Fox, Edward A.Heath, Lenwood S.Chen, Qi-FanDaoud, Amjad M.2013-06-192013-06-191990http://hdl.handle.net/10919/19628We describe the first practical algorithms for finding minimal perfect hash functions that have been used to access very large databases (i.e., having over 1 million keys). This method extends earlier work wherein an 0(n-cubed) algorithm was devised, building upon prior work by Sager that described an 0(n-to the fourth) algorithm. Our first linear expected time algorithm makes use of three key insights: applying randomness whereever possible, ordering our search for hash functions based on the degree of the vertices in a graph that represents word dependencies, and viewing hash value assignment in terms of adding circular patterns of related words to a partially filled disk. Our second algorithm builds functions that are slightly more complex, but does not build a word dependency graph and so approaches the theoretical lower bound on function specification size. While ultimately applicable to a wide variety of data and file access needs, these algorithms have already proven useful in aiding our work in improving the performance of CD-ROM systems and our construction of a Large External Network Database (LEND) for semantic networks and hypertext/hypermedia collections. Virginia Disc One includes a demonstration of a minimal perfect hash function running on a PC to access a 130,198 word list on that CD-ROM. Several other microcomputer, minicomputer, and parallel processor versions and applications of our algorithm have also been developed. Tests including those wiht a French word list of 420,878 entries and a library catalog key set with over 3.8 million keys have shown that our methods work with very large databases.application/pdfenIn CopyrightTechnical reportTR-90-41http://eprints.cs.vt.edu/archive/00000223/01/TR-90-41.pdf