MapReduce 编程实践：统计对象中的某些属性

import random
import time
consumer_type = ['会员', '非会员']
vip, novip = 0, 0
vipValue, novipValue = 0, 0
with open("consumer.txt",'w',encoding='utf-8') as f:
	for i in range(1000): # 1000条数据
		random.seed(time.time()+i)
		id = random.randint(0, 10000)
		t = time.strftime('%Y-%m-%d %H:%M',time.localtime(time.time()))
		value = random.randint(1, 500)
		type = consumer_type[random.randint(0, 1)]
		f.write(str(id)+'\t'+t+'\t'+str(value)+'\t'+type+'\n')

		if type == consumer_type[0]:
			vip += 1
			vipValue += value
		else:
			novip += 1
			novipValue += value
print(consumer_type[0] + ": 人数 " + str(vip) + ", 总金额: " + str(vipValue) +", 平均金额："+str(vipValue/vip))
print(consumer_type[1] + ": 人数 " + str(novip) + ", 总金额: " + str(novipValue) +", 平均金额："+str(novipValue/novip))

[dnn@master HDFS_example]$ python test.py
会员: 人数 510, 总金额: 128744, 平均金额：252.439215686
非会员: 人数 490, 总金额: 123249, 平均金额：251.528571429

package com.michael.mapreduce;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Writable;
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.util.Date;

public class Consumer implements Writable{
	private String id;
	private int money;
	private int vip; // 0 no, 1 yes
	public Consumer() {
		
	}
	public Consumer(String id, int money, int vip) {
		this.id = id;
		this.money = money;
		this.vip = vip;
	}
	public int getMoney() {
		return money;
	}
	public void setMoney() {
		this.money = money;
	}
	public String getId() {
		return id;
	}
	public void setId(String id) {
		this.id = id;
	}
	public int getVip() {
		return vip;
	}
	public void setVip(int vip) {
		this.vip = vip;
	}
	
	public void write(DataOutput dataOutput) throws IOException{
		dataOutput.writeUTF(id);
		dataOutput.writeInt(money);
		dataOutput.writeInt(vip);
	}
	
	public void readFields(DataInput dataInput) throws IOException{
		this.id = dataInput.readUTF();
		this.money = dataInput.readInt();
		this.vip = dataInput.readInt();
	}
	
	@Override
	public String toString() {
		return this.id + "\t" + this.money + "\t" + this.vip;
	}
}

package com.michael.mapreduce;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import java.io.IOException;

public class ConsumerMapper extends Mapper<LongWritable, Text, Text, IntWritable>{
	@Override
	protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException{
		String line = value.toString();
		String[] fields = line.split("\t");
		String id = fields[0];
		int money = Integer.parseInt(fields[2]);
		String vip = fields[3];
		
		context.write(new Text(vip), new IntWritable(money));
	}
}

package com.michael.mapreduce;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.io.IOException;

public class ConsumerReducer extends Reducer<Text, IntWritable, Text, LongWritable>{
	@Override
	protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException{
		int count = 0;
		long sum = 0;
		for(IntWritable v : values) {
			count++;
			sum += v.get();
		}
		long avg = sum/count;
		context.write(key, new LongWritable(avg));
	}
}

package com.michael.mapreduce;

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

public class ConsumerDriver {
	public static void main(String[] args) throws Exception{
		Configuration conf = new Configuration();
		Job job = Job.getInstance(conf);
		job.setJarByClass(ConsumerDriver.class);
		job.setMapperClass(ConsumerMapper.class);
		job.setReducerClass(ConsumerReducer.class);
		job.setMapOutputKeyClass(Text.class);
		job.setMapOutputValueClass(IntWritable.class);
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(LongWritable.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);
	}
}

[dnn@master Desktop]$ hadoop dfs -copyFromLocal /home/dnn/eclipse-workspace/HDFS_example/consumer.txt /InputDataTest

hadoop jar /home/dnn/eclipse-workspace/HDFS_example/consumer_avg.jar com.michael.mapreduce.ConsumerDriver /InputDataTest/consumer.txt /OutputTest2

[dnn@master Desktop]$ hadoop fs -cat /OutputTest2/part-r-00000
会员	252
非会员	251