双十一没有买到这本书，没想到图书馆有第一版，之前只能说对MySQL是一知半解，多读书才是王道。 数据库？数据库示例？简单讲，前者是文件，后者是操作这些文件的应用程序。 MySQL体系结构： 网上找了这张图片，和书里面的一样，不过书上的单词有错哈，难道图
双十一没有买到这本书，没想到图书馆有第一版，之前只能说对MySQL是一知半解，多读书才是王道。
数据库？数据库示例？简单讲，前者是文件，后者是操作这些文件的应用程序。
MySQL体系结构：
网上找了这张图片，和书里面的一样，不过书上的单词有错哈，难道图书馆买的是盗版书？
我简单理解MySQL就是三个部分：文件、存储引擎、各种组件。当然，没那么简单啦，组件类型有很多种，看图就很明了啦，虽然英文不怎么样，google下还是明白的，连接池、管理服务和工具、接口、查询分析、优化器、缓存。
有一个重要概念，插件式存储引擎，啥意思呢？所有人都可以开发存储引擎，可以随时更换的意思吗？网上查了查，大概和我想的是一致的，灵活性和可扩展性，甚至同一个数据库中的不同表可以使用不同的存储引擎，可以根据不同需求来选择数据库的存储引擎，比较牛逼。
网上也让我找到了这张图片，引用下啦，很明显可以看出各个存储引擎之间的区别，没有好与不好，只能说适用的场景不同，比较新奇的是Archive这种，只能进行INSERT和SELECT操作，而且用zlib算法进行压缩，比例达到1：10，对于像日志这种不许要修改的信息来讲，是最适合不过的啦。
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What are the key metrics to look for in an EXPLAIN output (type, key, rows, Extra)?Apr 15, 2025 am 12:15 AMKey metrics for EXPLAIN commands include type, key, rows, and Extra. 1) The type reflects the access type of the query. The higher the value, the higher the efficiency, such as const is better than ALL. 2) The key displays the index used, and NULL indicates no index. 3) rows estimates the number of scanned rows, affecting query performance. 4) Extra provides additional information, such as Usingfilesort prompts that it needs to be optimized.
What is the Using temporary status in EXPLAIN and how to avoid it?Apr 15, 2025 am 12:14 AMUsingtemporary indicates that the need to create temporary tables in MySQL queries, which are commonly found in ORDERBY using DISTINCT, GROUPBY, or non-indexed columns. You can avoid the occurrence of indexes and rewrite queries and improve query performance. Specifically, when Usingtemporary appears in EXPLAIN output, it means that MySQL needs to create temporary tables to handle queries. This usually occurs when: 1) deduplication or grouping when using DISTINCT or GROUPBY; 2) sort when ORDERBY contains non-index columns; 3) use complex subquery or join operations. Optimization methods include: 1) ORDERBY and GROUPB
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MySQL vs. Other Databases: Comparing the OptionsApr 15, 2025 am 12:08 AMMySQL is suitable for web applications and content management systems and is popular for its open source, high performance and ease of use. 1) Compared with PostgreSQL, MySQL performs better in simple queries and high concurrent read operations. 2) Compared with Oracle, MySQL is more popular among small and medium-sized enterprises because of its open source and low cost. 3) Compared with Microsoft SQL Server, MySQL is more suitable for cross-platform applications. 4) Unlike MongoDB, MySQL is more suitable for structured data and transaction processing.
How does MySQL index cardinality affect query performance?Apr 14, 2025 am 12:18 AMMySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.
MySQL: Resources and Tutorials for New UsersApr 14, 2025 am 12:16 AMThe MySQL learning path includes basic knowledge, core concepts, usage examples, and optimization techniques. 1) Understand basic concepts such as tables, rows, columns, and SQL queries. 2) Learn the definition, working principles and advantages of MySQL. 3) Master basic CRUD operations and advanced usage, such as indexes and stored procedures. 4) Familiar with common error debugging and performance optimization suggestions, such as rational use of indexes and optimization queries. Through these steps, you will have a full grasp of the use and optimization of MySQL.
Real-World MySQL: Examples and Use CasesApr 14, 2025 am 12:15 AMMySQL's real-world applications include basic database design and complex query optimization. 1) Basic usage: used to store and manage user data, such as inserting, querying, updating and deleting user information. 2) Advanced usage: Handle complex business logic, such as order and inventory management of e-commerce platforms. 3) Performance optimization: Improve performance by rationally using indexes, partition tables and query caches.
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