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Multiobjective Query Optimization

Summary: Shows Mariposa’s stride-based greedy optimizer for delay–cost trade-offs can be arbitrarily bad. Adapts multiobjective-optimization techniques to compute Pareto cost–delay curves to any accuracy, and gives a polynomial algorithm for the general problem without stride restrictions. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1222
Venue
PODS
Year
2001
Pagerank
9.812504e-05
Overall Rank
1,762 | 87.92%
DOI
10.1145/375551.375560

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{papadimitriou_pods01,
        address = {New York, NY, USA},
        series = {{PODS} '01},
        title = {{Multiobjective Query Optimization}},
        url = {https://dl.acm.org/doi/10.1145/375551.375560},
        doi = {10.1145/375551.375560},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Papadimitriou, Christos H. and Yannakakis, Mihalis},
        year = {2001}
}

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