mapreducr-分组GroupingComparator

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分组操作排序又称辅助排序，是在reducer操作之前对mapper传出的kv值进行shuffle操作并归并排序之后，对kv值进行的一系列操

作，比如对key中相同的一项或者两项相同的数据归为一组，以分组好的一个key值传入values。

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需求：

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实例：

注意在这个实例中为分组，并不是实际意义上的按照id相同的分为一组，要注意到在归并排序好的kv中，id相同的kv值其实还是分开的，只是根据compre方法的特殊性判断下一个key是否按照业务逻辑相同，从而选择性的跳过找到最大的订单金额。

key封装对象：

package com.order.bean;

//import org.apache.hadoop.hdfs.protocol.SnapshotInfo;
import org.apache.hadoop.io.WritableComparable;

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

public class orderBean implements WritableComparable<orderBean> {

    private int order_id;
    private double price;

    public orderBean() {
        super();
    }

    public orderBean(int order_id, double price) {
        super();
        this.order_id = order_id;
        this.price = price;
    }

    @Override
    public int compareTo(orderBean bean) {
        int res;
        if (order_id>bean.order_id) {
            res = 1;
        } else if (order_id<bean.order_id) {
            res = -1;
        } else {
            if (price>bean.price) {
                res = -1;
            } else if (price<bean.price) {
                res = 1;
            } else {
                res = 0;
            }
        }
        return res;
    }

    @Override
    public void write(DataOutput dataOutput) throws IOException {
        dataOutput.writeInt(order_id);
        dataOutput.writeDouble(price);
    }

    @Override
    public void readFields(DataInput dataInput) throws IOException {
        order_id = dataInput.readInt();
        price = dataInput.readDouble();
    }

    public int getOrder_id() {
        return order_id;
    }

    public double getPrice() {
        return price;
    }

    public void setOrder_id(int order_id) {
        this.order_id = order_id;
    }

    public void setPrice(double price) {
        this.price = price;
    }

    @Override
    public String toString() {
        return "order_id=" + order_id +
                " price=" + price;
    }
}

mapper：

package com.order.bean;

import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

import java.io.IOException;

public class orderMapper extends Mapper<LongWritable, Text,orderBean, NullWritable> {

    orderBean k = new orderBean();
    //NullWritable v = new NullWritable();

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        //super.map(key, value, context);

        String[] line = value.toString().split(" ");

        k.setOrder_id(Integer.parseInt(line[0]));
        k.setPrice(Double.parseDouble(line[2]));

        context.write(k,NullWritable.get());
    }
}

GroupingCompator

package com.order.bean;

import org.apache.hadoop.io.WritableComparable;
import org.apache.hadoop.io.WritableComparator;

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

public class orderGroupingComparator extends WritableComparator {

    protected orderGroupingComparator() {
        super(orderBean.class,true);
    }

    @Override
    public int compare(WritableComparable a, WritableComparable b) {
        int result;
        orderBean aBean = (orderBean)a;
        orderBean bBean = (orderBean)b;
        if (aBean.getOrder_id()>bBean.getOrder_id()) {
            result = 1;
        } else if (aBean.getOrder_id()<bBean.getOrder_id()) {
            result = -1;
        } else {
            result = 0;
        }
        return result;
    }
}

orderReducer：

package com.order.bean;

import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.Reducer;

import java.io.IOException;

public class orderReducer extends Reducer<orderBean, NullWritable,orderBean,NullWritable> {
    @Override
    protected void reduce(orderBean key, Iterable<NullWritable> values, Context context) throws IOException, InterruptedException {
        context.write(key,NullWritable.get());
    }
}

驱动类：

package com.order.bean;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

import java.io.IOException;

public class orderDriver {
    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {

        args = new String[]{"D:/mapreduceinput/input1","D:/mapreduceoutput/outputgroup"};
        Job job = Job.getInstance(new Configuration());

        job.setJarByClass(orderDriver.class);

        job.setMapperClass(orderMapper.class);
        job.setReducerClass(orderReducer.class);

        job.setMapOutputKeyClass(orderBean.class);
        job.setMapOutputValueClass(NullWritable.class);

        job.setOutputKeyClass(orderBean.class);
        job.setOutputValueClass(NullWritable.class);

        job.setGroupingComparatorClass(orderGroupingComparator.class);

        FileInputFormat.setInputPaths(job,new Path(args[0]));
        FileOutputFormat.setOutputPath(job,new Path(args[1]));

        boolean result = job.waitForCompletion(true);
        System.exit(result?0:1);
    }
}