TBSAM: An Access Method for Efficient Processing of Statistical Queries

Jaideep Srivastava, Jack S. Eddy Tan, Vincent Y. Lum

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Most research in database access methods has been aimed at providing efficient support for business data processing applications. New database applications such as Computer Aided Design (CAD), Computer Aided Manufacturing (CAM), and Computer Vision, have demonstrated the unsuitability of the popular access methods. This paper targets the domain of Statistical and Scientific Databases, and considers the class of aggregate queries, which are very often encountered in this domain. Such a query is aimed at retrieving some aggregate characteristics of the raw data. In this paper, we present TBSAM, an access method that provides support for the efficient processing of aggregate queries. It is related to the B+-tree, and also possesses the latter’s efficient update properties. Complementing TBSAM is the provision of a grouped update algorithm for minimizing expensive indexed database updates.

Original languageEnglish
Pages (from-to)414-423
Number of pages10
JournalIEEE Transactions on Knowledge and Data Engineering
Volume1
Issue number4
DOIs
Publication statusPublished - Dec 1989

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Keywords

  • Aggregate queries
  • Statistical and Scientific Databases
  • database access methods
  • descriptive and order statistics
  • grouped update algorithm
  • sampling

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

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