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1、WHERE字句的查询条件里有不等于号(WHERE column!=...),MYSQL将无法使用索引
2、类似地,如果WHERE字句的查询条件里使用了函数(如:WHERE DAY(column)=...),MYSQL将无法使用索引
3、在JOIN操作中(需要从多个数据表提取数据时),MYSQL只有在主键和外键的数据类型相同时才能使用索引,否则即使建立了
索引也不会使用
4、如果WHERE子句的查询条件里使用了比较操作符LIKE和REGEXP,MYSQL只有在搜索模板的第一个字符不是通配符的情况下才能
使用索引。比如说,如果查询条件是LIKE 'abc%',MYSQL将使用索引;如果条件是LIKE '%abc',MYSQL将不使用索引。
5、在ORDER BY操作中,MYSQL只有在排序条件不是一个查询条件表达式的情况下才使用索引。尽管如此,在涉及多个数据表的查
询里,即使有索引可用,那些索引在加快ORDER BY操作方面也没什么作用。
6、如果某个数据列里包含着许多重复的值,就算为它建立了索引也不会有很好的效果。比如说,如果某个数据列里包含了净是
些诸如“0/1”或“Y/N”等值,就没有必要为它创建一个索引。
7、索引有用的情况下就太多了。基本只要建立了索引,除了上面提到的索引不会使用的情况下之外,其他情况只要是使用在
WHERE条件里,ORDER BY 字段,联表字段,一般都是有效的。 建立索引要的就是有效果。 不然还用它干吗? 如果不能确定在
某个字段上建立的索引是否有效果,只要实际进行测试下比较下执行时间就知道。bitsCN.com

InnoDB uses redologs and undologs to ensure data consistency and reliability. 1.redologs record data page modification to ensure crash recovery and transaction persistence. 2.undologs records the original data value and supports transaction rollback and MVCC.

Key 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.

Usingtemporary 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

MySQL/InnoDB supports four transaction isolation levels: ReadUncommitted, ReadCommitted, RepeatableRead and Serializable. 1.ReadUncommitted allows reading of uncommitted data, which may cause dirty reading. 2. ReadCommitted avoids dirty reading, but non-repeatable reading may occur. 3.RepeatableRead is the default level, avoiding dirty reading and non-repeatable reading, but phantom reading may occur. 4. Serializable avoids all concurrency problems but reduces concurrency. Choosing the appropriate isolation level requires balancing data consistency and performance requirements.

MySQL 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.

MySQL 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.

The 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.

MySQL'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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