尚硅谷大数据技术之Hadoop（MapReduce）（新）第3章 MapReduce框架原理

package test;

import java.net.URI;

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.NullWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapreduce.Job;

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

import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class DistributedCacheDriver {

public static void main(String[] args) throws Exception {

// 0 根据自己电脑路径重新配置

args = new String[]{"e:/input/inputtable2", "e:/output1"};

// 1 获取job信息

Configuration configuration = new Configuration();

Job job = Job.getInstance(configuration);

// 2 设置加载jar包路径

job.setJarByClass(DistributedCacheDriver.class);

// 3 关联map

job.setMapperClass(DistributedCacheMapper.class);

// 4 设置最终输出数据类型

job.setOutputKeyClass(Text.class);

job.setOutputValueClass(NullWritable.class);

// 5 设置输入输出路径

FileInputFormat.setInputPaths(job, new Path(args[0]));

FileOutputFormat.setOutputPath(job, new Path(args[1]));

// 6 加载缓存数据

job.addCacheFile(new URI("file:///e:/input/inputcache/pd.txt"));

// 7 Map端Join的逻辑不需要Reduce阶段，设置reduceTask数量为0

job.setNumReduceTasks(0);

// 8 提交

boolean result = job.waitForCompletion(true);

System.exit(result ? 0 : 1);

}

}

package test;

import java.io.BufferedReader;

import java.io.FileInputStream;

import java.io.IOException;

import java.io.InputStreamReader;

import java.util.HashMap;

import java.util.Map;

import org.apache.commons.lang.StringUtils;

import org.apache.hadoop.io.LongWritable;

import org.apache.hadoop.io.NullWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapreduce.Mapper;

public class DistributedCacheMapper extends Mapper<LongWritable, Text, Text, NullWritable>{

Map<String, String> pdMap = new HashMap<>();

@Override

protected void setup(Mapper<LongWritable, Text, Text, NullWritable>.Context context) throws IOException, InterruptedException {

// 1 获取缓存的文件

URI[] cacheFiles = context.getCacheFiles();

String path = cacheFiles[0].getPath().toString();

BufferedReader reader = new BufferedReader(new InputStreamReader(new FileInputStream(path), "UTF-8"));

String line;

while(StringUtils.isNotEmpty(line = reader.readLine())){

// 2 切割

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

// 3 缓存数据到集合

pdMap.put(fields[0], fields[1]);

}

// 4 关流

reader.close();

}

Text k = new Text();

@Override

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

// 1 获取一行

String line = value.toString();

// 2 截取

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

// 3 获取产品id

String pId = fields[1];

// 4 获取商品名称

String pdName = pdMap.get(pId);

// 5 拼接

k.set(line + "\t"+ pdName);

// 6 写出

context.write(k, NullWritable.get());

}

}