[grid@hadoop1 ~]$ hadoop fs -cat ./in/7/dept.txt        10 ACCOUNTING     NEW YORK        20 RESEARCH       DALLAS        30 SALES          CHICAGO        40 OPERATIONS     BOSTON[grid@hadoop1 ~]$ hadoop fs -cat ./in/7/emp.txt      7369 SMITH      CLERK           7902 17-12月-80            800                    20      7499 ALLEN      SALESMAN        7698 20-2月 -81           1600        300         30      7521 WARD       SALESMAN        7698 22-2月 -81           1250        500         30      7566 JONES      MANAGER         7839 02-4月 -81           2975                    20      7654 MARTIN     SALESMAN        7698 28-9月 -81           1250       1400         30      7698 BLAKE      MANAGER         7839 01-5月 -81           2850                    30      7782 CLARK      MANAGER         7839 09-6月 -81           2450                    10      7839 KING       PRESIDENT            17-11月-81           5000                    10      7844 TURNER     SALESMAN        7698 08-9月 -81           1500          0         30      7900 JAMES      CLERK           7698 03-12月-81            950                    30      7902 FORD       ANALYST         7566 03-12月-81           3000                    20      7934 MILLER     CLERK           7782 23-1月 -82           1300                    10

dept 文件第一列是部门编号，第二列是部门名称，第三列是部门所在城市

import org.apache.hadoop.io.LongWritable;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Mapper;import java.io.IOException;public class JoinMapper extends Mapper
    
      {	@Override	public void map(LongWritable key, Text value, Context context)			throws IOException, InterruptedException {		String line = value.toString();		if (line.length() > 80) { //判断是左表还是右表			String deptno = line.substring(87, 89);			String sal = line.substring(62, 67).trim();			context.write(new Text(deptno), new Text("A" + sal));		} else {			String deptno = line.substring(8, 10);			String dname = line.substring(11, 25).trim();			context.write(new Text(deptno), new Text("B" + dname));		}	}}import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Reducer;import java.io.IOException;public class JoinReducer extends Reducer
     
       {	@Override	public void reduce(Text key, Iterable
      
        values, Context context)			throws IOException, InterruptedException {		int total = 0, count = 0;		String dname = null;		for (Text value : values) {			if (value.toString().startsWith("A")) {				total += Integer.parseInt(value.toString().substring(1));				count++;			} else {				dname = value.toString().substring(1);			}		}		String avg = (count == 0 ? "--" : ("" + total / count));		context.write(new Text(dname), new Text(count + "	" + avg));	}}import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;import org.apache.hadoop.mapreduce.Job;public class Join {	public static void main(String[] args) throws Exception {		if (args.length != 3) {			System.err.println("Usage: One 
        
        
       
");			System.exit(-1);		}		Job job = new Job();		job.setJarByClass(Join.class);		job.setJobName("Join");		FileInputFormat.addInputPath(job, new Path(args[0]));		FileInputFormat.addInputPath(job, new Path(args[1]));		FileOutputFormat.setOutputPath(job, new Path(args[2]));		job.setMapperClass(JoinMapper.class);		job.setReducerClass(JoinReducer.class);		job.setOutputKeyClass(Text.class);		job.setOutputValueClass(Text.class);		System.exit(job.waitForCompletion(true) ? 0 : 1);	}}
      
     
    

查看输出：

[grid@hadoop1 ~]$ hadoop fs -cat ./out/7/part-r-00000ACCOUNTING	3	2916RESEARCH	3	2258SALES	6	1566OPERATIONS	0	--