二次排序

输入文件 sort.txt 内容为

40 20  
40 10  
40 30  
40 5  
30 30  
30 20  
30 10  
30 40  
50 20  
50 50  
50 10  
50 60  

输出文件的内容（从小到大排序）如下

30 10  
30 20  
30 30  
30 40  
--------  
40 5  
40 10  
40 20  
40 30  
-------- 
50 10  
50 20  
50 50  
50 60  

从输出的结果可以看出Key实现了从小到大的排序，同时相同Key的Value也实现了从小到大的排序，这就是二次排序的结果

在本例中要比较两次。先按照第一字段排序，然后再对第一字段相同的按照第二字段排序。根据这一点，我们可以构造一个复合类IntPair ，它有两个字段，先利用分区对第一字段排序，再利用分区内的比较对第二字段排序。二次排序的流程分为以下几步。
1、自定义 key
2、自定义分区
3、Key的比较类
4、定义分组类函数

  package com.qr.mr.secondarysort;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Partitioner;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.util.*;

public class SecondarySort {
//    1、自定义 key
    public static class IntPair implements WritableComparable<IntPair> {
        private int first = 0;
        private int second = 0;

        /**
         * Read the two integers.
         * Encoded as: MIN_VALUE -&gt; 0, 0 -&gt; -MIN_VALUE, MAX_VALUE-&gt; -1
         */
        @Override
        public void readFields(DataInput in) throws IOException {
            first = in.readInt();
            second = in.readInt();
        }
        @Override
        public void write(DataOutput out) throws IOException {
            out.writeInt(first);
            out.writeInt(second);
        }
        @Override
        public int hashCode() {
            return first * 157 + second;
        }
        @Override
        public boolean equals(Object right) {
            if (right instanceof IntPair) {
                IntPair r = (IntPair) right;
                return r.first == first && r.second == second;
            } else {
                return false;
            }
        }

        @Override
        public int compareTo(IntPair o) {
            if (first != o.first) {
                return first < o.first ? -1 : 1;
            } else if (second != o.second) {
                return second < o.second ? -1 : 1;
            } else {
                return 0;
            }
        }

        /**
         * Set the left and right values.
         */
        public void set(int left, int right) {
            first = left;
            second = right;
        }
        public int getFirst() {
            return first;
        }
        public int getSecond() {
            return second;
        }
    }
//    2、自定义分区
    public static class FirstPartitioner extends Partitioner<IntPair,IntWritable> {
        @Override
        public int getPartition(IntPair key, IntWritable value, int numPartitions) {
            return Math.abs(key.getFirst() * 127) % numPartitions;
        }
    }
//    3、Key的比较类
    public static class FirstGroupingComparator implements RawComparator<IntPair> {
        @Override
        public int compare(byte[] b1, int s1, int l1, byte[] b2, int s2, int l2) {
            return WritableComparator.compareBytes(b1, s1, Integer.SIZE/8,
                    b2, s2, Integer.SIZE/8);
        }

        @Override
        public int compare(IntPair o1, IntPair o2) {
            int l = o1.getFirst();
            int r = o2.getFirst();
            return l == r ? 0 : (l < r ? -1 : 1);
        }
    }


    public static class MapClass extends Mapper<Object, Text,IntPair, IntWritable>{
        private final IntPair key = new IntPair();
        private final IntWritable value = new IntWritable();

        @Override
        public void map(Object inKey, Text inValue,
                        Context context) throws IOException, InterruptedException {
            StringTokenizer itr = new StringTokenizer(inValue.toString());
            int left = 0;
            int right = 0;
            if (itr.hasMoreTokens()) {
                left = Integer.parseInt(itr.nextToken());
                if (itr.hasMoreTokens()) {
                    right = Integer.parseInt(itr.nextToken());
                }
                key.set(left, right);
                value.set(right);
                context.write(key, value);
            }
        }

    }
    public static class Reduce extends Reducer<IntPair,IntWritable,Text,IntWritable>{
        private static final Text SEPARATOR =
                new Text("------------------------------------------------");
        private final Text first = new Text();
        public void reduce(IntPair key,Iterable<IntWritable> values,Context context) throws IOException, InterruptedException {
            context.write(SEPARATOR, null);
            first.set(Integer.toString(key.getFirst()));
            for(IntWritable value: values) {
                context.write(first, value);
            }
        }
    }

    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Configuration conf = new Configuration();
        Job job = Job.getInstance(conf, "secondary sort");
        job.setJarByClass(SecondarySort.class);
        job.setMapperClass(MapClass.class);
        job.setReducerClass(Reduce.class);

        // group and partition by the first int in the pair
        job.setPartitionerClass(FirstPartitioner.class);
        job.setGroupingComparatorClass(FirstGroupingComparator.class);

        // the map output is IntPair, IntWritable
        job.setMapOutputKeyClass(IntPair.class);
        job.setMapOutputValueClass(IntWritable.class);

        // the reduce output is Text, IntWritable
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

        FileInputFormat.addInputPath(job, new Path("/Users/lifei/qrproject/hiveudf/src/main/java/com/qr/mr/secondarysort/sort.txt"));
        FileOutputFormat.setOutputPath(job, new Path("/Users/lifei/qrproject/hiveudf/src/main/java/com/qr/mr/secondarysort/out"));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}