SQL Server 数据查询 --- 复杂查询 有需要的朋友可参考一下。
/********************************************
例1查询每个学生及其选修课程的情况
*********************************************/
代码如下 | 复制代码 |
SELECT STUDENT.*,SC.* FROM SC,STUDENT WHERE SC.SNO = STUDENT.SNO; |
/********************************************
对例1用自然连接完成
*********************************************/
代码如下 | 复制代码 |
SELECT STUDENT.SNAME,STUDENT.SSEX,STUDENT.SAGE,STUDENT.SDEPT,SC.* FROM SC,STUDENT WHERE SC.SNO = STUDENT.SNO; |
/*****************************************
查询每一门课程的间接先修课
*****************************************/
代码如下 | 复制代码 |
SELECT SY.CNO,SX.CPNO FROM COURSE SX,COURSE SY WHERE SX.CNO = SY.CPNO |
/********************************************
对例1用左外连接连接完成
*********************************************/
代码如下 | 复制代码 |
SELECT STUDENT.SNAME,STUDENT.SSEX,STUDENT.SAGE,STUDENT.SDEPT,SC.* FROM STUDENT LEFT JOIN SC ON(SC.SNO = STUDENT.SNO); |
/********************************************
查询每个学生的学号、姓名、选修的课程名及成绩 *********************************************/
代码如下 | 复制代码 |
SELECT STUDENT.SNO,STUDENT.SNAME,COURSE.CNAME,COURSE.CCREDIT |
/********************************************
查询与刘晨在同一个系学习的学生
*********************************************/
代码如下 | 复制代码 |
SELECT SX.* |
或者如下:
代码如下 | 复制代码 |
SELECT SX.* SELECT * |
/********************************************
查询选修了课程名为"信息系统"的学生学号和姓名 *********************************************/
代码如下 | 复制代码 |
SELECT SNO, SNAME FROM STUDENT WHERE SNO IN ( SELECT SNO FROM SC WHERE CNO IN ( SELECT CNO FROM COURSE WHERE CNAME = '信息系统' ) ); |
/********************************************
找出每个学生超过他选修课程平均成绩的课程号
*********************************************/
代码如下 | 复制代码 |
SELECT SX.SNO,SX.CNO /***************************************************** |
查询其他系中比计算机科学系某一学生年龄小的学生姓名和年龄
*******************************************************/
代码如下 | 复制代码 |
|
/*****************************************************
查询其他系中比计算机科学系所有学生年龄小的学生姓名和年龄
*******************************************************/
代码如下 | 复制代码 |
SELECT SNAME, SAGE FROM STUDENT WHERE SAGE SELECT SAGE FROM STUDENT WHERE SDEPT='CS' ) AND SDEPT'CS'; |
/*****************************************************
查询所有选修了1号课程的学生姓名
*******************************************************/
代码如下 | 复制代码 |
|
/******************************************
查询选修了全部课程的学生姓名
*******************************************/
代码如下 | 复制代码 |
SELECT SNAME FROM STUDENT WHERE NOT EXISTS ( SELECT * FROM COURSE WHERE NOT EXISTS ( SELECT * FROM SC WHERE STUDENT.SNO = SC.SNO AND COURSE.CNO = SC.CNO ) ); |
/*****************************************************
查询至少选修了学生200215122选修的全部课程的学生号码
*****************************************************/
代码如下 | 复制代码 |
SELECT DISTINCT SNO FROM SC X WHERE NOT EXISTS ( SELECT * FROM SC Y WHERE SNO='200215122' AND NOT EXISTS ( SELECT * FROM SC Z WHERE Z.SNO = X.SNO AND Y.CNO = Z.CNO ) ); |
/**********************************************************
从自身表中选择一条记录,修改某个字段再回插到自身表中
这里的INSERT INTO 可以用来插入子查询 *********************************************************/
代码如下 | 复制代码 |
INSERT INTO COURSE(CNO,CNAME,CPNO,CCREDIT) |

Stored procedures are precompiled SQL statements in MySQL for improving performance and simplifying complex operations. 1. Improve performance: After the first compilation, subsequent calls do not need to be recompiled. 2. Improve security: Restrict data table access through permission control. 3. Simplify complex operations: combine multiple SQL statements to simplify application layer logic.

The working principle of MySQL query cache is to store the results of SELECT query, and when the same query is executed again, the cached results are directly returned. 1) Query cache improves database reading performance and finds cached results through hash values. 2) Simple configuration, set query_cache_type and query_cache_size in MySQL configuration file. 3) Use the SQL_NO_CACHE keyword to disable the cache of specific queries. 4) In high-frequency update environments, query cache may cause performance bottlenecks and needs to be optimized for use through monitoring and adjustment of parameters.

The reasons why MySQL is widely used in various projects include: 1. High performance and scalability, supporting multiple storage engines; 2. Easy to use and maintain, simple configuration and rich tools; 3. Rich ecosystem, attracting a large number of community and third-party tool support; 4. Cross-platform support, suitable for multiple operating systems.

The steps for upgrading MySQL database include: 1. Backup the database, 2. Stop the current MySQL service, 3. Install the new version of MySQL, 4. Start the new version of MySQL service, 5. Recover the database. Compatibility issues are required during the upgrade process, and advanced tools such as PerconaToolkit can be used for testing and optimization.

MySQL backup policies include logical backup, physical backup, incremental backup, replication-based backup, and cloud backup. 1. Logical backup uses mysqldump to export database structure and data, which is suitable for small databases and version migrations. 2. Physical backups are fast and comprehensive by copying data files, but require database consistency. 3. Incremental backup uses binary logging to record changes, which is suitable for large databases. 4. Replication-based backup reduces the impact on the production system by backing up from the server. 5. Cloud backups such as AmazonRDS provide automation solutions, but costs and control need to be considered. When selecting a policy, database size, downtime tolerance, recovery time, and recovery point goals should be considered.

MySQLclusteringenhancesdatabaserobustnessandscalabilitybydistributingdataacrossmultiplenodes.ItusestheNDBenginefordatareplicationandfaulttolerance,ensuringhighavailability.Setupinvolvesconfiguringmanagement,data,andSQLnodes,withcarefulmonitoringandpe

Optimizing database schema design in MySQL can improve performance through the following steps: 1. Index optimization: Create indexes on common query columns, balancing the overhead of query and inserting updates. 2. Table structure optimization: Reduce data redundancy through normalization or anti-normalization and improve access efficiency. 3. Data type selection: Use appropriate data types, such as INT instead of VARCHAR, to reduce storage space. 4. Partitioning and sub-table: For large data volumes, use partitioning and sub-table to disperse data to improve query and maintenance efficiency.

TooptimizeMySQLperformance,followthesesteps:1)Implementproperindexingtospeedupqueries,2)UseEXPLAINtoanalyzeandoptimizequeryperformance,3)Adjustserverconfigurationsettingslikeinnodb_buffer_pool_sizeandmax_connections,4)Usepartitioningforlargetablestoi


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