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Stacked Filters: Learning to Filter by Structure

Summary: Stacked Filters blend workload knowledge of negatives into a hashed filter stack for fast filtering. Adaptive, they learn on the fly and outperform query-agnostic and classifier-based filters in end-to-end throughput, up to 130x within memory. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12766
Venue
VLDB
Year
2021
Pagerank
6.6436681e-05
Overall Rank
4,532 | 68.91%
DOI
10.14778/3436905.3436919

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{deeds_vldb21,
        title = {{Stacked Filters: Learning to Filter by Structure}},
        author = {Deeds, Kyle and Hentschel, Brian and Idreos, Stratos},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {4},
        pages = {600--612},
        doi = {10.14778/3436905.3436919},
        url = {https://doi.org/10.14778/3436905.3436919},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 10 of 10 citing papers.

Rank Citing Paper Year Venue Pagerank
1,954 Chucky: A Succinct Cuckoo Filter for LSM-Tree 2021 SIGMOD 9.4208165e-05
4,119 Proteus: A Self-Designing Range Filter 2022 SIGMOD 6.8907395e-05
4,664 GRF: A Global Range Filter for LSM-Trees with Shape Encoding 2024 SIGMOD 6.5787544e-05
4,960 InfiniFilter: Expanding Filters to Infinity and Beyond 2023 SIGMOD 6.4280133e-05
7,469 Optimizing Collections of Bloom Filters within a Space Budget 2024 VLDB 5.609743e-05
7,776 Aleph Filter: To Infinity in Constant Time 2024 VLDB 5.5464036e-05
8,880 Entropy-Learned Hashing: Constant Time Hashing with Controllable Uniformity 2022 SIGMOD 5.3524255e-05
8,892 Adaptive Quotient Filters 2024 SIGMOD 5.3505412e-05
9,463 Hourglass: An Adaptive Range Filter with Lightweight Hybrid Encoding 2026 SIGMOD 5.2634238e-05
11,554 Workload-Adaptive Filtering in Storage Engines 2022 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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