Relational Database Organization Based on Views and Fragments

  • Günther Pernul
  • Kamalakar Karlapalem
  • Shamkant B. Navathe


Traditionally data is organized at the logical level in relational databases on the basis of its semantics. But there are more abstractions of the real world to be represented. A part of this missing semantics is that of views. We include views as an integral part of the data model. After defining views on a relational scheme, we present a methodology to decompose the relations of this scheme into a set of disjoint fragments. One or more fragments represent a view. Then these fragments and not the relations of the relational scheme are materialized. We further develop a scheme for maintaining the consistency of a database made up of fragments (which include attributes of the left or right side of a split functional dependencies) of a non-3NF relation by introducing the concept of update clusters and virtual attributes. The methodology results in a database design where the database operations access less amount of irrelevant data in comparison to the design where the base relations are materialized. We briefly discuss the applicability of this methodology in designing databases based on centralized, distributed, parallel database environments and for secure database systems.


Global Scheme Relational Scheme Local Dependency Selection Attribute Database Design 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [Ceri83]
    Ceri S, Navathe S. B, Wiederhold G,: Distribution Design of Logical Database Schemes, IEEE ToSE, SE-9, July 1983.Google Scholar
  2. [Chan80]
    Chang, Cheng: A methodology for structured database decomposition, IEEE ToSE, vol. SE-6, 2, 1980.Google Scholar
  3. [Clay83]
    B. G. Claybrook. Using Views in a Multilevel Secure Database Management System. Proc. IEEE Symposium on Research in Security and Privacy, 1983.Google Scholar
  4. [Cope88]
    Copeland, G., Alexander, W., Boughter, E., and Keller, T. Data Placemnt in Bubba, Proc. of ACM SIGMOD, pages 99–108, May 1988.Google Scholar
  5. [DeBr86]
    De Bra, P: Horizontal Decompositions based on Functional Dependency Set Implications, Lecture Notes in Computer Science, ICDT86, Springer-Verlag, 1986.Google Scholar
  6. [Eich88]
    Eichler B.: Implementation of a prototype for database design according to user views, Master thesis, University of Vienna, 1988.Google Scholar
  7. [GaWu88]
    C. Garvey, A. Wu. ASD_Views. Proc. IEEE Symposium on Research in Security and Privacy, 1988.Google Scholar
  8. [LuDe90]
    T. F. Lunt, D. E. Denning, R. R. Schell, M. Heckman, W. R. Shockley. The SeaView Security Model, IEEE Trans. on Software Engineering, vol. 16, no. 6, June 1990.Google Scholar
  9. [Nava84]
    Navathe, S. B., Ceri, S., Wiederhold G., Dou, J.:Vertical Partitioning Algorithms for Database Design, ACM TODS, Vol. 9, No 4, Dec. 1984.Google Scholar
  10. [Nava90]
    Navathe, S. B., Ra, M., Varadarajan, R., Karlapalem, K., Sreewastav, K.: A Mixed Partitioning Methodology for Distributed Database Design, Technical Report OF-CIS TR-90–17, University of Florida, Feb. 1990.Google Scholar
  11. [Pern90]
    Pernul, G., Moser P., Luef, G.: Database Design according to user views, Parbase-90, Int. Conf. on databases and parallel architectures and their applications, IEEE Computer Science Press, 1990.Google Scholar
  12. [StTh90]
    P. D. Stachour, B. Thuraisingham. Design of LDV: A multilevel secure relational database management system. IEEE Trans. on Knowledge and Data Engineering, vol. 2, no. 2, June 1990.Google Scholar

Copyright information

© Springer-Verlag Wien 1991

Authors and Affiliations

  • Günther Pernul
    • 1
  • Kamalakar Karlapalem
    • 1
  • Shamkant B. Navathe
    • 1
  1. 1.College Of ComputingGeorgia Institute Of TechnologyAtlantaUSA

Personalised recommendations