-- Multiple aggregates, single grouping

SELECT

department,

COUNT(*) AS employee_count,

SUM(salary) AS total_payroll,

AVG(salary) AS avg_salary,

MIN(salary) AS min_salary,

MAX(salary) AS max_salary

FROM employees

GROUP BY department;

-- Multi-column grouping

SELECT

department,

job_title,

COUNT(*) AS count,

AVG(salary) AS avg_salary

FROM employees

GROUP BY department, job_title;

-- Complete pattern

SELECT

region,

category,

COUNT(*) AS orders,

SUM(total) AS revenue,

AVG(total) AS avg_order

FROM orders

WHERE order_date >= '2024-01-01'

GROUP BY region, category

HAVING COUNT(*) >= 10

ORDER BY revenue DESC;

Multiple aggregates computed in one pass per group

All non-aggregate columns must be in GROUP BY

More grouping columns = more granular groups

WHERE filters rows, HAVING filters groups

ORDER BY can reference any aggregate

Core references in this topic include WHERE, =, <, >, <=, >=. Learn what each one does, when to use it, and the execution or engine rules that matter.

WHERE

Filters rows before projection and sorting. It decides which rows continue through the query pipeline.

SELECT ... FROM table WHERE condition;

Most performance issues start with a weak WHERE clause or a missing supporting index.