Basic syntax of MySQL DDL and DML and DQL

Preface         

        SQL sentence , Structured query language (Structured Query Language), Is a special purpose programming language , Is a database query and programming language , For data access and query 、 Update and manage relational database system , It is also the extension of database script file .

      SQL standard-specified SQL Sentences are divided into ：DDL（Data Define Language Data definition language ）、  DML（Data Manipulation Language Data operation language ）、DQL（Data Query Language Data query language ）、DCL（Data Control Language Data control language ）. This article will introduce them in detail .

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First, learn about SQL Some grammatical considerations ：

1. SQL Statements can be written in one or more lines , It ends with a semicolon .

2. You can use spaces and indents to enhance the readability of statements .

3. MySQL Database SQL Statement is case insensitive , It is recommended to use uppercase .

4. 3 Species notes

① Single-line comments :  -- The comment or # The comment (mysql specific )

② Multiline comment :  /* notes */

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One 、DDL（ Data definition language ）

DDL Language ： Comprehensive data definition language （Data Define Language）, It is used to define and manage data objects , Such as a database , Data sheets, etc .DDL Command has CREATE（ establish ）、DROP（ Delete ）、ALTER（ modify ）.

Let's give you an example with code ：

-- SQL Syntax is case-insensitive 
--  Use a semicolon at the end of each sentence ;
#  Operation of the library 
--  Show all libraries 
show databases;

--  Create a library 
-- create database  Library name ;
create database ku;

--  Delete a library 
-- drop database  Library name ;
drop database ku;

--  Use the library 
-- use  Library name ;
use ku;


#  The operation of the table 
--  Look at all the tables in the library 
show tables;

--  Build table 
create table  Table name (
	 Field name    type    attribute ,
	 Field name    type    attribute ,
	....
	 Field name    type   attribute 
);

create table tab_teacher(
	tea_name varchar(10),
	tea_sex char(1),
	tea_birthday datetime,
	tea_money decimal(20,1)
);

show tables;

--  View table structure 
desc tab_teacher;

show create table tab_teacher;

-- `  The quotation marks   Disable keywords 
CREATE TABLE `tab_teacher` (
  `tea_name` varchar(10) DEFAULT NULL,
  `tea_sex` char(1) DEFAULT NULL,
  `tea_birthday` datetime DEFAULT NULL,
  `tea_money` decimal(20,1) DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 
    COLLATE=utf8mb4_0900_ai_ci

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Two 、DML（ Data operation language ）

DML Language ： Data operation language （Data Manipulation Language）, It is used to operate the data contained in the database object .DML Command has INSERT（ increase ）、DELETE（ Delete ）、UPDATE（ modify ）.

Let's give you an example with code ：

# DML  sentence 

--  newly added 
--  grammar 
-- insert into  Table name ( Field name , Field name ... Field name ) values( value , value ... value );

--  The date is expressed as a string 
insert into student(sid,sname,birthday,ssex,classid) values(9,' Zhang San ','1999-1-1',' male ',3);

insert into student(sid,ssex,classid) values(11,' male ',2);

--  Let the primary key increase 
insert into student(sname) values(" Wang sang ");
insert into student values(default,' Lao Wang ','1970-6-1',' male ',2);
insert into student values(null,' Lao Wang ','1970-6-1',' male ',2);

--  Insert multiple pieces of data at once 
insert into student(sname,ssex) values(' Wang Shuai ',' male '),(' Wang Liangliang ',' male '),(' Sister Wang ',' Woman ');

--  Unusual new methods 
--  Tables must exist 
create table stu1(
	xingming varchar(10),
	ssex varchar(2)
)
-- insert into select 
insert into stu1 select sname,ssex from student;

--  Insert data when creating a new table 
--  New table cannot exist 
create table newstu select sname,birthday,ssex from student;


--  modify 
--  grammar 
-- update  Table name  set  Field name = value , Field name = value ... where  Clause 

update stu1 set xingming = ' Zhao Leilei ';

update newstu set ssex= ' Woman ' where sname=' Lao Wang ';

--  Range 
update student set ssex = ' Woman ',classid = 10 where sid >= 10 and sid <= 15;

-- between  Little data  and  big data 
update student set ssex=' ha-ha ',classid = 20 where sid between 10 and 15;


--  Delete 
-- delete from  Table name   where  Clause 
delete from stu1;
delete from student  where sname = ' Lao Wang ';

--  Clear the table 
truncate  Table name 
truncate student;

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3、 ... and 、DQL（ Data query language ）

DQL Language ： Data query language （Data Query Language）, It is used to query database data .DQL Command has SELECT（ Inquire about ）.

Let's give you an example with code ：

# DQL

--  Inquire about 
--  Query the data of all rows and columns of the table ( What you get is a virtual table )
-- select * from  Table name ;
select * from student;

--  Query the specified field 
-- select  Field name 1, Field name 2... from  Table name ;
select sid,sname,birthday,ssex,classid from student;


--  The field is aliased 
-- select  Old field name  as ' new field name ';
select sname as ' full name ', birthday ' Birthday ',ssex  Gender  from student;


--  Remove duplication  distinct
-- select distinct  Field name ... from  Table name ; 
select distinct ssex,classid,sid from student;


--  Conditional inquiry   WHERE  Clause 
select * from student where ssex = ' male ' and classid = 1;

--  Birthday   Greater than  1990-1-1  Of the students 
select * from student where birthday < '1990-1-1';

--  Fuzzy query  like
insert into student(sname) 
values(' Zhang Sanfeng '),(' Zhang San '),(' Zhang Sansan ');

--  Zhang Zi related data 
--  Fuzzy symbols  %  Any number of any characters 
select * from student where sname like '% Zhang %';

--  Zhang 
select * from student where sname like ' Zhang %';

--  Fuzzy symbols _  An arbitrary character 
select * from student where sname like ' Zhang __';

--  The student number is  2,5,6,8,9,20,300,4000
-- in  Find in a specific range 
select * from student  where sid in (2,5,6,8,9,20,300,4000);


--  Students without birthdays   is  It's right null The judgment of the 
select * from student where birthday is null;
select * from student where birthday is not null;



#  grouping 
-- group by  Field 
select count(1) from student where ssex = ' male ';
select count(1) from student where ssex = ' Woman ';
select ssex,count(sid) from student group by ssex;

--  How many students are there in each class 
select classid,count(sid) from student group by classid;

-- sc   The average score of each student 
select sid,avg(score)  average , sum(score)  Total score ,max(score)  The highest , min(score)  Lowest score , count(*)  frequency  from sc group by sid;

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Four 、 Aggregate functions

grammar ： Before we do the query is horizontal query , They are judged line by line according to the conditions , The aggregate function query is vertical query , It calculates the values of a column , And then return a result value . Aggregate functions ignore null values NULL.

-- Number of Statistics count( Field )/ Fields can be written *、 Constant 、 Any field name /count The statistical data is null The number of .

-- Statistical average avg( Field )

-- Statistical maximum max( Field )

-- Statistical minimum min( Field )

-- Statistical sum sum( Field )

eg: select count(*) Total number , sum(score) Total score , avg(score) average , max(score) The highest , min(score) Lowest score from sc;

#  Aggregate functions 
count( Field ) --  Number of Statistics 
--  Numbers 
avg( Field ) --  Average 
sum( Field ) --  The sum of the 
max( Field ) --  Maximum 
min( Field ) --  minimum value 

-- count  Number of Statistics 
select count(*) from student where ssex = ' male ';
select count(sname) from student where ssex = ' male ';
select count(1) from student where ssex = ' male ';
select count('a') from student where ssex = ' male ';
-- count()  No statistics null
select count(birthday) from student;


-- avg  Average 
--  The average score of all students 
select avg(score) from sc;

-- sum  Total score 
select sum(score) from sc;


select count(*)  frequency , sum(score)  Total score , avg(score)  average , max(score)  The highest ,min(score) Lowest score  from sc;