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FIND_IN_SET: Solve the mystery of multi-value association query
Home Database Mysql Tutorial How to implement multi-value association query through FIND_IN_SET?

How to implement multi-value association query through FIND_IN_SET?

Apr 08, 2025 am 09:33 AM
mysql

How to implement multi-value association query through FIND_IN_SET?

FIND_IN_SET: Solve the mystery of multi-value association query

Many friends will encounter a difficult problem in database operations: How to efficiently handle multi-value association query? For example, a user can have multiple tags. How to find users based on tags? This article will explore in-depth how to use MySQL's FIND_IN_SET function to gracefully solve this problem and reveal the pitfalls and optimization strategies behind it.

Let's make it clear first: FIND_IN_SET is not the best solution to deal with multi-value correlation queries. It has performance bottlenecks, especially when the data volume is huge. But understanding how it works and limitations is crucial for database design and optimization. It is more suitable for some special scenarios, such as small data volume or temporary queries, rather than long-term dependencies.

Review of basic knowledge:

The function of the FIND_IN_SET function is to determine whether a string is in a comma-separated string list. Its syntax is simple: FIND_IN_SET(str,strlist) , where str is the string to be looked for and strlist is a comma-separated list of strings. If str is in strlist , return the position of str in the list (starting from 1); otherwise return 0.

Core concepts and working principles:

The core of FIND_IN_SET lies in string matching. It is essentially a string lookup operation, not a native associated query of the database. MySQL compares each element in str to strlist one by one until a match is found or the full list is traversed. This determines that its efficiency is proportional to the length of the list, and the longer the list, the lower the efficiency. Worse, FIND_IN_SET cannot take advantage of database indexing, which makes it very slow to query on large datasets.

Code example:

Suppose we have two tables: users and user_tags . The users table contains the user ID and username, user_tags table contains the user ID and comma-separated tag list.

 <code class="sql">-- users 表<br>CREATE TABLE users (</code><pre class='brush:php;toolbar:false;'> user_id INT PRIMARY KEY,
username VARCHAR(255)

);

-- user_tags table
CREATE TABLE user_tags (

 user_id INT,
tags VARCHAR(255)

);

-- Insert some data
INSERT INTO users (user_id, username) VALUES (1, 'Alice'), (2, 'Bob'), (3, 'Charlie');
INSERT INTO user_tags (user_id, tags) VALUES (1, 'tag1,tag2'), (2, 'tag2,tag3'), (3, 'tag1,tag3');

-- Use FIND_IN_SET to query users with the 'tag1' tag
SELECT * FROM users WHERE user_id IN (SELECT user_id FROM user_tags WHERE FIND_IN_SET('tag1', tags) > 0);

This code first filters out the user ID containing the 'tag1' tag from user_tags table, and then uses IN clause to find the corresponding user in the users table. Although this achieves the goal, it is inefficient.

Advanced usage and potential problems:

Does FIND_IN_SET support wildcard matching? Not supported! This further limits its application scenarios. If you need fuzzy matching, you have to process the string first and then do the matching, which will reduce efficiency.

Performance optimization and best practices:

Avoid using FIND_IN_SET for multi-value association queries! This is the most important advice. The correct way is to transform the user_tags table into a standardized database design: create an intermediate table user_tag_mapping , which contains two columns: user_id and tag_id , where tag_id is the ID of the tag. This allows database indexing to be used to achieve efficient association query.

 <code class="sql">-- user_tag_mapping 表<br>CREATE TABLE user_tag_mapping (</code><pre class='brush:php;toolbar:false;'> user_id INT,
tag_id INT,
PRIMARY KEY (user_id, tag_id)

);

-- tags table
CREATE TABLE tags (

 tag_id INT PRIMARY KEY,
tag_name VARCHAR(255)

);

-- Reinsert data (need to create tags table first and insert tag1, tag2, tag3)
INSERT INTO user_tag_mapping (user_id, tag_id) VALUES (1, 1), (1, 2), (2, 2), (2, 3), (3, 1), (3, 3);

-- Efficient association query
SELECT u.* FROM users u JOIN user_tag_mapping utm ON u.user_id = utm.user_id JOIN tags t ON utm.tag_id = t.tag_id WHERE t.tag_name = 'tag1';

This standardized design significantly improves query efficiency and avoids the performance bottlenecks brought by FIND_IN_SET . Remember, database design is the cornerstone of performance optimization. Choosing the right database structure is far more important than dependent on skill functions. Never sacrifice long-term performance and maintainability for temporary convenience.

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