What metrics prove Query Execution Plans is healthy in prod?

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Quick interview answer

Prove Query Execution Plans is healthy with latency (p50/p95/p99), error/saturation rates, and queue/event-loop lag — not just CPU. Context: Use Query Execution Plans as the core idea. Example shape: Sudden seq scan on million-row table traced to outdated stats after bulk load..

Detailed answer

Production health signals for Query Execution Plans: • Latency: p50/p95/p99 of the critical path that uses Query Execution Plans. • Errors: failure rate, timeouts, and retry storms. • Saturation: queue depth, event-loop delay, thread/pool utilization. • Business SLIs: request success and user-visible freshness where relevant. Trade-off lens: Pros: Visual plan reveals missing indexes and bad estimates. Cons: Plans vary by engine; hints are last resort. Explain thresholds + alerts, then how you triage. Parent context: Use Query Execution Plans as the core idea. Example shape: Sudden seq scan on million-row table traced to outdated stats after bulk load..

Full explanation

Good answers name measurable signals and what “bad” looks like for Query Execution Plans. Optimizer chooses join order, access paths (seek vs scan), and algorithms (hash vs merge join). EXPLAIN/EXPLAIN ANALYZE shows estimated vs actual rows — key for tuning.

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Parent context — Query Execution Plans

Use Query Execution Plans as the core idea. Example shape: Sudden seq scan on million-row table traced to outdated stats after bulk load..

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