RANK in Spark SQL

This page is a quick reference checkpoint for RANK in Spark SQL: behavior, syntax rules, edge cases, and a minimal example; plus the official vendor documentation.


Function Details

RANK assigns a ranking number to each row, giving equal values the same rank and leaving gaps after ties.

Returns the rank of the current row with gaps after ties, determined by the ORDER BY in the window.

If this behavior feels unintuitive, the tutorial below explains the underlying pattern step-by-step.

`RANK()` takes no arguments and must be used with an OVER clause; documented as a window ranking function.

SELECT category, amount, RANK() OVER (PARTITION BY category ORDER BY amount) AS category_rank FROM sales;

What should you do next?

If you came here to confirm syntax, you’re done. If you came here to get better at window functions, choose your next step.

Understand the pattern

RANK is part of a bigger window-function pattern. If you want the “why”, start here: Ranking Functions

Prove it with a real query

Reading docs is useful. Writing the query correctly under pressure is the skill.

Species Revenue Rankings

Support Status

  • Supported: yes
  • Minimum Version: 1.4

Official Documentation

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.