MapReduce 编程

MapReduce 编程 Wordcount很像 统计海选通票 每个选手得的票数 选秀全国各个地方的投票 写出map 和reduce函数

不会

package com.hpu.hadoop.mapreduce.wordcount;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

import java.io.IOException;

public class WCMapper extends Mapper<LongWritable, Text,Text, IntWritable> {
    private Text text;
    private IntWritable intWritable;

//    @Override
//    protected void setup(Context context) throws IOException, InterruptedException {
//        text = new Text();
//        intWritable = new IntWritable(1);
//    }
//
//    @Override
//    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
//        String line = value.toString();
        //假设一行内容为多个姓名
//        String[] words = line.split(" ");
//        for (String word : words) {
//            text.set(word);
//            context.write(text,intWritable);
//        }
//    }

    @Override
    protected void setup(Context context) throws IOException, InterruptedException {
        text = new Text();
        intWritable = new IntWritable(1);
    }

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        String line = value.toString();
        //假设一行内容为：姓名
        text.set(line);
        context.write(text,intWritable);

    }
}

以上是两种不同数据格式的方案
这里的Reducer代码是WordCount中Reducer的代码一模一样