Comparing Window Functions and Aggregate Functions in SQL: When to Use Each

SQL provides powerful tools to summarize and analyze data. Two common approaches are using aggregate functions and window functions. While they may seem similar, each serves different purposes and is suited for particular tasks. Understanding their differences will help you write clearer and more efficient SQL queries.

Aggregate functions perform calculations on a group of rows and return a single result per group. Examples include SUM(), COUNT(), AVG(), MIN(), and MAX(). When you use aggregate functions, you typically group data using the GROUP BY clause, which reduces the number of rows in the result.

Window functions also perform calculations across a set of rows, but they do not reduce the number of rows returned. Instead, they return a value for each row while still considering the context of other rows. This allows you to calculate running totals, ranks, moving averages, and more, without grouping the result set.

Let's compare how aggregate and window functions work with a simple example. Suppose we have a sales table:

CREATE TABLE sales (
  id INT,
  salesperson VARCHAR(100),
  amount DECIMAL(10,2)
);

INSERT INTO sales (id, salesperson, amount) VALUES
(1, 'Alice', 100.00),
(2, 'Bob', 150.00),
(3, 'Alice', 200.00),
(4, 'Bob', 50.00),
(5, 'Alice', 300.00);

Now, suppose you want to find the total sales amount per salesperson. Using aggregates with GROUP BY gives:

SELECT salesperson, SUM(amount) AS total_sales
FROM sales
GROUP BY salesperson;

This query returns one row per salesperson, summarizing their total sales.

But what if you want to see each sale alongside the total sales the salesperson made? The aggregate approach won't work here because it collapses rows. Instead, you use a window function:

SELECT
  id,
  salesperson,
  amount,
  SUM(amount) OVER (PARTITION BY salesperson) AS total_sales_per_person
FROM sales;

Here, the window function SUM() OVER partitions the data by salesperson but does not reduce rows. Each row shows the individual sale and the total sales sum for that salesperson.

To summarize:

- Use aggregate functions with GROUP BY when you want one summary row per group. - Use window functions when you want calculations relative to each row but still want to keep all rows in the result.

Understanding these distinctions will help you decide which tool fits your analytical needs best.