• DocumentCode
    511173
  • Title

    Research on Materialized View Selection Algorithm in Data Warehouse

  • Author

    Lijuan, Zhou ; Xuebin, Ge ; Linshuang, Wang ; Qian, Shi

  • Author_Institution
    Inf. Eng. Coll., Capital Normal Univ., Beijing, China
  • Volume
    2
  • fYear
    2009
  • fDate
    25-27 Dec. 2009
  • Firstpage
    326
  • Lastpage
    329
  • Abstract
    In view of some deficiencies which traditional static materialized view selection algorithms have, the paper brings forward an efficient materialized view selection adjustment algorithm which could overcome some deficiencies such as large storage, long running time and different querying probability. Besides, the algorithm can be carried out simultaneously from source data to data warehouse immediately when the changes occur in source database. It integrates some advantages such as PBS, IGA and so on, performances of the algorithm has been proved in experiment. The efficient materialized view selection adjustment algorithm reduces search spaces and shortens running time. Most of all, the algorithm considers materialized views mutual relations in influencing view benefit. Consequently, the algorithm can be dynamically adjusted online and attains anticipative purpose. It makes some contributions for materialized view selection.
  • Keywords
    data warehouses; query processing; IGA; PBS; data warehouse; efficient materialized view selection adjustment algorithm; querying probability; Algorithm design and analysis; Application software; Computer applications; Costs; Data analysis; Data engineering; Data warehouses; Greedy algorithms; Heuristic algorithms; Material storage; MVA; data warehouse; materialized view; query probability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-0-7695-3930-0
  • Electronic_ISBN
    978-1-4244-5423-5
  • Type

    conf

  • DOI
    10.1109/IFCSTA.2009.202
  • Filename
    5384573