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ecommercerecommendsystem's Introduction

ECommerceRecommendSystemIntroduction

电商网站商品推荐系统采用前后端分离开发的方式,通过 JSON 交互数据。

在线浏览:liruiha.com:8080/business/

视频简介:点击打开视频演示

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前端使用 Vue + TypeScript + ElementUI 构建,build 的时候自动部署到后端业务工程的 webapps/static 目录下,随 Tomcat 一同启动

点击查看前端工程目录及详细介绍

后端又分为业务模块和推荐模块,业务模块与前端交互、接收与反馈数据。推荐模块监听 Kafka 的用户行为数据,然后进行实时计算,将结果写回 MongoDB,并周期性执行离线计算,根据用户最近的操作记录进行离线推荐,并将推荐结果写入到 MongoDB

点击查看后端工程目录及详细介绍

开发工具

  1. 环境:Win 10、JDK-1.8、Scala-2.11、Spark-2.1
  2. IDE:IDEA
  3. 组件:Kafka、Redis、MongoDB
  4. 其他:Flink-1.7(计划已关闭)

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