Reviewed by Aditya Kumar · Last reviewed 2026-03-24
Optimization: indexes on filter/join columns; avoid SELECT *; use EXPLAIN; replace subqueries with JOINs; partition large tables; materialized views; update statistics; avoid functions on columns; use IN instead of multiple OR; limit result sets; consider query rewrite. **Why it...
Optimization: indexes on filter/join columns; avoid SELECT *; use EXPLAIN; replace subqueries with JOINs; partition large tables; materialized views; update statistics; avoid functions on columns; use IN instead of multiple OR; limit result sets; consider query rewrite. 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.
Red Flag: Optimizing without EXPLAIN or baseline. Pro-Move: 'EXPLAIN ANALYZE + composite index cut P99 80%; we measured write impact before rollout.'
According to DataEngPrep.tech, this is one of the most frequently asked SQL interview questions, reported at 1 company. DataEngPrep.tech maintains an editor-reviewed database of 1,863 data engineering interview questions across 7 categories.