This page is a quick reference checkpoint for AVG OVER in Spark SQL: behavior, syntax rules, edge cases, and a minimal example; plus the official vendor documentation.
AVG OVER returns the average value of an expression across the window frame.
AVG used with OVER` returns one value per row in the window rather than collapsing rows like GROUP BY.
If this behavior feels unintuitive, the tutorial below explains the underlying pattern step-by-step.
`avg(expr) OVER (window_spec)is allowed; Spark explicitly states aggregate functions may be used withOVER.
SELECT category, amount, AVG(amount) OVER (PARTITION BY category) AS category_avg FROM sales;
If you came here to confirm syntax, you’re done. If you came here to get better at window functions, choose your next step.
AVG OVER is part of a bigger window-function pattern. If you want the “why”, start here: Aggregate Window Functions
Reading docs is useful. Writing the query correctly under pressure is the skill.
For the authoritative spec, use the vendor docs. This page is the fast “sanity check”.
View Spark SQL Documentation →Looking for more functions across all SQL dialects? Visit the full SQL Dialects & Window Functions Documentation.