If Else SQL

Galaxy Glossary

How can I use conditional logic (IF-ELSE) in SQL?

SQL's IF-ELSE statements allow you to execute different blocks of code based on conditions. This is crucial for creating dynamic queries and manipulating data based on specific criteria. They are not directly supported in standard SQL but can be achieved using CASE statements.
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Description

While SQL doesn't have a direct IF-ELSE construct like some programming languages, the `CASE` statement provides a powerful way to implement conditional logic within SQL queries. The `CASE` statement evaluates a condition and returns a value based on the result. This allows you to perform different actions depending on the outcome of the evaluation. It's a fundamental tool for data manipulation and filtering. For example, you might want to categorize customer orders based on their total value, or assign different discounts based on product type. The `CASE` statement enables this kind of dynamic behavior within your SQL queries.The `CASE` statement is structured to evaluate conditions and return different results. It's a crucial part of SQL for making queries more flexible and responsive to different data scenarios. It's important to understand that `CASE` statements are not limited to simple comparisons; they can handle complex conditions and nested logic.Using `CASE` statements, you can create more sophisticated queries that respond to various conditions. This is a common requirement in data analysis and reporting, where you might need to categorize data, apply different rules, or generate different outputs based on the data's characteristics. This flexibility is a key advantage of using `CASE` statements in SQL.In essence, `CASE` statements in SQL are a powerful tool for implementing conditional logic, enabling you to tailor your queries to specific data requirements and create dynamic results.

Why If Else SQL is important

Conditional logic is essential for creating dynamic and responsive SQL queries. It allows you to tailor your results to specific criteria, making your queries more powerful and useful. This is crucial for data analysis, reporting, and data manipulation tasks.

Example Usage


-- Sample table
CREATE TABLE Customers (
    CustomerID INT PRIMARY KEY,
    FirstName VARCHAR(50),
    LastName VARCHAR(50),
    City VARCHAR(50),
    OrderTotal DECIMAL(10, 2)
);

-- Insert some sample data
INSERT INTO Customers (CustomerID, FirstName, LastName, City, OrderTotal)
VALUES
(1, 'John', 'Doe', 'New York', 100.00),
(2, 'Jane', 'Smith', 'Los Angeles', 250.00),
(3, 'Peter', 'Jones', 'Chicago', 50.00),
(4, 'Mary', 'Brown', 'Houston', 150.00);

-- Query to categorize customers based on order total
SELECT
    CustomerID,
    FirstName,
    LastName,
    City,
    OrderTotal,
    CASE
        WHEN OrderTotal > 100 THEN 'High Value'
        WHEN OrderTotal BETWEEN 50 AND 100 THEN 'Medium Value'
        ELSE 'Low Value'
    END AS CustomerCategory
FROM
    Customers;

Common Mistakes

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