• DocumentCode
    2437086
  • Title

    Progressive Hash-Merge Join Algorithm

  • Author

    Chen, Gang ; Li, Guohui ; Yang, Bing ; Tang, Xianghong ; Chen, Hui

  • Volume
    2
  • fYear
    2008
  • fDate
    19-20 Dec. 2008
  • Firstpage
    117
  • Lastpage
    121
  • Abstract
    In data streams or Web scenario at highly variable and unpredictable rates, most fast join algorithms to date rely upon shifting to external join stage as soon as possible when blocked in order to enhance efficiency. But they have trouble with the following issues: the limit of external join and practical executing time. Classical progressive two-way joining technique based on hash, however, fail to deliver acceptable performance in such a scenario where relatively short intermittent delay exists in the gross. We propose a new progressive join algorithm based on hash-merge for improving the query response time, separating one merging transaction into multi-subtask, whose transacting sizes rest with the interval time. Additionally, a refined replacement selection tree and a fine granularity timestamp are applied, which help to make use of finite memory and ensure correctness respectively. Theory and experimental results show that our technique delivers results significantly fast under both reliable and unreliable network.
  • Keywords
    Internet; merging; query processing; relational databases; storage management; tree data structures; Web scenario; data stream; fine granularity timestamp; finite memory use; progressive hash-merge join algorithm; query response time; refined replacement selection tree; Computational intelligence; Computer industry; Computer science; Conferences; Delay; Merging; Query processing; Scheduling algorithm; Software algorithms; Telecommunication traffic; external join; hash-merge; non-blocking; replacement selection tree; unreliable network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3490-9
  • Type

    conf

  • DOI
    10.1109/PACIIA.2008.234
  • Filename
    4756747