How to perform exact matching and fuzzy matching of data in MySQL?

How to perform exact matching and fuzzy matching of data in MySQL?

MySQL is a widely used relational database management system. When performing data queries, we often need to perform exact matching or fuzzy matching. This article will introduce how to perform these two matching methods in MySQL and provide corresponding code examples.

Exact matching refers to the requirement that the query results must completely match the data of the given conditions. Usually the equal sign "=" is used for exact matching. The following is a simple example:

SELECT * FROM students WHERE name = 'John';

The above code will return the student information named "John". Here "name" is a column name in the table, and 'John' is the value we want to match. Only rows with the value "John" in the "name" column will be returned.

In addition to using the equal sign, we can also use other comparison operators for exact matching, such as "", "=", etc. Here is an example:

SELECT * FROM products WHERE price > 50;

The above code will return product information with a price greater than 50. Here "price" is a column name in the table, and 50 is the value we want to match. Only rows with a value greater than 50 in the "price" column will be returned.

Fuzzy matching means that the query results can partially match the given conditions. Wildcards are often used for fuzzy matching. Common wildcard characters in MySQL include "%" and "_". "%" represents any length of characters, "_" represents one character. Here is an example:

SELECT * FROM users WHERE email LIKE '%@gmail.com';

The above code will return all user information using Gmail mailboxes. Here "email" is a column name in the table, and '%@gmail.com' is the value we want to match. Only rows whose values ​​in the "email" column end with "@gmail.com" will be returned.

We can also use multiple wildcards for complex fuzzy matching. Here is an example:

SELECT * FROM customers WHERE phone_number LIKE '180%5_';

The above code will return customer information whose mobile phone number starts with "180" and the second to last digit is "5". Here "phone_number" is a column name in the table, and '180%5_' is the value we want to match. Only rows whose values ​​in the "phone_number" column meet the above conditions will be returned.

It should be noted that fuzzy matching is usually less efficient than exact matching because the query engine needs to perform pattern matching on each row. Therefore, when performing fuzzy matching, try to avoid using fuzzy matching before wildcards to improve query efficiency.

To summarize, exact matching and fuzzy matching are commonly used data matching methods in MySQL. By using appropriate operators and wildcards, we can perform exact or fuzzy matching based on specific needs. These matching methods are very practical in daily database queries and can help us accurately obtain the required data.

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