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The Case for Deep Query Optimisation

Summary: Proposes Deep Query Optimisation (DQO): decompose physical operators into fine-grained subcomponents to enumerate sub-plans offline/at query time, enabling deeper plan search than shallow QO. Defines MAVs and the Algorithmic View Selection Problem (AVSP), evaluates DQO on hash-based grouping, and sketches a research agenda. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
365
Venue
CIDR
Year
2020
Pagerank
5.686096e-05
Overall Rank
7,156 | 50.91%
DOI
-

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BibTeX Citation

@inproceedings{dittrich_cidr20,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '20},
        title = {{The Case for Deep Query Optimisation}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Dittrich, Jens and Nix, Joris},
        year = {2020}
}

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