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How would you optimize a SQL query for better performance when working with large datasets?

SQLhard0.7 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
Tredence
Key Concepts Tested
joinoptimizationpartitionsql
Expert AnswerPremium
131 wordsInterview-ready
SQL query optimization for large datasets: (1) Indexing—create indexes on filter and join columns; avoid over-indexing on write-heavy tables. (2) Partitioning—partition by date, region, or key columns to enable partition pruning. (3) Avoid SELECT *—select only needed columns. (4) Push filters early—apply WHERE before JOINs. (5) Replace subqueries with JOINs or CTEs. (6) Use EXPLAIN to analyze execution plans. (7) Denormalize where read performance outweighs storage....
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 Tredence. The answer also includes follow-up discussion points that interviewers commonly explore.

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