用Hadoop扔飞镖算Pi——献给圆周率日

[代码] MapReduce的mainRunner忽略，咱们可根据需要改下输入输出KeyValue的意义 // Mapper
public class PieMapper extends
		Mapper {
	private Random random = new Random();
	  @Override
	protected void map(IntWritable key, LongWritable value, Context context)
			throws IOException, InterruptedException {
		long inside = 0;
		for (int i = 0; i < value.get(); i  ) {
			double a = random.nextDouble();
			double b = random.nextDouble();
			if ((a * a   b * b) <= 1) {
				inside  ;
			}
		}
		context.write(value, new LongWritable(inside));
	}
}
// 输入为第几行（忽略） 本行所算的抛飞镖次数

// Reducer
public class PieReducer extends
		Reducer {
	@Override
	protected void reduce(LongWritable key, Iterable values,
			Context context) throws IOException, InterruptedException {
		long total = 0;
		long inside = 0;
		for (LongWritable value : values) {
			total  = key.get();
			inside  = value.get();
		}
		context.write(key, new DoubleWritable(
				4 * (inside / total)));
	}
}

// 代码大约比较清楚，输出为抛的总次数所对应的算出的圆周率，可以用来对比抛N次所得到的精度。当然Double是非常不精确的，要想更精确则需要从头完成大的浮点类型