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Efficiently Computing Join Orders with Heuristic Search

Summary: The paper reduces join-order optimization to a shortest-path problem within a formal framework, enabling principled heuristic search for query plans. In a real DBMS, it achieves order-of-magnitude speedups on star- and clique-shaped queries, with suboptimal variants expanding the cost–time Pareto frontier. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6638
Venue
SIGMOD
Year
2023
Pagerank
5.5237338e-05
Overall Rank
7,882 | 45.93%
DOI
10.1145/3588927

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{haffner_sigmod23,
        title = {{Efficiently Computing Join Orders with Heuristic Search}},
        author = {Haffner, Immanuel and Dittrich, Jens},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3588927},
        url = {https://dl.acm.org/doi/10.1145/3588927},
        year = {2023}
}

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