以下是对SQL中的数据查询语句进行了汇总介绍,需要的朋友可以过来参考下 where条件表达式 --统计函数 复制代码 代码如下: Select count(1) from student; --like模糊查询 --统计班上姓张的人数 复制代码 代码如下: select count(*) from student where realN
以下是对SQL中的数据查询语句进行了汇总介绍,需要的朋友可以过来参考下
where条件表达式
--统计函数
复制代码 代码如下:
Select count(1) from student;
--like模糊查询
--统计班上姓张的人数
复制代码 代码如下:
select count(*) from student where realName like '张%';
--统计班上张姓两个字的人数
复制代码 代码如下:
select count(*) from student where realName like '张_';
--统计班上杭州籍的学生人数
复制代码 代码如下:
select count(*) from student where home like '%杭州%';
--查询班上每位学生的年龄
复制代码 代码如下:
select realName,year(now())-year(birthday) as age from student;
--查询90年出生的学生
复制代码 代码如下:
select realName from student where year(birthday)>='1990';
--查询1987-1990年出生的学生
复制代码 代码如下:
select realName from student where year(birthday)='1987';
select * from student where year(birthday) between '1987' and '1990';
--查询班上男女生人数
复制代码 代码如下:
select sex,count(*) from student group by sex;
--in子句查询班上B或O型血的学生
复制代码 代码如下:
select realName,blood from student where blood in('B','O');
子查询
子查询也可称之为嵌套查询,有些时候,一次查询不能解决问题,需要多次查询。
按子查询返回的记录行数区分,可分为单行子查询和多行子查询;
复制代码 代码如下:
select * from emp where sal>( select sal from emp where ename='ALLEN‘ or ename =‘KING')
上例是找出比allen工资高的所有员工
A.子查询一般先于主语句的运行
B.必须有( ),表示一个整体
C.习惯上把子查询放在条件的右边
多行子查询:some,any,all
连接语句(应用于多表查询)
包括:内联,,外联(左外连和右外联)
内联(inner join):把两张表相匹配的行查询出来。
--查询每个学生的各科成绩,显示“姓名”“课程名”“分数”三列
复制代码 代码如下:
select a.realname,c.courseName,b.score from stu_student as a inner join stu_score as b on a.sid=b.sid inner join stu_course c on b.cid=c.cid
还有一种方法,不采用inner join:
复制代码 代码如下:
select a.realname,c.courseName,b.score from student a,score b,course c where a.sid=b.sid and c.cid=b.cid
外联分左外联和右外联:
Left outer join:查询两边表的匹配记录,且将左表的不匹配记录也查询出来。
Right outer join:等上,将右表不匹配记录也查询出来。
复制代码 代码如下:
select a.realname,b.score from stu_student as a left outer join stu_score as b on a.sid=b.sid

TograntpermissionstonewMySQLusers,followthesesteps:1)AccessMySQLasauserwithsufficientprivileges,2)CreateanewuserwiththeCREATEUSERcommand,3)UsetheGRANTcommandtospecifypermissionslikeSELECT,INSERT,UPDATE,orALLPRIVILEGESonspecificdatabasesortables,and4)

ToaddusersinMySQLeffectivelyandsecurely,followthesesteps:1)UsetheCREATEUSERstatementtoaddanewuser,specifyingthehostandastrongpassword.2)GrantnecessaryprivilegesusingtheGRANTstatement,adheringtotheprincipleofleastprivilege.3)Implementsecuritymeasuresl

ToaddanewuserwithcomplexpermissionsinMySQL,followthesesteps:1)CreatetheuserwithCREATEUSER'newuser'@'localhost'IDENTIFIEDBY'password';.2)Grantreadaccesstoalltablesin'mydatabase'withGRANTSELECTONmydatabase.TO'newuser'@'localhost';.3)Grantwriteaccessto'

The string data types in MySQL include CHAR, VARCHAR, BINARY, VARBINARY, BLOB, and TEXT. The collations determine the comparison and sorting of strings. 1.CHAR is suitable for fixed-length strings, VARCHAR is suitable for variable-length strings. 2.BINARY and VARBINARY are used for binary data, and BLOB and TEXT are used for large object data. 3. Sorting rules such as utf8mb4_unicode_ci ignores upper and lower case and is suitable for user names; utf8mb4_bin is case sensitive and is suitable for fields that require precise comparison.

The best MySQLVARCHAR column length selection should be based on data analysis, consider future growth, evaluate performance impacts, and character set requirements. 1) Analyze the data to determine typical lengths; 2) Reserve future expansion space; 3) Pay attention to the impact of large lengths on performance; 4) Consider the impact of character sets on storage. Through these steps, the efficiency and scalability of the database can be optimized.

MySQLBLOBshavelimits:TINYBLOB(255bytes),BLOB(65,535bytes),MEDIUMBLOB(16,777,215bytes),andLONGBLOB(4,294,967,295bytes).TouseBLOBseffectively:1)ConsiderperformanceimpactsandstorelargeBLOBsexternally;2)Managebackupsandreplicationcarefully;3)Usepathsinst

The best tools and technologies for automating the creation of users in MySQL include: 1. MySQLWorkbench, suitable for small to medium-sized environments, easy to use but high resource consumption; 2. Ansible, suitable for multi-server environments, simple but steep learning curve; 3. Custom Python scripts, flexible but need to ensure script security; 4. Puppet and Chef, suitable for large-scale environments, complex but scalable. Scale, learning curve and integration needs should be considered when choosing.

Yes,youcansearchinsideaBLOBinMySQLusingspecifictechniques.1)ConverttheBLOBtoaUTF-8stringwithCONVERTfunctionandsearchusingLIKE.2)ForcompressedBLOBs,useUNCOMPRESSbeforeconversion.3)Considerperformanceimpactsanddataencoding.4)Forcomplexdata,externalproc


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