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Explain your approach to optimizing a slow-running query on a table with billions of rows.

SQLmedium0.3 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
Goldman Sachs
Key Concepts Tested
partition
Expert AnswerPremium
69 wordsInterview-ready
**Approach**: (1) Execution plan—identify full scans, shuffle size, sort. (2) Partition pruning—filter on partition key (e.g., dt) before scan. (3) Predicate pushdown—ensure filters reach storage layer. (4) Index/Clustering—B-tree on filter; Z-order on multi-column. (5) Reduce scope—narrow columns; APPROX_COUNT_DISTINCT when exact not needed. (6) Incremental—process only new/changed data. (7) Materialized aggregation—pre-aggregate for frequent patterns....
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 Goldman Sachs. The answer also includes follow-up discussion points that interviewers commonly explore.

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