Microprocessor Assisted Tuple Access, Decompression and Assembly for Statistical Database Systems.

@inproceedings{DBLP:conf/vldb/Hawthorn82,
  author    = {Paula B. Hawthorn},
  title     = {Microprocessor Assisted Tuple Access, Decompression and Assembly
               for Statistical Database Systems},
  booktitle = {Eigth International Conference on Very Large Data Bases, September
               8-10, 1982, Mexico City, Mexico, Proceedings},
  publisher = {Morgan Kaufmann},
  year      = {1982},
  isbn      = {0-934613-14-1},
  pages     = {223-233},
  ee        = {db/conf/vldb/Hawthorn82.html},
  crossref  = {DBLP:conf/vldb/82},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

A methodology is formulated for determining if a microprocessor-based specialized system is practical for the solution of a problem in an application. This methodology is followed in the description and justification of of a back-end system for use with a statistical database system. The functions to be performed by the back-end system include those related to attribute partitioning, compression, and data access. It is shown that the system designed (the Microprocessor Assist System) will be cost-effective in increasing the performance of a statistical data management system.

Additionally, a category-based access method is introduced. This access method is a variation of B-trees, but its use results in smaller indices.

Copyright © 1982 by the 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 the permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.

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Referenced by

1. Mostafa A. Bassiouni, N. Ranganathan, Amar Mukherjee: Software and Hardware Enhancement of Arithmetic Coding. SSDBM 1988: 120-132
2. Matthias Jarke, Jürgen Koch: Query Optimization in Database Systems. ACM Comput. Surv. 16(2): 111-152(1984)
3. Hamid Farsi, John Tartar: A Relational Database Machine for Efficient Processing of Statistical Queries. SSDBM 1983: 64-72
4. Paul Chan, Susan J. Eggers, Fredric C. Gey, Harvard Holmes, Peter Kreps, John McCarthy, Deane Merrill, Frank Olken, Arie Shoshani, Harry K. T. Wong: Statistical Data Management Research at Lawrence Berkeley Laboratory. SSDBM 1983: 273-279
5. Arie Shoshani: Statistical Databases: Characteristics, Problems, and some Solutions. VLDB 1982: 208-222