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The Fittest Survives: An Adaptive Approach to Query Optimization

Summary: An adaptive query optimizer tunes its search space and strategy to changing conditions, rather than relying on fixed procedures. It incrementally replaces cached plans for canned queries with fitter alternatives, demonstrating gains on large multijoin workloads. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
8464
Venue
VLDB
Year
1995
Pagerank
5.4331924e-05
Overall Rank
8,400 | 42.37%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{lu_vldb95,
        title = {{The Fittest Survives: An Adaptive Approach to Query Optimization}},
        author = {Lu, Hongjun and Tan, Kian-Lee and Dao, Son},
        journal = {PVLDB},
        series = {{VLDB} '95},
        year = {1995}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
4,790 A Characterization of the Sensitivity of Query Optimization to Storage Access Cost Parameters 2003 SIGMOD 6.5068083e-05
8,163 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 5.4751517e-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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