Reviewed by Aditya Kumar · Last reviewed 2026-03-24
**ROW_NUMBER()**: Unique sequential numbers (1, 2, 3...); no ties—deterministic only with ORDER BY uniqueness. **RANK()**: Same rank for ties; skips (1, 2, 2, 4). **DENSE_RANK()**: Same rank for ties; no gaps (1, 2, 2, 3). **Project examples**: ROW_NUMBER() to deduplicate events...
Red Flag: Using ROW_NUMBER for ranking when ties should exist. Pro-Move: Explain that ROW_NUMBER for dedup requires a deterministic ORDER BY; otherwise results can vary across runs.
This medium-level SQL question appears frequently in data engineering interviews at companies like Aarete, Accenture, Fossil Group, and 1 others. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (window) will help you answer variations of this question confidently.
Break this problem into components. Identify the core trade-offs involved, then walk the interviewer through your reasoning step by step. Demonstrate awareness of edge cases and production considerations - this is what separates good answers from great ones.
ROW_NUMBER(): Unique sequential numbers (1, 2, 3...); no ties—deterministic only with ORDER BY uniqueness. RANK(): Same rank for ties; skips (1, 2, 2, 4). DENSE_RANK(): Same rank for ties; no gaps (1, 2, 2, 3). Project examples: ROW_NUMBER() to deduplicate events by (user_id, event_time) keeping first—critical when upstream sends duplicates. DENSE_RANK() for 'top 10 products per category' reports—avoids gaps when filtering. RANK() for leaderboards where ties share position (e.g., two people at 2nd). Why it matters architecturally: Dedup with ROW_NUMBER affects downstream freshness and storage; wrong choice can inflate fact tables. Scalability: Window functions are expensive on huge datasets; push filters before the window when possible.
Red Flag: Using ROW_NUMBER for ranking when ties should exist. Pro-Move: Explain that ROW_NUMBER for dedup requires a deterministic ORDER BY; otherwise results can vary across runs.
Practice the 46 most asked data engineering questions at Aarete. Covers SQL, Behavioral, General/Other and more.
9 min read →Practice the 33 most asked data engineering questions at Accenture. Covers SQL, Spark/Big Data, Behavioral and more.
8 min read →Master 487 sql questions with expert answers. Real questions from 97+ companies.
60 min read →Window functions and CTEs are the #1 tested SQL topics at Amazon, Google, and Databricks. This guide covers every pattern you'll face with production-ready answers.
18 min read →Some links below are affiliate links. If you buy through them we may earn a small commission at no extra cost to you — it helps keep DataEngPrep free.
According to DataEngPrep.tech, this is one of the most frequently asked SQL interview questions, reported at 4 companies. DataEngPrep.tech maintains an editor-reviewed database of 1,863 data engineering interview questions across 7 categories.