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Optimize a slow SQL query for a large orders table containing billions of rows.

SQLmedium0.5 min readPremium

Optimize billion-row orders: (1) Partition by date, shard. (2) Index order_id, customer_id, status. (3) Avoid SELECT *; select needed columns. (4) Use covering index. (5) Archive old data. (6) Consider read replicas. (7) Materialized views for common aggregations. (8) Query...

🤖 Analyze Your Answer
Frequency
Low
Asked at 1 company
Category
487
questions in SQL
Difficulty Split
130E|271M|86H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Swiggy
Key Concepts Tested
partitionsql

Why This Question Matters

This medium-level SQL question appears frequently in data engineering interviews at companies like Swiggy. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (partition, sql) will help you answer variations of this question confidently.

How to Approach This

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.

Expert Answer
90 words

Optimize billion-row orders: (1) Partition by date, shard. (2) Index order_id, customer_id, status. (3) Avoid SELECT *; select needed columns. (4) Use covering index. (5) Archive old data. (6) Consider read replicas. (7) Materialized views for common aggregations. (8) Query timeout and limit. Example: Partition by order_date; WHERE order_date >= '2023-01-01' AND status = 'shipped' uses partition + index. Why it matters: Design choices compound at scale—wrong approach can cause 100× overhead. Scalability trade-offs: Profile before optimizing; validate on sample then full. Cost implications: Suboptimal choices multiply at billion-row scale.

The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations covering performance optimization and real-world examples.

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According 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.

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