• DocumentCode
    1122671
  • Title

    View adaptation in the fragment-based approach

  • Author

    Bellahsene, Zohra

  • Author_Institution
    CNRS, Univ. Montpellier II, France
  • Volume
    16
  • Issue
    11
  • fYear
    2004
  • Firstpage
    1441
  • Lastpage
    1455
  • Abstract
    View adaptation relies on adapting a set of materialized views in response to schema changes of source relations and/or after view redefinition. Recently, several view selection methods that are based on materializing fragments of the view rather than the whole view have been proposed. We call this approach the fragment-based approach. This paper presents a view adaptation method in the fragment-based approach, which is aimed at exploiting the opportunities to share not only materialized data, but also computation between the different views. In order to do this, the views are modeled using the so-called multiview materialization graph, which represents the views as a bipartite directed acyclic graph whose nodes are operations and fragments of the views. Then, the adaptation is performed regarding all materialized views and not solely the old materialization of the view. However, the data independence is preserved for the views that are not affected by the change. On the contrary, in related work, the adaptation technique is based solely on the old materialization of the same view. We studied the impact of the fragmentation on the adaptation techniques and showed the advantages and drawbacks of this approach.
  • Keywords
    data warehouses; directed graphs; query processing; synchronisation; bipartite directed acyclic graph; data independence; data warehouse evolution; fragment-based approach; materialized view; multiview materialization graph; source relation; view adaptation; view redefinition; view selection method; view synchronization; Computer Society; Data warehouses; Warehousing; 65; Index Terms- Materialized views; data warehouse evolution; view adaptation; view redefinition; view synchronization.;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/TKDE.2004.79
  • Filename
    1339269