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在menzhi007的blog里看到非常有意思的东西:
http:///database/201003/45293.html
在mysql手册里:
phpchina.com/manual/mysql/functions.html#comparison-operators">http://www.phpchina.com/manual/mysql/functions.html#comparison-operators
MySQL按照以下规则进行数值比较:
- 若有一个或两个参数为 NULL,除非NULL-safe 等算符,则比较运算的结果为NULL。
- 若同一个比较运算中的两个参数都是字符串,则按照字符串进行比较。
- 若两个参数均为整数,则按照整数进行比较。
- 十六进制值在不需要作为数字进行比较时,则按照二进制字符串进行处理。
- 假如参数中的一个为 TIMESTAMP 或 DATETIME 列,而其它参数均为常数, 则在进行比较前将常数转为 timestamp。这样做的目的是为了使ODBC的进行更加顺利。 注意,这不适合IN()中的参数!为了更加可靠,在进行对比时通常使用完整的 datetime/date/time字符串。
- 在其它情况下,参数作为浮点数进行比较。
在默认状态下,字符串比较不区分大小写,并使用现有字符集(默认为cp1252 Latin1,同时对英语也适合)。
为了进行比较,可使用CAST()函数将某个值转为另外一种类型。 使用CONVERT()将字符串值转为不同的字符集。请参见12.8节,“Cast函数和操作符”。
以下例子说明了比较运算中将字符串转为数字的过程:
mysql> SELECT 1 > 6x;
-> 0
mysql> SELECT 7 > 6x;
-> 1
mysql> SELECT 0 > x6;
-> 0
mysql> SELECT 0 = x6;
-> 1
这个如果不注意好确实可以导致安全问题的,比如menzhi007里举的那个列子,如果字符变量查询没有引号,但是用某些函数过滤了不可以直接注射,那么可以直接提交0就可以绕过了...
最后感谢menzhi007及hi群的各大牛的讨论,尤其是ryat牛的指点:)
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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.

SQL commands in MySQL can be divided into categories such as DDL, DML, DQL, DCL, etc., and are used to create, modify, delete databases and tables, insert, update, delete data, and perform complex query operations. 1. Basic usage includes CREATETABLE creation table, INSERTINTO insert data, and SELECT query data. 2. Advanced usage involves JOIN for table joins, subqueries and GROUPBY for data aggregation. 3. Common errors such as syntax errors, data type mismatch and permission problems can be debugged through syntax checking, data type conversion and permission management. 4. Performance optimization suggestions include using indexes, avoiding full table scanning, optimizing JOIN operations and using transactions to ensure data consistency.

InnoDB achieves atomicity through undolog, consistency and isolation through locking mechanism and MVCC, and persistence through redolog. 1) Atomicity: Use undolog to record the original data to ensure that the transaction can be rolled back. 2) Consistency: Ensure the data consistency through row-level locking and MVCC. 3) Isolation: Supports multiple isolation levels, and REPEATABLEREAD is used by default. 4) Persistence: Use redolog to record modifications to ensure that data is saved for a long time.

MySQL's position in databases and programming is very important. It is an open source relational database management system that is widely used in various application scenarios. 1) MySQL provides efficient data storage, organization and retrieval functions, supporting Web, mobile and enterprise-level systems. 2) It uses a client-server architecture, supports multiple storage engines and index optimization. 3) Basic usages include creating tables and inserting data, and advanced usages involve multi-table JOINs and complex queries. 4) Frequently asked questions such as SQL syntax errors and performance issues can be debugged through the EXPLAIN command and slow query log. 5) Performance optimization methods include rational use of indexes, optimized query and use of caches. Best practices include using transactions and PreparedStatemen

MySQL is suitable for small and large enterprises. 1) Small businesses can use MySQL for basic data management, such as storing customer information. 2) Large enterprises can use MySQL to process massive data and complex business logic to optimize query performance and transaction processing.

InnoDB effectively prevents phantom reading through Next-KeyLocking mechanism. 1) Next-KeyLocking combines row lock and gap lock to lock records and their gaps to prevent new records from being inserted. 2) In practical applications, by optimizing query and adjusting isolation levels, lock competition can be reduced and concurrency performance can be improved.


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