MySQL中视图的使用及多表INNER JOIN的技巧分享_MySQL
创建视图
Sql代码
CREATE VIEW view_name AS SELECT t1.xxx, t2.xxx, t3.xxx FROM (table1 t1 INNER JOIN table2 t2 ON t1.fid = t2.fid) INNER JOIN table3 t3 ON t1.mid = t3.mid;
这里使用了3表关联,对于多表关联的 INNER JOIN 写法有一个技巧
1. 先写最简单的2表关联 INNER JOIN
2. 然后使用 () 从 FROM 之后到语句结尾全部扩起来
3. 在语句结尾开始连接与下一个表的 INNER JOIN
记住这个原则,未来进行4表关联,5表关联就都不是什么难事了
删除视图
复制代码 代码如下:
DROP VIEW view_name
以下是其它网友的补充:
多表联接是十分有用的技术,因为某 些情况下,我们需要跨越多个表查询数据。
语法格式:
FROM (((表1 INNER JOIN 表2 ON 表1.字段号=表2.字段号) INNER JOIN 表3 ON 表1.字段号=表3.字段号) INNER JOIN 表4 ON Member.字段号=表4.字段号) INNER JOIN 表X ON Member.字段号=表X.字段号,只要套用该格式就可以了。
注意事项:
在输入字母过程中,一定要用英文半角标点符号,单词之间留一半角空格;
在建立数据表时,如果一个表与多个表联接,那么这一个表中的字段必须是“数字”数据类型,而多个表中的相同字段必须是主键,而且是“自动编号”数 据类型。否则,很难联接成功。
代码嵌套快速方法:如,想连接五个表,则只要在连接四个表的代码上加一个前后括号(前括号加在FROM的后面,后括号加在代码的末尾即可),然后 在后括号后面继续添加“INNER JOIN 表名X ON 表1.字段号=表X.字段号”代码即可,这样就可以无限联接数据表了。
连接两个数据表的用法:
FROM 表1 INNER JOIN 表2 ON 表1.字段号=表2.字段号
连接三个数据表的用法:
FROM (表1 INNER JOIN 表2 ON 表1.字段号=表2.字段号) INNER JOIN 表3 ON 表1.字段号=表3.字段号
连接四个数据表的用法:
FROM ((表1 INNER JOIN 表2 ON 表1.字段号=表2.字段号) INNER JOIN 表3 ON 表1.字段号=表3.字段号) INNER JOIN 表4 ON Member.字段号=表4.字段号
连接五个数据表的用法:
FROM (((表1 INNER JOIN 表2 ON 表1.字段号=表2.字段号) INNER JOIN 表3 ON 表1.字段号=表3.字段号) INNER JOIN 表4 ON Member.字段号=表4.字段号) INNER JOIN 表5 ON Member.字段号=表5.字段号

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



InnoDB's full-text search capabilities are very powerful, which can significantly improve database query efficiency and ability to process large amounts of text data. 1) InnoDB implements full-text search through inverted indexing, supporting basic and advanced search queries. 2) Use MATCH and AGAINST keywords to search, support Boolean mode and phrase search. 3) Optimization methods include using word segmentation technology, periodic rebuilding of indexes and adjusting cache size to improve performance and accuracy.

The article discusses using MySQL's ALTER TABLE statement to modify tables, including adding/dropping columns, renaming tables/columns, and changing column data types.

Full table scanning may be faster in MySQL than using indexes. Specific cases include: 1) the data volume is small; 2) when the query returns a large amount of data; 3) when the index column is not highly selective; 4) when the complex query. By analyzing query plans, optimizing indexes, avoiding over-index and regularly maintaining tables, you can make the best choices in practical applications.

Yes, MySQL can be installed on Windows 7, and although Microsoft has stopped supporting Windows 7, MySQL is still compatible with it. However, the following points should be noted during the installation process: Download the MySQL installer for Windows. Select the appropriate version of MySQL (community or enterprise). Select the appropriate installation directory and character set during the installation process. Set the root user password and keep it properly. Connect to the database for testing. Note the compatibility and security issues on Windows 7, and it is recommended to upgrade to a supported operating system.

The difference between clustered index and non-clustered index is: 1. Clustered index stores data rows in the index structure, which is suitable for querying by primary key and range. 2. The non-clustered index stores index key values and pointers to data rows, and is suitable for non-primary key column queries.

Article discusses popular MySQL GUI tools like MySQL Workbench and phpMyAdmin, comparing their features and suitability for beginners and advanced users.[159 characters]

Article discusses strategies for handling large datasets in MySQL, including partitioning, sharding, indexing, and query optimization.

The article discusses dropping tables in MySQL using the DROP TABLE statement, emphasizing precautions and risks. It highlights that the action is irreversible without backups, detailing recovery methods and potential production environment hazards.
