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DQDigital Qasas Courses/SQL for Professionals
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  • What SQL is, and why professionals learn it
  • Learn faster: pair this course with a free AI assistant
  • SELECT and FROM: your first real query
  • WHERE: keep only the rows you want
  • Combine conditions: AND, OR, IN, BETWEEN, LIKE, NULL
  • ORDER BY, LIMIT, and DISTINCT
  • COUNT, SUM, AVG, MIN, MAX
  • GROUP BY: one number per group
  • HAVING: filter the groups
  • Why tables relate: keys and joins
  • INNER JOIN: matching rows from two tables
  • LEFT JOIN: keep everything, find what is missing
  • Subqueries: a query inside a query
  • CASE: if-and-then inside a query
  • Window functions: a first look
  • Putting it together, and a cheat sheet
  • Practice challenges
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Window functions: a first look

Last updated 14 June 2026

A GROUP BY collapses rows. A window function computes across a set of rows but keeps every row in the result. That is the difference, and it is what makes running totals and rankings possible.

You write a function followed by OVER (...). The OVER clause describes the window of rows to work across.

Numbering rows

ROW_NUMBER() assigns 1, 2, 3 in the order you give it. Here it ranks products from most to least expensive.

Rank products by price, keeping every row.

CREATE TABLE customers (
  id INTEGER PRIMARY KEY,
  name TEXT,
  city TEXT,
  signup_date TEXT
);
INSERT INTO customers VALUES
  (1, 'Aisyah Rahman', 'Kuala Lumpur', '2023-01-12'),
  (2, 'Lim Wei Jie', 'Penang', '2023-02-03'),
  (3, 'Arjun Pillai', 'Johor Bahru', '2023-02-20'),
  (4, 'Nurul Huda', 'Kuala Lumpur', '2023-03-15'),
  (5, 'Tan Mei Ling', 'Ipoh', '2023-05-01'),
  (6, 'Faiz Hassan', 'Penang', '2023-06-10');

CREATE TABLE products (
  id INTEGER PRIMARY KEY,
  name TEXT,
  category TEXT,
  price REAL
);
INSERT INTO products VALUES
  (1, 'Standard License', 'Software', 199.0),
  (2, 'Pro License', 'Software', 499.0),
  (3, 'Onboarding Workshop', 'Service', 1200.0),
  (4, 'Support Plan', 'Service', 300.0),
  (5, 'Data Pack', 'Add-on', 89.0);

CREATE TABLE orders (
  id INTEGER PRIMARY KEY,
  customer_id INTEGER,
  order_date TEXT,
  status TEXT
);
INSERT INTO orders VALUES
  (1001, 1, '2023-03-01', 'paid'),
  (1002, 1, '2023-04-12', 'paid'),
  (1003, 2, '2023-04-15', 'paid'),
  (1004, 3, '2023-05-02', 'refunded'),
  (1005, 4, '2023-05-20', 'paid'),
  (1006, 2, '2023-06-01', 'pending'),
  (1007, 5, '2023-06-18', 'paid');

CREATE TABLE order_items (
  order_id INTEGER,
  product_id INTEGER,
  quantity INTEGER
);
INSERT INTO order_items VALUES
  (1001, 1, 2), (1001, 5, 1),
  (1002, 2, 1),
  (1003, 1, 1), (1003, 4, 1),
  (1004, 3, 1),
  (1005, 2, 2), (1005, 5, 3),
  (1006, 1, 1),
  (1007, 3, 1), (1007, 4, 2);
SELECT name, price,
  ROW_NUMBER() OVER (ORDER BY price DESC) AS price_rank
FROM products;

A running total

Add SUM(...) OVER (ORDER BY ...) to accumulate as you go. This walks the orders by date and keeps a running count.

CREATE TABLE customers (
  id INTEGER PRIMARY KEY,
  name TEXT,
  city TEXT,
  signup_date TEXT
);
INSERT INTO customers VALUES
  (1, 'Aisyah Rahman', 'Kuala Lumpur', '2023-01-12'),
  (2, 'Lim Wei Jie', 'Penang', '2023-02-03'),
  (3, 'Arjun Pillai', 'Johor Bahru', '2023-02-20'),
  (4, 'Nurul Huda', 'Kuala Lumpur', '2023-03-15'),
  (5, 'Tan Mei Ling', 'Ipoh', '2023-05-01'),
  (6, 'Faiz Hassan', 'Penang', '2023-06-10');

CREATE TABLE products (
  id INTEGER PRIMARY KEY,
  name TEXT,
  category TEXT,
  price REAL
);
INSERT INTO products VALUES
  (1, 'Standard License', 'Software', 199.0),
  (2, 'Pro License', 'Software', 499.0),
  (3, 'Onboarding Workshop', 'Service', 1200.0),
  (4, 'Support Plan', 'Service', 300.0),
  (5, 'Data Pack', 'Add-on', 89.0);

CREATE TABLE orders (
  id INTEGER PRIMARY KEY,
  customer_id INTEGER,
  order_date TEXT,
  status TEXT
);
INSERT INTO orders VALUES
  (1001, 1, '2023-03-01', 'paid'),
  (1002, 1, '2023-04-12', 'paid'),
  (1003, 2, '2023-04-15', 'paid'),
  (1004, 3, '2023-05-02', 'refunded'),
  (1005, 4, '2023-05-20', 'paid'),
  (1006, 2, '2023-06-01', 'pending'),
  (1007, 5, '2023-06-18', 'paid');

CREATE TABLE order_items (
  order_id INTEGER,
  product_id INTEGER,
  quantity INTEGER
);
INSERT INTO order_items VALUES
  (1001, 1, 2), (1001, 5, 1),
  (1002, 2, 1),
  (1003, 1, 1), (1003, 4, 1),
  (1004, 3, 1),
  (1005, 2, 2), (1005, 5, 3),
  (1006, 1, 1),
  (1007, 3, 1), (1007, 4, 2);
SELECT id, order_date,
  COUNT(*) OVER (ORDER BY order_date) AS orders_so_far
FROM orders
ORDER BY order_date;

PARTITION BY restarts the window per group, the way GROUP BY splits rows, while still keeping every row. That is the next step once these two feel comfortable.

A window function is computed after WHERE runs, so you cannot filter on its result in the same query. To keep, say, only rank 1 per group, wrap the query in a subquery and filter the outer query.

What is the main difference between GROUP BY and a window function?

  • A window function keeps every row; GROUP BY collapses rows into one per group
  • They are two names for the same thing
  • Window functions cannot do sums
Both aggregate, but GROUP BY returns one row per group, while a window function adds the computed value onto every original row.
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