I knew what the question was asking, sort of, but the syntax just evaporated from my brain mid-test.
Start by clarifying the business question and the grain of the data, then outline the window function logic using PARTITION BY and ORDER BY before writing the final query. Use ROW_NUMBER (or RANK/DENSE_RANK) to assign ranks within partitions and filter to the desired rows, explaining each step along the way.
Pro tip: Always confirm the tie-breaking rules and whether the ranking should be deterministic; mention that ROW_NUMBER gives unique ranks while RANK/DENSE_RANK handle ties differently, and choose based on the business need.
Ask questions to understand the exact output: which records to rank or filter, the partition key, the ordering column, and how ties should be handled.
Specify the PARTITION BY columns (e.g., user_id, category) and the ORDER BY columns (e.g., timestamp DESC, amount DESC) that determine the ranking.
Select ROW_NUMBER for unique sequential ranks, RANK for gaps on ties, or DENSE_RANK for no gaps; justify your choice based on the business logic.
Use a common table expression (CTE) or subquery to compute the window function, then filter the outer query to keep only the desired rows (e.g., rn = 1).
Check edge cases (nulls, duplicates, ties) and mention indexing or partitioning strategies to optimize the window function for large datasets.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Opened it with 10 minutes left, wrote two lines, stared at the screen.
First, restate the problem in your own words to confirm understanding, then break it into logical sub-steps and outline the SQL operations needed for each. Write the query incrementally, testing each part mentally or with sample data, and optimize for clarity and performance under time pressure.
Pro tip: Before diving into complex SQL, clarify the expected output format and edge cases with the interviewer; this shows you think about correctness and scalability, not just syntax.
Ask questions to confirm the input tables, desired output, and any time or performance constraints. This ensures you solve the right problem and avoid rework.
Decompose the multi-step query into smaller, manageable parts (e.g., filtering, aggregating, joining). Identify the order of operations and any dependencies.
Sketch the query skeleton using CTEs or subqueries to modularize each step. This makes the logic clear and easier to debug under time pressure.
Implement each part step by step, mentally testing with sample data or explaining expected results. Check for correctness and edge cases as you go.
Review the final query for performance (e.g., indexing, avoiding unnecessary joins) and readability. Discuss potential improvements or trade-offs with the interviewer.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.