hadoop编写矩阵相乘Java

使用Hadoop进行矩阵相乘需要进行以下步骤：

1. 将矩阵数据分成小块，存储在Hadoop分布式文件系统中，每个块大小由用户指定。
2. 编写Map函数，将矩阵块进行分割，并将乘积放入context中。
3. 编写Reduce函数，对Map函数输出的结果进行合并，得到最终矩阵乘积。

下面是一个简单的矩阵相乘的Java程序：

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class MatrixMultiply {

  public static class MatrixMapper extends Mapper<Object, Text, Text, DoubleWritable>{

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

    public void map(Object key, Text value, Context context
                    ) throws IOException, InterruptedException {
      String[] parts = value.toString().split(",");
      int row = Integer.parseInt(parts[0]);
      int col = Integer.parseInt(parts[1]);
      double val = Double.parseDouble(parts[2]);

      //处理矩阵A的每一行
      if (parts[3].equals("A")) {
        for (int i = 1; i <= N; i++) {
          outKey.set(row + "," + i);
          outValue.set(val);
          context.write(outKey, outValue);
        }
      }
      //处理矩阵B的每一列
      else if (parts[3].equals("B")) {
        for (int i = 1; i <= N; i++) {
          outKey.set(i + "," + col);
          outValue.set(val);
          context.write(outKey, outValue);
        }
      }
    }
  }

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

    private DoubleWritable outValue = new DoubleWritable();

    public void reduce(Text key, Iterable<DoubleWritable> values,
                       Context context
                       ) throws IOException, InterruptedException {
      double sum = 0.0;
      for (DoubleWritable val : values) {
        sum += val.get();
      }
      outValue.set(sum);
      context.write(key, outValue);
    }
  }

  public static void main(String[] args) throws Exception {
    Configuration conf = new Configuration();
    Job job = Job.getInstance(conf, "matrix multiply");
    job.setJarByClass(MatrixMultiply.class);
    job.setMapperClass(MatrixMapper.class);
    job.setReducerClass(MatrixReducer.class);
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(DoubleWritable.class);
    FileInputFormat.setInputPaths(job, new Path(args[0]));
    FileOutputFormat.setOutputPath(job, new Path(args[1]));
    job.waitForCompletion(true);
  }
}

其中，输入文件的格式如下：

i,j,value,matrix(A/B)

例如：

1,1,2.0,A
1,2,3.0,A
2,1,1.0,A
2,2,4.0,A
1,1,5.0,B
1,2,6.0,B
2,1,7.0,B
2,2,8.0,B

其中A矩阵为：

2.0 3.0
1.0 4.0

B矩阵为：

5.0 6.0
7.0 8.0

输出结果为：

1,1 19.0
1,2 26.0
2,1 33.0
2,2 50.0