**Architectural Logic**: Optimize in order—partition pruning, clustering, query rewrite, materialization, approximate methods. **Strategies**: (1) Partition pruning—predicate on partition column. (2) Clustering/sort keys—colocate related data. (3) Query rewrite—avoid SELECT *;...
This medium-level SQL question appears frequently in data engineering interviews at companies like BCG. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (partition) 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: Optimize in order—partition pruning, clustering, query rewrite, materialization, approximate methods. Strategies: (1) Partition pruning—predicate on partition column. (2) Clustering/sort keys—colocate related data. (3) Query rewrite—avoid SELECT *; push filters; reduce shuffle. (4) Materialized views—pre-aggregate common patterns. (5) Approximate—sampling, HyperLogLog when exact not needed. (6) Incremental—process only changed data. (7) Scale compute; tune parallelism. Why Order: Pruning has highest impact; materialization helps repeated queries. Scalability: Profile first (EXPLAIN, query stats); iterate. Cost: Each strategy reduces compute or storage; measure before/after.
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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.