**Elastic Resize**: Add/remove nodes same type; data stays in place via leader node redistribution; ~2–5 min; no data copy. **Classic Resize**: Change node type or count; full data redistribution; hours for large clusters. **Why Elastic**: Quick scale for concurrency (e.g.,...
This easy-level SQL question appears frequently in data engineering interviews at companies like Capco. While less common, it tests deeper understanding that distinguishes strong candidates.
Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.
Elastic Resize: Add/remove nodes same type; data stays in place via leader node redistribution; ~2–5 min; no data copy. Classic Resize: Change node type or count; full data redistribution; hours for large clusters. Why Elastic: Quick scale for concurrency (e.g., holiday); same node type required. Why Classic: Migrate dc2 → ra3 (managed storage); major capacity change. Scalability: Elastic limited to 2× nodes; Classic supports full resize. Cost: Elastic—minimal downtime; Classic—plan during maintenance.
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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.