Simple operation of SQL server data table

1. Create table

 

create table  Student information 
(
-- Define the data format of the column of the table 
    Student number  int not null,
    full name  char(20),
    Gender  char(4),
    Age  int,
    class  char(20),
    departments  char(30),
-- Add related constraints 
   constraint  Gender  check( Gender  = ' male ' or  Gender  = ' Woman '),   The data in the restricted gender column can only be   male   Woman 
   constraint  Age  check( Age  between 0 and 50)        The age limit can only be 0 To 50
)

2. Modify table

-- Add column 
alter table  Student information               -- Specify the table to modify 
add  Place of instruction  char(50) not null    -- Add column   Place of instruction 

-- Modify the column 
alter table  Student information               -- Specify the table to modify 
alter column  Place of instruction  char(50)    -- Modify the column （ Place of instruction ） Data format  

-- Delete column 
alter table  Student information               -- Specify the table to modify 
drop column  Place of instruction               -- Delete column   Place of instruction   

-- Set the primary key of the data table 
alter table  Student information  with nocheck
add constraint pk_num_id
primary key clustered( Student number )

3. Data insertion

-- Add data to the created table 
insert into  Employee information ( Number , full name , Department number , Job number , Age , Current address )
values(1,' Zhang San ','001','1001',25,'A'),
      (2,' Li Si ','002','2001',19,'S')

-- Copy table 
insert into DataBack(tid,tname,tdid,tmid,tage,taddress)  -- Choice and   Employee information   Tables with the same data format 
select  Number , full name , Department number , Job number , Age , Current address               -- Select the corresponding column 
from  Employee information 


-- Copy table 
select  Number , full name , Department number , Job number , Age , Current address 
into new_datas
from  Employee information 
where  Department number  is not null and  Job number  is not null   -- Copy   Employee information   Columns in the table where the department number and job number are not empty 

4. Update of data in the table

 

-- Unconditional update 
uodate  Student information 
set  departments =' School of Internet of things engineering '    -- The Department column in the student information table has been changed to   School of Internet of things engineering 

-- Condition update 
update  Student information 
set  class =' class A '
where  Student number  < 14160150

-- Modify the table before n Data 
update top(n)  Student information 
set  class =' class A '

5. Delete data from table

-- Delete all data in the table 
delete from  Employee information 

-- Delete data in the table according to conditions 
delete from  Employee information 
where  Number  <5

--truncate table Delete data in table 
truncate table  Student information     -- Use truncate table  Delete more than select It's a lot faster 

6. Query the data in the table

-- Query all columns 
select * from  Student information          -- Inquire about   Student information   All the columns in the table 

-- Query partial Columns 
select  Student number , full name 
from  Student information                   -- Inquire about   Student information   In the table   Student number , full name   Two 

-- Use alias when querying   
select  Student number  as no, full name  as name
from  Student information                   -- Inquire about   Student information   In the table   Student number , full name   Two , And use  no,name  Express 

-- Conditions of the query 
select  full name  from  Student information 
where  Student number  between 1 and 4     -- Inquire about   Student information   In the table   The student number is in 1 To 4 Name column between 

-- Operator query 
select * from  Student information 
where  Gender  = ' male ' or  Student number  > 2 and  Age  < 22  --or Represents or ,and Represents and   And and The priority ratio or high 

-- Fuzzy query 
select * from  Student information 
where  class  like '% Connected to the Internet --'  --%  Indicates the location （ Front, middle and rear ） And the characters （ Variable quantity ）,-  Represents an unknown character 
where  class  like ' The Internet of things [-]2'    --  Represents a query   The Internet of things -2  Class data  [-] It is practical -

-- To repeat the record 
selcet distinct( Number ), The unit price 
from  inventory                    -- take   Number   Put the same columns together 

-- Before query n Bar record 
select top 4 *
from  Student information                    -- Before query 4 Bar record 

-- Sort query information 
select * from  Student information 
order by  Student number 
 

# 7. Link query

-- Multi table join query 
select * from  Student information , Class information 
where  Student information . class = Class information . class             -- List all the data in the two tables that meet the constraints   The result is shown in Fig. Fig3

-- Internal link query 
select * from  Student information  inner join  Class information 
on  Student information . class = Class information . class     -- List the data in two tables that meet the constraints （ and where Restrictions are similar to ）  The result is shown in Fig. Fig4

-- The left outer join 
select * from  Student information  left join  Class information 
on  Student information . class = Class information . class        -- Show left table （ Student information ） All the information about , Fill in the blank on the right table    The result is shown in Fig. Fig5


-- Right connection 
select * from  Student information  right join  Class information 
on  Student information . class = Class information . class        -- Show right table （ Class information ） All the information about , Fill in the blank on the left table    The result is shown in Fig. Fig6

-- Full outer join 
select * from  Student information  full outer join  Class information 
on  Student information . class = Class information . class        -- Display all the information of the two tables , Fill in the blanks    The result is shown in Fig. Fig7

-- Self connect query 
select * from  Class information  as a1, Class information  as a2
where  a1. average >85                -- Self connection is a query that uses an alias to connect with itself   The result is shown in Fig. Fig8

-- Cross query 
select * from  Student information  cross join  Class information 
where  Class information . average  >85           -- Similar to self join query   The result is shown in Fig. fig9

The experiment used two tables -- Student information （Fig1） And class information （Fig2）

Fig1 Student information sheet

 

Fig2 Class information table

Experimental results ：Fig3-9

Fig3

Fig4

Fig5

Fig6

Fig7

 

Fig8

 

Fig9

#8 The joint query

--UNION Statement query 
select  Number , name , Number , Warehousing date 
from  inventory 
union
select  Number , name , Number , Warehousing date 
from  Cargo information                             -- Merge the same parts of the two tables , Different parts show   Pictured Fig3

--INTERSECT Statement query 
select  Number , name , Number , Warehousing date 
from  inventory 
intersect
select  Number , name , Number , Warehousing date 
from  Cargo information                             -- Show the parts of the two tables where the query columns are exactly the same    Pictured Fig4

--EXCEPT Statement query 
select  Number , name , Number , Warehousing date 
from  inventory 
except
select  Number , name , Number , Warehousing date 
from  Cargo information                             -- Show the parts with different query columns in the two tables    Pictured Fig5

The experiment used two tables -- Cargo information （Fig1） And merchandise inventory （Fig2）

Fig1 Cargo information

 

Fig2 inventory

The experimental results are shown in the figure Fig3-5

Fig3

Fig4

Fig5

#9. Subquery

--SELECT Sentence query 
select
avg( Number ) as  Average inventory quantity ,
(select avg( Number ) from  Cargo information )  as  Average quantity of goods ,
max( Number ) as  Maximum quantity in stock ,
(select avg( Number ) from  Cargo information )  as  Maximum quantity of goods  
from  inventory                                        -- Goods information query is embedded in commodity inventory query 


--IN Statement query 
select
 Number , name , Number 
from  Cargo information 
where  Number  in (select  Number  from  inventory  where  Number <300)  
                                      -- Find out that the quantity in the goods information is equal to the quantity in the goods inventory and less than 300 The number of columns 


--EXISTS Statement query 
select
 Number , name , Number 
from  Cargo information  as a
where exists (select  name  from  inventory  where  name =a. name ) 

--ANY Statement query 
select
 Number , name , Number 
from  Cargo information 
where  Number = any(select  Number  from  inventory ) -- Display the data of the quantity in the goods information in the quantity set in the goods inventory 


--
select
 Number , name , Number 
from  Cargo information 
where  Number  > all(select  Number  from  inventory ) -- Display the data that the quantity in the goods information is greater than all the quantities in the commodity inventory 

#10. Crosstab query

-- Use CASE Statement to realize crosstab query 
select
(case  name  when ' rice ' then  Number  end)  as  The quantity of rice purchased each time ,
(case  name  when ' millet ' then  Number  end)  as  Each purchase quantity of Xiaomi ,
(case  name  when ' soybean ' then  Number  end)  as  The quantity of soybeans purchased each time 
from  inventory                           -- Search each row of names and extract the number of corresponding names to form a new table    result Fig1


-- Use PIVOT Statement to realize crosstab query 
select  Warehousing date ,
        a.[ rice ] as ' rice ',
        a.[ millet ] as ' millet ',    
        a.[ soybean ] as ' soybean '
from  inventory 
     pivot(sum( Number ) for  name  in([ rice ],[ millet ],[ soybean ])) as a

order by  Warehousing date                         -- The result is shown in Fig.  Fig2

The experiment uses a table inventory （ And the 9 The stanzas are the same ）

Result chart ：

Fig1

Fig2