Usage of like and in in sql

In SQL, LIKE is used to find strings containing specific patterns. It supports wildcards, but is not as efficient as the IN operator. IN is used to find fields that match a specified list of values. It is faster and supports index optimization. It is recommended to use IN when looking for specific values, use LIKE when looking for similar strings, and use IN in preference to optimize performance.

Usage of LIKE and IN in SQL

LIKE and IN are both in SQL Operators for filtering data, but their usage and effects differ. The

LIKE operator is used to find a string that matches a specified pattern. The pattern can contain wildcard characters, such as the percent sign (%) and the underscore (_), to represent any single or multiple characters. For example:

SELECT * FROM customers WHERE name LIKE '%John%';

This will return all customer records that contain the string "John" in their name. The

IN operator is used to find fields that match a specified list of values. Lists of values ​​are enclosed in parentheses. For example:

SELECT * FROM customers WHERE id IN (1, 2, 3);

This will return customer records with ID 1, 2 or 3.

Difference

• ##Versatility: LIKE is more general and can find any string that matches the pattern, while IN can only match The specified list of values.
• Efficiency: IN is generally more efficient than LIKE because it only needs to check a limited list of values, while LIKE needs to scan the entire string.
• Index: If an index is built on the field, IN can use the index to improve query performance, but LIKE cannot.
• Wildcard characters: LIKE supports the use of wildcard characters, but IN does not.

Usage Suggestions

• Find a specific value: Use IN.
• Find similar strings: Use LIKE.
• Optimize performance: If there is an index on the field, IN is preferred.

Example

Find customers whose names are "John" or "Jane":

SELECT * FROM customers WHERE name IN ('John', 'Jane');

Find customers whose names contain the character "smith" Customers of string:

SELECT * FROM customers WHERE name LIKE '%smith%';

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