MR案例：外连接代码实现

【外连接】是在【内连接】的基础上稍微修改即可。具体HQL语句详见Hive查询Join

package join.map;import java.io.IOException;
import java.util.ArrayList;
import java.util.List;import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.VLongWritable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.FileSplit;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;public class JoinOn {    public static void main(String[] args) throws Exception {        //临时配置windows的环境变量
        System.setProperty("hadoop.home.dir", "D:\\workspace\\hadoop-2.2.0");        Configuration conf = new Configuration();
        Job job = Job.getInstance(conf);
        job.setJarByClass(JoinOn.class);        job.setMapperClass(JOMapper.class);
        job.setReducerClass(JOReducer.class);        job.setMapOutputKeyClass(VLongWritable.class);
        job.setMapOutputValueClass(Text.class);        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);        FileInputFormat.addInputPath(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));        System.exit(job.waitForCompletion(true)? 0:1);    }    public static class JOMapper extends Mapper<LongWritable, Text, VLongWritable, Text>{
        @Override
        protected void map(LongWritable key, Text value, Context context)
                throws IOException, InterruptedException {            //获取当前分片所对应的文件名
            String name = ((FileSplit)context.getInputSplit()).getPath().getName();            String[] splited = value.toString().split("\t");            if(name.endsWith("sales")){                //sales表
                //<key,value> --> <id, things+':'+name+'\t'+id>
                context.write(new VLongWritable(Long.parseLong(splited[1])), new Text(name+":"+value.toString()));
            }else if(name.endsWith("things")) {

                //<key,value> --> <id, sales+':'+id+'\t'+name>
                context.write(new VLongWritable(Long.parseLong(splited[0])), new Text(name+":"+value.toString()));
            }
        }
    }    public static class JOReducer extends Reducer<VLongWritable, Text, Text, Text>{
        @Override
        protected void reduce(VLongWritable key, Iterable<Text> v2s, Context context)
                throws IOException, InterruptedException {            //分别存储sales和things两表的name
            List<String> sales=new ArrayList<String>();
            List<String> things=new ArrayList<String>();            for(Text text : v2s){
                String[] splited = text.toString().split(":");                //sales表中的数据
                if(splited[0].endsWith("sales")){                    //加入集合
                    sales.add(splited[1]);
                }
                //things表中数据
                else if(splited[0].endsWith("things")){
                    things.add(splited[1]);
                }
            }
            //笛卡尔积
            /**
             * 左外连接：只要求左表中有数据即可
             */
            if(sales.size()!=0 /*&& things.size()!=0*/){
                for(String sale : sales){

 
                    //如果右表中没有数据,则使用 NULL 代替
                    if(things.size()==0){
                        context.write(new Text(sale), new Text("NULL"+"\t"+"NILL"));

 
                    }else {//如果右表中有数据，则直接输出
                        for(String thing : things){
                            context.write(new Text(sale), new Text(thing));
                        }
                    }
                }
            }
        }
    }
}

总结：

　1).左外连接：左表全部显示，右表不匹配的部分以NULL替代。

　2).代码实现即要求左表不为空即可，右表为空则以NULL输出，右表不为空则直接输出。