欢迎进入Linux社区论坛,与200万技术人员互动交流 >>进入 创建数据库:create database [if not exist]name [character set 编码方式 collate 校对规则] 显示库的创建信息:show create database name 数据库的删除:drop database [if exist]name 备份数据
欢迎进入Linux社区论坛,与200万技术人员互动交流 >>进入
创建数据库:create database [if not exist]name [character set 编码方式 collate 校对规则]
显示库的创建信息:show create database name
数据库的删除:drop database [if exist]name
备份数据库:mysqldump -u用户名 -p数据库名>(路径)文件名。sql(windows命令、脚本文件,要退出sql命令窗口quit)
数据库恢复(1):Source 文件名。sql(sql命令)
1、创建库 create database name;
2、恢复数据 Source (加路径)文件。sql
数据库恢复(2):(上面步骤2改为)mysqldump -u用户名 -p数据库名
查看表的结构:desc table_name;
更改表的名字:rename table table_name to new_name;
更改表的列名:alter table table_name change column name new_name 类型;
1、插入失败的解决方案:
show variables like 'chara%'
set character_set_client=gb2312
显示失败后的解决方案:set character_set_results=gb2312(只对这次有效窗口关闭后失效,永久有效应该改配置文件)
修改表中数据:update table_name set col_name=value where …;
删除一条记录:delete from table_name where …;
不能删除某一列的值,也不能删除表;删除时应注意与其他表的参照完整性问题
truncate 也可以删除表中的记录(先摧毁表再重建表的结构)
查询语句:select [distinct](过滤掉重复数据) col1,col2 from table_name;
可以多数据进行运算:select col_name+10 from table_name;select(col1+col2+col3)from table_name
使用别名进行显示:select(col1+col2+col3) as 总数 from table_name(不用as也可以)
模糊查询中%代表一个或多个字符_代表一个字符
order by 放在select语句后面进行排序 …order by col_name asc/desc;
count统计:select count(*) from table_name;统计有多少行
sum合计函数:select sum(列名) from table_name;统计该列数据总和
AVG返回平均值
Max/min返回最大值最小值
group by:对列进行分组
有合计函数时使用having子句过滤where放在最后 而不能用where
定义主键(primary key)不允许为空不允许重复
定义主键自动增长 auto_increment
定义唯一性:unique
非空:not null;
定义外键约束:constraint ordersid_FK foreign key (ordersid) references others(id);

InnoDB uses redologs and undologs to ensure data consistency and reliability. 1.redologs record data page modification to ensure crash recovery and transaction persistence. 2.undologs records the original data value and supports transaction rollback and MVCC.

Key metrics for EXPLAIN commands include type, key, rows, and Extra. 1) The type reflects the access type of the query. The higher the value, the higher the efficiency, such as const is better than ALL. 2) The key displays the index used, and NULL indicates no index. 3) rows estimates the number of scanned rows, affecting query performance. 4) Extra provides additional information, such as Usingfilesort prompts that it needs to be optimized.

Usingtemporary indicates that the need to create temporary tables in MySQL queries, which are commonly found in ORDERBY using DISTINCT, GROUPBY, or non-indexed columns. You can avoid the occurrence of indexes and rewrite queries and improve query performance. Specifically, when Usingtemporary appears in EXPLAIN output, it means that MySQL needs to create temporary tables to handle queries. This usually occurs when: 1) deduplication or grouping when using DISTINCT or GROUPBY; 2) sort when ORDERBY contains non-index columns; 3) use complex subquery or join operations. Optimization methods include: 1) ORDERBY and GROUPB

MySQL/InnoDB supports four transaction isolation levels: ReadUncommitted, ReadCommitted, RepeatableRead and Serializable. 1.ReadUncommitted allows reading of uncommitted data, which may cause dirty reading. 2. ReadCommitted avoids dirty reading, but non-repeatable reading may occur. 3.RepeatableRead is the default level, avoiding dirty reading and non-repeatable reading, but phantom reading may occur. 4. Serializable avoids all concurrency problems but reduces concurrency. Choosing the appropriate isolation level requires balancing data consistency and performance requirements.

MySQL is suitable for web applications and content management systems and is popular for its open source, high performance and ease of use. 1) Compared with PostgreSQL, MySQL performs better in simple queries and high concurrent read operations. 2) Compared with Oracle, MySQL is more popular among small and medium-sized enterprises because of its open source and low cost. 3) Compared with Microsoft SQL Server, MySQL is more suitable for cross-platform applications. 4) Unlike MongoDB, MySQL is more suitable for structured data and transaction processing.

MySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.

The MySQL learning path includes basic knowledge, core concepts, usage examples, and optimization techniques. 1) Understand basic concepts such as tables, rows, columns, and SQL queries. 2) Learn the definition, working principles and advantages of MySQL. 3) Master basic CRUD operations and advanced usage, such as indexes and stored procedures. 4) Familiar with common error debugging and performance optimization suggestions, such as rational use of indexes and optimization queries. Through these steps, you will have a full grasp of the use and optimization of MySQL.

MySQL's real-world applications include basic database design and complex query optimization. 1) Basic usage: used to store and manage user data, such as inserting, querying, updating and deleting user information. 2) Advanced usage: Handle complex business logic, such as order and inventory management of e-commerce platforms. 3) Performance optimization: Improve performance by rationally using indexes, partition tables and query caches.


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