• DocumentCode
    897464
  • Title

    Applying segmented right-deep trees to pipelining multiple hash joins

  • Author

    Chen, Ming-Syan ; Lo, Mingling ; Yu, Philip S. ; Young, Honesty C.

  • Author_Institution
    IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
  • Volume
    7
  • Issue
    4
  • fYear
    1995
  • fDate
    8/1/1995 12:00:00 AM
  • Firstpage
    656
  • Lastpage
    668
  • Abstract
    The pipelined execution of multijoin queries in a multiprocessor-based database system is explored in this paper. Using hash-based joins, multiple joins can be pipelined so that the early results from a join, before the whole join is completed, are sent to the next join for processing. The execution of a query is usually denoted by a query execution tree. To improve the execution of pipelined hash joins, an innovative approach to query execution tree selection is proposed to exploit segmented right-deep trees, which are bushy trees of right-deep subtrees. We first derive an analytical model for the execution of a pipeline segment, and then, in the light of the model, we develop heuristic schemes to determine the query execution plan based on a segmented right-deep tree so that the query can be efficiently executed. As shown by our simulation, the proposed approach, without incurring additional overhead on plan execution, possesses more flexibility in query plan generation, and can lead to query plans of better performance than those achievable by the previous schemes using right-deep trees
  • Keywords
    database machines; database theory; distributed databases; parallel processing; pipeline processing; query processing; software performance evaluation; tree data structures; bushy trees; flexibility; heuristic schemes; multijoin queries; multiple hash joins; multiprocessor-based database system; parallel query processing; performance; pipelined execution; query execution plan; query execution tree selection; query plan generation; segmented right-deep trees; simulation; Analytical models; Artificial intelligence; Database systems; Graphics; Industrial relations; Pipeline processing; Query processing; Relational databases; Solid modeling; Spatial databases;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/69.404036
  • Filename
    404036