Indexing true/false: TRUE—Indexes speed up SELECT with WHERE/JOIN on indexed columns; indexes can slow down INSERT/UPDATE/DELETE (writes must update index); unique indexes enforce uniqueness; composite indexes support left-prefix queries. FALSE—Indexes always improve all queries...
This hard-level SQL question appears frequently in data engineering interviews at companies like Myntra. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (join, optimization) will help you answer variations of this question confidently.
This is a senior-level question that tests architectural thinking. Lead with the high-level design, then drill into specifics. Discuss trade-offs explicitly - there is rarely one correct answer. Show awareness of scale, fault tolerance, and operational complexity.
Indexing true/false: TRUE—Indexes speed up SELECT with WHERE/JOIN on indexed columns; indexes can slow down INSERT/UPDATE/DELETE (writes must update index); unique indexes enforce uniqueness; composite indexes support left-prefix queries. FALSE—Indexes always improve all queries (no: only relevant columns); more indexes always better (no: diminishing returns, write cost); indexes work on all data types equally (some types less effective). Best practice: index columns used in filters and joins; avoid indexing low-cardinality columns (e.g., boolean); monitor index usage and drop unused indexes. 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.
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Analyze My Answer — FreeAccording 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.