"RE-Tree: An Efficient Index Structure for Regular Expressions"

by Chee-Yong Chan, Minos Garofalakis, and Rajeev Rastogi.
Proceedings of VLDB'2002, Hong Kong, China, August 2002, pp. 251-262.
[** Invited to the "Best of VLDB'2002" Special Issue of The VLDB Journal **]


Abstract

 Due to their expressive power, Regular Expressions (REs) are quickly becoming an integral part of language specifications for several important application scenarios. Many of these applications have to manage huge databases of RE specifications and need to provide an effective matching mechanism that, given an input string, quickly identifies the REs in the database that match it. In this paper, we propose the RE-tree, a novel index structure for large databases of RE specifications. Given an input query string, the RE-tree speeds up the retrieval of matching REs by focusing the search and comparing the input string with only a small fraction of REs in the database. Even though the RE-tree is similar in spirit to other tree-based structures that have been proposed for indexing multi-dimensional data, RE indexing is significantly more challenging since REs typically represent infinite sets of strings with no well-defined notion of spatial locality. To address these new challenges, our RE-tree index structure relies on novel measures for comparing the relative sizes of infinite regular languages. We also propose innovative solutions for the various RE-tree operations, including the effective splitting of RE-tree nodes and computing a "tight" bounding RE for a collection of REs. Finally, we demonstrate how sampling-based approximation algorithms can be used to significantly speed up the performance of RE-tree operations. Our experimental results with synthetic data sets indicate that the RE-tree is very effective in pruning the search space and easily outperforms naive sequential search approaches.

[ camera-ready paper (pdf) (ps.gz) | journal version (pdf) (in The VLDB Journal) | Chee-Yong's talk slides (ppt.gz) ]


Copyright © 2002, VLDB Endowment. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.