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New Wine in an Old Bottle: Data-Aware Hash Functions for Bloom Filters

Summary: Partitioned Bloom filter with data-aware, projection-based hashes as an alternative to learned Bloom filters. Theory guides hash and partition choices; empirics show up to 100× FP reduction for the same memory and ~50% better compression, beating learned variants. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12691
Venue
VLDB
Year
2022
Pagerank
4.1945683e-05
Overall Rank
11,374 | 20.88%
DOI
10.14778/3538598.3538613

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

Rank Cited Paper Year Venue Pagerank
102 The Case for Learned Index Structures 2018 SIGMOD 0.00049545203
4,378 Fast Processing and Querying of 170TB of Genomics Data via a Repeated And Merged BloOm Filter (RAMBO) 2021 SIGMOD 6.2404547e-05
4,446 Stable Learned Bloom Filters for Data Streams 2020 VLDB 6.1800659e-05
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