Reducing Space Requirements for Disk Resident Suffix Arrays

Alistair Moffat
Department of Computer Science and Software Engineering, The University of Melbourne, Victoria 3010, Australia.

Simon J. Puglisi
School of Computer Science and Information Technology, RMIT University, Victoria 3001, Australia.

Ranjan Sinha
Department of Computer Science and Software Engineering, The University of Melbourne, Victoria 3010, Australia.

Status

Proc. Conf. Database Systems for Advanced Applications, Brisbane, Australia, April 2009, pages 730-744, LNCS volume 5463.

Abstract

Suffix trees and suffix arrays are important data structures for string processing, providing efficient solutions for many applications involving pattern matching. Recent work by Sinha et al. (SIGMOD 2008) addressed the problem of arranging a suffix array on disk so that querying is fast, and showed that the combination of a small trie and a suffix array-like blocked data structure allows queries to be answered many times faster than alternative disk-based suffix trees. A drawback of their LOF-SA structure, and common to all current disk resident suffix tree/array approaches, is that the space requirement of the data structure, though on disk, is large relative to the text -- for the LOF-SA, 13n bytes including the underlying n byte text. In this paper we explore techniques for reducing the space required by the LOF-SA. Experiments show these methods cut the data structure to nearly half its original size, without, for large strings that necessitate on-disk structures, any impact on search times.

Full text

http://dx.doi.org/10.1007/978-3-642-00887-0_63 .