MySQL-DQL

/* DQL Data query language , The full English name is Data Query Language, Used to query the data records of tables in the database .  Grammar format ： select [all|distinct] < The expression of the target column 1> [ Alias ], < The expression of the target column 2> [ Alias ]... from < Table or view name > [ Alias ],< Table or view name > [ Alias ]... [where< Conditional expression >] [group by < Name > [having < Conditional expression >]] [order by < Name > [asc|desc]] [limit < Number or list >];  Simplified syntax ： select *|  Name  from  surface  where  Conditions  */
--  Create a product list ：
create table product
(
    pid         int primary key auto_increment, --  Product id 
    pname       varchar(20) not null,           --  Commodity name 
    price       double,                         --  commodity price 
    category_id varchar(20)                     --  Classification of goods 
);
insert into product
values (null, ' Haier washing machine ', 5000, 'c001');
insert into product
values (null, ' Midea refrigerator ', 3000, 'c001');
insert into product
values (null, ' Gree air conditioning ', 5000, 'c001');
insert into product
values (null, ' Jiuyang rice cooker ', 200, 'c001');

insert into product
values (null, ' Woodpecker shirt ', 300, 'c002');
insert into product
values (null, ' Hengyuanxiang trousers ', 800, 'c002');
insert into product
values (null, ' Playboy jacket ', 440, 'c002');
insert into product
values (null, ' Jinba casual pants ', 266, 'c002');
insert into product
values (null, ' Hailan home sweater ', 180, 'c002');
insert into product
values (null, ' Jack Jones Sweatpants ', 430, 'c002');

insert into product
values (null, ' Lancome cream ', 300, 'c003');
insert into product
values (null, ' Estee Lauder essence water ', 200, 'c003');
insert into product
values (null, ' Chanel perfume ', 350, 'c003');
insert into product
values (null, 'SK-II GHb ', 350, 'c003');
insert into product
values (null, ' Shiseido foundation solution ', 180, 'c003');

insert into product
values (null, ' Old Beijing instant noodles ', 56, 'c004');
insert into product
values (null, ' Liangpin shop kelp silk ', 17, 'c004');
insert into product
values (null, ' Three squirrel nuts ', 88, null);

-- 1. Query all products .
select *
from product;

-- 2. Query the product name and price .
select pname, price
from product;

-- 3. Alias query . The keywords used are as（as Omission ）.
-- 3.1 Table alias :
# select * from product as p;
select *
from product p;
-- 3.2 Column alias ：
select pname pn
from product;

-- 4. Remove the repetition value .
select distinct price
from product;

#  When all columns are the same , duplicate removal 
# select distinct *
# from product;

-- 5. The query result is an expression （ Arithmetic query ）： Put the price of all the goods +10 Yuan to display .
select pname, price + 10 as new_price
from product;

#  Conditions of the query 
--  The product name is “ Haier washing machine ” All information about our products 
select *
from product
where pname = ' Haier washing machine ';

--  The inquiry price is 800 goods 
select *
from product
where price = 800;

--  Inquiry price is not 800 All of our products 
select *
from product
where price != 800;

select *
from product
where price <> 800;

select *
from product
where not price = 800;

--  The inquiry commodity price is greater than 60 All the product information of yuan 
select *
from product
where price > 60;

--  Inquire about the price of goods in 200 To 1000 Between all the goods 
select *
from product
where price >= 200
  and price <= 1000;

select *
from product
where price >= 200
          && price <= 1000;

select *
from product
where price between 200 and 1000;

--  The inquiry of commodity price is 200 or 800 All of our products 
select *
from product
where price = 200
   or price = 800;

select *
from product
where price = 200
          || price = 800;

select *
from product
where price in (200, 800);

/* _: Match any single character  %: Match any number of characters  */
--  Query contains ' pants ' All the goods of the word 
select *
from product
where pname like '% pants %';

--  Query to ' The sea ' All the merchandise at the beginning 
select *
from product
where pname like ' The sea %';

--  The second word is ' Cardamom ' All of our products 
select *
from product
where pname like '_ Cardamom %';

--  Inquire about category_id by null The goods 
select *
from product
where category_id is null;

--  Inquire about category_id Not for null Classified Goods 
select *
from product
where category_id is not null;

#  For the minimum 
select least(15, 48, 2, 45) min;
#  contain null Will not be compared , The result is directly null
select least(15, null, 2, 45) min;

#  For maximum 
select greatest(15, 48, 89, 45) max;
#  contain null Will not be compared , The result is directly null
select greatest(15, 48, null, 45) max;

#  Sort query 
#  Price in descending order 
select *
from product
order by price desc;

#  On the basis of price descending order , In descending order of classification 
#  At the same price , Sort by category 
select *
from product
order by price desc, category_id desc;

#  Sort the de duplicated prices in descending order 
select distinct price
from product
order by price desc;

#  Aggregate query 
# count()  The specified column of statistics is not NULL The number of record lines ;
# sum()  Calculates the value of the specified column and , If the specified column type is not a numeric type , So the result is 0;
# max()  Calculate the maximum value of the specified column , If the specified column is of string type , So use string sort operation ;
# min()  Calculate the minimum value of the specified column , If the specified column is of string type , So use string sort operation ;
# avg()  Calculate the average value of the specified column , If the specified column type is not a numeric type , So the result is 0

#  Query the total number of items 
select count(*)
from product;

#  The inquiry price is greater than 200 The total number of items 
select count(*)
from product
where price > 200;

#  The query is classified as 'c001' The sum of the prices of all the goods 
select sum(price)
from product
where category_id = 'c001';

#  Query the maximum price of goods 
select max(price) max_price
from product;

#  Query the minimum price of goods 
select min(price) min_price
from product;

#  The query is classified as 'c002' The average price of all goods 
select avg(price)
from product
where category_id = 'c002';

/* 1、count Function pair null Value handling   If count The argument of the function is asterisk （*）, Then count the number of all records . If the parameter is a field , Excluding statistics null Number of records of value . 2、sum and avg Function pair null Value handling   These two functions ignore null Existence of value , It's like the record doesn't exist . 3、max and min Function pair null Value handling  max and min Both functions also ignore null Existence of value . */

#  Group query 
#  Count the number of commodities in each category 
#  If you want to group , be select After that, only group fields and aggregate functions can appear 
select category_id, count(*)
from product
group by category_id;

#  Count the number of commodities in each category , And only show the number greater than 4 Product information of 
select category_id, count(*) cnt
from product
group by category_id
having cnt > 4
order by cnt;


#  Query exercise 
create table student
(
    id      int,
    gender  varchar(10),
    name    varchar(20),
    chinese int,
    english int,
    math    int
);
insert into student
values (1, ' male ', ' Zhang Xiaoming ', 89, 78, 90);
insert into student
values (2, ' male ', ' Li Jin ', 67, 53, 95);
insert into student
values (3, ' male ', ' Wang Wu ', 87, 78, 77);
insert into student
values (4, ' male ', ' Li Yi ', 88, 98, 92);
insert into student
values (5, ' male ', ' Li Laicai ', 82, 84, 67);
insert into student
values (6, ' Woman ', ' Zhang Jinbao ', 55, 85, 45);
insert into student
values (7, ' Woman ', ' Huang Rong ', 75, 65, 30);
insert into student
values (7, ' Woman ', ' Huang Rong ', 75, 65, 30);

--  Query the information of all students in the table 
select *
from student;

--  Look up the names of all the students and their English scores 
select name, english
from student;

--  Filter duplicate data in table 
select distinct *
from student;

--  Count the total score of each student 
select name, chinese + english + math total_score
from student;

--  Add... To the total score of all students 10 Points of specialty points of 
select name, chinese + english + math + 10 total_score
from student;

--  Use aliases to indicate student scores 
select name, chinese chi, english eng, math
from student;

--  Query English score greater than 90 Classmate 
select *
from student
where english > 90;

--  Total query score greater than 200 All students 
select *, chinese + english + math
from student
where chinese + english + math > 200;

--  Query English scores in  80－90 Between the students 
select *
from student
where english >= 80
  and english <= 90;

select *
from student
where english between 80 and 90;
--  Query English score is not in  80－90 Between the students 
select *
from student
where english < 80
   or english > 90;

select *
from student
where english not between 80 and 90;

--  Query math score is 89,90,91 Classmate 
select *
from student
where math in (89, 90, 91);

select *
from student
where math = 89
   or math = 90
   or math = 91;

--  Check the English scores of all students surnamed Li 
select name, english
from student
where name like ' Li %';

--  Query math score 80 And Chinese is divided into 80 Classmate 
select *
from student
where math = 80
  and chinese = 80;

--  Query English 80 Or total score 200 Classmate 
select *
from student
where english = 80
   or chinese + english + math = 200;

--  Sort the math grades and output them 
select *
from student
order by math desc;

--  After sorting the total score, output , And then output it from high to low 
select *, chinese + english + math
from student
order by chinese + english + math desc;

--  Sort the students' grades by their surname Li 
select *, chinese + english + math
from student
where name like ' Li %'
order by chinese + english + math desc;

#  How many boys and girls are there , Sort by number of people in descending order , The number of people detected is greater than 4 Gender of 
select gender, count(*) cnt
from student
group by gender
having cnt > 4
order by cnt desc;


create table emp
(
    empno    int,         --  Employee number 
    ename    varchar(50), --  Employee name 
    job      varchar(50), --  Job name 
    mgr      int,         --  Superior leader number 
    hiredate date,        --  Date of entry 
    sal      int,         --  Salary 
    comm     int,         --  Bonus 
    deptno   int          --  Department number 
);

insert into emp
values (7369, 'smith', 'clerk', 7902, '1980-12-17', 800, null, 20);
insert into emp
values (7499, 'allen', 'salesman', 7698, '1981-02-20', 1600, 300, 30);
insert into emp
values (7521, 'ward', 'salesman', 7698, '1981-02-22', 1250, 500, 30);
insert into emp
values (7566, 'jones', 'manager', 7839, '1981-04-02', 2975, null, 20);
insert into emp
values (7654, 'martin', 'salesman', 7698, '1981-09-28', 1250, 1400, 30);
insert into emp
values (7698, 'blake', 'manager', 7839, '1981-05-01', 2850, null, 30);
insert into emp
values (7782, 'clark', 'manager', 7839, '1981-06-09', 2450, null, 10);
insert into emp
values (7788, 'scott', 'analyst', 7566, '1987-04-19', 3000, null, 20);
insert into emp
values (7839, 'king', 'president', null, '1981-11-17', 5000, null, 10);
insert into emp
values (7844, 'turner', 'salesman', 7698, '1981-09-08', 1500, 0, 30);
insert into emp
values (7876, 'adams', 'clerk', 7788, '1987-05-23', 1100, null, 20);
insert into emp
values (7900, 'james', 'clerk', 7698, '1981-12-03', 950, null, 30);
insert into emp
values (7902, 'ford', 'analyst', 7566, '1981-12-03', 3000, null, 20);
insert into emp
values (7934, 'miller', 'clerk', 7782, '1982-01-23', 1300, null, 10);

-- 1、 It is not listed in ascending order of employee number 10 Employee information of department No 
select *
from emp
where deptno != 10
order by empno;

-- 2、 The second letter of the query name is not ”A” And the salary is greater than 800 Employee information for , In descending order of annual salary 
select *, (sal * 12 + ifnull(comm, 0)) year_sal
from emp
where ename not like '_a%'
  and sal > 800
order by year_sal desc;

-- 3、 Average salary for each department 
select deptno, avg(sal)
from emp
group by deptno;

-- 4、 Ask for the highest salary in each department 
select deptno, max(sal)
from emp
group by deptno;

-- 5、 Ask for the highest salary for each position in each department 
select deptno, job, max(sal)
from emp
group by deptno, job;

-- 6、 The average salary is greater than 2000 Department number of 
select deptno, avg(sal) avg_sal
from emp
group by deptno
having avg_sal > 2000;

-- 7、 The average salary of the Department will be greater than 1500 The department number of the , Rank by department average salary in descending order 
select deptno, avg(sal) avg_sal
from emp
group by deptno
having avg_sal > 1500
order by avg_sal desc;

-- 8、 Choose the name of the employee in the company who has the bonus , Wages 
select ename, sal, comm
from emp
where comm is not null;

-- 9、 Find out the difference between the maximum wage and the minimum wage 
select max(sal) - min(sal)
from emp;