SELECT c.name, COUNT(o.id) AS order_count FROM customers c LEFT JOIN orders o ON c.id = o.customer_id GROUP BY c.id, c.name;

GROUP BY comes after JOIN

Include all non-aggregated SELECT columns in GROUP BY

Use COUNT(column) not COUNT(*) with LEFT JOIN

HAVING filters aggregated results

WHERE filters before aggregation

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.

=

Returns rows where the left and right values are exactly equal.

column = value

Use with exact matches. Do not use = NULL.

<, >, <=, >=

Range comparison operators for less-than, greater-than, and inclusive boundary checks.

salary >= 80000

IS NULL / IS NOT NULL

Tests whether a value is missing. SQL NULL semantics require dedicated NULL predicates.

manager_id IS NULL

Never use = NULL or != NULL.

ANY / ALL

Compares one value against every or at least one value from a subquery result.

salary > ALL (SELECT salary FROM interns)

INTERVAL

Represents a duration that can be added to or subtracted from dates and timestamps.

order_date + INTERVAL '7 days'

PRIMARY KEY

Uniquely identifies each row and implicitly requires NOT NULL.

customer_id INT PRIMARY KEY

COUNT

Counts rows or non-NULL values depending on the argument.

COUNT(*)

SUM

Adds numeric values together across the current group or window frame.

SUM(revenue)

AVG

Calculates the arithmetic mean of numeric values.

AVG(salary)