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english : Structured Query Language, abbreviation SQL, Structured query language
Programming language for operating relational databases
Define a unified standard for operating all relational databases

MySQL Data model

Relational database

A relational database is a database based on a relational model , In short , Relational database is a database composed of multiple two-dimensional tables that can be connected with each other .

advantage

They all use the table structure , The format is consistent , Easy to maintain .
Use the universal SQL Language operation , Easy to use , Can be used for complex queries .
Data is stored on disk , Security .

SQL

SQL brief introduction

english : Structured Query Language, abbreviation SQL
Structured query language , A programming language for operating relational databases
Define a unified standard for operating all relational databases
For the same need , There may be some differences in each way of database operation , We call it “ dialect "

SQL General grammar

SQL Statements can be written in one or more lines , It ends with a semicolon .
MySQL Database SQL Statement is case insensitive , It is recommended to use uppercase .
notes · Single-line comments :-- Note content or # The comment (MySQL specific ). Multiline comment :/* notes */

SQL classification

DDL(Data Definition Language) Data definition language , Used to define database objects : database , surface , Column, etc.
DML(Data Manipulation Language) Data operation language , It is used to add, delete and modify the data in the database
DQL(Data Query Language) Data query language , Used to query the records of tables in the database ( data )
DCL(Data Control Language) Data control language , It is used to define the access rights and security level of the database , And create users

DDL—— Operating the database

1. Inquire about

SHOW DATABASES;

2. establish

Create database

CREATE DATABASE Database name ;

Create database ( Judge , Create... If it doesn't exist )

CREATE DATABASE IF NOT EXISTS Database name ;

3. Delete

Delete database

DROP DATABASE Database name ;

· Delete database ( Judge , Delete... If it exists )

DROP DATABASE IF EXISTS Database name ;

4. Using a database

View currently used databases

SELECT DATABASE();

Using a database

USE Database name ;

DDL -- Operation table

establish (Create)
Inquire about (Retrieve)
modify (Update)
Delete （Delete)

Query table

Query the names of all tables in the current database SHOW TABLES;
· Query table structure DESC The name of the table ;

Create table

CREATE TABLE Table name (

Field name 1 data type 1,

Field name 2 data type 2,
.....
Field name n data type n
);
Be careful : At the end of the last line , No commas

data type
MySQL Support for multiple types , It can be divided into three categories :

The number
date
character string

create table student(
id int,
name varchar(10),
gender char(1),
birthday date,
score double(5,2),
email varchar(64),
tel varchar( 15),
status tinyint
);

Delete table

Delete table DROP TABLE Table name ;
When deleting a table, judge whether the table exists DROPTABLE IF EXISTS Table name ;

Modify table
1. Modify the name of the table
ALTER TABLE Table name RENAME TO New table name ;

mysql> alter table student rename stu;
Query OK, 0 rows affected (0.01 sec)

⒉ Add a column
ALTER TABLE Table name ADD Column name data type ;

mysql> alter table stu add address varchar(50);
Query OK, 0 rows affected (0.05 sec)
Records: 0  Duplicates: 0  Warnings: 0

3. Change data type
ALTER TABLE Table name MODIFY Column name new data type ;

mysql> alter table stu modify address char(30);
Query OK, 0 rows affected (0.04 sec)
Records: 0  Duplicates: 0  Warnings: 0

4. Change column name and data type
ALTER TABLE Table name CHANGE Column name new column name new data type ;

mysql>  alter table stu change address addr varchar(50);
Query OK, 0 rows affected (0.03 sec)
Records: 0  Duplicates: 0  Warnings: 0

5. Delete column
ALTER TABLE Table name DROP Name ;

mysql> alter table stu drop addr;
Query OK, 0 rows affected (0.03 sec)
Records: 0  Duplicates: 0  Warnings: 0

DML

Add data
1. Add data to the specified column
INSERT INTO Table name ( Name 1, Name 2,-.)VALUES( value 1, value 2,.-);
2. Add data to all columns
INSERT INTO Table name VALUES( value 1, value 2,);
3. Batch add data
INSERT INTO Table name ( Name 1, Name 2.….）VALUES( value 1, value 2...),( value 1, value 2...),( value 1, value 2....;INSERT INTO Table name VALUES( value 1, value 2,...),( value 1, value 2...),( value 1, value 2..)..;

Modifying data
1. Modify table data
UPDATE Table name SET Name 1= value 1, Name 2= value 2,... [WHEREI Conditions ];
Be careful : If no condition is added in the modification statement , Then all data will be modified !

Delete data
1. Delete data
DELETE FROM Table name [WHERE Conditions ];
Be careful : Delete statements without conditions , Then all data will be deleted !

--  Query all the data 
SELECT
	*
FROM
	stu;

--  Add data to the specified column  INSERT INTO  Table name ( Name 1, Name 2,…) VALUES( value 1, value 2,…);
INSERT INTO stu (id, NAME)
VALUES
	(1, ' Zhang San ');

--  Add data to all columns , The list of column names can be omitted 
INSERT INTO stu (
	id, --  Number 
	NAME,--  full name 
	sex,
	birthday,
	score,
	email,
	tel,
	STATUS
)
VALUES
	(
		2,
		' Li Si ',
		' male ',
		'1999-11-11',
		88.88,
		'[email protected]',
		'13888888888',
		1
	);

INSERT INTO stu
VALUES
	(
		2,
		' Li Si ',
		' male ',
		'1999-11-11',
		88.88,
		'[email protected]',
		'13888888888',
		1
	);


INSERT INTO stu
VALUES
	(
		2,
		' Li Si ',
		' male ',
		'1999-11-11',
		88.88,
		'[email protected]',
		'13888888888',
		1
	),(
		2,
		' Li Si ',
		' male ',
		'1999-11-11',
		88.88,
		'[email protected]',
		'13888888888',
		1
	),(
		2,
		' Li Si ',
		' male ',
		'1999-11-11',
		88.88,
		'[email protected]',
		'13888888888',
		1
	);

select * from stu;

--  Modifying data  UPDATE  Table name  SET  Name 1= value 1, Name 2= value 2,… [WHERE  Conditions ] ;

--  Change Zhang San's gender to female 

update stu set sex = ' Woman ' where name = ' Zhang San ';

--  Change Zhang San's birthday to  1999-12-12  Change the score to 99.99

update stu set birthday = '1999-12-12', score = 99.99 where name = ' Zhang San ';

--  Be careful ： If update Statement not added where Conditions , All data in the table will be modified ！

update stu set sex = ' Woman ';


--  Delete   DELETE FROM  Table name  [WHERE  Conditions ] ;


--  Delete three records 

delete from stu where name = ' Zhang San ';

delete from stu;

DQL

Basic query
Conditions of the query (wHERE)
Group query (GROUP BY)
Sort query (ORDER BY)
Paging query (LIMIT)

Basic query
1. Query multiple fields
SELECT Field list FROM Table name ;
SELECT * FROM Table name ; -- Query all the data
2. Remove duplicate records
SELECT DISTINCT Field list FROM Table name ;
3. names
AS: AS You can omit it

Conditions of the query
1. Conditional query syntax
SELECT Field list FROM Table name wHERE List of conditions ;

2. Conditions
Symbol function

> Greater than
< Less than
>= Greater than or equal to
<= Less than or equal to
= be equal to
<> or != It's not equal to
BETWEEN ...AND ... Within a certain range ( Both contain )
IN(...) A commonplace
LIKE Place holder
Fuzzy query _ Any single character % More than one arbitrary character
IS NULL yes NULL
IS NOT NULL No NULL
AND or && also
OR or || perhaps
NOT or ! Not , No

SELECT * FROM stu;

--  Conditions of the query  =====================

-- 1. Query age is greater than 20 The information of the 20-year-old student 
select * from stu where age > 20;

-- 2. Query age is greater than or equal to 20 The information of the 20-year-old student 
select * from stu where age >= 20;

-- 3. Query age is greater than or equal to 20 year   also   Age   Less than or equal to  30 year   Student information for 
select * from stu where age >= 20 &&  age <= 30;
select * from stu where age >= 20 and  age <= 30;

select * from stu where age BETWEEN 20 and 30;

-- 4. Check the enrollment date in '1998-09-01'  To  '1999-09-01'   Student information between 

select * from stu where hire_date BETWEEN '1998-09-01' and '1999-09-01';


-- 5.  Query age = 18 The information of the 20-year-old student 

select * from stu where age = 18;

-- 6.  Inquiry age is not equal to 18 The information of the 20-year-old student 
select * from stu where age != 18;

select * from stu where age <> 18;

-- 7.  Query age = 18 year   perhaps   Age equals 20 year   perhaps   Age equals 22 The information of the 20-year-old student 
select * from stu where age = 18 or age = 20 or age = 22;
select * from stu where age in (18,20 ,22);

-- 8.  The English score is  null Student information for   
--  Be careful ： null Value comparison cannot use  = != . Need to use  is  is not
 
select * from stu where english = null; --  No good 

select * from stu where english is null;

select * from stu where english is not null;


--  Fuzzy query  like =====================
/*
	 wildcard ：
	 (1)_: Represents a single arbitrary character 
	 (2)%: Represents any number of characters 
*/

-- 1.  Check the last name ' Horse ' Student information for 

select * from stu where name like ' Horse %';

-- 2.  The second word of the query is ' flowers ' Student information for    

select * from stu where name like '_ flowers %';

-- 3.  The query name contains  ' Virtue '  Student information for 

select * from stu where name like '% Virtue %';

Sort query
1. Sort query syntax
SELECT Field list FROW Table name ORDER BY Sort field names 1[ sort order 1], Sort field names 2[ sort order 2]...;
sort order :

ASC: Ascending order （ The default value is )
DESC: Descending order

Be careful : If there are multiple sorting conditions , When the condition values of the current edge are the same , Will be sorted according to the second condition

/*
	 Sort query ：
		*  grammar ：SELECT  Field list  FROM  Table name   ORDER BY  Sort field names 1 [ sort order 1], Sort field names 2 [ sort order 2] …;
		*  sort order ：
				* ASC： Ascending order （ The default value is ）
				* DESC： Descending order 
*/

-- 1. Search for student information , In ascending order of age  

select * from stu order by age ;

-- 2. Search for student information , In descending order of math scores 

select * from stu order by math desc ;

-- 3. Search for student information , In descending order of math scores , If the math scores are the same , Then arrange them in ascending order of English scores 

select * from stu order by math desc , english asc ;

Aggregate functions
1． Concept : Take a column of data as a whole , Do the longitudinal calculation .
2. Aggregate function classification :
Function name function

count( Name ) Statistical quantity ( Generally, it is not null The column of )
max( Name ) Maximum
min( Name ) minimum value
sum( Name ) Sum up
avg( Name ) Average

3. Aggregate function syntax :
SELECT Aggregate function name ( Name )FROM surface ;
Be careful :null Value does not participate in all aggregate function operations

/*
	 Group function 
			SELECT  Field list  FROM  Table name  [WHERE  Conditions before grouping are limited ] GROUP BY  Group field name  [HAVING  Conditional filtering after grouping ]…;
*/
select * from stu ;
-- 1.  Check the average math scores of male and female students 

select sex, avg(math) from stu group by sex;

--  Be careful ： After grouping , The query fields are aggregate functions and grouping fields , Querying other fields makes no sense 
select name, sex, avg(math) from stu group by sex;

-- 2.  Check the average math scores of male and female students , And their respective numbers 

select sex, avg(math),count(*) from stu group by sex;

-- 3.  Check the average math scores of male and female students , And their respective numbers , requirement ： The score is below 70 Points do not participate in grouping 

select sex, avg(math),count(*) from stu where math > 70 group by sex;

-- 4.  Check the average math scores of male and female students , And their respective numbers , requirement ： The score is below 70 Points do not participate in grouping , The number of people after grouping is greater than 2 One of the .

select sex, avg(math),count(*) from stu where math > 70 group by sex having count(*)  > 2;

Paging query
1. Paging query syntax
SELECT Field list FROM Table name LIMIT Starting index , Number of query entries R
Starting index : from 0 Start
Calculation formula : Starting index =( The current page number -1)· Number of entries per page
tips :

Paging query limit yes MySQL Dialect of database
Oracle Paging query use rownumber
SQL Server Paging query use top

/*
	 Paging query :

			SELECT  Field list  FROM  Table name  LIMIT   Starting index  ,  Number of query entries 
				*  Starting index ： from 0 Start 

*/
select * from stu ;
-- 1.  from 0 Start searching , Inquire about 3 Data 
select * from stu limit 0 , 3;


-- 2.  Each page shows 3 Data , Query the first 1 Page data 
select * from stu limit 0 , 3;
-- 3.  Each page shows 3 Data , Query the first 2 Page data 
select * from stu limit 3 , 3;
-- 4.  Each page shows 3 Data , Query the first 3 Page data 

select * from stu limit 6 , 3;

--  Starting index  = （ The current page number  - 1） *  Number of entries per page

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