procedure analyse();语法如下
select column from table_name procedure analyse();
以下引用一段文章:
PROCEDURE ANALYSE 通过分析select查询结果对现有的表的每一列给出优化的建议。
PROCEDURE ANALYSE的语法如下:
SELECT ... FROM ... WHERE ... PROCEDURE ANALYSE([max_elements,[max_memory]])
max_elements (默认值256) analyze查找每一列不同值时所需关注的最大不同值的数量.
analyze还用这个值来检查优化的数据类型是否该是ENUM,如果该列的不同值的数量超过了
max_elements值ENUM就不做为建议优化的数据类型。
max_memory (默认值8192) analyze查找每一列所有不同值时可能分配的最大的内存数量
样例程序
------------------------------------------------------------------------------------ mysql> DESC user_account; +-----------+------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +-----------+------------------+------+-----+---------+----------------+ | USERID | int(10) unsigned | NO | PRI | NULL | auto_increment | | USERNAME | varchar(10) | NO | | NULL | | | PASSSWORD | varchar(30) | NO | | NULL | | | GROUPNAME | varchar(10) | YES | | NULL | | +-----------+------------------+------+-----+---------+----------------+ 4 rows in set (0.00 sec) mysql> select * from user_account PROCEDURE ANALYSE(1)\G; *************************** 1. row *************************** Field_name: ibatis.user_account.USERID Min_value: 1 Max_value: 103 Min_length: 1 Max_length: 3 Empties_or_zeros: 0 Nulls: 0 Avg_value_or_avg_length: 51.7500 Std: 50.2562 Optimal_fieldtype: TINYINT(3) UNSIGNED NOT NULL *************************** 2. row *************************** Field_name: ibatis.user_account.USERNAME Min_value: dfsa Max_value: LMEADORS ......................................................... ---------------------------------------------------------------------------------------
从第一行输出我们可以看到analyze分析ibatis.user_account.USERID列最小值1,最大值103,最小长度1,
最大长度3...,并给出了改字段的优化建议:建议将该字段的数据类型改成TINYINT(3) UNSIGNED NOT NULL。

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Common security vulnerabilities in MySQL include SQL injection, weak passwords, improper permission configuration, and unupdated software. 1. SQL injection can be prevented by using preprocessing statements. 2. Weak passwords can be avoided by forcibly using strong password strategies. 3. Improper permission configuration can be resolved through regular review and adjustment of user permissions. 4. Unupdated software can be patched by regularly checking and updating the MySQL version.

Identifying slow queries in MySQL can be achieved by enabling slow query logs and setting thresholds. 1. Enable slow query logs and set thresholds. 2. View and analyze slow query log files, and use tools such as mysqldumpslow or pt-query-digest for in-depth analysis. 3. Optimizing slow queries can be achieved through index optimization, query rewriting and avoiding the use of SELECT*.

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The main difference between MySQL and MariaDB is performance, functionality and license: 1. MySQL is developed by Oracle, and MariaDB is its fork. 2. MariaDB may perform better in high load environments. 3.MariaDB provides more storage engines and functions. 4.MySQL adopts a dual license, and MariaDB is completely open source. The existing infrastructure, performance requirements, functional requirements and license costs should be taken into account when choosing.

MySQL uses a GPL license. 1) The GPL license allows the free use, modification and distribution of MySQL, but the modified distribution must comply with GPL. 2) Commercial licenses can avoid public modifications and are suitable for commercial applications that require confidentiality.

The situations when choosing InnoDB instead of MyISAM include: 1) transaction support, 2) high concurrency environment, 3) high data consistency; conversely, the situation when choosing MyISAM includes: 1) mainly read operations, 2) no transaction support is required. InnoDB is suitable for applications that require high data consistency and transaction processing, such as e-commerce platforms, while MyISAM is suitable for read-intensive and transaction-free applications such as blog systems.

In MySQL, the function of foreign keys is to establish the relationship between tables and ensure the consistency and integrity of the data. Foreign keys maintain the effectiveness of data through reference integrity checks and cascading operations. Pay attention to performance optimization and avoid common errors when using them.


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