "");
            outValue.set("A," + col + "," + val);
        } else {
            // 第二个矩阵
            outKey.set(col + "");
            outValue.set("B," + row + "," + val);
        }
        context.write(outKey, outValue);
    }
}

Reduce阶段：

public static class MatrixReducer extends Reducer<Text, Text, Text, IntWritable> {

    private Text outKey = new Text();
    private IntWritable outValue = new IntWritable();

    public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
        Map<Integer, Integer> mapA = new HashMap<Integer, Integer>();
        Map<Integer, Integer> mapB = new HashMap<Integer, Integer>();

        for (Text value : values) {
            String[] data = value.toString().split(",");
            String flag = data[0];
            int row = Integer.parseInt(data[1]);
            int val = Integer.parseInt(data[2]);
            if (flag.equals("A")) {
                mapA.put(row, val);
            } else {
                mapB.put(row, val);
            }
        }

        int result = 0;
        for (Map.Entry<Integer, Integer> entry : mapA.entrySet()) {
            int k = entry.getKey();
            int v = entry.getValue();
            if (mapB.containsKey(k)) {
                result += v * mapB.get(k);
            }
        }

        outKey.set(key);
        outValue.set(result);
        context.write(outKey, outValue);
    }
}

在Driver中设置MapReduce作业的输入、输出路径、Mapper和Reducer类，然后运行作业即可。