MySQL regular expressions are a powerful tool for flexibly searching and manipulating strings within a database. They enable pattern matching that is difficult with ordinary string searches, allowing you to extract data that matches specific formats or conditions. For example, you can easily extract names that start with a particular character or codes that contain only numbers. This feature is especially useful in data cleansing and scenarios that involve complex search criteria.
Benefits of using regular expressions in MySQL
Handling complex search conditions
You can specify complex string patterns that the standard LIKE operator cannot handle.
Bulk data replacement and extraction possible
For example you can extract only data that follows a specific format or replace parts of a string.
Feature enhancements in MySQL 8.0 and later
New functions (such as REGEXP_LIKE, REGEXP_SUBSTR, etc.) have been added, enabling more flexible operations.
Purpose of this article
This article provides a detailed explanation of MySQL regular expressions (REGEXP), covering basic usage, advanced examples, and cautions. It offers practical information useful for everyone from beginners to semi‑professionals, so please read through to the end. The next section will explain the fundamentals of regular expressions in MySQL in detail.
2. Basics of Regular Expressions in MySQL
What is the REGEXP operator?
In MySQL, the REGEXP operator is used to work with regular expressions. This operator is used to determine whether a given pattern matches. Also, RLIKE functions as an alias for REGEXP. The following example is a query that checks whether a string matches the pattern “abc”.
SELECT * FROM users WHERE name REGEXP 'abc';
Basic Syntax of the REGEXP Operator
The basic syntax for searches using regular expressions is as follows.
SELECT * FROM table_name WHERE column_name REGEXP 'pattern';
Common REGEXP Patterns
Symbol
Description
Example
^
Matches start of line
^abc → strings that start with “abc”
$
Matches end of line
abc$ → strings that end with “abc”
.
Matches any single character
a.c → matches “abc”, “adc”, etc.
|
OR (matches either)
abc|xyz → matches “abc” or “xyz”
[]
Matches any one of the specified characters
[abc] → matches “a”, “b”, or “c”
*
Matches zero or more repetitions
ab*c → matches “ac”, “abc”, “abbc”, etc.
Differences Between REGEXP and LIKE
Feature
LIKE
REGEXP
Flexibility
Only wildcards (% and _)
Supports advanced pattern matching
Performance
Fast
May be slightly slower when patterns are complex
Practical Example: Searches Using REGEXP
Example 1: Search for email address format
SELECT * FROM users WHERE email REGEXP '^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+.[a-zA-Z]{2,}$';
Example 2: Search for fields containing only numbers
SELECT * FROM orders WHERE order_id REGEXP '^[0-9]+$';
Summary
This section explained the basic usage and patterns of the REGEXP operator in MySQL. With this knowledge, you can perform a wide range of data operations, from simple searches to complex pattern matching.
3. Regular Expression Functions Added in MySQL 8.0
The regular expression functions added in MySQL 8.0 enable detailed and flexible string manipulation. By leveraging them, efficient data extraction and processing become possible.
4. Practical Examples of Regular Expressions
Searching for Data Matching Specific Patterns
Example 1: Detecting Email Address Format
SELECT * FROM users WHERE email REGEXP '^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+.[a-zA-Z]{2,}$';
Example 2: Detecting Phone Number Format
SELECT * FROM contacts WHERE phone REGEXP '^[0-9]{3}-[0-9]{4}-[0-9]{4}$';
SELECT * FROM users WHERE email NOT REGEXP '^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+.[a-zA-Z]{2,}$';
Summary
Using these examples, you can efficiently perform various tasks such as searching, extracting, replacing, and validating data.
5. Considerations and Best Practices
Handling Multibyte (Full-width) Characters
MySQL’s regular expressions are evaluated byte-by-byte by default, so you need to be careful when dealing with multibyte characters such as Japanese. Solution:
ALTER TABLE users CONVERT TO CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;
Impact on Performance
Issue: Regular expressions involve complex processing, so searching large datasets can cause performance slowdowns. Solution:
SELECT * FROM users WHERE email LIKE '%@example.com' AND email REGEXP '^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+.[a-zA-Z]{2,}$';
Mitigating ReDoS (Regular Expression Denial of Service) Attacks
Issue: Malicious patterns can impose excessive load. Solution:
Use simple patterns.
Strengthen input validation.
Monitor query execution time.
Checking Version Compatibility
New functions are unavailable in MySQL versions below 8.0. You need to verify the version according to your environment.
Verification in a Test Environment
Test the query behavior and performance in advance, including handling of edge cases.
Summary
Keep in mind the key points for using regular expressions safely and efficiently while considering performance and security.
6. Summary
Recap of Article Points
By learning basic operations and how to use regular expression patterns, you can handle everything from simple searches to complex extractions.
The regular expression functions added in MySQL 8.0 enable even more flexible operations.
Leveraging practical examples streamlines concrete data manipulation.
By covering cautions and best practices, you can achieve safe and high‑performance queries.
Benefits of Using MySQL Regular Expressions
Support for advanced search criteria: Conditions that are difficult with simple string searches can be set easily.
Streamlined data processing: Extraction, replacement, and validation can be done entirely within SQL.
Broad applicability: Suitable for everything from data cleansing to log analysis.
Future Learning and Application
Deepen understanding by testing queries with real data.
Proactively use the latest version features to optimize performance.
Regularly review queries to maintain safety and speed.
Finally
Leverage your knowledge of MySQL regular expressions to improve operational efficiency and enhance data analysis capabilities.
7. Frequently Asked Questions (FAQ)
Q1. What is the difference between MySQL’s REGEXP and LIKE?
A. REGEXP allows advanced pattern matching, while LIKE is for partial match searches.
SELECT * FROM users WHERE email LIKE '%example.com';
SELECT * FROM users WHERE email REGEXP '^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+.[a-zA-Z]{2,}$';
Q2. How can performance be improved?
A.
Apply filter conditions in advance.
Leverage indexes.
Simplify the query.
Q3. How to handle multibyte characters?
A. Set up UTF-8 support.
ALTER TABLE users CONVERT TO CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;
Q4. Example of replacement using regular expressions?
