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bi-backend's Introduction

智能BI开发文档

需求分析

1、 智能分析:用户输入目标和原始数据,可以自动生成图表和分析结论

2、 图表的管理:增删改查

3、 图表生成的异步化

4、 对接AI的能力

架构分析

基础方案:

客户输入分析目标和原始数据,向业务后端发送请求。业务后端利用AI服务处理客户端数据,保存到数据库,并生成图表和分析结果。处理后的数据由业务后端发送给AI服务,AI服务生成结果并返回给后端,最终将结果返回客户端展示。

问题:

AI服务(ChatGPT)回复需要时间且分钟内需求个数有限制,用户发送消息速率与AI服务接受速率存在同步场景。

改进方案:

增加消息队列,实现异步化

客户输入分析目标和原始数据,向业务后端发送请求。业务后端将请求事件放入消息队列,并为客户端生成排队号,消息队列根据AI服务负载情况,定期检查进度。如AI服务能处理更多请求,就向任务模块发送消息。

主流框架

  • Spring Boot 2.7.x
  • Spring MVC
  • MyBatis + MyBatis Plus 数据访问(开启分页)
  • Spring Boot 调试工具和项目处理器
  • Spring 事务注解

数据存储

  • MySQL 数据库
  • Redis 内存数据库

工具类

  • Easy Excel 表格处理

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