**WHERE**: Filters rows before grouping/aggregation; cannot use aggregate functions. **HAVING**: Filters groups after GROUP BY; used with aggregate functions. **Why it matters**: WHERE reduces rows early (cheaper); HAVING filters on computed values. Misplacing predicates causes...
Red Flag: Using HAVING for non-aggregate conditions (e.g., HAVING status = 'active')—belongs in WHERE. Pro-Move: Say you push filters to WHERE first, and use HAVING only for aggregate conditions (e.g., HAVING COUNT(*) > 1).
This medium-level SQL question appears frequently in data engineering interviews at companies like Accenture, Cognizant, EPAM, and 1 others. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (sql) 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.
WHERE: Filters rows before grouping/aggregation; cannot use aggregate functions. HAVING: Filters groups after GROUP BY; used with aggregate functions. Why it matters: WHERE reduces rows early (cheaper); HAVING filters on computed values. Misplacing predicates causes wrong results or inefficiency. Scalability: Pushing filters to WHERE reduces data before aggregation; HAVING on large grouped result can be expensive. Cost: Always prefer WHERE when possible; HAVING is necessary only for aggregate conditions.
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According to DataEngPrep.tech, this is one of the most frequently asked SQL interview questions, reported at 4 companies. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.