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Move-r: Optimizing the r-index

Authors Nico Bertram, Johannes Fischer , Lukas Nalbach

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Author Details

Nico Bertram
  • Technische Universität Dortmund, Germany
Johannes Fischer
  • Technische Universität Dortmund, Germany
Lukas Nalbach
  • Technische Universität Dortmund, Germany

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Nico Bertram, Johannes Fischer, and Lukas Nalbach. Move-r: Optimizing the r-index. In 22nd International Symposium on Experimental Algorithms (SEA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 301, pp. 1:1-1:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.SEA.2024.1

Abstract

We present a static text index called Move-r, which is a highly optimized version of the r-index ([Travis Gagie et al., 2020] Gagie et al., 2020) that encorporates recent theoretical developments of the move data structure ([Takaaki Nishimoto and Yasuo Tabei, 2021] Nishimoto and Tabei, 2021). The r-index is the method of choice for indexing highly repetitive texts, such as different versions of a text document or DNA from the same species, as it exploits the compressibilty of the underlying data. With Move-r, we can answer count- and locate queries 2-35 (typically 15) times as fast as with any other r-index supporting locate queries while being 0.8-2.5 (typically 2) times as large. A Move-r index can be constructed 0.9-2 (typically 2) times as fast while using 1/3-1 (typically 1/2) times as much space.

Subject Classification

ACM Subject Classification
  • Theory of computation → Pattern matching
Keywords
  • Compressed Text Index
  • Burrows-Wheeler Transform

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