**Refactor steps**: (1) Extract nested SELECTs to CTEs (WITH)—named, reusable. (2) Replace correlated subqueries with JOINs—planner optimizes better. (3) Window functions instead of self-joins for row comparisons. (4) Materialize hot paths—temp table if CTE scanned multiple...
This medium-level SQL question appears frequently in data engineering interviews at companies like Goldman Sachs. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (join, 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.
Refactor steps: (1) Extract nested SELECTs to CTEs (WITH)—named, reusable. (2) Replace correlated subqueries with JOINs—planner optimizes better. (3) Window functions instead of self-joins for row comparisons. (4) Materialize hot paths—temp table if CTE scanned multiple times. (5) Push predicates into CTEs. Why: Readability = maintainability; optimizer may flatten CTEs or may not—benchmark. Trade-off: Explicit temp table with stats can beat inlined CTE for complex plans.
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Analyze My Answer — FreeAccording to DataEngPrep.tech, this is one of the most frequently asked SQL interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.