Reformulating Query Plans for Multidatabase Systems

Abstract

A practical heterogeneous, distributed multidatabase system must answer queries efficiently. Conventional query optimization techniques are not adequate here because these techniques are dependent on the database structure, and rely on limited information which is not sufficient in complicated multidatabase queries. This paper presents an automated approach to reformulating query plans to improve the efficiency of multidatabase queries. This approach uses database abstractions, the knowledge about the contents of databases, to reformulate a query plan into a less expensive but semantically equivalent one. We present two algorithms. The first algorithm reformulates subqueries to individual databases, the second algorithm extends the first one and reformulates the entire query plan. Empirical results show that the reformulations can provide significant savings with minimal overhead. The reformulation approach provides a global reduction in the amount of the intermediate data as well as local optimizations on the subqueries. Semantic query optimization, Query reformulation, Multidatabase queries, SIMS.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1993
Accession Number
ADA278688

Entities

People

  • Chu-nan Hsu
  • Craig Knoblock

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Computer Science
  • Computers
  • Cost Models
  • Cost Reductions
  • Costs
  • Databases
  • Efficiency
  • Information Science
  • Information Systems
  • Knowledge Management
  • Language
  • Latitude
  • Learning
  • Optimization
  • Relational Databases

Fields of Study

  • Computer science
  • Engineering

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Artificial Intelligence
  • Geospatial Intelligence and Artificial Intelligence Analytics