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Xor Filters: Faster and Smaller Than Bloom and Cuckoo Filters [r-libre/1857]

Graf, Thomas Mueller, & Lemire, Daniel (2020). Xor Filters: Faster and Smaller Than Bloom and Cuckoo Filters. Journal of Experimental Algorithmics, 25 (1). https://doi.org/10.1145/3376122

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Content : Submitted Version
License : Creative Commons Attribution.
 
Item Type: Journal Articles
Refereed: Yes
Status: Published
Abstract: The Bloom filter provides fast approximate set membership while using little memory. Engineers often use these filters to avoid slow operations such as disk or network accesses. As an alternative, a cuckoo filter may need less space than a Bloom filter and it is faster. Chazelle et al. proposed a generalization of the Bloom filter called the Bloomier filter. Dietzfelbinger and Pagh described a variation on the Bloomier filter that can be used effectively for approximate membership queries. It has never been tested empirically, to our knowledge. We review an efficient implementation of their approach, which we call the xor filter. We find that xor filters can be faster than Bloom and cuckoo filters while using less memory. We further show that a more compact version of xor filters (xor+) can use even less space than highly compact alternatives (e.g., Golomb-compressed sequences) while providing speeds competitive with Bloom filters.
Depositor: Lemire, Daniel
Owner / Manager: Daniel Lemire
Deposited: 17 Dec 2019 20:22
Last Modified: 09 Oct 2020 15:22

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