day36总结
day04 数据库
昨日回顾
单表的操作:
分组:
group by:
select count(id) from xxx group by gender;
having:
select count(id) from xxx group by gender having count(id) > 23;
group by > having
排序:
order by 要排序的字段名(id)
升序: asc 例子:order by id asc;
降序: desc 例子: order by id desc;
order by age asc, id desc;
先根据年龄升序,然后如果年纪一样的时候,再根据id进行降序
分页:
limit offset, size
offset: 行数据的索引
size: 取多少行数据
select * from 表名 limit 0, 10
先后顺序:
where > group by > having > order by > limit
多表关系
一对多:
create table department(
id int,
name varchar(32) not null default ''
)charset utf8;
create table userinfo (
id int,
name varchar(32) not null default '',
depart_id int,
constraint 外键名 foreign key (depart_id) references department(id)
)charset utf8;
多对多:
create table boy(
id int,
bname varchar(32) not null default ''
)
create table girl(
id int,
gname varchar(32) not null default ''
)
create table boy2girl(
id int,
bid int ,
gid int ,
constraint 外键名 foreign key (bid) references boy(id),
constraint 外键名 foreign key (gid) references girl(id),
)
一对一:
create table userinfo (
id int, #### 主键id
name varchar(32),
salary decimal
)
userinfo:
id name
1 zekai
2 xxxx
3 hhhh
create table pri(
id int,
salary decimal(23,4)
uid int,
unique(uid)
constraint 外键
)
pri
id salary uid (外键 + unique)
1 1234.5 1
2 2345.56 2
3 897.56 3
4 5678.56 4
多表查询:
3.
left join
select * from department left join userinfo on department.id = userinfo.depart_id where group by order by limit ;
right join
inner join
join
今天内容:
作业讲解
python操作mysql
安装: pip install pymysql
sql注入问题
输入用户名:zekai ' or 1=1 #
输入密码:dsadsa
select * from user where name='zekai ' or 1=1 #' and password='dsadsa'
[{'id': 1, 'name': 'zhangsan', 'password': ''}, {'id': 2, 'name': 'zekai', 'password': '123'}, {'id': 3, 'name': 'kkk', 'password': ''}]
产生的原因:
因为过于相信用户输入的内容, 根本没有做任何的检验
解决的方法:
sql = "select * from user where name=%s and password=%s"
cursor.execute(sql, (user, pwd))
连接:
### 连接数据库的参数
conn = pymysql.connect(host='localhost',user='root',password='123qwe',database='test',charset='utf8')
# cursor = conn.cursor() ### 默认返回的值是元祖类型
cursor = conn.cursor(cursor=pymysql.cursors.DictCursor) ### 返回的值是字典类型 (*********)
查:
fetchall() : 取出所有的数据 返回的是列表套字典
fetchone() : 取出一条数据 返回的是字典
fetchmany(size) : 取出size条数据 返回的是列表套字典
增:
sql = "insert into user (name, password) values (%s, %s)"
# cursor.execute(sql, ('xxx', 'qwe')) ### 新增一条数据
data = [
('zekai1', 'qwe'),
('zekai2', 'qwe1'),
('zekai3', 'qwe2'),
('zekai4', 'qwe3'),
]
cursor.executemany(sql, data) ### 新增多条数据
#### 加如下代码
conn.commit()
print(cursor.lastrowid) ### 获取最后一行的ID值
修:
sql = "update user set name=%s where id=%s"
cursor.execute(sql, ('dgsahdsa', 2))
conn.commit()
cursor.close()
conn.close()
删除:
sql = "delete from user where id=%s"
cursor.execute(sql, ('dgsahdsa', 2))
conn.commit()
cursor.close()
conn.close()
索引
为啥使用索引以及索引的作用:
使用索引就是为了提高查询效率的
类比:
字典中的目录
索引的本质:
一个特殊的文件
索引的底层原理:
B+树
索引的种类:(**************************)
主键索引: 加速查找 + 不能重复 + 不能为空 primary key
唯一索引: 加速查找 + 不能重复 unique(name)
联合唯一索引:unique(name, email)
例子:
zekai 123@qq.com
zekai 123@qq.cmm
普通索引: 加速查找 index (name)
联合索引: index (name, email)
索引的创建:
主键索引:
新增主键索引:
create table xxx(
id int auto_increment ,
primary key(id)
)
alter table xxx change id id int auto_increment primary key;
alter table t1 add primary key (id);
删除主键索引:
mysql> alter table t1 drop primary key;
唯一索引:
新增:
1.
create table t2(
id int auto_increment primary key,
name varchar(32) not null default '',
unique u_name (name)
)charset utf8
2.
CREATE UNIQUE INDEX 索引名 ON 表名 (字段名) ;
create unique index ix_name on t2(name);
3.
alter table t2 add unique index ix_name (name)
删除:
alter table t2 drop index u_name;
普通索引:
新增:
1.
create table t3(
id int auto_increment primary key,
name varchar(32) not null default '',
index u_name (name)
)charset utf8
2.
CREATE INDEX 索引名 ON 表名 (字段名) ;
create index ix_name on t3(name);
3.
alter table t3 add index ix_name (name)
删除:
alter table t3 drop index u_name;
索引的优缺点:
通过观察 *.ibd文件可知:
1.索引加快了查询速度
2.但加了索引之后,会占用大量的磁盘空间
索引加的越多越好?
不是
不会命中索引的情况:
a. 不能在SQl语句中,进行四则运算, 会降低SQL的查询效率
b. 使用函数
select * from tb1 where reverse(email) = 'zekai';
c. 类型不一致
如果列是字符串类型,传入条件是必须用引号引起来,不然...
select * from tb1 where email = 999;
#排序条件为索引,则select字段必须也是索引字段,否则无法命中
d. order by
select name from s1 order by email desc;
当根据索引排序时候,select查询的字段如果不是索引,则速度仍然很慢
select email from s1 order by email desc;
特别的:如果对主键排序,则还是速度很快:
select * from tb1 order by nid desc;
e. count(1)或count(列)代替count(*)在mysql中没有差别了
f. 组合索引最左前缀
什么时候会创建联合索引?
根据公司的业务场景, 在最常用的几列上添加索引
select * from user where name='zekai' and email='zekai@qq.com';
如果遇到上述业务情况, 错误的做法:
index ix_name (name),
index ix_email(email)
正确的做法:
index ix_name_email(name, email)
如果组合索引为:ix_name_email (name,email) ************
where name='zekai' and email='xxxx' -- 命中索引
where name='zekai' -- 命中索引
where email='zekai@qq.com' -- 未命中索引
例子:
index (a,b,c,d)
where a=2 and b=3 and c=4 and d=5 --->命中索引
where a=2 and c=3 and d=4 ----> 未命中
g:
explain
mysql> explain select * from user where name='zekai' and email='zekai@qq.com'\G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: user
partitions: NULL
type: ref 索引指向 all
possible_keys: ix_name_email 可能用到的索引
key: ix_name_email 确实用到的索引
key_len: 214 索引长度
ref: const,const
rows: 1 扫描的长度
filtered: 100.00
Extra: Using index 使用到了索引
索引覆盖:
select id from user where id=2000;
慢查询日志:
查看慢SQL的相关变量
mysql> show variables like '%slow%'
-> ;
+---------------------------+-----------------------------------------------+
| Variable_name | Value |
+---------------------------+-----------------------------------------------+
| log_slow_admin_statements | OFF |
| log_slow_slave_statements | OFF |
| slow_launch_time | 2 |
| slow_query_log | OFF ### 默认关闭慢SQl查询日志, on |
| slow_query_log_file | D:\mysql-5.7.28\data\DESKTOP-910UNQE-slow.log | ## 慢SQL记录的位置
+---------------------------+-----------------------------------------------+
5 rows in set, 1 warning (0.08 sec)
mysql> show variables like '%long%';
+----------------------------------------------------------+-----------+
| Variable_name | Value |
+----------------------------------------------------------+-----------+
| long_query_time | 10.000000 |
配置慢SQL的变量:
set global 变量名 = 值
set global slow_query_log = on;
set global slow_query_log_file="D:/mysql-5.7.28/data/myslow.log";
set global long_query_time=1;