hadoop实现购物商城推荐系统

hadoop实现购物商城推荐系统

1，商城：是单商家，多买家的商城系统。数据库是mysql，语言java。

2，sqoop1.9.33：在mysql和hadoop中交换数据。

3，hadoop2.2.0：这里用于练习的是伪分布模式。

4，完成内容：喜欢该商品的人还喜欢，相同购物喜好的好友推荐。

步骤：

1，通过sqoop从mysql中将 “用户收藏商品” （这里用的是用户收藏商品信息表作为推荐系统业务上的依据，业务依据可以很复杂。这里主要介绍推荐系统的基本原理，所以推荐依据很简单）的表数据导入到hdfs中。

2，用MapReduce实现推荐算法。

3，通过sqoop将推荐系统的结果写回mysql。

4，java商城通过推荐系统的数据实现<喜欢该商品的人还喜欢，相同购物喜好的好友推荐。>两个功能。

实现：

1，

推荐系统的数据来源：

左边是用户，右边是商品。用户每收藏一个商品都会生成一条这样的信息，<喜欢该商品的人还喜欢，相同购物喜好的好友推荐。>的数据来源都是这张表。

sqoop导入数据，这里用的sqoop1.9.33。sqoop1.9.33的资料很少，会出现一些错误，搜索不到的可以发到我的邮箱keepmovingzx@163.com。

创建链接信息

这个比较简单

创建job

信息填对就可以了

导入数据执行 start job --jid 上面创建成功后返回的ID

导入成功后的数据

2，eclipse开发MapReduce程序

ShopxxProductRecommend<喜欢该商品的人还喜欢>

整个项目分两部，一，以用户对商品进行分组，二，求出商品的同现矩阵。

一

  第1大步的数据为输入参数对商品进行分组

   输出参数：

  

二，以第一步的输出数据为输入求商品的同现矩阵

        输出数据

第一列数据为当前商品，第二列为与它相似的商品，第三列为相似率（越高越相似）。

整个过程就完了，下面

package xian.zhang.common;

import java.util.regex.Pattern;

public class Util {
	 public static final Pattern DELIMITER = Pattern.compile("[\t,]");
}

package xian.zhang.core;

import java.io.IOException;
import java.util.Iterator;

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.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

/**
 * 将输入数据 userid1，product1  userid1，product2   userid1，product3
 * 合并成 userid1 product1,product2,product3输出
 * @author zx
 *
 */
public class CombinProductInUser {
	
	public static class CombinProductMapper extends Mapper<LongWritable, Text, IntWritable, Text>{
		@Override
		protected void map(LongWritable key, Text value,Context context)
				throws IOException, InterruptedException {
			String[] items = value.toString().split(","); 
			context.write(new IntWritable(Integer.parseInt(items[0])), new Text(items[1]));
		}
	}
	
	public static class CombinProductReducer extends Reducer<IntWritable, Text, IntWritable, Text>{

		@Override
		protected void reduce(IntWritable key, Iterable<Text> values,Context context)
				throws IOException, InterruptedException {
			StringBuffer sb = new StringBuffer();
			Iterator<Text> it = values.iterator();
			sb.append(it.next().toString());
			while(it.hasNext()){
				sb.append(",").append(it.next().toString());
			}
			context.write(key, new Text(sb.toString()));
		}
		
	}
	
	@SuppressWarnings("deprecation")
	public static boolean run(Path inPath,Path outPath) throws IOException, ClassNotFoundException, InterruptedException{
		
		Configuration conf = new Configuration();
		Job job = new Job(conf,"CombinProductInUser");
		
		job.setJarByClass(CombinProductInUser.class);
		job.setMapperClass(CombinProductMapper.class);
		job.setReducerClass(CombinProductReducer.class);

		job.setOutputKeyClass(IntWritable.class);
		job.setOutputValueClass(Text.class);
		
		FileInputFormat.addInputPath(job, inPath);
		FileOutputFormat.setOutputPath(job, outPath);
		
		return job.waitForCompletion(true);
		
	}
	
}

package xian.zhang.core;

import java.io.IOException;
import java.util.Iterator;

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.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

/**
 * 将输入数据 userid1，product1  userid1，product2   userid1，product3
 * 合并成 userid1 product1,product2,product3输出
 * @author zx
 *
 */
public class CombinProductInUser {
	
	public static class CombinProductMapper extends Mapper<LongWritable, Text, IntWritable, Text>{
		@Override
		protected void map(LongWritable key, Text value,Context context)
				throws IOException, InterruptedException {
			String[] items = value.toString().split(","); 
			context.write(new IntWritable(Integer.parseInt(items[0])), new Text(items[1]));
		}
	}
	
	public static class CombinProductReducer extends Reducer<IntWritable, Text, IntWritable, Text>{

		@Override
		protected void reduce(IntWritable key, Iterable<Text> values,Context context)
				throws IOException, InterruptedException {
			StringBuffer sb = new StringBuffer();
			Iterator<Text> it = values.iterator();
			sb.append(it.next().toString());
			while(it.hasNext()){
				sb.append(",").append(it.next().toString());
			}
			context.write(key, new Text(sb.toString()));
		}
		
	}
	
	@SuppressWarnings("deprecation")
	public static boolean run(Path inPath,Path outPath) throws IOException, ClassNotFoundException, InterruptedException{
		
		Configuration conf = new Configuration();
		Job job = new Job(conf,"CombinProductInUser");
		
		job.setJarByClass(CombinProductInUser.class);
		job.setMapperClass(CombinProductMapper.class);
		job.setReducerClass(CombinProductReducer.class);

		job.setOutputKeyClass(IntWritable.class);
		job.setOutputValueClass(Text.class);
		
		FileInputFormat.addInputPath(job, inPath);
		FileOutputFormat.setOutputPath(job, outPath);
		
		return job.waitForCompletion(true);
		
	}
	
}

package xian.zhang.core;

import java.io.IOException;

import org.apache.hadoop.fs.Path;

public class Main {
	
	public static void main(String[] args) throws ClassNotFoundException, IOException, InterruptedException {
		
		if(args.length < 2){
			throw new IllegalArgumentException("要有两个参数，数据输入的路径和输出路径");
		}
		
		Path inPath1 = new Path(args[0]);
		Path outPath1 = new Path(inPath1.getParent()+"/CombinProduct");
		
		Path inPath2 = outPath1;
		Path outPath2 = new Path(args[1]);
		
		if(CombinProductInUser.run(inPath1, outPath1)){
			System.exit(ProductCo_occurrenceMatrix.run(inPath2, outPath2)?0:1);
		}
	}
	
}

ShopxxUserRecommend<相同购物喜好的好友推荐>

整个项目分两部，一，以商品对用户进行分组，二，求出用户的同现矩阵。

原理和ShopxxProductRecommend一样

下面附上代码

package xian.zhang.common;

import java.util.regex.Pattern;

public class Util {
	 public static final Pattern DELIMITER = Pattern.compile("[\t,]");
}

package xian.zhang.core;

import java.io.IOException;
import java.util.Iterator;

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.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

/**
 * 将输入数据 userid1，product1  userid1，product2   userid1，product3
 * 合并成 productid1 user1,user2,user3输出
 * @author zx
 *
 */
public class CombinUserInProduct {
	
	public static class CombinUserMapper extends Mapper<LongWritable, Text, IntWritable, Text>{
		@Override
		protected void map(LongWritable key, Text value,Context context)
				throws IOException, InterruptedException {
			String[] items = value.toString().split(","); 
			context.write(new IntWritable(Integer.parseInt(items[1])), new Text(items[0]));
		}
	}
	
	public static class CombinUserReducer extends Reducer<IntWritable, Text, IntWritable, Text>{

		@Override
		protected void reduce(IntWritable key, Iterable<Text> values,Context context)
				throws IOException, InterruptedException {
			StringBuffer sb = new StringBuffer();
			Iterator<Text> it = values.iterator();
			sb.append(it.next().toString());
			while(it.hasNext()){
				sb.append(",").append(it.next().toString());
			}
			context.write(key, new Text(sb.toString()));
		}
		
	}
	
	@SuppressWarnings("deprecation")
	public static boolean run(Path inPath,Path outPath) throws IOException, ClassNotFoundException, InterruptedException{
		Configuration conf = new Configuration();
		Job job = new Job(conf,"CombinUserInProduct");
		
		job.setJarByClass(CombinUserInProduct.class);
		job.setMapperClass(CombinUserMapper.class);
		job.setReducerClass(CombinUserReducer.class);

		job.setOutputKeyClass(IntWritable.class);
		job.setOutputValueClass(Text.class);
		
		FileInputFormat.addInputPath(job, inPath);
		FileOutputFormat.setOutputPath(job, outPath);
		
		return job.waitForCompletion(true);
		
	}
	
}

package xian.zhang.core;

import java.io.IOException;
import java.util.Iterator;

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.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

import xian.zhang.common.Util;

/**
 * 用户的同先矩阵
 * @author zx
 *
 */
public class UserCo_occurrenceMatrix {

	public static class Co_occurrenceMapper extends Mapper<LongWritable, Text, Text, IntWritable>{

		IntWritable one = new IntWritable(1);
		
		@Override
		protected void map(LongWritable key, Text value, Context context)throws IOException, InterruptedException {
			
			String[] products = Util.DELIMITER.split(value.toString());
			for(int i=1;i<products.length;i++){
				for(int j=1;j<products.length;j++){
					if(i != j){
						context.write(new Text(products[i] + ":" + products[j]), one);
					}
				}
			}
			
		}
		
	}
	
	public static class Co_occurrenceReducer extends Reducer<Text, IntWritable, NullWritable, Text>{

		NullWritable nullKey =NullWritable.get();
		
		@Override
		protected void reduce(Text key, Iterable<IntWritable> values,Context context)
				throws IOException, InterruptedException {
			int sum = 0;
			Iterator<IntWritable> it = values.iterator();
			while(it.hasNext()){
				sum += it.next().get();
			}
			context.write(nullKey, new Text(key.toString().replace(":", ",") + "," + sum));
		}
		
	}
	
	@SuppressWarnings("deprecation")
	public static boolean run(Path inPath,Path outPath) throws IOException, ClassNotFoundException, InterruptedException{
		
		Configuration conf = new Configuration();
		Job job = new Job(conf,"UserCo_occurrenceMatrix");
		
		job.setJarByClass(UserCo_occurrenceMatrix.class);
		job.setMapperClass(Co_occurrenceMapper.class);
		job.setReducerClass(Co_occurrenceReducer.class);

		job.setMapOutputKeyClass(Text.class);
		job.setMapOutputValueClass(IntWritable.class);
		
		job.setOutputKeyClass(NullWritable.class);
		job.setOutputKeyClass(Text.class);
		
		FileInputFormat.addInputPath(job, inPath);
		FileOutputFormat.setOutputPath(job, outPath);
		
		return job.waitForCompletion(true);
	}
	
}

package xian.zhang.core;

import java.io.IOException;

import org.apache.hadoop.fs.Path;

public class Main {
	
	public static void main(String[] args) throws ClassNotFoundException, IOException, InterruptedException {
		
		if(args.length < 2){
			throw new IllegalArgumentException("要有两个参数，数据输入的路径和输出路径");
		}
		
		Path inPath1 = new Path(args[0]);
		Path outPath1 = new Path(inPath1.getParent()+"/CombinUser");
		
		Path inPath2 = outPath1;
		Path outPath2 = new Path(args[1]);
		
		if(CombinUserInProduct.run(inPath1, outPath1)){
			System.exit(UserCo_occurrenceMatrix.run(inPath2, outPath2)?0:1);
		}
	}
	
}

代码在github上有

git@github.com:chaoku/ShopxxProductRecommend.git