大数据之Hadoop(MapReduce)：GroupingComparator分组案例实操

Posted 2021-06-26 浊酒南街

目录

• 1.需求
• 2.需求分析
• 3.代码实现

1.需求

有如下订单数据，现在需要求出每一个订单中最贵的商品。
（1）输入数据 GroupingComparator.txt

0000001	Pdt_01	222.8
0000002	Pdt_05	722.4
0000001	Pdt_02	33.8
0000003	Pdt_06	232.8
0000003	Pdt_02	33.8
0000002	Pdt_03	522.8
0000002	Pdt_04	122.4

（2）期望输出数据

1	222.8
2	722.4
3	232.8

2.需求分析

（1）利用“订单id和成交金额”作为key，可以将Map阶段读取到的所有订单数据按照id升序排序，如果id相同再按照金额降序排序，发送到Reduce。
（2）在Reduce端利用groupingComparator将订单id相同的kv聚合成组，然后取第一个即是该订单中最贵商品，如图4-18所示。

3.代码实现

（1）定义订单信息OrderBean类

package com.jinghang.mapreduce.order;
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import org.apache.hadoop.io.WritableComparable;

public class OrderBean implements WritableComparable<OrderBean> {

	private int order_id; // 订单id号
	private double price; // 价格

	public OrderBean() {
		super();
	}

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

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

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

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

	public int getOrder_id() {
		return order_id;
	}

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

	public double getPrice() {
		return price;
	}

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

	// 二次排序
	@Override
	public int compareTo(OrderBean o) {

		int result;

		if (order_id > o.getOrder_id()) {
			result = 1;
		} else if (order_id < o.getOrder_id()) {
			result = -1;
		} else {
			// 价格倒序排序
			result = price > o.getPrice() ? -1 : 1;
		}

		return result;
	}
}

（2）编写OrderSortMapper类

package com.jinghang.mapreduce.order;
import java.io.IOException;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

public class OrderMapper extends Mapper<LongWritable, Text, OrderBean, NullWritable> {

	OrderBean k = new OrderBean();
	
	@Override
	protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
		
		// 1 获取一行
		String line = value.toString();
		
		// 2 截取
		String[] fields = line.split("\\t");
		
		// 3 封装对象
		k.setOrder_id(Integer.parseInt(fields[0]));
		k.setPrice(Double.parseDouble(fields[2]));
		
		// 4 写出
		context.write(k, NullWritable.get());
	}
}

（3）编写OrderSortGroupingComparator类

package com.jinghang.mapreduce.order;
import org.apache.hadoop.io.WritableComparable;
import org.apache.hadoop.io.WritableComparator;

public class OrderGroupingComparator extends WritableComparator {

	protected OrderGroupingComparator() {
		super(OrderBean.class, true);
	}

	@Override
	public int compare(WritableComparable a, WritableComparable b) {

		OrderBean aBean = (OrderBean) a;
		OrderBean bBean = (OrderBean) b;

		int result;
		if (aBean.getOrder_id() > bBean.getOrder_id()) {
			result = 1;
		} else if (aBean.getOrder_id() < bBean.getOrder_id()) {
			result = -1;
		} else {
			result = 0;
		}

		return result;
	}
}

（4）编写OrderSortReducer类

package com.jinghang.mapreduce.order;
import java.io.IOException;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.mapreduce.Reducer;

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());
	}
}

（5）编写OrderSortDriver类

package com.jinghang.mapreduce.order;
import java.io.IOException;
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;

public class OrderDriver {

	public static void main(String[] args) throws Exception, IOException {

// 输入输出路径需要根据自己电脑上实际的输入输出路径设置
		args  = new String[]{"e:/input/inputorder" , "e:/output1"};

		// 1 获取配置信息
		Configuration conf = new Configuration();
		Job job = Job.getInstance(conf);

		// 2 设置jar包加载路径
		job.setJarByClass(OrderDriver.class);

		// 3 加载map/reduce类
		job.setMapperClass(OrderMapper.class);
		job.setReducerClass(OrderReducer.class);

		// 4 设置map输出数据key和value类型
		job.setMapOutputKeyClass(OrderBean.class);
		job.setMapOutputValueClass(NullWritable.class);

		// 5 设置最终输出数据的key和value类型
		job.setOutputKeyClass(OrderBean.class);
		job.setOutputValueClass(NullWritable.class);

		// 6 设置输入数据和输出数据路径
		FileInputFormat.setInputPaths(job, new Path(args[0]));
		FileOutputFormat.setOutputPath(job, new Path(args[1]));

		// 8 设置reduce端的分组
	job.setGroupingComparatorClass(OrderGroupingComparator.class);

		// 7 提交
		boolean result = job.waitForCompletion(true);
		System.exit(result ? 0 : 1);
	}
}