Publications

Stats

View publication

Title Practical Approaches to Reduce the Space Requirement of Lempel-Ziv-Based Compressed Text Indices
Authors Diego Arroyuelo, Gonzalo Navarro
Publication date 2010
Abstract Given a text T[1..n] over an alphabet of size s, the full-text search problem consists in locating the occ occurrences of a given pattern P[1..m] in T. Compressed full-text self-indices are space-efficient representations of the text that provide direct access to and indexed search on it.

The LZ-index of Navarro is a compressed full-text self-index based on the LZ78 compression algorithm. This index requires about 5 times the size of the compressed text (in theory, 4nHk(T)+o(nlog?) bits of space, where Hk(T) is the k-th order empirical entropy of T). In practice, the average locating complexity of the LZ-index is O(? m log? n + occ ?m/2), where occ is the number of occurrences of P. It can extract text substrings of length ℓ in O(ℓ) time. This index outperforms competing schemes both to locate short patterns and to extract text snippets. However, the LZ-index can be up to 4 times larger than the smallest existing indices (which use nHk(T)+o(nlog?) bits in theory), and it does not offer space/time tuning options. This limits its applicability.

In this article, we study practical ways to reduce the space of the LZ-index. We obtain new LZ-index variants that require 2(1+&epsis;)nHk(T) + o(nlog?) bits of space, for any 0\<&epsis; \<1. They have an average locating time of O(1/&epsis;(mlog n + occ ?m/2)), while extracting takes O(ℓ) time.

We perform extensive experimentation and conclude that our schemes are able to reduce the space of the original LZ-index by a factor of 2/3, that is, around 3 times the compressed text size. Our schemes are able to extract about 1 to 2 MB of the text per second, being twice as fast as the most competitive alternatives. Pattern occurrences are located at a rate of up to 1 to 4 million per second. This constitutes the best space/time trade-off when indices are allowed to use 4 times the size of the compressed text or more.
Volume 15
Journal name ACM Journal of Experimental Algorithmics
Publisher ACM Press (New York, NY, USA)
Reference URL View reference page