MySQL模糊查询提供了两种模式:LIKE模式和REGEXP模式。
MySQL模糊查询提供了两种模式:LIKE模式和REGEXP模式。
LIKE模式LIKE模式是使用的LIKE 或 NOT LIKE 比较运算符进行模糊查询。
'条件'
针对条件,有以下几种通配符:
通配符 含义
% 表示任意一个或多个字符,可匹配任意类型和长度的字符
_ 表示任意单个字符,匹配单个任意字符
ESCAPE 关键字定义转义符。在模式中,当转义符置于通配符之前时,该通配符就解释为普通字符。
示例:
# 从 "Persons" 表中选取居住在以 "Ne" 开始的城市里的人 Persons # 从 "Persons" 表中选取居住在包含 "lond" 的城市里的人 Persons # 从 "Persons" 表中选取名字的第一个字符之后是 "eorge" 的人 Persons # 从 "Persons" 表中选取的这条记录的姓氏以 "C" 开头,然后是一个任意字符,然后是 "r",然后是任意字符,然后是 "er" Persons # 从 "KPI" 表中查找计算过程中含有0%的指标 KPI
注意:
REGEXP模式是使用 REGEXP 操作符来进行正则表达式匹配查询。
针对条件,有以下几种通配符:
通配符 含义
^ 匹配输入字符串的开始位置。如果设置了 RegExp 对象的 Multiline 属性,^ 也匹配 '\n' 或 '\r' 之后的位置。
$ 匹配输入字符串的结束位置。如果设置了RegExp 对象的 Multiline 属性,$ 也匹配 '\n' 或 '\r' 之前的位置。
. 匹配除 "\n" 之外的任何单个字符。要匹配包括 '\n' 在内的任何字符,请使用象 '[.\n]' 的模式。
[...] 字符集合。匹配所包含的任意一个字符。例如, '[abc]' 可以匹配 "plain" 中的 'a'。
[^...] 负值字符集合。匹配未包含的任意字符。例如, '[^abc]' 可以匹配 "plain" 中的'p'。
p1|p2|p3 匹配 p1 或 p2 或 p3。例如,'z|food' 能匹配 "z" 或 "food"。'(z|f)ood' 则匹配 "zood" 或 "food"。
* 匹配前面的子表达式零次或多次。例如,zo* 能匹配 "z" 以及 "zoo"。* 等价于{0,}。
+ 匹配前面的子表达式一次或多次。例如,'zo+' 能匹配 "zo" 以及 "zoo",但不能匹配 "z"。+ 等价于 {1,}。
{n} n 是一个非负整数。匹配确定的 n 次。例如,'o{2}' 不能匹配 "Bob" 中的 'o',但是能匹配 "food" 中的两个 o。
{n,m} m 和 n 均为非负整数,其中n
示例:
# 查找name字段中以为开头的所有数据: ; # 查找name字段中以为结尾的所有数据: ; # 查找name字段中包含字符串的所有数据: ; # 查找name字段中以元音字符开头且以字符串结尾的所有数据: ;
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MySQL is an open source relational database management system, mainly used to store and retrieve data quickly and reliably. Its working principle includes client requests, query resolution, execution of queries and return results. Examples of usage include creating tables, inserting and querying data, and advanced features such as JOIN operations. Common errors involve SQL syntax, data types, and permissions, and optimization suggestions include the use of indexes, optimized queries, and partitioning of tables.

MySQL is an open source relational database management system suitable for data storage, management, query and security. 1. It supports a variety of operating systems and is widely used in Web applications and other fields. 2. Through the client-server architecture and different storage engines, MySQL processes data efficiently. 3. Basic usage includes creating databases and tables, inserting, querying and updating data. 4. Advanced usage involves complex queries and stored procedures. 5. Common errors can be debugged through the EXPLAIN statement. 6. Performance optimization includes the rational use of indexes and optimized query statements.

MySQL is chosen for its performance, reliability, ease of use, and community support. 1.MySQL provides efficient data storage and retrieval functions, supporting multiple data types and advanced query operations. 2. Adopt client-server architecture and multiple storage engines to support transaction and query optimization. 3. Easy to use, supports a variety of operating systems and programming languages. 4. Have strong community support and provide rich resources and solutions.

InnoDB's lock mechanisms include shared locks, exclusive locks, intention locks, record locks, gap locks and next key locks. 1. Shared lock allows transactions to read data without preventing other transactions from reading. 2. Exclusive lock prevents other transactions from reading and modifying data. 3. Intention lock optimizes lock efficiency. 4. Record lock lock index record. 5. Gap lock locks index recording gap. 6. The next key lock is a combination of record lock and gap lock to ensure data consistency.

The main reasons for poor MySQL query performance include not using indexes, wrong execution plan selection by the query optimizer, unreasonable table design, excessive data volume and lock competition. 1. No index causes slow querying, and adding indexes can significantly improve performance. 2. Use the EXPLAIN command to analyze the query plan and find out the optimizer error. 3. Reconstructing the table structure and optimizing JOIN conditions can improve table design problems. 4. When the data volume is large, partitioning and table division strategies are adopted. 5. In a high concurrency environment, optimizing transactions and locking strategies can reduce lock competition.

In database optimization, indexing strategies should be selected according to query requirements: 1. When the query involves multiple columns and the order of conditions is fixed, use composite indexes; 2. When the query involves multiple columns but the order of conditions is not fixed, use multiple single-column indexes. Composite indexes are suitable for optimizing multi-column queries, while single-column indexes are suitable for single-column queries.

To optimize MySQL slow query, slowquerylog and performance_schema need to be used: 1. Enable slowquerylog and set thresholds to record slow query; 2. Use performance_schema to analyze query execution details, find out performance bottlenecks and optimize.

MySQL and SQL are essential skills for developers. 1.MySQL is an open source relational database management system, and SQL is the standard language used to manage and operate databases. 2.MySQL supports multiple storage engines through efficient data storage and retrieval functions, and SQL completes complex data operations through simple statements. 3. Examples of usage include basic queries and advanced queries, such as filtering and sorting by condition. 4. Common errors include syntax errors and performance issues, which can be optimized by checking SQL statements and using EXPLAIN commands. 5. Performance optimization techniques include using indexes, avoiding full table scanning, optimizing JOIN operations and improving code readability.


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