Basic syntax of MySQL DDL and DML and DQL

        stay Mysql In the process of learning , More commonly used is ：DML,DDL and DQL, The following is a detailed introduction to these common sentences , The commands commonly used in the three languages are shown in the following figure ： 

One 、DDL( Data customization statement )

        1.creat: Usually use this command to create a database or create a data table , The grammar is as follows ：

        ①create  database  Database name ;         -- Create a database

        ②create  table  Table name （

                Field name     data type     attribute     constraint condition ,

                Field name     data type     attribute     constraint condition , 

                .....

                Field name   data type     attribute

        );

        When we build the data table , There are several points to pay attention to in the sentence ：

        a. Attributes and constraints are not necessary , It can be omitted

        b. The last field is followed by no    ,    Of

        c. In the same table , Field names cannot be the same

        The usage of these two statements is shown in the following figure （ About attributes and constraints in statements , I will post a detailed description later ：

 2.drop： This command is usually used to delete the data table , It will also be used with other commands to delete fields in the table , Common commands are as follows ：

        ①drop  table  Table name   -- Delete data table

3.alter: This command is usually used to modify the structure of the table

        ①alter  table  The old name of the table    rename  as    The new name of the table ; -- Modify the name of the table

        ②alter  table  Table name    modify  Field name   Column type 【 attribute 】; -- Modify field properties

        ③alter  table  Table name    change  Old field name     new field name   Column type   【 attribute 】  -- Modify field names and properties

        It needs to be noted that the above modify and change Both statements can modify the properties of fields , The difference is change At the same time, you can modify the name of the field , however modify no way

        ④alter  table  Table name   drop    Field name ;     -- Delete field

        ⑤alter  table  Table name   add    Field name   type     attribute ;   -- Add fields

The simple usage of the above statements is shown in the following figure ：

  Two 、DML( Data operation statement )

        1.insert: This statement is usually used to add data , Now let's add some data to the student table

        ①insert  into  Table name ( Field 1, Field 2.....）values  ( Field 1 The value of the corresponding type , Field 2 The value of the corresponding type .....);

        -- The new data （ One thing to note here is that we need to use string representation when adding date type data ）

        2.update: Modifying data

        ①update  Table name set  Field name = value ( Note the modified value )  where  Conditions ;   -- Modifying data

        3.detele: Delete data

        ① delete  from  Table name   where  Conditions ;

         ②truncate  【table】  Table name ;-- This statement is very simple, which is to empty the data of a table , among table It can be omitted

3、 ... and 、DQL( Data query statement ) This statement is more important in the database , The specific sentences are as follows ：

Single table query ：

1. Simple query syntax

        ①select  Field /*  from  Table name ; -- Query the corresponding data from a table （* Represents all data )

        ②select  Field new field name   from  Table name :  -- When querying field data, you can alias the field

        ③select  distinct  Field name    from  Table name ;   -- You can reprocess the queried data

        

     2.DQL Conditional query syntax ( There are several keywords about conditional query , The following examples are the simple usage of these keywords ）

        ①where keyword ( Conditions of the query ）

                select    Field name   from    Table name     where    Conditions ;

        ② like keyword ( Fuzzy query ）： Often and %（ Represents several characters ）_( Represents a character ） Use it together

                select    Field name    from    Table name   where  Field  like    Conditions ;       

          ③in keyword ( Range queries ）

                select  Field name    from    Table name    where    Field   in  ( value 1, value 2....);

        

         ③null Value query ： What needs to be noted here is , Yes null The keyword of value query should be is

         ④group by Group queries and having（ Group query ）： Often used with aggregate functions

        select  Field   from  Table name    group  by  Field name    having    Conditions ;

        Common aggregate functions ：    avg( Field name )—— averaging ,sum( Field name )—— Sum up ,max( Field name )—— For maximum , min( Field name )—— For the minimum ,  count( Field name )—— Sum up , These five aggregate functions are frequently used , The usage is not very complicated , Here is an example combined with grouping query ：

        ⑤order by( Sort )： The main thing here is to match two keywords when sorting   asc( Ascending sort , It can be omitted ) and desc( null , Do not omit , If omitted, the system will default to ascending )

        select  Field    from  Table name   order  by  Field name    desc/asc;

         ⑥limit( Restrict query keywords ): Usually used to limit the number of query pages

        select  Field   from  Table name   limit n,m;-- Generally speaking, query from n( It doesn't contain n) Data starts , The length is m A few pieces of data , This keyword is often used to realize paging query of data , here n and m The value of can be expressed by formula

n=( Page number -1)* The amount of data displayed per page ,m= The amount of data displayed per page

 3.DQL Advanced query statements

        ① Multiple tables associated query

        Non equivalent query ：select  *  from  surface 1, surface 2;-- It should be noted that this kind of query method without judgment , The queried data will be duplicated , You may not get the data you want , So in most cases, we will use the method of equivalent joint query to query data .

        Equivalent query ：

              a. Inline query ：

                        Writing a ：SELECT Field name FROM Table name ... where conditional AND conditional

                        Write two ：select  *  from    Table name    inner   join    Table name   on  Equivalent condition judgment   where    Conditions ;

The above two methods can achieve the same query effect , We can choose which query method to use according to our own needs

          b.  Outreach query ：

                     select  * from Table name   left  join  Table name    on   Equivalent judgment condition    where    Judge the condition ;-- Left joint query

                     select  * from Table name   right  join  Table name    on   Equivalent judgment condition    where    Judge the condition ;-- Right associated query

External query and internal query , Although we can get the data we want to query , There are still some differences between them ：            

As shown in the figure above ：

a. Inline query ：select  *  from    surface A  inner  join  surface B   on  Equivalent judgment condition ;

                This inline query statement is actually a query surface A and surface B Shared data Set C

b. Left outer query ：select  *  from    surface A  left  jion  surface B   on    Equivalent judgment condition ;

                This leftist query statement is actually to   jion  The table on the left A As the main table , Take out the watch first A All data , then         Then judge the condition according to the equivalence , Look up the table A And table B Common data sets   C, So the result of the query is in the figure ： surface A Data sets +C Data sets   

c. Right query ：select  *  from  surface A  right  join  surface B on  Equivalent judgment condition ;

                The principle of this right join query statement is similar to that of the left join , Just put join Table on the right B As the main table , Query the table first B All the data in , Then query the table according to the judgment conditions B And table A Common data sets C, So the result is in the figure : surface B Data sets +C Data sets

  One more point , The basis for judging left and right couplets is jion The left and right of keywords are the main tables .

② Subquery

        a.where Subquery （ Take the queried data set as where The latter condition judgment )

        As shown in the figure below , Find out the student with the largest student number as where The conditions of judgment ,where How to write a subquery

        b.from Subquery （ Treat the inner query results as a temporary table , For external queries , It is better to alias the temporary table when using )

        c. exist Subquery （exists Follow the internal query , If this inner query is true , The outer query will take effect , The final result is the data of outer layer query )

        d.any/some( These two sub queries must be used together with the condition evaluator )

        select  *  from  Table name   where  a>any(2,3,4);    This statement is equivalent to the following

        select  *  from  Table name   where  a>2  or  a>3  or  a>4;

        some and any The usage of is exactly the same , It's just a different name

        e.all Subquery ( This seed query and any similar , Only the latter needs to meet all the conditions )

        select  *  from  Table name   where  a>all(2,3,4);    This statement is equivalent to the following

        select  *  from  Table name   where  a>2  and  a>3  and  a>4;