格式:select [选项子句] 字段表达式子句 [from子句] [where子句] [group by子句] [having子句] [order by子句] [limit子句];
提示:子句的顺序是固定的
select 选项子句 [ all | distinct ]
这个参数主要影响查询结果是否包含重复记录
All:代表保留所有的记录,这个默认选项,可以省略不写
Distinct:代表去除重复的记录
格式:select all|distinct 字段表达式 from...;
from子句
格式:from 数据表
FROM子句用于指定要查询使用的数据源
数据表可以有多个,中间用逗号分开,数据表也可以起别名
如果数据源是两个表时,结果会是一个交叉连接的方式,记录数相当于笛卡尔积
两个表的数据总和=表1的记录数*表2的记录数
写*时,字段名总数是两个表的字段数量的和
数据表也可以起别名,还可以加条件
WHERE子句
功能是进行数据的筛选过滤。
格式:where 条件表达式
条件表达式使用关系运算符和逻辑运算符
关系运算符
> 大于
>= 大于等于
!= 不等于
不等于
= 等于
逻辑运算符
&& and 与
|| or 或
! not 非
Xor 异或
运算符存在优先级的问题
在where子句中不能使用字段的别名
GROUP BY子句
主要用于分组。通常在字段表达式中使用分组函数。
格式:group by 字段1 [asc|desc], 字段2 [asc|desc], ……
排序不写默认是asc正序
使用count(*)和count(字段名)时,注意字段的值为null的问题
count(字段名)统计时,会把值为null的记录忽略掉!
HAVING子句
它用于对查询出来的结果进行再次的过滤。
比较显著的就是如对分组查询出来的结果再次使用条件。
省略where和group by子句时,不等于having就是where
不能把where放到having的位置
ORDER BY子句
主要用于对数据进行排序。
格式:order by 字段1 [asc|desc], 字段2 [asc|desc], ……
Asc代表正序,它是默认选项,不写就是asc
Desc代表倒序
当用一个字段做排序时,如果出现针对排序字段相同的记录时,会隐含去使用主键进行第二排序
LIMIT子句
这个子句是做分页的。
格式:limit 起始记录位置, 记录数
注意:如果省略起始记录位置,只给出记录数,表示从第一条数据开始取内容
Limit 10 相当于 limit 0, 10
提示:记录的位置是从0开始计算的

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.

SQL commands in MySQL can be divided into categories such as DDL, DML, DQL, DCL, etc., and are used to create, modify, delete databases and tables, insert, update, delete data, and perform complex query operations. 1. Basic usage includes CREATETABLE creation table, INSERTINTO insert data, and SELECT query data. 2. Advanced usage involves JOIN for table joins, subqueries and GROUPBY for data aggregation. 3. Common errors such as syntax errors, data type mismatch and permission problems can be debugged through syntax checking, data type conversion and permission management. 4. Performance optimization suggestions include using indexes, avoiding full table scanning, optimizing JOIN operations and using transactions to ensure data consistency.

InnoDB achieves atomicity through undolog, consistency and isolation through locking mechanism and MVCC, and persistence through redolog. 1) Atomicity: Use undolog to record the original data to ensure that the transaction can be rolled back. 2) Consistency: Ensure the data consistency through row-level locking and MVCC. 3) Isolation: Supports multiple isolation levels, and REPEATABLEREAD is used by default. 4) Persistence: Use redolog to record modifications to ensure that data is saved for a long time.

MySQL's position in databases and programming is very important. It is an open source relational database management system that is widely used in various application scenarios. 1) MySQL provides efficient data storage, organization and retrieval functions, supporting Web, mobile and enterprise-level systems. 2) It uses a client-server architecture, supports multiple storage engines and index optimization. 3) Basic usages include creating tables and inserting data, and advanced usages involve multi-table JOINs and complex queries. 4) Frequently asked questions such as SQL syntax errors and performance issues can be debugged through the EXPLAIN command and slow query log. 5) Performance optimization methods include rational use of indexes, optimized query and use of caches. Best practices include using transactions and PreparedStatemen

MySQL is suitable for small and large enterprises. 1) Small businesses can use MySQL for basic data management, such as storing customer information. 2) Large enterprises can use MySQL to process massive data and complex business logic to optimize query performance and transaction processing.

InnoDB effectively prevents phantom reading through Next-KeyLocking mechanism. 1) Next-KeyLocking combines row lock and gap lock to lock records and their gaps to prevent new records from being inserted. 2) In practical applications, by optimizing query and adjusting isolation levels, lock competition can be reduced and concurrency performance can be improved.


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