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Digging Database Statistics and Costs Parameters for Distributed Query Processing

  • Nicolaas Ruberg
  • Gabriela Ruberg
  • Marta Mattoso
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2888)

Abstract

Cost parameters and database statistics are the basis of query optimization techniques. However, in distributed and heterogeneous database systems, acquiring and treating information in order to help the optimization process are often tasks of a global query processor, which adapts its functionalities to a specific system architecture. Moreover, this acquisition process involves a large number of parameters and requires customized methods to retrieve data from specific sources. DIG (Distributed Information Gatherer) is a provider of data statistics and query costs that, through an independent and flexible service, aims to support global query optimization processing in distributed and heterogeneous database systems over autonomous data sources. We have developed a DIG prototype and experimented it with specific wrappers for a query middleware on both semi-structured data sources and an object DBMS.

Keywords

Query Processing Cost Parameter Database Statistic Query Optimization Query Execution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Nicolaas Ruberg
    • 1
  • Gabriela Ruberg
    • 1
  • Marta Mattoso
    • 1
  1. 1.Department of Computer ScienceCOPPE/UFRJRio de JaneiroBrazil

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