day37总结

昨日回顾

# 	1.pymysql
#
# 		介绍:
# 			Python操作mysql的模块
# 		安装:
# 			pip install mysql
#
# 		连接:
# 			import pymysql
# 			conn = pymysql.connect(host='主机名', user='用户名', password='密码', database='数据库名',charset='utf8');
#
# 			cursor = conn.cursor()  ### 返回的是元祖套元祖
# 			cursor = conn.cursor(cursor=pymysql.cursors.DictCursor) ### 返回的是列表套字典
#
# 		执行sql语句:
# 			cursor.execute(sql)
#
# 		查:
# 			fetchall() : 获取多个, 返回 列表套字典
# 			fetchone() : 获取一个, 返回 字典
# 			fetchmany(size) : 获取size个数据, 返回的是 列表套字典
#
# 		增删改:
#
# 			conn.commit()
#
# 		SQL注入:
# 			原因:
# 				太相信用户输入的数据
#
# 			解决的方法:
# 				# sql = "select * from user where name='%s' and password='%s'" % (user, pwd)
# 				sql = "select * from user where name=%s and password=%s"
#
# 				cursor.execute(sql, (user, pwd))
# 		csrf攻击
#
#
#
# 	2.索引
#
# 		a.索引的作用?
# 			提高查询的效率
#
# 		b.类比:字典中的目录
#
# 		c.底层采用的数据结构:(******************)
# 			B+树
#
# 		d.索引本质上就是一个特殊的文件, 只不过这个特殊的文件底层的数据结构是B+树
#
#
# 		e.索引的分类:
#
# 			- 主键索引
#
# 				作用: 加快查询速度 + 不能重复 + 不能为空
#
# 				增加:
#
# 					第一种方法:(**********************)
# 						create table user (
# 							id int auto_increment primary key,  ### 主键自增id
# 						)
#
# 						注意:auto_increment 依赖 primary key, 而primary key 不依赖auto_increment
#
# 					第二种方法:
# 						alter table user change id id int auto_increment primary key;
# 				删除:
#
# 					如果要删除带有 auto_increment的primary key的话, 需要提前删除auto_increment
# 					alter table user change id id int  primary key;
#
# 					然后再删除
# 					alter table user drop primary key;
#
# 				场景:
# 					一般都是加在 id 这一列
#
# 				技术是服务于业务的
#
#
# 			- 唯一索引
# 				作用: 加快查询速度 + 不能重复
#
# 				增加:
#
# 					第一种方法:
#
# 						create table user (
# 							id int auto_increment primary key,
# 							phone int not null default 0,
# 							name varchar(32)
# 							unique ix_phone(索引名) (phone(字段名))
# 						)
#
# 					第二种方法:
# 						alter table user add unique index ix_phone (phone);
#
# 					第三种方法:
# 						create unique index ix_phone on user (phone);
#
#
# 				删除:
# 					alter table user drop index ix_phone;
#
#
# 				场景:
# 					应用在唯一值得时候,根据自己的业务去定
# 					脱离业务谈技术就是耍流氓
#
#
# 				- 联合唯一索引
#
# 					使用方法同上
#
# 					场景:
# 						根据项目或者业务方的需求,灵活的加上联合唯一索引
#
# 				例子:
# 					create table user (
# 						id int auto_increment primary key,
# 						a int not null default 0,
# 						b int not null default 0,
# 						unique ix_ab (a,b)
# 					)charset utf8;
#
# 					insert into user (a,b) values (1,2);
# 					insert into user (a,b) values (1,3);
# 					insert into user (a,b) values (3,2);
#
# 					mysql> insert into user (a,b) values (1,2);
# 					ERROR 1062 (23000): Duplicate entry '1-2' for key 'ix_ab'
# 					mysql>
# 					mysql> insert into user (a,b) values (1,3);
# 					Query OK, 1 row affected (0.05 sec)
#
#
# 			- 普通索引
#
#
# 				作用:加速查找
#
# 				增加:
#
# 					第一种方法:
# 						create table user (
# 							id int auto_increment primary key,
# 							name varchar(32) not null default '',
# 							index ix_name (name)
# 						)
#
# 					第二种方式:
# 						alter table user add index ix_name (name);
#
#
# 					第三种方法:
# 						create  index ix_name on user (name);
#
# 				删除:
# 					alter table user drop index ix_name;
#
#
# 				- 联合(组合)索引
# 					index(name, age)
#
#
# 		f.索引的命中:
# 			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
#
# 					如果组合索引为:ix_name_email_age (name, email, age):
#
# 						where name='zekai' and email='xxx' and age=12;  ---- 命中索引
# 						where name='zekai' and age=12;              ---- 命中索引
#
# 						mysql> explain select * from user where name='zekai' and email='zekai@163.com' and age=12 \G
# 						*************************** 1. row ***************************
# 								   id: 1
# 						  select_type: SIMPLE
# 								table: user
# 						   partitions: NULL
# 								 type: ref
# 						possible_keys: ix_name_email_age
# 								  key: ix_name_email_age
# 							  key_len: 218
# 								  ref: const,const,const
# 								 rows: 1
# 							 filtered: 100.00
# 								Extra: Using index
# 						1 row in set, 1 warning (0.00 sec)
#
# 						mysql> explain select * from user where name='zekai'  and age=12 \G
# 						*************************** 1. row ***************************
# 								   id: 1
# 						  select_type: SIMPLE
# 								table: user
# 						   partitions: NULL
# 								 type: ref
# 						possible_keys: ix_name_email_age
# 								  key: ix_name_email_age
# 							  key_len: 62
# 								  ref: const
# 								 rows: 1
# 							 filtered: 10.00
# 								Extra: Using where; Using index
# 						1 row in set, 1 warning (0.00 sec)
#
# 						mysql> explain select * from user where email='zekai@qq.com'  and age=12 \G
# 						*************************** 1. row ***************************
# 								   id: 1
# 						  select_type: SIMPLE
# 								table: user
# 						   partitions: NULL
# 								 type: index
# 						possible_keys: NULL
# 								  key: ix_name_email_age
# 							  key_len: 218
# 								  ref: NULL
# 								 rows: 2987635
# 							 filtered: 1.00
# 								Extra: Using where; Using index
# 						1 row in set, 1 warning (0.00 sec)
#
# 						mysql> explain select * from user where age=12 \G
# 						*************************** 1. row ***************************
# 								   id: 1
# 						  select_type: SIMPLE
# 								table: user
# 						   partitions: NULL
# 								 type: index
# 						possible_keys: NULL
# 								  key: ix_name_email_age
# 							  key_len: 218
# 								  ref: NULL
# 								 rows: 2987635
# 							 filtered: 10.00
# 								Extra: Using where; Using index
# 						1 row in set, 1 warning (0.00 sec)
#
# 						mysql> explain select * from user where email=12 \G
# 						*************************** 1. row ***************************
# 								   id: 1
# 						  select_type: SIMPLE
# 								table: user
# 						   partitions: NULL
# 								 type: index
# 						possible_keys: NULL
# 								  key: ix_name_email_age
# 							  key_len: 218
# 								  ref: NULL
# 								 rows: 2987635
# 							 filtered: 10.00
# 								Extra: Using where; Using index
# 						1 row in set, 1 warning (0.00 sec)
#
# 						mysql> explain select * from user where email='zekai@163.com' \G
# 						*************************** 1. row ***************************
# 								   id: 1
# 						  select_type: SIMPLE
# 								table: user
# 						   partitions: NULL
# 								 type: index
# 						possible_keys: NULL
# 								  key: ix_name_email_age
# 							  key_len: 218
# 								  ref: NULL
# 								 rows: 2987635
# 							 filtered: 10.00
# 								Extra: Using where; Using index
# 						1 row in set, 1 warning (0.00 sec)
#
# 						mysql> explain select * from user where name='zekai' \G
# 						*************************** 1. row ***************************
# 								   id: 1
# 						  select_type: SIMPLE
# 								table: user
# 						   partitions: NULL
# 								 type: ref
# 						possible_keys: ix_name_email_age
# 								  key: ix_name_email_age
# 							  key_len: 62
# 								  ref: const
# 								 rows: 1
# 							 filtered: 100.00
# 								Extra: Using index
# 						1 row in set, 1 warning (0.00 sec)
#
# 						mysql> tee D:/a.log
# 						Logging to file 'D:/a.log'
#
#
#
# 				explain
#
#
# 				g.慢日志:
#
# 					查询:
# 						show variables like '%slow%';
# 						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 |
#
#
# 				排查慢SQL的原因:
#
# 					1. 将慢SQL记录到日志中
#
# 					2. 获取慢SQl,根据慢SQL来优化查询效率 (加索引或者修改索引)

今日内容

# 今日内容:
#
# 	1.作业题
#
#
# 	2.事务
# 		通俗的说,事务指一组操作,要么都执行成功,要么都执行失败
#
# 		思考:
# 			我去银行给朋友汇款,
# 			我卡上有1000元,
# 			朋友卡上1000元,
# 			我给朋友转账100元(无手续费),
# 			如果,我的钱刚扣,而朋友的钱又没加时,
# 			网线断了,怎么办?
#
# 		演示:
# 			create table user (
# 				id int auto_increment primary key,
# 				name varchar(32) not null default '',
# 				salary int not null default 0
# 			)charset utf8;
#
# 			insert into user (name, salary) values ('zekai', 1000);
# 			insert into user (name, salary) values ('min', 1000);
#
# 		解决的方法:
# 			使用事务:
# 				start transaction;
# 					sql语句
# 				commit/rollback;
#
# 			例子:
# 				commit成功:
# 				mysql> start transaction;
# 				Query OK, 0 rows affected (0.00 sec)
#
# 				mysql> update user set salary=900 where name='zekai';
# 				Query OK, 1 row affected (0.01 sec)
# 				Rows matched: 1  Changed: 1  Warnings: 0
#
# 				mysql> select * from user;
# 				+----+-------+--------+
# 				| id | name  | salary |
# 				+----+-------+--------+
# 				|  1 | zekai |    900 |
# 				|  2 | min   |   1000 |
# 				+----+-------+--------+
# 				2 rows in set (0.00 sec)
#
# 				mysql> update user set salary=1100 where name='min';
# 				Query OK, 1 row affected (0.00 sec)
# 				Rows matched: 1  Changed: 1  Warnings: 0
#
# 				mysql> select * from user;
# 				+----+-------+--------+
# 				| id | name  | salary |
# 				+----+-------+--------+
# 				|  1 | zekai |    900 |
# 				|  2 | min   |   1100 |
# 				+----+-------+--------+
# 				2 rows in set (0.00 sec)
#
# 				mysql> #2.提交
# 				mysql> commit;
# 				Query OK, 0 rows affected (0.06 sec)
#
# 				rollback回滚:
# 					mysql> start transaction;
# 					Query OK, 0 rows affected (0.00 sec)
#
# 					mysql>
# 					mysql>
# 					mysql> update user set salary=800 where name='zekai';
# 					Query OK, 1 row affected (0.01 sec)
# 					Rows matched: 1  Changed: 1  Warnings: 0
#
# 					mysql> select * from user;
# 					+----+-------+--------+
# 					| id | name  | salary |
# 					+----+-------+--------+
# 					|  1 | zekai |    800 |
# 					|  2 | min   |   1100 |
# 					+----+-------+--------+
# 					2 rows in set (0.00 sec)
#
# 					mysql> rollback;
# 					Query OK, 0 rows affected (0.11 sec)
#
# 					mysql> select * from user;
# 					+----+-------+--------+
# 					| id | name  | salary |
# 					+----+-------+--------+
# 					|  1 | zekai |    900 |
# 					|  2 | min   |   1100 |
# 					+----+-------+--------+
# 					2 rows in set (0.00 sec)
#
# 				rollback回滚,影响所有:
#
# 					mysql> start transaction;
# 					Query OK, 0 rows affected (0.00 sec)
#
# 					mysql> update user set salary=800 where name='zekai';
# 					Query OK, 1 row affected (0.00 sec)
# 					Rows matched: 1  Changed: 1  Warnings: 0
#
# 					mysql> update user set salary=700 where name='zekai';
# 					Query OK, 1 row affected (0.00 sec)
# 					Rows matched: 1  Changed: 1  Warnings: 0
#
# 					mysql> select * from user;
# 					+----+-------+--------+
# 					| id | name  | salary |
# 					+----+-------+--------+
# 					|  1 | zekai |    700 |
# 					|  2 | min   |   1100 |
# 					+----+-------+--------+
# 					2 rows in set (0.00 sec)
#
# 					mysql> rollback;
# 					Query OK, 0 rows affected (0.05 sec)
#
# 					mysql> select * from user;
# 					+----+-------+--------+
# 					| id | name  | salary |
# 					+----+-------+--------+
# 					|  1 | zekai |    900 |
# 					|  2 | min   |   1100 |
# 					+----+-------+--------+
# 					2 rows in set (0.00 sec)
#
# 			特性:(****************)
# 				原子性(Atomicity),原子意为最小的粒子,即不能再分的事务,要么全部执行,要么全部取消(就像上面的银行例子)
# 				一致性(Consistency):指事务发生前和发生后,数据的总额依然匹配
# 				隔离性(Isolation):简单点说,某个事务的操作对其他事务不可见的
# 				持久性(Durability):当事务完成后,其影响应该保留下来,不能撤消,只能通过“补偿性事务”来抵消之前的错误
#
# 			存储引擎:(**************)
#
# 				InnoDB  : 保时捷引擎
#
# 				MyIsam  : 奔奔引擎
#
# 				建表的时候,
# 					create table user (
# 						id int auto_increment primary key,
# 						name varchar(32) not null default '',
# 						salary int not null default 0
# 					)engine=Innodb charset utf8;
#
# 				mysql5.5以上, 默认用到就是InnoDB
#
# 				两个引擎的区别:(**************)
# 					1. Innodb支持事务,MyISAM不支持
# 					2. InnoDB支持行锁,MyISAM支持的表锁
#
#
#
#
# 	3.视图
#
# 		项目, 有100个SQl, 其中80个SQL都是:select * from user where name='xxx';
#
#
# 		增加视图:
# 			create view 视图名 as SQL语句;
#
# 		删除:
# 			drop view v1;
#
# 		例子:
# 			mysql> select * from user where name='zekai';
# 			+----+-------+--------+
# 			| id | name  | salary |
# 			+----+-------+--------+
# 			|  1 | zekai |    900 |
# 			+----+-------+--------+
# 			1 row in set (0.00 sec)
#
#
# 			mysql> create view v1 as select * from user where name='zekai';
# 			Query OK, 0 rows affected (0.07 sec)
#
# 			mysql>
# 			mysql> show tables;
# 			+-----------------+
# 			| Tables_in_test3 |
# 			+-----------------+
# 			| user            |
# 			| v1              |
# 			+-----------------+
# 			2 rows in set (0.00 sec)
#
# 			mysql> select * from v1;
# 			+----+-------+--------+
# 			| id | name  | salary |
# 			+----+-------+--------+
# 			|  1 | zekai |    900 |
# 			+----+-------+--------+
# 			1 row in set (0.00 sec)
#
#
#
# 	4.触发器
#
# 		两张表:
# 			订单表     库存表
#
# 		场景:
# 			当我下一个订单的时候, 订单表中需要增加一个记录, 同时库存表中需要减1
# 			这两个操作是同时发生的,  并且前一个操作出发后一个操作
#
# 		使用方法:
#
# 			增加:
# 				delimiter //
#
# 				CREATE TRIGGER tri_before_insert_tb1 BEFORE INSERT ON t2 FOR EACH ROW
# 				BEGIN
# 					INSERT INTO t3 (NAME) VALUES ('aa');
# 				END //
#
# 				delimiter ;
#
# 			### 当向tb1表中添加一条数据的同时, 向tb2表添加一条数据
#
# 			查看:
# 			 show triggers\G
# 				*************************** 1. row ***************************
# 							 Trigger: tri_before_insert_tb1
# 							   Event: INSERT
# 							   Table: t2
# 						   Statement: BEGIN
# 				INSERT INTO t3 (NAME) VALUES ('aa');
# 				END
# 							  Timing: BEFORE
# 							 Created: 2019-11-01 11:47:20.65
# 							sql_mode: ONLY_FULL_GROUP_BY
# 							 Definer: root@localhost
# 				character_set_client: gbk
# 				collation_connection: gbk_chinese_ci
# 				  Database Collation: latin1_swedish_ci
#
# 			删除:drop trigger 触发器名;
#
# 			例子:
# 				mysql> select * from t2;
# 				Empty set (0.00 sec)
#
# 				mysql> select * from t3;
# 				Empty set (0.00 sec)
# 				mysql> insert into t2 (name) values ('zekai');
# 				Query OK, 1 row affected (0.06 sec)
#
# 				mysql> select * from t2;
# 				+----+-------+
# 				| id | name  |
# 				+----+-------+
# 				|  1 | zekai |
# 				+----+-------+
# 				1 row in set (0.00 sec)
#
# 				mysql> select * from t3;
# 				+----+------+
# 				| id | name |
# 				+----+------+
# 				|  1 | aa   |
# 				+----+------+
# 				1 row in set (0.00 sec)
#
#
# 	5.存储过程
#
# 		像  一个 SQL函数
#
# 		创建:
#
# 			delimiter //
#
# 			create procedure p1()
# 			BEGIN
# 				select * from user where id=2;
# 			END //
#
# 			delimiter ;
#
# 		例子:
#
# 			mysql> delimiter //
#
# 			mysql> create procedure p1()
# 				-> BEGIN
# 				-> select * from user where id=2;
# 				-> END //
# 			Query OK, 0 rows affected (0.10 sec)
#
# 			mysql> delimiter ;
#
# 			mysql> call p1();
# 			+----+------+--------+
# 			| id | name | salary |
# 			+----+------+--------+
# 			|  2 | min  |   1100 |
# 			+----+------+--------+
# 			1 row in set (0.00 sec)
#
# 			Query OK, 0 rows affected (0.01 sec)
#
# 		删除:
# 			drop procedure p1;
#
#
#
# 	6.函数
# 		CHAR_LENGTH(str)
# 			返回值为字符串str 的长度,长度的单位为字符。一个多字节字符算作一个单字符。
# 			对于一个包含五个二字节字符集, LENGTH()返回值为 10, 而CHAR_LENGTH()的返回值为5。
#
# 		CONCAT(str1,str2,...)
# 			字符串拼接
# 			如有任何一个参数为NULL ,则返回值为 NULL。
# 		FORMAT(X,D)
# 			将数字X 的格式写为'#,###,###.##',以四舍五入的方式保留小数点后 D 位, 并将结果以字符串的形式返回。若  D 为 0, 则返回结果不带有小数点,或不含小数部分。
# 			例如:
# 				SELECT FORMAT(12332.1,4); 结果为: '12,332.1000'
# 		INSTR(str,substr)
# 			返回字符串 str 中子字符串的第一个出现位置。
# 		LEFT(str,len)
# 			返回字符串str 从开始的len位置的子序列字符。
# 		LOWER(str)
# 			变小写
# 		UPPER(str)
# 			变大写
# 		LTRIM(str)
# 			返回字符串 str ,其引导空格字符被删除。
# 		RTRIM(str)
# 			返回字符串 str ,结尾空格字符被删去。
# 		SUBSTRING(str,pos,len)
# 			获取字符串子序列
# 		LOCATE(substr,str,pos)
# 			获取子序列索引位置
# 		REPEAT(str,count)
# 			返回一个由重复的字符串str 组成的字符串,字符串str的数目等于count 。
# 			若 count <= 0,则返回一个空字符串。
# 			若str 或 count 为 NULL,则返回 NULL 。
# 		REPLACE(str,from_str,to_str)
# 			返回字符串str 以及所有被字符串to_str替代的字符串from_str 。
# 		REVERSE(str)
# 			返回字符串 str ,顺序和字符顺序相反。
# 		RIGHT(str,len)
# 			从字符串str 开始,返回从后边开始len个字符组成的子序列
#
#
# 		http://doc.mysql.cn/mysql5/refman-5.1-zh.html-chapter/functions.html#encryption-functions
#
#
#
#
# 	7.运维方向:
# 		数据库的备份
#
# 			为啥要备份?
# 				将重要的数据保存下来
#
# 			用法:
# 				#语法:
# 				# mysqldump -h 服务器 -u用户名 -p密码 数据库名 表名,  表名,.... > aaa.sql
#
# 				#示例:
# 				#单库备份
# 				mysqldump -uroot -p123 db1 > db1.sql
# 				mysqldump -uroot -p123 db1 table1 table2 > db1-table1-table2.sql
#
# 				#多库备份
# 				mysqldump -uroot -p123 --databases db1 db2 mysql db3 > db1_db2_mysql_db3.sql
#
# 				#备份所有库
# 				mysqldump -uroot -p123 --all-databases > all.sql
#
# 			重新导入:
# 				mysql> source D:/test3.sql;
posted @ 2019-11-03 20:13  lucky_陈  阅读(136)  评论(0编辑  收藏  举报