从功能上划分,SQL 语言可以分为DDL,DML和DCL三大类。 1. DDL(Data Definition Language) 数据定义语言,用于定义和管理 SQL 数据库中的所有对象的语言 ; CREATE---创建表 ALTER---修改表 DROP---删除表 2. DML(Data Manipulation Language) 数据操纵语
从功能上划分,SQL 语言可以分为DDL,DML和DCL三大类。1. DDL(Data Definition Language)
数据定义语言,用于定义和管理 SQL 数据库中的所有对象的语言 ;
CREATE---创建表
ALTER---修改表
DROP---删除表
2. DML(Data Manipulation Language)
数据操纵语言,SQL中处理数据等操作统称为数据操纵语言 ;
INSERT---数据的插入
DELETE---数据的删除
UPDATE---数据的修改
SELECT---数据的查询
3. DCL(Data Control Language)
数据控制语言,用来授予或回收访问数据库的某种特权,并控制 数据库操纵事务发生的时间及效果,对数据库实行监视等;
GRANT--- 授权。
ROLLBACK---回滚。
COMMIT--- 提交。
4. 提交数据有三种类型:显式提交、隐式提交及自动提交。
下面分 别说明这三种类型。
(1) 显式提交
用 COMMIT 命令直接完成的提交为显式提交。
(2) 隐式提交
用 SQL 命令间接完成的提交为隐式提交。这些命令是:
ALTER FUNCTION, ALTER PROCEDURE, ALTER TABLE, BEGIN, CREATEDATABASE, CREATE FUNCTION, CREATE INDEX, CREATE PROCEDURE, CREATETABLE, DROP DATABASE, DROP FUNCTION, DROP INDEX, DROP PROCEDURE,DROP TABLE, LOAD MASTER DATA, LOCK TABLES, RENAME TABLE, SETAUTOCOMMIT=1, START TRANSACTION, TRUNCATE TABLE, UNLOCK TABLES.
(3) 自动提交
若把 AUTOCOMMIT 设置为 ON ,则在插入、修改、删除语句执行后,
系统将自动进行提交,这就是自动提交。其格式为: SQL>SET AUTOCOMMIT=ON;(也可以set autocommit=1(打开), set autocommit=0(关闭));
COMMIT / ROLLBACK这两个命令用的时候要小心。 COMMIT / ROLLBACK 都是用在执行DML语句(INSERT / DELETE / UPDATE / SELECT )之后的。DML语句,执行完之后,处理的数据,都会放在回滚段中(除了 SELECT 语句),等待用户进行提交(COMMIT)或者回滚(ROLLBACK),当用户执行 COMMIT / ROLLBACK后,放在回滚段中的数据就会被删除。
(SELECT语句执行后,数据都存在共享池。提供给其他人查询相同的数据时,直接在共享池中提取,不用再去数据库中提取,提高了数据查询的速度。)
所有的 DML 语句都是要显式提交的,也就是说要在执行完DML语句之后,执行 COMMIT 。而其他的诸如 DDL语句的,都是隐式提交的。也就是说,在运行那些非 DML 语句后,数据库已经进行了隐式提交,例如 CREATETABLE,在运行脚本后,表已经建好了,并不在需要你再进行显式提交。
在提交事务(commit)之前可以用rollbacl回滚事务

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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