This page is a quick reference checkpoint for PERCENT_RANK in Spark SQL: behavior, syntax rules, edge cases, and a minimal example; plus the official vendor documentation.
PERCENT_RANK returns a row's relative rank as a percentage between 0 and 1.
Returns the relative rank of the current row: (rank - 1) / (rows_in_partition - 1); defined only over the window's ORDER BY.
If this behavior feels unintuitive, the tutorial below explains the underlying pattern step-by-step.
`PERCENT_RANK()` takes no arguments and must be used with an OVER clause; Spark documents it as a window function.
SELECT id, PERCENT_RANK() OVER (ORDER BY id) AS pct_rank FROM table;
If you came here to confirm syntax, you’re done. If you came here to get better at window functions, choose your next step.
PERCENT_RANK is part of a bigger window-function pattern. If you want the “why”, start here: Percentile Distribution
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.