pom.xml

<groupId>com.huang</groupId>
    <artifactId>Hadoop</artifactId>
    <version>1.0-SNAPSHOT</version>
    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <configuration>
                    <source>7</source>
                    <target>7</target>
                </configuration>
            </plugin>
        </plugins>
    </build>
    <dependencies>
    <dependency>
        <groupId>junit</groupId>
        <artifactId>junit</artifactId>
        <version>RELEASE</version>
    </dependency>
    <dependency>
        <groupId>org.apache.logging.log4j</groupId>
        <artifactId>log4j-core</artifactId>
        <version>2.8.2</version>
    </dependency>
    <dependency>
        <groupId>org.apache.hadoop</groupId>
        <artifactId>hadoop-common</artifactId>
        <version>2.7.2</version>
    </dependency>
    <dependency>
        <groupId>org.apache.hadoop</groupId>
        <artifactId>hadoop-client</artifactId>
        <version>2.7.2</version>
    </dependency>
    <dependency>
        <groupId>org.apache.hadoop</groupId>
        <artifactId>hadoop-hdfs</artifactId>
        <version>2.7.2</version>
    </dependency>
    <dependency>
        <groupId>junit</groupId>
        <artifactId>junit</artifactId>
        <version>RELEASE</version>
        <scope>compile</scope>
    </dependency>

</dependencies>
</project>

输入数据

order.txt

1001	01	1
1002	02	2
1003	03	3
1004	01	4
1005	02	5
1006	03	6

pd.txt

01	小米
02	华为
03	格力

期望结果

需求分析

Mapper类

package com.mr.mapjoin;

import org.apache.commons.lang.StringUtils;
import org.apache.hadoop.io.IOUtils;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

import java.io.BufferedReader;
import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.net.URI;
import java.util.HashMap;


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


    HashMap<String, String> pdMap = new HashMap<>();
    Text text = new Text();


    @Override
    protected void setup(Context context) throws IOException, InterruptedException {
//        获取到缓存文件，是一个 URI 的数组
        URI[] cacheFiles = context.getCacheFiles();
//        由于只有一个缓存文件 pd.txt，我们这里只需要拿到第一个元素即可
        URI pdUri = cacheFiles[0];
//        获取到缓存文件的路径
        String path = pdUri.getPath();

//        获取到bufferedReader对象（缓冲字符流）
       // FileInputStream fileInputStream = new FileInputStream(path);
       // InputStreamReader inputStreamReader = new InputStreamReader(fileInputStream);
        BufferedReader bufferedReader = new BufferedReader(new InputStreamReader(new FileInputStream(path)));

//        对每行数据做迭代，进行切割，切割后的数据放入到map中
        String line;
       // String line = bufferedReader.readLine();
//        while (!(line = bufferedReader.readLine()).isEmpty()) {
        while (StringUtils.isNotEmpty(line = bufferedReader.readLine())) {
            String[] split = line.split("\t");
            pdMap.put(split[0], split[1]);
        }
//        关闭资源
        IOUtils.closeStream(bufferedReader);

    }

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
//        读取order.txt 的每行数据，并进行切割
        String[] split = value.toString().split("\t");
//        获取 pid 公共字段
        String pid = split[1];
//        根据pid从map中获取到pname
        String pname = pdMap.get(pid);

//        拼接最后的结果
        text.set(split[0] + "\t" + pname + "\t" + split[2]);
        context.write(text, NullWritable.get());

    }
}

Reducer类

无，这里需要，在driver里面设就行

Driver类

package com.mr.mapjoin;

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;

import java.io.IOException;
import java.net.URI;
import java.net.URISyntaxException;


public class MapJoinDriver {
    public static void main(String[] args) throws IOException, URISyntaxException, ClassNotFoundException, InterruptedException {
        args = new String[]{"E:/Hadoop/src/main/resources/input/jointest", "E:/Hadoop/src/main/resources/ouput/join"};

        Configuration configuration = new Configuration();
        Job job = Job.getInstance(configuration);

        job.setJarByClass(MapJoinDriver.class);

        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(NullWritable.class);

        job.setMapperClass(MapJoinMapper.class);

        job.addCacheFile(new URI("file:///E:/Hadoop/src/main/resources/input/tablenum/pd.txt"));
        job.setNumReduceTasks(0);

        FileInputFormat.setInputPaths(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));

        boolean b = job.waitForCompletion(true);
        System.exit(b ? 0 : 1);



    }
}

执行结果