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The Fittest Survives: An Adaptive Approach to Query Optimization

Summary: Adaptive optimizer with parameter-tuned search space and strategy enables selection of the best plans under changing workloads. Learning capability for canned queries incrementally replaces old plans with fitter ones, demonstrated on large multijoin workloads using an analytical model. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
8273
Venue
VLDB
Year
1995
Pagerank
4.5618179e-05
Overall Rank
8,194 | 43.00%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
4,516 A Characterization of the Sensitivity of Query Optimization to Storage Access Cost Parameters 2003 SIGMOD 6.1178799e-05
8,659 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 4.4722928e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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