Binary Fuse Filters: Fast and Smaller Than Xor Filters

January 04, 2022 Β· Declared Dead Β· πŸ› ACM Journal of Experimental Algorithmics

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Authors Thomas Mueller Graf, Daniel Lemire arXiv ID 2201.01174 Category cs.DS: Data Structures & Algorithms Citations 40 Venue ACM Journal of Experimental Algorithmics Last Checked 3 months ago
Abstract
Bloom and cuckoo filters provide fast approximate set membership while using little memory. Engineers use them to avoid expensive disk and network accesses. The recently introduced xor filters can be faster and smaller than Bloom and cuckoo filters. The xor filters are within 23% of the theoretical lower bound in storage as opposed to 44% for Bloom filters. Inspired by Dietzfelbinger and Walzer, we build probabilistic filters -- called binary fuse filters -- that are within 13% of the storage lower bound -- without sacrificing query speed. As an additional benefit, the construction of the new binary fuse filters can be more than twice as fast as the construction of xor filters. By slightly sacrificing query speed, we further reduce storage to within 8% of the lower bound. We compare the performance against a wide range of competitive alternatives such as Bloom filters, blocked Bloom filters, vector quotient filters, cuckoo filters, and the recent ribbon filters. Our experiments suggest that binary fuse filters are superior to xor filters.
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