**Architectural Logic**: Distribution, sort keys, vacuum, materialized views—foundation for Redshift. **Strategies**: (1) DISTKEY on join column. (2) SORTKEY on filter columns (date, region). (3) VACUUM and ANALYZE regularly. (4) Result cache. (5) Materialized views for common...
This medium-level SQL question appears frequently in data engineering interviews at companies like Capco. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (join) 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.
Architectural Logic: Distribution, sort keys, vacuum, materialized views—foundation for Redshift. Strategies: (1) DISTKEY on join column. (2) SORTKEY on filter columns (date, region). (3) VACUUM and ANALYZE regularly. (4) Result cache. (5) Materialized views for common aggregates. (6) Column compression. (7) Avoid SELECT *. Scalability: Design distribution and sort from start; monitor query plans. Cost: Right-sizing; concurrency scaling for spikes. Best Practice: EXPLAIN; WLM for reporting; date in sort key; tune based on workload.
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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.