MapReduce实现推荐系统

1.开发环境：

Windows 2008 64bit

Java 1.6.0_30

MyEclipse 6.5

环境部署见：http://www.linuxidc.com/Linux/2014-02/96528.htm

　　2.Hadoop集群环境：

Oracle Linux Enterprise 5.9

Java 1.6.0_18

Hadoop:hadoop 1.2.1三节点

namenode:10.1.32.91

datanode:10.1.32.93

datanode:10.1.32.95

环境部署见： http://www.linuxidc.com/Linux/2014-02/96529.htm

　　3.各java类功能介绍：

Recommend.java，主任务启动程序

Step1.java，按用户分组，计算所有物品出现的组合列表，得到用户对物品的评分矩阵

Step2.java，对物品组合列表进行计数，建立物品的同现矩阵

Step3.java，对同现矩阵和评分矩阵转型

Step4.java，合并矩阵，并计算推荐结果列表

HdfsDAO.java，HDFS操作工具类

4.执行代码和运行结果：

Recommend.java 代码：

import java.util.HashMap;

import java.util.Map;

import java.util.regex.Pattern;

import org.apache.hadoop.mapred.JobConf;

public class Recommend {

public static final String HDFS = "hdfs://10.1.32.91:9000";

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

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

Map<String, String> path = new HashMap<String, String>();

path.put("data", "C:\\Users\\licz\\workspace\\Mapreduce1\\small2.csv");

path.put("Step1Input", HDFS + "/user/hdfs/recommend");

path.put("Step1Output", path.get("Step1Input") + "/step1");

path.put("Step2Input", path.get("Step1Output"));

path.put("Step2Output", path.get("Step1Input") + "/step2");

path.put("Step3Input1", path.get("Step1Output"));

path.put("Step3Output1", path.get("Step1Input") + "/step3_1");

path.put("Step3Input2", path.get("Step2Output"));

path.put("Step3Output2", path.get("Step1Input") + "/step3_2");

path.put("Step4Input1", path.get("Step3Output1"));

path.put("Step4Input2", path.get("Step3Output2"));

path.put("Step4Output", path.get("Step1Input") + "/step4");

Step1.run(path);

Step2.run(path);

Step3.run1(path);

Step3.run2(path);

Step4.run(path);

System.exit(0);

}

public static JobConf config() {

JobConf conf = new JobConf(Recommend.class);

conf.setJobName("Recommand");

conf.addResource("classpath:/hadoop/core-site.xml");

conf.addResource("classpath:/hadoop/hdfs-site.xml");

conf.addResource("classpath:/hadoop/mapred-site.xml");

//conf.set("io.sort.mb", "1024");

return conf;

}

}