Follow-up · depth 1
How would you test Query Execution Plans?
How would you test Query Execution Plans?
Answers use simple, clear English.
Quick interview answer
Test Query Execution Plans with unit checks for the happy path, integration tests for real I/O boundaries, and load/chaos checks so regressions show up before prod. Core idea: Baseline: 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.
Detailed answer
Interview answer for testing Query Execution Plans: 1) Unit: isolate the pure logic behind Query Execution Plans with deterministic fixtures. 2) Integration: exercise real timers/I/O/network boundaries the way production does. 3) Load & soak: prove the event path still meets SLOs under concurrency. 4) Failure injection: break dependencies and assert recovery/backpressure. Best practices to include: ANALYZE/UPDATE STATISTICS after bulk changes; compare before/after cost. Call out mistakes: Tuning without measuring; ignoring rows mismatch (estimate 10, actual 1M). Parent context: Baseline: 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.
Full explanation
Interviewers want a test strategy, not “I would write tests.” Tie each layer back to how Query Execution Plans fails: correctness, latency, and starvation. 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.
Follow-up questions
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Parent context — Query Execution Plans
Baseline: 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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