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

SQLmedium0.5 min readPremium
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
Expert AnswerPremium
90 wordsInterview-ready
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....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Swiggy. The answer also includes follow-up discussion points that interviewers commonly explore.

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