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Including Bloom Filters in Bottom-up Optimization

Summary: Bloom filters embedded in a bottom-up cost-based optimizer enable Bloom-filter-aware optimization beyond top-down plans. Heuristics bound search-space growth; improves join order and predicate transfer; 32.8% latency reduction for Bloom queries. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7165
Venue
SIGMOD
Year
2025
Pagerank
5.2934632e-05
Overall Rank
9,279 | 36.34%
DOI
10.1145/3722212.3724440

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zeyl_sigmod25,
        title = {{Including Bloom Filters in Bottom-up Optimization}},
        author = {Zeyl, Timothy and Cheng, Qi and Pournaghi, Reza and Lam, Jason and Wang, Weicheng and Wong, Calvin and Chen, Chong and Larson, Per-Ake},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3722212.3724440},
        url = {https://dl.acm.org/doi/10.1145/3722212.3724440},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,135 I Can't Believe It's Not Yannakakis: Pragmatic Bitmap Filters in Microsoft SQL Server 2026 CIDR 5.093636e-05
10,529 Robust Predicate Transfer with Dynamic Execution 2026 VLDB 5.093636e-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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