如何在hadoopmapeduce中使用reducer

Question

嗨，我是使用还原剂的新手

将其视为我的输入文件

hi,how,1,a,b,are,you,xxx,xxxx,xxxxx
hi,how,1,a,b,are,you,xxx,xxxx,xxxxx
hi,how,1,a,b,i,am,yyyy,yyyy,yyyy
hi,how,1,a,b,i,am,yyyy,yyyy,yyyy
hi,how,2,a,b,are,you,xxx,xxxx,xxxxx
hi,how,2,a,b,are,you,xxx,xxxx,xxxxx
hi,how,2,a,b,i,am,yyyy,yyyy,yyyy
hi,how,3,a,b,are,you,yyyy,yyyy,yyyy
hi,how,3,a,b,i,am,yyyy,yyyy,yyyy
hi,how,4,a,b,are,you,yyyy,yyyy,yyyy
hi,how,4,a,b,are,you,yyyy,yyyy,yyyy
hi,how,4,a,b,i,am,xxx,xxxx,xxxxx

这是我的地图功能

@Override
        public  void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException 
        {
          String Str_line = value.toString();
          String[] input = Str_line.split(",");
          Text Outkey = new Text();
          Outkey.set(input[2]);
          context.write(Outkey),null);
         }

这是我的还原函数

public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
                context.write(key, null);
            }

我需要这样的输出你好，你好吗，你嗨，你好，我你好，你好，你嗨，你好，2，我嗨，你好，3嗨，你好，3，我你好，你好，你你好，我是

Answer 1

映射器代码：-

  @Override
            public  void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException 
            {
              String Str_line = value.toString();
              String[] input = Str_line.split(",");
              Text Outkey = new Text();
              Outkey.set(input[0]+","+input[1]+","+input[2]+","+input[5]+","+input[6]);
              context.write(Outkey,NullWritable.get);
             }

减速器代码：-

 public void reduce(Text Key,Iterable<NullWritable> Values,Context context) throws IOException, InterruptedException {
       context.write(NullWritable.get(),key);
        }