如何在mapReduce Hadoop框架中排序值(与其对应的键)？

import org.apache.hadoop.io.Text;
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.output.FileOutputFormat;
import org.apache.hadoop.conf.Configuration;

public class SortValues {
  
  public static class SortMapper extends Mapper<Object, Text, IntWritable, Text> {
    
    private IntWritable value = new IntWritable();
    private Text key = new Text();
    
    public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
      // 将输入的键值对拆分为键和值
      String[] parts = value.toString().split("\t");
      key.set(parts[0]);
      value.set(Integer.parseInt(parts[1]));
      
      // 将值作为键，键作为值输出
      context.write(value, key);
    }
  }
  
  public static class SortReducer extends Reducer<IntWritable, Text, Text, IntWritable> {
    
    public void reduce(IntWritable key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
      // 将键值对进行反转，输出结果
      for (Text value : values) {
        context.write(value, key);
      }
    }
  }
  
  public static void main(String[] args) throws Exception {
    Configuration conf = new Configuration();
    Job job = Job.getInstance(conf, "sort values");
    job.setJarByClass(SortValues.class);
    job.setMapperClass(SortMapper.class);
    job.setReducerClass(SortReducer.class);
    job.setOutputKeyClass(IntWritable.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);
  }
}