java - 如何重新排列wordcount hadoop输出结果并按值排序

Question

我使用下面的代码来获得输出结果，如(键，值)

Apple 12
Bee 345 
Cat 123

我想要的是按值 ( 345 ) 降序排序并将它们放在键 ( Value , Key ) 之前

345 Bee
123 Cat
12 Apple

我发现有一种叫做“二次排序”的东西不会说谎，但我迷路了 - 我试图改变 .. context.write(key, result); 但惨败。我是 Hadoop 的新手，不确定如何开始解决这个问题。任何建议将不胜感激。我需要更改哪个功能？或者我需要修改哪个类？

这是我的类(class):

package org.apache.hadoop.examples;

import java.io.IOException;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
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.util.GenericOptionsParser;

public class WordCount {

  public static class TokenizerMapper 
       extends Mapper<Object, Text, Text, IntWritable>{

    private final static IntWritable one = new IntWritable(1);
    private Text word = new Text();

    public void map(Object key, Text value, Context context
                    ) throws IOException, InterruptedException {
      StringTokenizer itr = new StringTokenizer(value.toString());
      while (itr.hasMoreTokens()) {
        word.set(itr.nextToken());
        context.write(word, one);
      }
    }
  }

  public static class IntSumReducer 
       extends Reducer<Text,IntWritable,Text,IntWritable> {
    private IntWritable result = new IntWritable();

    public void reduce(Text key, Iterable<IntWritable> values, 
                       Context context
                       ) throws IOException, InterruptedException {
      int sum = 0;
      for (IntWritable val : values) {
        sum += val.get();
      }
      result.set(sum);
      context.write(key, result);
    }
  }

  public static void main(String[] args) throws Exception {
    Configuration conf = new Configuration();
    String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
    if (otherArgs.length < 2) {
      System.err.println("Usage: wordcount <in> [<in>...] <out>");
      System.exit(2);
    }
    Job job = new Job(conf, "word count");
    job.setJarByClass(WordCount.class);
    job.setMapperClass(TokenizerMapper.class);
    job.setCombinerClass(IntSumReducer.class);
    job.setReducerClass(IntSumReducer.class);
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(IntWritable.class);
    for (int i = 0; i < otherArgs.length - 1; ++i) {
      FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
    }
    FileOutputFormat.setOutputPath(job,
      new Path(otherArgs[otherArgs.length - 1]));
    System.exit(job.waitForCompletion(true) ? 0 : 1);
  }
}

Answer 1

您已经能够正确地进行字数统计。

您将需要第二个 map only 作业来执行降序排序和键值交换的第二个要求

1. 使用 DecreasingComparator 作为排序比较器
2. 使用 InverseMapper 交换键值
3. 使用 Identity Reducer，即 Reducer.class - 如果使用 Identity Reducer，则不会发生聚合(因为每个值都是针对键单独输出的)
4. 将 reduce 任务数设置为 1 或使用 TotalOderPartitioner