This page is a quick reference checkpoint for SUM OVER in Spark SQL: behavior, syntax rules, edge cases, and a minimal example; plus the official vendor documentation.
SUM OVER returns the running or partitioned sum within the window frame.
Window form returns one value per row in the window instead of collapsing rows like GROUP BY.
If this behavior feels unintuitive, the tutorial below explains the underlying pattern step-by-step.
Use standard sum(...) OVER (window_spec) as a window aggregate.
SELECT category, amount, SUM(amount) OVER (PARTITION BY category) AS category_sum 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.
SUM 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.