**Architectural Logic**: PK: Unique, NOT NULL identifier for entity integrity; often clustered index. FK: Reference to PK in another table; enforces referential integrity (no orphans). **Why**: PKs enable uniqueness checks, join performance, replication. FKs prevent orphaned...
This medium-level SQL question appears frequently in data engineering interviews at companies like Presidio, Swiggy. 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: PK: Unique, NOT NULL identifier for entity integrity; often clustered index. FK: Reference to PK in another table; enforces referential integrity (no orphans). Why: PKs enable uniqueness checks, join performance, replication. FKs prevent orphaned child rows and encode relationships. In warehouses, PKs/FKs are often logical (not enforced) for load performance. Scalability: Enforced FKs add validation cost on INSERT/UPDATE; in high-throughput ingestion, logical FKs + batch validation are common. Cost: PK index is usually clustered (one per table); FK indexes speed up joins but add write overhead.
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According to DataEngPrep.tech, this is one of the most frequently asked SQL interview questions, reported at 2 companies. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.