mysql trigger, process control, and other matters

• view
• trigger
• Affairs
• Stored Procedures
• Built-in functions
• Process Control
• index

view

1. What is the view

View is obtained by querying a virtual table, and then saved, the next can be used directly

2, why should view

If you frequently use a virtual table, you can not repeat the query

3, How to view

create view teacher2course as
select * from teacher inner join course on teacher.tid = course.teacher_id;

Stressed
1, in the hard disk, view the table structure only files, not data files Table
2, the view is usually used to query, try not to modify the data view

drop view teacher2course;

Question: Will the development process to use view?

will not! A view is a function mysql, if you use a lot of items inside view, that means that when you want to expand the latter a function of this function happens to need to make changes to the view, which means you need to be here in mysql first view changed a bit, and then go to modify the application corresponding sql statement, which relates to the issue of inter-departmental communication, so do not usually use a view, but to extend the functionality through re-edit sql statement

trigger

In the case of satisfying a particular table data add, delete, change, automatically trigger the trigger function is called

Why should trigger

Trigger specifically for our data add insert, delete to delete a certain table, change the update behavior, this kind of behavior once executed
execution will trigger a trigger that automatically runs another section of the code sql

The syntax to create a trigger

# 针对插入
create trigger tri_after_insert_t1 after insert on 表名 for each row
begin
    sql代码。。。
end 
create trigger tri_after_insert_t2 before insert on 表名 for each row
begin
    sql代码。。。
end

# 针对删除
create trigger tri_after_delete_t1 after delete on 表名 for each row
begin
    sql代码。。。
end
create trigger tri_after_delete_t2 before delete on 表名 for each row
begin
    sql代码。。。
end

# 针对修改
create trigger tri_after_update_t1 after update on 表名 for each row
begin
    sql代码。。。
end
create trigger tri_after_update_t2 before update on 表名 for each row
begin
    sql代码。。。
end

# 案例
CREATE TABLE cmd (
    id INT PRIMARY KEY auto_increment,
    USER CHAR (32),
    priv CHAR (10),
    cmd CHAR (64),
    sub_time datetime, #提交时间
    success enum ('yes', 'no') #0代表执行失败
);

CREATE TABLE errlog (
    id INT PRIMARY KEY auto_increment,
    err_cmd CHAR (64),
    err_time datetime
);

delimiter $$  # 将mysql默认的结束符由;换成$$
create trigger tri_after_insert_cmd after insert on cmd for each row
begin
    if NEW.success = 'no' then  # 新记录都会被MySQL封装成NEW对象
        insert into errlog(err_cmd,err_time) values(NEW.cmd,NEW.sub_time);
    end if;
end $$
delimiter ;  # 结束之后记得再改回来，不然后面结束符就都是$$了

#往表cmd中插入记录，触发触发器，根据IF的条件决定是否插入错误日志
INSERT INTO cmd (
    USER,
    priv,
    cmd,
    sub_time,
    success
)
VALUES
    ('egon','0755','ls -l /etc',NOW(),'yes'),
    ('egon','0755','cat /etc/passwd',NOW(),'no'),
    ('egon','0755','useradd xxx',NOW(),'no'),
    ('egon','0755','ps aux',NOW(),'yes');

# 查询errlog表记录
select * from errlog;
# 删除触发器
drop trigger tri_after_insert_cmd;

Affairs

What is a transaction

Open a transaction can contain some sql statements, these statements are either simultaneously sql success
or even think about a successful call transaction atomicity

The role of the transaction

It ensures data security for data manipulation

Case: Commerce account to transfer money using the bank card operations of Bank ATM machine

Transaction should have four properties: atomicity, consistency, isolation, durability. These four properties are usually called ACID properties .

Atomicity (atomicity). A transaction is an indivisible unit of work, all operations in the transaction include either do or do not do.

Consistency (consistency). The database transaction must be changed from one consistent state to another consistent state. Consistency and atomicity are closely related.

Isolation (isolation). Execution of a transaction can not be other transactions interference. I.e., operation and use of the data inside a transaction other concurrent transactions are isolated and can not interfere with each other between the respective transaction executed concurrently.

Persistence (durability). Persistence also known as permanent (permanence), means that once a transaction commits, changing its data in the database should be permanent. The next operation or other faults should not have any effect on them.

How to use

create table user(
id int primary key auto_increment,
name char(32),
balance int
);

insert into user(name,balance)
values
('wsb',1000),
('egon',1000),
('ysb',1000);

# 修改数据之前先开启事务操作
start transaction;

# 修改操作
update user set balance=900 where name='wsb'; #买支付100元
update user set balance=1010 where name='egon'; #中介拿走10元
update user set balance=1090 where name='ysb'; #卖家拿到90元

# 回滚到上一个状态
rollback;

# 开启事务之后，只要没有执行commit操作，数据其实都没有真正刷新到硬盘
commit;
"""开启事务检测操作是否完整，不完整主动回滚到上一个状态，如果完整就应该执行commit操作"""

# 站在python代码的角度，应该实现的伪代码逻辑，
try:
    update user set balance=900 where name='wsb'; #买支付100元
    update user set balance=1010 where name='egon'; #中介拿走10元
    update user set balance=1090 where name='ysb'; #卖家拿到90元
except 异常:
    rollback;
else:
    commit;

# 那如何检测异常？

Stored Procedures

Stored procedure contains a series of executable sql statements, stored procedures stored in MySQL, you can perform a bunch of inside sql by calling its name

Three kinds of development model

The first

"""
应用程序：只需要开发应用程序的逻辑
mysql:编写好存储过程，以供应用程序调用
优点：开发效率，执行效率都高
缺点：考虑到人为因素、跨部门沟通等问题，会导致扩展性差
"""

The second

"""
应用程序：除了开发应用程序的逻辑，还需要编写原生sql
优点：比方式1，扩展性高(非技术性的)
缺点：
1、开发效率，执行效率都不如方式1
2、编写原生sql太过于复杂，而且需要考虑到sql语句的优化问题
"""

The third

"""
应用程序：开发应用程序的逻辑，不需要编写原生sql，基于别人编写好的框架来处理数据，ORM
优点：不用再编写纯生sql，这意味着开发效率比方式2高，同时兼容方式2扩展性高的好处
缺点：执行效率连方式2都比不过
"""

Create a stored procedure

delimiter $$
create procedure p1(
    in m int,  # in表示这个参数必须只能是传入不能被返回出去
    in n int,  
    out res int  # out表示这个参数可以被返回出去，还有一个inout表示即可以传入也可以被返回出去
)
begin
    select tname from teacher where tid > m and tid < n;
    set res=0;
end $$
delimiter ;

# 小知识点补充，当一张表的字段特别多记录也很多的情况下，终端下显示出来会出现显示错乱的问题
select * from mysql.user\G;

How to use stored procedures

# 大前提:存储过程在哪个库下面创建的只能在对应的库下面才能使用！！！

# 1、直接在mysql中调用
set @res=10  # res的值是用来判断存储过程是否被执行成功的依据，所以需要先定义一个变量@res存储10
call p1(2,4,10);  # 报错
call p1(2,4,@res);  

# 查看结果
select @res;  # 执行成功，@res变量值发生了变化

# 2、在python程序中调用
pymysql链接mysql
产生的游表cursor.callproc('p1',(2,4,10))  # 内部原理：@_p1_0=2,@_p1_1=4,@_p1_2=10;
cursor.excute('select @_p1_2;')


# 3、存储过程与事务使用举例(了解)
delimiter //
create PROCEDURE p5(
    OUT p_return_code tinyint
)
BEGIN
    DECLARE exit handler for sqlexception
    BEGIN
        -- ERROR
        set p_return_code = 1;
        rollback;
    END;


  DECLARE exit handler for sqlwarning
  BEGIN
      -- WARNING
      set p_return_code = 2;
      rollback;
  END;

  START TRANSACTION;
      update user set balance=900 where id =1;
      update user123 set balance=1010 where id = 2;
      update user set balance=1090 where id =3;
  COMMIT;

  -- SUCCESS
  set p_return_code = 0; #0代表执行成功


END //
delimiter ;

function

Note the difference with a stored procedure, mysql built-in function only in sql statement!

Reference blog: http://www.cnblogs.com/linhaifeng/articles/7495918.html#_label2

CREATE TABLE blog (
    id INT PRIMARY KEY auto_increment,
    NAME CHAR (32),
    sub_time datetime
);

INSERT INTO blog (NAME, sub_time)
VALUES
    ('第1篇','2015-03-01 11:31:21'),
    ('第2篇','2015-03-11 16:31:21'),
    ('第3篇','2016-07-01 10:21:31'),
    ('第4篇','2016-07-22 09:23:21'),
    ('第5篇','2016-07-23 10:11:11'),
    ('第6篇','2016-07-25 11:21:31'),
    ('第7篇','2017-03-01 15:33:21'),
    ('第8篇','2017-03-01 17:32:21'),
    ('第9篇','2017-03-01 18:31:21');

select date_format(sub_time,'%Y-%m'),count(id) from blog group by date_format(sub_time,'%Y-%m');

Process Control

# if条件语句
delimiter //
CREATE PROCEDURE proc_if ()
BEGIN
    
    declare i int default 0;
    if i = 1 THEN
        SELECT 1;
    ELSEIF i = 2 THEN
        SELECT 2;
    ELSE
        SELECT 7;
    END IF;

END //
delimiter ;

# while循环
delimiter //
CREATE PROCEDURE proc_while ()
BEGIN

    DECLARE num INT ;
    SET num = 0 ;
    WHILE num < 10 DO
        SELECT
            num ;
        SET num = num + 1 ;
    END WHILE ;

END //
delimiter ;

Slow indexing and query optimization

Knowledge Review: Data are, inevitably requires that query data on the hard disk IO operations presence

In MySQL indexes also called "key", it is a data structure storage engine used to quickly find the record.

• primary key
• unique key
• index key

Note that foreign key is not used to speed up queries, and we are not within the scope of the study, in addition to the above two accelerating query results as well as additional constraints before the three kinds of key (primary key: non-empty and only, unique key : The only), while the index key without any constraint function will help you speed up queries

The index is a data structure similar to the directory book. It means the later survey data should go first to find the data directory, instead of querying the data page of the way

Essentially: to filter through continuous narrow range of data you want to get the final results you want, while the random events become the order of events, that is to say, with this indexing mechanism, we can always use Find a way to lock the same data.

Index of influence:

• Subject to the availability of large amounts of data in tables, creating the index can be slow
• After the index is created, query performance to the table will be greatly improved, but write performance is reduced

b + tree

https://images2017.cnblogs.com/blog/1036857/201709/1036857-20170912011123500-158121126.png

Only leaf nodes store the actual data, root and branch nodes exist only virtual data

The number of inquiries by the hierarchical decision tree, the lower the level, the less often

A disk the size of the pieces is a certain amount of data that can be stored is means certain. How to ensure the lowest level of the tree it? A disk storage space is relatively small pieces of data items

I think we should give us a table inside what Fields can reduce the level of index tree height >>> primary key id field

Clustered index (primary key)

Clustered index actually refers to the primary key of the table, innodb engine specified in the table must have a primary key. First look at the storage engine.

myisam when construction of the table corresponds to the hard disk has several files (three)?

innodb when construction of the table corresponds to the hard disk has several files (two)? frm file stores the table structure, it is impossible to put the index, which means innodb index with data on the idb table data file.

: Features a complete record of a section of the leaf nodes put

Secondary index (unique, index)

Secondary indexes: query data when not all be used as a screening id conditions, may also use the information field name, password, etc., then you can not use this time to speed up query performance clustered index. It needs to be indexed to other fields, these indexes is called secondary indexes

Features: leaf node is stored in the primary key of that record index field corresponding to the value of the auxiliary (for example: creating an index according to the name field, then the leaf node is stored: the value corresponding to {name: name of the master that record is located } key)

select name from user where name='jason';

The above statement is called a covering index: only the leaf nodes of the secondary index has found all the data we want

select age from user where name='jason';

The above statement is called a non-covering indexes, though, when the index hit a query field name, but to check that the age field, so it needs to find it using the master key

Testing Index

ready

#1. 准备表
create table s1(
id int,
name varchar(20),
gender char(6),
email varchar(50)
);

#2. 创建存储过程，实现批量插入记录
delimiter $$ #声明存储过程的结束符号为$$
create procedure auto_insert1()
BEGIN
    declare i int default 1;
    while(i<3000000)do
        insert into s1 values(i,'jason','male',concat('jason',i,'@oldboy'));
        set i=i+1;
    end while;
END$$ #$$结束
delimiter ; #重新声明分号为结束符号

#3. 查看存储过程
show create procedure auto_insert1\G 

#4. 调用存储过程
call auto_insert1();

# 表没有任何索引的情况下
select * from s1 where id=30000;
# 避免打印带来的时间损耗
select count(id) from s1 where id = 30000;
select count(id) from s1 where id = 1;

# 给id做一个主键
alter table s1 add primary key(id);  # 速度很慢

select count(id) from s1 where id = 1;  # 速度相较于未建索引之前两者差着数量级
select count(id) from s1 where name = 'jason'  # 速度仍然很慢


"""
范围问题
"""
# 并不是加了索引，以后查询的时候按照这个字段速度就一定快   
select count(id) from s1 where id > 1;  # 速度相较于id = 1慢了很多
select count(id) from s1 where id >1 and id < 3;
select count(id) from s1 where id > 1 and id < 10000;
select count(id) from s1 where id != 3;

alter table s1 drop primary key;  # 删除主键 单独再来研究name字段
select count(id) from s1 where name = 'jason';  # 又慢了

create index idx_name on s1(name);  # 给s1表的name字段创建索引
select count(id) from s1 where name = 'jason'  # 仍然很慢！！！
"""
再来看b+树的原理，数据需要区分度比较高，而我们这张表全是jason，根本无法区分
那这个树其实就建成了“一根棍子”
"""
select count(id) from s1 where name = 'xxx';  
# 这个会很快，我就是一根棍，第一个不匹配直接不需要再往下走了
select count(id) from s1 where name like 'xxx';
select count(id) from s1 where name like 'xxx%';
select count(id) from s1 where name like '%xxx';  # 慢 最左匹配特性

# 区分度低的字段不能建索引
drop index idx_name on s1;

# 给id字段建普通的索引
create index idx_id on s1(id);
select count(id) from s1 where id = 3;  # 快了
select count(id) from s1 where id*12 = 3;  # 慢了  索引的字段一定不要参与计算

drop index idx_id on s1;
select count(id) from s1 where name='jason' and gender = 'male' and id = 3 and email = 'xxx';
# 针对上面这种连续多个and的操作，mysql会从左到右先找区分度比较高的索引字段，先将整体范围降下来再去比较其他条件
create index idx_name on s1(name);
select count(id) from s1 where name='jason' and gender = 'male' and id = 3 and email = 'xxx';  # 并没有加速

drop index idx_name on s1;
# 给name，gender这种区分度不高的字段加上索引并不难加快查询速度

create index idx_id on s1(id);
select count(id) from s1 where name='jason' and gender = 'male' and id = 3 and email = 'xxx';  # 快了  先通过id已经讲数据快速锁定成了一条了
select count(id) from s1 where name='jason' and gender = 'male' and id > 3 and email = 'xxx';  # 慢了  基于id查出来的数据仍然很多，然后还要去比较其他字段

drop index idx_id on s1

create index idx_email on s1(email);
select count(id) from s1 where name='jason' and gender = 'male' and id > 3 and email = 'xxx';  # 快 通过email字段一剑封喉 

Joint index

select count(id) from s1 where name='jason' and gender = 'male' and id > 3 and email = 'xxx';  
# 如果上述四个字段区分度都很高，那给谁建都能加速查询
# 给email加然而不用email字段
select count(id) from s1 where name='jason' and gender = 'male' and id > 3; 
# 给name加然而不用name字段
select count(id) from s1 where gender = 'male' and id > 3; 
# 给gender加然而不用gender字段
select count(id) from s1 where id > 3; 

# 带来的问题是所有的字段都建了索引然而都没有用到，还需要花费四次建立的时间
create index idx_all on s1(email,name,gender,id);  # 最左匹配原则，区分度高的往左放
select count(id) from s1 where name='jason' and gender = 'male' and id > 3 and email = 'xxx';  # 速度变快

Summary: The above these operations, you can knock a knock interested, not interested in you can not knock, when the right to see a Lehe. Mastered the theory on the line

Slow query log

Setting a time detecting all sql statement exceeds the time change, and then targeted for optimization!