• DocumentCode
    1444658
  • Title

    Algebraic identities and query optimization in a parametric model for relational temporal databases

  • Author

    Gadia, Shashi K. ; Nair, Sunil S.

  • Author_Institution
    Dept. of Comput. Sci., Iowa State Univ., Ames, IA, USA
  • Volume
    10
  • Issue
    5
  • fYear
    1998
  • Firstpage
    793
  • Lastpage
    807
  • Abstract
    This paper presents algebraic identities and algebraic query optimization for a parametric model for temporal databases. The parametric model has several features not present in the classical model. In this model, a key is explicitly designated with a relation, and an operator is available to change the key. The algebra for the parametric model is three-sorted; it includes 1) relational expressions that evaluate to relations, 2) domain expressions that evaluate to time domains, and 3) Boolean expressions that evaluate to TRUE or FALSE. The identities in the parametric model are classified as weak identities and strong identities. Weak identities in this model are largely counterparts of the identities in classical relational databases. Rather than establishing weak identities from scratch, a meta inference mechanism, introduced in the paper, allows weak identities to be induced from their respective classical counterpart. On the other hand, the strong identities will be established from scratch. An algorithm is presented for algebraic optimization to transform a query to an equivalent query that will execute more efficiently
  • Keywords
    database theory; query processing; relational databases; temporal databases; algebraic query optimization; parametric model; query optimization; relational temporal databases; temporal databases; Algebra; Computer Society; Indexes; Inference algorithms; Inference mechanisms; Parametric statistics; Query processing; Relational databases; Spatial databases; Transaction databases;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/69.729733
  • Filename
    729733