| 摘 要: 随着移动互联网时代数年的发展,数据的量级不断增长,业务不断的迭代进而软件系统出现性能瓶颈,系统程序复杂度随时间呈指数式增长,开发效率直线下降,在微服务架构中默认占据主导地位的数据库MySQL发生业务发展不匹配,慢查询爆发等问题时变更传统软件架构设计,替换数据库是否可以彻底解决根本问题？本文从一次实际业务系统Elasticsearch替换传统MySQL数据库的重构出发,通过问题、解决方案、实现细节的方式详细描述Elasticsearch的数据实时性问题,增量及存量数据的处理、灰度、对数以及如何通过两级缓存机制同时解决Elasticsearch数据实时性以及开发效率的问题。 |
| 关键词: Elasticsearch实时性 两级缓存 重构 |
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| Business System DataBase Refactoring Based on Elasticsearch |
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zhao zhi cheng
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Guangzhou University of Software
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| Abstract: With the development of the mobile internet era over the past few years, data volume has continued to grow, and as businesses iterate, software systems have encountered performance bottlenecks. The complexity of system programs has increased exponentially over time, leading to a sharp decline in development efficiency. In the microservices architecture, MySQL, which is the default dominant database, faces issues such as business development mismatches and a surge in slow queries. When these problems arise, is replacing the database to address traditional software architecture design changes enough to fundamentally solve the core issues? This article starts from a real-world business system where Elasticsearch replaces the traditional MySQL database. It provides a detailed description of the data synchronization issues in Elasticsearch, how to handle incremental and historical data, gray release and logarithmic problems, and how a two-level cache mechanism can simultaneously solve the issues of data real-time performance and development efficiency in Elasticsearch. |
| Keywords: Elasticsearch Two-level cache Refactoring |
