ReduceJoin 案例 Mapper| 学习笔记

package com.liun.mr.reducejoin;

import java.io.IOException;

import org.apache.hadoop.io.LongWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapreduce.Mapper;

import org.apache.hadoop.mapreduce.lib.input.FileSplit;

public class TableMapper extends Mapper<LongWritable, Text, Text, TableBean> {

String name;

TableBean tableBean = new TableBean();

Text k = new Text();

@Override

protected void setup(Context context) throws IOException, InterruptedException {

// 获取文件名称

FileSplit inputSplit = (FileSplit) context.getInputSplit();

name = inputSplit.getPath().getName();

}

@Override

protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {

// 获取一行

String line = value.toString();

if (name.startsWith("order")) {// 订单表

String[] fields = line.split("\t");

tableBean.setOrder_id(fields[0]);

tableBean.setP_id(fields[1]);

tableBean.setAmount(Integer.parseInt(fields[2]));

tableBean.setPname("");

tableBean.setFlag("order");

k.set(fields[1]);

} else {// 产品表

String[] fields = line.split("\t");

tableBean.setOrder_id("");

tableBean.setP_id(fields[0]);

tableBean.setAmount(0);

tableBean.setPname(fields[1]);

tableBean.setFlag("pd");

k.set(fields[0]);

}

// 写出

context.write(k, tableBean);

}

}