SQL GROUP BY statement

Here is a clear, practical, and complete guide to the SQL GROUP BY statement, with examples, rules, and common pitfalls.

What SQL GROUP BY statement Does

GROUP BY groups rows that share the same values so you can apply aggregate functions such as:

COUNT()
SUM()
AVG()
MIN()
MAX()

It turns many rows into summary rows.

Basic Syntax

Basic Examples

1. Count employees per department

2. Total sales per customer

3. Average score per class

GROUP BY with Multiple Columns

This groups first by country, then city.

GROUP BY + HAVING (Filter Aggregated Results)

HAVING is used after aggregation.
WHERE filters rows before grouping.

Example: Departments with more than 10 employees

GROUP BY with ORDER BY

Sort aggregated results:

Real-World Examples

Monthly revenue

(PostgreSQL example using DATE_TRUNC)

Count logins per user

Maximum order per customer

Important Rules & Pitfalls

1. Every non-aggregated column MUST be in GROUP BY

Invalid:

Valid:

2. Aggregate functions ignore NULLs

COUNT(column) ignores NULL
SUM, AVG, MIN, MAX ignore NULL

3. Use HAVING for aggregated filters

WHERE → before grouping
HAVING → after grouping

4. GROUP BY with DISTINCT isn’t usually needed

This:

Is equal to:

Performance Tips

Index columns used in GROUP BY
Use GROUP BY on low-cardinality columns carefully
Avoid grouping on expressions unless necessary
In large datasets, consider materialized views