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The Fuse XORier Lookup Table: Exploration, Implementation, and Revision of Probabilistic Sets and Maps (2312.13541v1)

Published 21 Dec 2023 in cs.DS

Abstract: This paper presents an exploration, implementations, and revisions of probabilistic sets and maps, specifically focusing on Bloomier filters and related data structures. The paper introduces the Fuse XORier Lookup Table (FXLT), an enhanced version of the Bloomier Filter incorporating spatial coupling, linear construction, and optimizations. The authors provide implementations in C and Python, comparing the FXLT's performance with other data structures like bloom filters, XOR filters, binary fuse filters, hash tables, and red-black trees. The FXLT demonstrates improvements in both space and time efficiency over traditional Bloomier Filters and appears competitive with hash tables for large datasets.

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References (5)
  1. “The Bloomier Filter: An Efficient Data Structure for Static Support Lookup Tables” In Proceedings of the Fifteenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA ’04 New Orleans, Louisiana: Society for IndustrialApplied Mathematics, 2004, pp. 30–39 URL: https://www.cs.princeton.edu/~chazelle/pubs/soda-rev04.pdf
  2. Thomas Mueller Graf and Daniel Lemire “Xor Filters: Faster and Smaller Than Bloom and Cuckoo Filters” arXiv:1912.08258 [cs] In ACM Journal of Experimental Algorithmics 25, 2020, pp. 1–16 DOI: 10.1145/3376122
  3. Thomas Mueller Graf and Daniel Lemire “Binary Fuse Filters: Fast and Smaller Than Xor Filters” arXiv:2201.01174 [cs] In ACM Journal of Experimental Algorithmics 27, 2022, pp. 1–15 DOI: 10.1145/3510449
  4. Stefan Walzer “Peeling Close to the Orientability Threshold: Spatial Coupling in Hashing-Based Data Structures”, 2020 arXiv:2001.10500 [cs.DS]
  5. “Approximate membership queries - Stanford University”, pp. 49– URL: https://web.stanford.edu/class/archive/cs/cs166/cs166.1216/lectures/13/Slides13.pdf#page=49

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