Hadoop_26_MapReduce_Reduce端使用GroupingComparator求同一订单中最大金额的订单

1. 自定义GroupingComparator

1.1.需求：有如下订单

现在需要求出每一个订单中成交金额最大的一笔交易

1.2.分析：

　　1、利用“订单id和成交金额”Bean作为key，可以将map阶段读取到的所有订单数据按照id分区，按照金额排序，

发送到reduce

　　2、在reduce端利用GroupingComparator将订单id相同的kv聚合成组，然后取第一个即是最大值

定义订单信息bean，实现CompareTo()方法用于排序

package cn.bigdata.hdfs.secondarySort;

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

import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.WritableComparable;

/**
 * 订单信息bean，实现hadoop的序列化机制
 */
public class OrderBean implements WritableComparable<OrderBean>{

    private Text itemid;
    private DoubleWritable amount;

    public OrderBean() {
    }

    public OrderBean(Text itemid, DoubleWritable amount) {
        set(itemid, amount);

    }

    public void set(Text itemid, DoubleWritable amount) {

        this.itemid = itemid;
        this.amount = amount;

    }

    public Text getItemid() {
        return itemid;
    }

    public DoubleWritable getAmount() {
        return amount;
    }
    //1.模型必须实现Comparable<T>接口
    /*2.Collections.sort(list);会自动调用compareTo，如果没有这句，list是不会排序的，也不会调用compareTo方法
      3.如果是数组则用的是Arrays.sort(a)方法*/
    //implements WritableComparable必须要实现的方法,用于比较排序
    @Override
    public int compareTo(OrderBean o) {
        //根據ID排序
        int cmp = this.itemid.compareTo(o.getItemid());
        //id相同根据金额排序
        if (cmp == 0) {
            cmp = -this.amount.compareTo(o.getAmount());
        }
        return cmp;
    }

    @Override
    public void write(DataOutput out) throws IOException {
        out.writeUTF(itemid.toString());
        out.writeDouble(amount.get());
    }

    @Override
    public void readFields(DataInput in) throws IOException {
        String readUTF = in.readUTF();
        double readDouble = in.readDouble();
        
        this.itemid = new Text(readUTF);
        this.amount= new DoubleWritable(readDouble);
    }

    @Override
    public String toString() {
        return itemid.toString() + "\t" + amount.get();
    }
}

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