How to Properly Escape MySQL Wildcards in LIKE Statements?
Escaping MySQL Wild Cards
In an environment where prepared statements are not an option, it's essential to thoroughly escape user input before submitting it to MySQL to prevent SQL injection. PHP's mysql_real_escape_string function is commonly used for this purpose, but it falls short of escaping MySQL wild card characters '%' and '_'.
To account for this, addcslashes can be used additionally. However, as observed by a user, when input containing wild cards is sent to the database and retrieved, there's a discrepancy in the displayed results.
The Escaping Enigma
The user encountered a peculiar behavior where the '_' character was prefixed with a backslash ('_'), while the '"' and "'" characters were not, even though all three were escaped with ''. This raises the question: why are these characters handled differently?
Understanding MySQL Context
The key to resolving this conundrum lies in understanding the context of LIKE-matching in MySQL. '_' and '%' are not considered wild cards in general MySQL usage and should not be escaped when constructing a string literal. mysql_real_escape_string addresses the escaping needs for this purpose.
However, when preparing strings for use in a LIKE statement, a different set of escaping rules apply. To ensure that literals are interpreted correctly, additional LIKE escaping is required.
Double Escaping Dilemma
In the context of LIKE-matching, '_' and '%' become special characters. MySQL uses the backslash ('') as the escape character for both the LIKE-escaping and string literal-escaping steps. This can lead to confusion, as demonstrated by the user's example where matching a literal percent sign with LIKE requires double-backslash escaping.
Proper LIKE Escaping
To avoid portability issues, ANSI SQL dictates the use of a designated escape character for LIKE statements. One way to achieve this in PHP is to use the following function:
function like($s, $e) { return str_replace(array($e, '_', '%'), array($e.$e, $e.'_', $e.'%'), $s); }
Usage with Prepared Statements
For added security and portability, it's advisable to use prepared statements when available. This eliminates the need for manual escaping while ensuring proper data handling.
The above is the detailed content of How to Properly Escape MySQL Wildcards in LIKE Statements?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











The main role of MySQL in web applications is to store and manage data. 1.MySQL efficiently processes user information, product catalogs, transaction records and other data. 2. Through SQL query, developers can extract information from the database to generate dynamic content. 3.MySQL works based on the client-server model to ensure acceptable query speed.

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.

Compared with other programming languages, MySQL is mainly used to store and manage data, while other languages such as Python, Java, and C are used for logical processing and application development. MySQL is known for its high performance, scalability and cross-platform support, suitable for data management needs, while other languages have advantages in their respective fields such as data analytics, enterprise applications, and system programming.

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 basic operations of MySQL include creating databases, tables, and using SQL to perform CRUD operations on data. 1. Create a database: CREATEDATABASEmy_first_db; 2. Create a table: CREATETABLEbooks(idINTAUTO_INCREMENTPRIMARYKEY, titleVARCHAR(100)NOTNULL, authorVARCHAR(100)NOTNULL, published_yearINT); 3. Insert data: INSERTINTObooks(title, author, published_year)VA

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.

InnoDBBufferPool reduces disk I/O by caching data and indexing pages, improving database performance. Its working principle includes: 1. Data reading: Read data from BufferPool; 2. Data writing: After modifying the data, write to BufferPool and refresh it to disk regularly; 3. Cache management: Use the LRU algorithm to manage cache pages; 4. Reading mechanism: Load adjacent data pages in advance. By sizing the BufferPool and using multiple instances, database performance can be optimized.

MySQL efficiently manages structured data through table structure and SQL query, and implements inter-table relationships through foreign keys. 1. Define the data format and type when creating a table. 2. Use foreign keys to establish relationships between tables. 3. Improve performance through indexing and query optimization. 4. Regularly backup and monitor databases to ensure data security and performance optimization.
