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在命令行连接MySQL数据库
格式: mysql -h主机地址 -u用户名 -p用户密码 数据库1、连接到本机上的MySQL。
首先在打开cmd命令行,然后键入命令mysql -uroot -p,回车后提示你输密码,输入密码后直接回车即可进入到MYSQL中了,MySQL的提示符是:mysql>
示例如下:
C:/> mysql -uroot -pmysql test
mysql> show databases; 显示所有的数据库
mysql> use mysql; 切换数据库
mysql> show tables; 显示数据库中的所有表
mysql> exit;(回车) 退出mysql
2、连接到远程主机上的MySQL。假设远程主机的IP为:192.168.1.22,用户名为root,密码为root。键入以下命令:
C:/> mysql -h192.168.1.22 -uroot -proot
(注:u与root可以不用加空格,其它也一样)
3、退出MySQL命令: exit (回车)
MySQL控制台部分命令
1、启动和关闭数据库
>net start mysql
>net stop mysql
所以命令必须是一行的第一个,并且以分号结尾:
All text commands must be first on line and end with ";"
2、根据用户名密码,登录数据库
>mysql -uroot -p;
如果数据库没有密码则使用
>mysql -uroot;
3、查看在当前服务器中有多少个数据库
>show databases;
4、删除某个数据库
>drop database databaseName;
>commit;
5、创建数据库
>create database databaseName;
6、选择使用某个数据库
>use databaseName;
7、查看数据库中有多少的表
>show tables;
8、创建表
>create table tableName(
id bigint ...
name varchar(20)...
...
);
9、显示表结构
>describe tableName;
10、向表中加入数据并查看
>insert into tableName(id、name...) values('1'、'admin'、...);
>select * from tableName;
11、导入.sql文件(文件所在路径是F:/file.sql
>source F:/file.sql;
12、删除表
>drop table tableName;
13、删除表中的所有数据,但是表结构依然存在
>delete from tableName;
14、更新表中的数据、如果没有where,则将影响所有的记录
>update tableName set name='administrator' where id='1';
15、查看服务器版本和当前日期
>select version()、current_date;
>select version();
>select now();
16、把mysql作为一个简单的计算器
>select pi();
>select pi()*10;
17、查看用户
>select user();
18、使用load
>load data local infile filePath into table tableName

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The difference between MySQL and SQLServer is: 1) MySQL is open source and suitable for web and embedded systems, 2) SQLServer is a commercial product of Microsoft and is suitable for enterprise-level applications. There are significant differences between the two in storage engine, performance optimization and application scenarios. When choosing, you need to consider project size and future scalability.

In enterprise-level application scenarios that require high availability, advanced security and good integration, SQLServer should be chosen instead of MySQL. 1) SQLServer provides enterprise-level features such as high availability and advanced security. 2) It is closely integrated with Microsoft ecosystems such as VisualStudio and PowerBI. 3) SQLServer performs excellent in performance optimization and supports memory-optimized tables and column storage indexes.

MySQLmanagescharactersetsandcollationsbyusingUTF-8asthedefault,allowingconfigurationatdatabase,table,andcolumnlevels,andrequiringcarefulalignmenttoavoidmismatches.1)Setdefaultcharactersetandcollationforadatabase.2)Configurecharactersetandcollationfor

A MySQL trigger is an automatically executed stored procedure associated with a table that is used to perform a series of operations when a specific data operation is performed. 1) Trigger definition and function: used for data verification, logging, etc. 2) Working principle: It is divided into BEFORE and AFTER, and supports row-level triggering. 3) Example of use: Can be used to record salary changes or update inventory. 4) Debugging skills: Use SHOWTRIGGERS and SHOWCREATETRIGGER commands. 5) Performance optimization: Avoid complex operations, use indexes, and manage transactions.

The steps to create and manage user accounts in MySQL are as follows: 1. Create a user: Use CREATEUSER'newuser'@'localhost'IDENTIFIEDBY'password'; 2. Assign permissions: Use GRANTSELECT, INSERT, UPDATEONmydatabase.TO'newuser'@'localhost'; 3. Fix permission error: Use REVOKEALLPRIVILEGESONmydatabase.FROM'newuser'@'localhost'; then reassign permissions; 4. Optimization permissions: Use SHOWGRA

MySQL is suitable for rapid development and small and medium-sized applications, while Oracle is suitable for large enterprises and high availability needs. 1) MySQL is open source and easy to use, suitable for web applications and small and medium-sized enterprises. 2) Oracle is powerful and suitable for large enterprises and government agencies. 3) MySQL supports a variety of storage engines, and Oracle provides rich enterprise-level functions.

The disadvantages of MySQL compared to other relational databases include: 1. Performance issues: You may encounter bottlenecks when processing large-scale data, and PostgreSQL performs better in complex queries and big data processing. 2. Scalability: The horizontal scaling ability is not as good as Google Spanner and Amazon Aurora. 3. Functional limitations: Not as good as PostgreSQL and Oracle in advanced functions, some functions require more custom code and maintenance.


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