Pattern Search

Sometimes, we need to find customers whose names start with “J,” products that include the word “phone,” or emails ending in “@example.com.” These are not exact matches; they require pattern matching, which is where this pattern comes into play. Whether it’s for filtering specific user behavior, parsing text inputs, or validating form fields, Pattern search is a practical and essential technique.

In this lesson, we’ll learn how to search within strings using SQL patterns, with tools like LIKE, ILIKE, wildcards, and REGEXP. We’ll also explore best practices for clarity and performance.

By the end of this lesson, we will be able to:

• Understand how and when to use pattern-based filters in SQL.

• Use LIKE, %, _, and regular expressions (REGEXP) to match text.

• Identify common mistakes and performance pitfalls in pattern matching.

• Apply pattern search to solve real-world text filtering problems.

Pattern overview

Category:

• Filtering Patterns

Intent:

To retrieve rows based on partial matches in text fields by using pattern matching techniques such as LIKE or regular expressions.

Motivation:

In real-world databases, we often need to find partial or fuzzy matches, such as emails containing a domain, product names that include a brand, or phone numbers in a specific format. Pattern search allows us to flexibly filter rows without relying on exact equality.

Also known as

• Text match

• Wildcard filter

• Regex match

Structure

There are two main ways we structure pattern searches:

1. Basic wildcard matching using LIKE and ILIKE:

   1. % for any number of characters.

   2. _ for a single character.