• DocumentCode
    140990
  • Title

    HOPE: Iterative and interactive database partitioning for OLTP workloads

  • Author

    Yu Cao ; Xiaoyan Guo ; Baoyao Zhou ; Todd, Simon

  • Author_Institution
    EMC Labs., USA
  • fYear
    2014
  • fDate
    March 31 2014-April 4 2014
  • Firstpage
    1274
  • Lastpage
    1277
  • Abstract
    This paper demonstrates HOPE, an efficient and effective database partitioning system that is designed for OLTP workloads. HOPE is built on top of a novel tuple-group based database partitioning model, which is able to minimize the number of distributed transactions as well as the extent of partition and workload skews during the workload execution. HOPE conducts the partitioning in an iterative manner in order to achieve better partitioning quality, save the user´s time spent on partitioning design and increase its application scenes. HOPE is also highly interactive, as it provides rich opportunities for the user to help it further improve the partitioning quality by passing expertise and indirect domain knowledge.
  • Keywords
    transaction processing; HOPE system; OLTP workloads; database partitioning system; distributed transactions; domain knowledge; hypergraph based OLTP database partitioning engine; online transaction processing; partitioning design; partitioning quality; tuple-group based database partitioning model; workload execution; Computer architecture; Database systems; Distributed databases; Partitioning algorithms; Scalability; Throughput;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering (ICDE), 2014 IEEE 30th International Conference on
  • Conference_Location
    Chicago, IL
  • Type

    conf

  • DOI
    10.1109/ICDE.2014.6816759
  • Filename
    6816759