【MySQL】语法简介

本文涉及的产品
RDS MySQL Serverless 基础系列,0.5-2RCU 50GB
云数据库 RDS MySQL,集群系列 2核4GB
推荐场景:
搭建个人博客
云数据库 RDS PostgreSQL,集群系列 2核4GB
简介: 本篇文章主要简介下MySQL中where,group by ,order by ,limit,join,union ,union all,子表等查询语法。

本篇文章主要简介下MySQL中where,group by ,order by ,limit,join,union ,union all,子表等查询语法。


测试数据准备

create table emp (
    empno numeric(4) not null,
    ename varchar(10),
    job varchar(9),
    mgr numeric(4),
    hiredate datetime,
    sal numeric(7, 2),
    comm numeric(7, 2),
    deptno numeric(2)
);
create table dept (
    deptno numeric(2),
    dname varchar(14),
    loc varchar(13)
);
create table salgrade (
    grade numeric,
    losal numeric,
    hisal numeric
);
insert into dept values (10, 'ACCOUNTING', 'NEW YORK');
insert into dept values (20, 'RESEARCH', 'DALLAS');
insert into dept values (30, 'SALES', 'CHICAGO');
insert into dept values (40, 'OPERATIONS', 'BOSTON');
insert into salgrade values (1, 700, 1200);
insert into salgrade values (2, 1201, 1400);
insert into salgrade values (3, 1401, 2000);
insert into salgrade values (4, 2001, 3000);
insert into salgrade values (5, 3001, 9999);
insert into emp values (7369, 'SMITH', 'CLERK', 7902, '1980-12-17', 800, null, 20);
insert into emp values (7499, 'ALLEN', 'SALESMAN', 7698, '1981-02-20', 1600, 300, 30);
insert into emp values (7521, 'WARD', 'SALESMAN', 7698, '1981-02-22', 1250, 500, 30);
insert into emp values (7566, 'JONES', 'MANAGER', 7839, '1981-04-02', 2975, null, 20);
insert into emp values (7654, 'MARTIN', 'SALESMAN', 7698, '1981-09-28', 1250, 1400, 30);
insert into emp values (7698, 'BLAKE', 'MANAGER', 7839, '1981-05-01', 2850, null, 30);
insert into emp values (7782, 'CLARK', 'MANAGER', 7839, '1981-06-09', 2450, null, 10);
insert into emp values (7788, 'SCOTT', 'ANALYST', 7566, '1982-12-09', 3000, null, 20);
insert into emp values (7839, 'KING', 'PRESIDENT', null, '1981-11-17', 5000, null, 10);
insert into emp values (7844, 'TURNER', 'SALESMAN', 7698, '1981-09-08', 1500, 0, 30);
insert into emp values (7876, 'ADAMS', 'CLERK', 7788, '1983-01-12', 1100, null, 20);
insert into emp values (7900, 'JAMES', 'CLERK', 7698, '1981-12-03', 950, null, 30);
insert into emp values (7902, 'FORD', 'ANALYST', 7566, '1981-12-03', 3000, null, 20);
insert into emp values (7934, 'MILLER', 'CLERK', 7782, '1982-01-23', 1300, null, 10);


1.模糊查询

mysql> select * from emp where ename like '%S%'; 
+-------+-------+---------+------+---------------------+---------+------+--------+
| empno | ename | job     | mgr  | hiredate            | sal     | comm | deptno |
+-------+-------+---------+------+---------------------+---------+------+--------+
|  7369 | SMITH | CLERK   | 7902 | 1980-12-17 00:00:00 |  800.00 | NULL |     20 |
|  7566 | JONES | MANAGER | 7839 | 1981-04-02 00:00:00 | 2975.00 | NULL |     20 |
|  7788 | SCOTT | ANALYST | 7566 | 1982-12-09 00:00:00 | 3000.00 | NULL |     20 |
|  7876 | ADAMS | CLERK   | 7788 | 1983-01-12 00:00:00 | 1100.00 | NULL |     20 |
|  7900 | JAMES | CLERK   | 7698 | 1981-12-03 00:00:00 |  950.00 | NULL |     30 |
+-------+-------+---------+------+---------------------+---------+------+--------+
5 rows in set (0.00 sec)
mysql> select * from emp where ename like 'S%'; 
+-------+-------+---------+------+---------------------+---------+------+--------+
| empno | ename | job     | mgr  | hiredate            | sal     | comm | deptno |
+-------+-------+---------+------+---------------------+---------+------+--------+
|  7369 | SMITH | CLERK   | 7902 | 1980-12-17 00:00:00 |  800.00 | NULL |     20 |
|  7788 | SCOTT | ANALYST | 7566 | 1982-12-09 00:00:00 | 3000.00 | NULL |     20 |
+-------+-------+---------+------+---------------------+---------+------+--------+
2 rows in set (0.01 sec)
mysql> select * from emp where ename like '%S';
+-------+-------+---------+------+---------------------+---------+------+--------+
| empno | ename | job     | mgr  | hiredate            | sal     | comm | deptno |
+-------+-------+---------+------+---------------------+---------+------+--------+
|  7566 | JONES | MANAGER | 7839 | 1981-04-02 00:00:00 | 2975.00 | NULL |     20 |
|  7876 | ADAMS | CLERK   | 7788 | 1983-01-12 00:00:00 | 1100.00 | NULL |     20 |
|  7900 | JAMES | CLERK   | 7698 | 1981-12-03 00:00:00 |  950.00 | NULL |     30 |
+-------+-------+---------+------+---------------------+---------+------+--------+
3 rows in set (0.00 sec)
mysql> select * from emp where ename like '_O%';
+-------+-------+---------+------+---------------------+---------+------+--------+
| empno | ename | job     | mgr  | hiredate            | sal     | comm | deptno |
+-------+-------+---------+------+---------------------+---------+------+--------+
|  7566 | JONES | MANAGER | 7839 | 1981-04-02 00:00:00 | 2975.00 | NULL |     20 |
|  7902 | FORD  | ANALYST | 7566 | 1981-12-03 00:00:00 | 3000.00 | NULL |     20 |
+-------+-------+---------+------+---------------------+---------+------+--------+
2 rows in set (0.00 sec)
总结:
%表示任意0个或多个字符,可匹配任意类型和长度的字符;
_表示任意单个字符,匹配单个任意字符。


2.排序

mysql> select * from emp order by  sal;
+-------+--------+-----------+------+---------------------+---------+---------+--------+
| empno | ename  | job       | mgr  | hiredate            | sal     | comm    | deptno |
+-------+--------+-----------+------+---------------------+---------+---------+--------+
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 00:00:00 |  800.00 |    NULL |     20 |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 00:00:00 |  950.00 |    NULL |     30 |
|  7876 | ADAMS  | CLERK     | 7788 | 1983-01-12 00:00:00 | 1100.00 |    NULL |     20 |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 00:00:00 | 1250.00 |  500.00 |     30 |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 00:00:00 | 1250.00 | 1400.00 |     30 |
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 00:00:00 | 1300.00 |    NULL |     10 |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 00:00:00 | 1500.00 |    0.00 |     30 |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 00:00:00 | 1600.00 |  300.00 |     30 |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 00:00:00 | 2450.00 |    NULL |     10 |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 00:00:00 | 2850.00 |    NULL |     30 |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 00:00:00 | 2975.00 |    NULL |     20 |
|  7788 | SCOTT  | ANALYST   | 7566 | 1982-12-09 00:00:00 | 3000.00 |    NULL |     20 |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 00:00:00 | 3000.00 |    NULL |     20 |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 00:00:00 | 5000.00 |    NULL |     10 |
+-------+--------+-----------+------+---------------------+---------+---------+--------+
14 rows in set (0.00 sec)
mysql> select * from emp order by  sal asc;
+-------+--------+-----------+------+---------------------+---------+---------+--------+
| empno | ename  | job       | mgr  | hiredate            | sal     | comm    | deptno |
+-------+--------+-----------+------+---------------------+---------+---------+--------+
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 00:00:00 |  800.00 |    NULL |     20 |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 00:00:00 |  950.00 |    NULL |     30 |
|  7876 | ADAMS  | CLERK     | 7788 | 1983-01-12 00:00:00 | 1100.00 |    NULL |     20 |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 00:00:00 | 1250.00 |  500.00 |     30 |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 00:00:00 | 1250.00 | 1400.00 |     30 |
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 00:00:00 | 1300.00 |    NULL |     10 |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 00:00:00 | 1500.00 |    0.00 |     30 |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 00:00:00 | 1600.00 |  300.00 |     30 |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 00:00:00 | 2450.00 |    NULL |     10 |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 00:00:00 | 2850.00 |    NULL |     30 |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 00:00:00 | 2975.00 |    NULL |     20 |
|  7788 | SCOTT  | ANALYST   | 7566 | 1982-12-09 00:00:00 | 3000.00 |    NULL |     20 |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 00:00:00 | 3000.00 |    NULL |     20 |
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 00:00:00 | 5000.00 |    NULL |     10 |
+-------+--------+-----------+------+---------------------+---------+---------+--------+
14 rows in set (0.00 sec)
mysql> select * from emp order by  sal desc;
+-------+--------+-----------+------+---------------------+---------+---------+--------+
| empno | ename  | job       | mgr  | hiredate            | sal     | comm    | deptno |
+-------+--------+-----------+------+---------------------+---------+---------+--------+
|  7839 | KING   | PRESIDENT | NULL | 1981-11-17 00:00:00 | 5000.00 |    NULL |     10 |
|  7788 | SCOTT  | ANALYST   | 7566 | 1982-12-09 00:00:00 | 3000.00 |    NULL |     20 |
|  7902 | FORD   | ANALYST   | 7566 | 1981-12-03 00:00:00 | 3000.00 |    NULL |     20 |
|  7566 | JONES  | MANAGER   | 7839 | 1981-04-02 00:00:00 | 2975.00 |    NULL |     20 |
|  7698 | BLAKE  | MANAGER   | 7839 | 1981-05-01 00:00:00 | 2850.00 |    NULL |     30 |
|  7782 | CLARK  | MANAGER   | 7839 | 1981-06-09 00:00:00 | 2450.00 |    NULL |     10 |
|  7499 | ALLEN  | SALESMAN  | 7698 | 1981-02-20 00:00:00 | 1600.00 |  300.00 |     30 |
|  7844 | TURNER | SALESMAN  | 7698 | 1981-09-08 00:00:00 | 1500.00 |    0.00 |     30 |
|  7934 | MILLER | CLERK     | 7782 | 1982-01-23 00:00:00 | 1300.00 |    NULL |     10 |
|  7521 | WARD   | SALESMAN  | 7698 | 1981-02-22 00:00:00 | 1250.00 |  500.00 |     30 |
|  7654 | MARTIN | SALESMAN  | 7698 | 1981-09-28 00:00:00 | 1250.00 | 1400.00 |     30 |
|  7876 | ADAMS  | CLERK     | 7788 | 1983-01-12 00:00:00 | 1100.00 |    NULL |     20 |
|  7900 | JAMES  | CLERK     | 7698 | 1981-12-03 00:00:00 |  950.00 |    NULL |     30 |
|  7369 | SMITH  | CLERK     | 7902 | 1980-12-17 00:00:00 |  800.00 |    NULL |     20 |
+-------+--------+-----------+------+---------------------+---------+---------+--------+
14 rows in set (0.00 sec)
总结:
order by排序默认按asc升序来排列
也可指定desc降序排列


3.限制多少行

mysql> select * from emp limit  3;
+-------+-------+----------+------+---------------------+---------+--------+--------+
| empno | ename | job      | mgr  | hiredate            | sal     | comm   | deptno |
+-------+-------+----------+------+---------------------+---------+--------+--------+
|  7369 | SMITH | CLERK    | 7902 | 1980-12-17 00:00:00 |  800.00 |   NULL |     20 |
|  7499 | ALLEN | SALESMAN | 7698 | 1981-02-20 00:00:00 | 1600.00 | 300.00 |     30 |
|  7521 | WARD  | SALESMAN | 7698 | 1981-02-22 00:00:00 | 1250.00 | 500.00 |     30 |
+-------+-------+----------+------+---------------------+---------+--------+--------+
3 rows in set (0.00 sec)
mysql> select * from emp order by  sal desc limit  3;
+-------+-------+-----------+------+---------------------+---------+------+--------+
| empno | ename | job       | mgr  | hiredate            | sal     | comm | deptno |
+-------+-------+-----------+------+---------------------+---------+------+--------+
|  7839 | KING  | PRESIDENT | NULL | 1981-11-17 00:00:00 | 5000.00 | NULL |     10 |
|  7902 | FORD  | ANALYST   | 7566 | 1981-12-03 00:00:00 | 3000.00 | NULL |     20 |
|  7788 | SCOTT | ANALYST   | 7566 | 1982-12-09 00:00:00 | 3000.00 | NULL |     20 |
+-------+-------+-----------+------+---------------------+---------+------+--------+
3 rows in set (0.00 sec)
总结:
limit限定显示前多少行,可与order by联合使用


4.聚合函数

count() sum()函数用法:
#1.各个部门的薪水和
mysql> select deptno,sum(sal) from  emp group by deptno;
+--------+----------+
| deptno | sum(sal) |
+--------+----------+
|     10 |  8750.00 |
|     20 | 10875.00 |
|     30 |  9400.00 |
+--------+----------+
3 rows in set (0.01 sec)
#2.group by字段必须出现在select字段后面   各个部门的各个岗位的薪水和
mysql> select deptno,job, sum(sal) from  emp group by deptno ,job;
+--------+-----------+----------+
| deptno | job       | sum(sal) |
+--------+-----------+----------+
|     10 | CLERK     |  1300.00 |
|     10 | MANAGER   |  2450.00 |
|     10 | PRESIDENT |  5000.00 |
|     20 | ANALYST   |  6000.00 |
|     20 | CLERK     |  1900.00 |
|     20 | MANAGER   |  2975.00 |
|     30 | CLERK     |   950.00 |
|     30 | MANAGER   |  2850.00 |
|     30 | SALESMAN  |  5600.00 |
+--------+-----------+----------+
9 rows in set (0.01 sec)
#3.having    薪水和>5000的各个部门的各个岗位
mysql> select deptno,job,  sum(sal) 
    -> from  emp 
    -> group by deptno ,job
    -> having  sum(sal)>5000; 
+--------+----------+----------+
| deptno | job      | sum(sal) |
+--------+----------+----------+
|     20 | ANALYST  |  6000.00 |
|     30 | SALESMAN |  5600.00 |
+--------+----------+----------+
2 rows in set (0.00 sec)
#4.常用组合where  order  limit 
select deptno,job,  sum(sal) as sum_sal
from  emp 
where job='SALESMAN'
group by deptno ,job
having  sum(sal)>5000 
order by sum(sal) desc 
limit 1;


下面介绍下join及union的用法

数据准备:

create table testa(aid int,aname varchar(40));
create table testb(bid int,bname varchar(40),age int);
insert into testa values(1,'xiaoming');
insert into testa values(2,'LY');
insert into testa values(3,'KUN');
insert into testa values(4,'ZIDONG');
insert into testa values(5,'HB');
insert into testb values(1,'xiaoming',10);
insert into testb values(2,'LY',100);
insert into testb values(3,'KUN',200);
insert into testb values(4,'ZIDONG',110);
insert into testb values(6,'niu',120);
insert into testb values(7,'meng',130);
insert into testb values(8,'mi',170);


5.left join

mysql> select
    -> a.aid,a.aname,
    -> b.bid,b.bname,b.age
    -> from testa as a
    -> left join testb as b on a.aid=b.bid; 
+------+----------+------+----------+------+
| aid  | aname    | bid  | bname    | age  |
+------+----------+------+----------+------+
|    1 | xiaoming |    1 | xiaoming |   10 |
|    2 | LY       |    2 | LY       |  100 |
|    3 | KUN      |    3 | KUN      |  200 |
|    4 | ZIDONG   |    4 | ZIDONG   |  110 |
|    5 | HB       | NULL | NULL     | NULL |
+------+----------+------+----------+------+
5 rows in set (0.00 sec)
总结:
a left join b  a表全,用b表去匹配a表
LEFT JOIN 关键字会从左表 (a) 那里返回所有的行,即使在右表 (b) 中没有匹配的行,匹配不到的列用NULL代替


6.right join

mysql> select
    -> a.aid,a.aname,
    -> b.bid,b.bname,b.age
    -> from testa as a
    -> right join testb as b on a.aid=b.bid;
+------+----------+------+----------+------+
| aid  | aname    | bid  | bname    | age  |
+------+----------+------+----------+------+
|    1 | xiaoming |    1 | xiaoming |   10 |
|    2 | LY       |    2 | LY       |  100 |
|    3 | KUN      |    3 | KUN      |  200 |
|    4 | ZIDONG   |    4 | ZIDONG   |  110 |
| NULL | NULL     |    6 | niu      |  120 |
| NULL | NULL     |    7 | meng     |  130 |
| NULL | NULL     |    8 | mi       |  170 |
+------+----------+------+----------+------+
7 rows in set (0.00 sec)
总结:
a right join b  b表全,用a表去匹配b表
RIGHT JOIN 关键字会右表 (b) 那里返回所有的行,即使在左表 (a) 中没有匹配的行,匹配不到的列用NULL代替


7.inner join

mysql> select
    -> a.aid,a.aname,
    -> b.bid,b.bname,b.age
    -> from testa as a
    -> inner join testb as b on a.aid=b.bid; 
+------+----------+------+----------+------+
| aid  | aname    | bid  | bname    | age  |
+------+----------+------+----------+------+
|    1 | xiaoming |    1 | xiaoming |   10 |
|    2 | LY       |    2 | LY       |  100 |
|    3 | KUN      |    3 | KUN      |  200 |
|    4 | ZIDONG   |    4 | ZIDONG   |  110 |
+------+----------+------+----------+------+
4 rows in set (0.00 sec)
mysql> select
    -> a.aid,a.aname,
    -> b.bid,b.bname,b.age
    -> from testa as a
    -> join testb as b on a.aid=b.bid; 
+------+----------+------+----------+------+
| aid  | aname    | bid  | bname    | age  |
+------+----------+------+----------+------+
|    1 | xiaoming |    1 | xiaoming |   10 |
|    2 | LY       |    2 | LY       |  100 |
|    3 | KUN      |    3 | KUN      |  200 |
|    4 | ZIDONG   |    4 | ZIDONG   |  110 |
+------+----------+------+----------+------+
4 rows in set (0.00 sec)
总结:
inner join 与join 效果一样
在表中存在至少一个匹配时,INNER JOIN 关键字返回行


8.union与union all

mysql> select aid,aname from testa
    -> union
    -> select bid,bname from testb;
+------+----------+
| aid  | aname    |
+------+----------+
|    1 | xiaoming |
|    2 | LY       |
|    3 | KUN      |
|    4 | ZIDONG   |
|    5 | HB       |
|    6 | niu      |
|    7 | meng     |
|    8 | mi       |
+------+----------+
8 rows in set (0.01 sec)
mysql> select aid,aname from testa
    -> union all
    -> select bid,bname from testb;
+------+----------+
| aid  | aname    |
+------+----------+
|    1 | xiaoming |
|    2 | LY       |
|    3 | KUN      |
|    4 | ZIDONG   |
|    5 | HB       |
|    1 | xiaoming |
|    2 | LY       |
|    3 | KUN      |
|    4 | ZIDONG   |
|    6 | niu      |
|    7 | meng     |
|    8 | mi       |
+------+----------+
12 rows in set (0.00 sec)
总结:
union 会去重 union all不去重


相关实践学习
如何快速连接云数据库RDS MySQL
本场景介绍如何通过阿里云数据管理服务DMS快速连接云数据库RDS MySQL,然后进行数据表的CRUD操作。
全面了解阿里云能为你做什么
阿里云在全球各地部署高效节能的绿色数据中心,利用清洁计算为万物互联的新世界提供源源不断的能源动力,目前开服的区域包括中国(华北、华东、华南、香港)、新加坡、美国(美东、美西)、欧洲、中东、澳大利亚、日本。目前阿里云的产品涵盖弹性计算、数据库、存储与CDN、分析与搜索、云通信、网络、管理与监控、应用服务、互联网中间件、移动服务、视频服务等。通过本课程,来了解阿里云能够为你的业务带来哪些帮助     相关的阿里云产品:云服务器ECS 云服务器 ECS(Elastic Compute Service)是一种弹性可伸缩的计算服务,助您降低 IT 成本,提升运维效率,使您更专注于核心业务创新。产品详情: https://www.aliyun.com/product/ecs
目录
相关文章
|
22天前
|
SQL 关系型数据库 MySQL
数据库数据恢复——MySQL简介和数据恢复案例
MySQL数据库数据恢复环境&故障: 本地服务器,安装的windows server操作系统。 操作系统上部署MySQL单实例,引擎类型为innodb,表空间类型为独立表空间。该MySQL数据库没有备份,未开启binlog。 人为误操作,在用Delete命令删除数据时未添加where子句进行筛选导致全表数据被删除,删除后未对该表进行任何操作。
|
1月前
|
SQL 监控 关系型数据库
MySQL原理简介—12.MySQL主从同步
本文介绍了四种为MySQL搭建主从复制架构的方法:异步复制、半同步复制、GTID复制和并行复制。异步复制通过配置主库和从库实现简单的主从架构,但存在数据丢失风险;半同步复制确保日志复制到从库后再提交事务,提高了数据安全性;GTID复制简化了配置过程,增强了复制的可靠性和管理性;并行复制通过多线程技术降低主从同步延迟,保证数据一致性。此外,还讨论了如何使用工具监控主从延迟及应对策略,如强制读主库以确保即时读取最新数据。
MySQL原理简介—12.MySQL主从同步
|
1月前
|
SQL 关系型数据库 MySQL
MySQL原理简介—11.优化案例介绍
本文介绍了四个SQL性能优化案例,涵盖不同场景下的问题分析与解决方案: 1. 禁止或改写SQL避免自动半连接优化。 2. 指定索引避免按聚簇索引全表扫描大表。 3. 按聚簇索引扫描小表减少回表次数。 4. 避免产生长事务长时间执行。
|
1月前
|
SQL 存储 关系型数据库
MySQL原理简介—10.SQL语句和执行计划
本文介绍了MySQL执行计划的相关概念及其优化方法。首先解释了什么是执行计划,它是SQL语句在查询时如何检索、筛选和排序数据的过程。接着详细描述了执行计划中常见的访问类型,如const、ref、range、index和all等,并分析了它们的性能特点。文中还探讨了多表关联查询的原理及优化策略,包括驱动表和被驱动表的选择。此外,文章讨论了全表扫描和索引的成本计算方法,以及MySQL如何通过成本估算选择最优执行计划。最后,介绍了explain命令的各个参数含义,帮助理解查询优化器的工作机制。通过这些内容,读者可以更好地理解和优化SQL查询性能。
|
1月前
|
SQL 存储 关系型数据库
MySQL原理简介—9.MySQL索引原理
本文详细介绍了MySQL索引的设计与使用原则,涵盖磁盘数据页的存储结构、页分裂机制、主键索引设计及查询过程、聚簇索引和二级索引的原理、B+树索引的维护、联合索引的使用规则、SQL排序和分组时如何利用索引、回表查询对性能的影响以及索引覆盖的概念。此外还讨论了索引设计的案例,包括如何处理where筛选和order by排序之间的冲突、低基数字段的处理方式、范围查询字段的位置安排,以及通过辅助索引来优化特定查询场景。总结了设计索引的原则,如尽量包含where、order by、group by中的字段,选择离散度高的字段作为索引,限制索引数量,并针对频繁查询的低基数字段进行特殊处理等。
MySQL原理简介—9.MySQL索引原理
|
1月前
|
SQL 缓存 关系型数据库
MySQL原理简介—8.MySQL并发事务处理
这段内容深入探讨了SQL语句执行原理、事务并发问题、MySQL事务隔离级别及其实现机制、锁机制以及数据库性能优化等多个方面。
|
1月前
|
SQL 缓存 关系型数据库
MySQL原理简介—7.redo日志的底层原理
本文介绍了MySQL中redo日志和undo日志的主要内容: 1. redo日志的意义:确保事务提交后数据不丢失,通过记录修改操作并在系统宕机后重做日志恢复数据。 2. redo日志文件构成:记录表空间号、数据页号、偏移量及修改内容。 3. redo日志写入机制:redo日志先写入Redo Log Buffer,再批量刷入磁盘文件,减少随机写以提高性能。 4. Redo Log Buffer解析:描述Redo Log Buffer的内存结构及刷盘时机,如事务提交、Buffer过半或后台线程定时刷新。 5. undo日志原理:用于事务回滚,记录插入、删除和更新前的数据状态,确保事务可完整回滚。
121 22
|
1月前
|
关系型数据库 MySQL Linux
MySQL原理简介—6.简单的生产优化案例
本文介绍了数据库和存储系统的几个主题: 1. **MySQL日志的顺序写和数据文件的随机读指标**:解释了磁盘随机读和顺序写的原理及对数据库性能的影响。 2. **Linux存储系统软件层原理及IO调度优化原理**:解析了Linux存储系统的分层架构,包括VFS、Page Cache、IO调度等,并推荐使用deadline算法优化IO调度。 3. **数据库服务器使用的RAID存储架构**:介绍了RAID技术的基本概念及其如何通过多磁盘阵列提高存储容量和数据冗余性。 4. **数据库Too many connections故障定位**:分析了MySQL连接数限制问题的原因及解决方法。
|
1月前
|
存储 缓存 关系型数据库
MySQL原理简介—5.存储模型和数据读写机制
本文介绍了MySQL中InnoDB存储引擎的物理存储结构和读写机制。主要内容包括: 1. 为什么不能直接更新磁盘上的数据 2. 数据页的概念 3. 一行数据的存储 4. 数据头的内容 5. 行溢出和溢出页 6. 数据页的物理结构 7. 表空间的物理结构 8. InnoDB存储模型及读写机制总结 这些机制共同确保了InnoDB在高并发场景下的高效运行和数据一致性。
|
1月前
|
缓存 NoSQL 关系型数据库
MySQL原理简介—4.深入分析Buffer Pool
本文介绍了MySQL的Buffer Pool机制,包括其作用、配置方法及内部结构。Buffer Pool是MySQL用于缓存磁盘数据页的关键组件,能显著提升数据库读写性能。默认大小为128MB,可根据服务器配置调整(如32GB内存可设为2GB)。它通过free链表管理空闲缓存页,flush链表记录脏页,并用LRU链表区分冷热数据以优化淘汰策略。此外,还探讨了多Buffer Pool实例、chunk动态调整等优化并发性能的方法,以及如何通过`show engine innodb status`查看Buffer Pool状态。关键词:MySQL内存数据更新机制。