Hadoop编写矩阵相乘
时间: 2024-05-05 22:03:23 浏览: 106
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:
```java
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:
```java
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。
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