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Hint-QPT: Hints for Robust Query Performance Tuning

Summary: Hint-QPT: an interactive system that models selectivity uncertainty to recommend and visualize robust execution plans (plan-cost distributions) rather than relying on point estimates. Identifies sensitivity hotspots for targeted selectivity acquisition or tuning so users can pick robust plans or selectively collect stats to fix optimizer errors. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
14148
Venue
VLDB
Year
2025
Pagerank
4.1945683e-05
Overall Rank
10,808 | 24.82%
DOI
10.14778/3750601.3750663

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Rank Citing Paper Year Venue Pagerank
10,751 PAR2QO: Parametric Penalty-Aware Robust Query Optimization 2025 VLDB 4.1945683e-05
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