MapReduce-流量统计求和-排序-Mapper和Reducer编写

定义FlowMapper

package cn.learn.mapreduce_sort;

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

import java.io.IOException;

public class FlowCountSortMapper extends Mapper<LongWritable,Text,FlowBean,Text> {
    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, 
InterruptedException {
        FlowBean flowBean = new FlowBean();
        String[] split = value.toString().split("\t");

        //获取手机号，作为V2
        String phoneNum = split[0];
        //获取其他流量字段,封装flowBean，作为K2
        flowBean.setUpFlow(Integer.parseInt(split[1]));
        flowBean.setDownFlow(Integer.parseInt(split[2]));
        flowBean.setUpCountFlow(Integer.parseInt(split[3]));
        flowBean.setDownCountFlow(Integer.parseInt(split[4]));

        //将K2和V2写入上下文中
        context.write(flowBean, new Text(phoneNum));

    }
}

定义FlowReducer

package cn.learn.mapreduce_sort;

import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

import java.io.IOException;

public class FlowCountSortReducer extends Reducer<FlowBean,Text,Text,FlowBean> {
    @Override
    protected void reduce(FlowBean key, Iterable<Text> values, Context context) throws 
IOException, InterruptedException {
        for (Text value : values) {
            context.write(value, key);
        }
    }
}