• DocumentCode
    140924
  • Title

    DBDesigner: A customizable physical design tool for Vertica Analytic Database

  • Author

    Varadarajan, Ravi ; Bharathan, V. ; Cary, A. ; Dave, Jaimin ; Bodagala, S.

  • Author_Institution
    Vertica Syst. Co., Hewlett Packard, Cambridge, MA, USA
  • fYear
    2014
  • fDate
    March 31 2014-April 4 2014
  • Firstpage
    1084
  • Lastpage
    1095
  • Abstract
    In this paper, we present Vertica´s customizable physical design tool, called the DBDesigner (DBD), that produces designs optimized for various scenarios and applications. For a given workload and space budget, DBD automatically recommends a physical design that optimizes query performance, storage footprint, fault tolerance and recovery to meet different customer requirements. Vertica is a distributed, massively parallel columnar database that physically organizes data into projections. Projections are attribute subsets from one or more tables with tuples sorted by one or more attributes, that are replicated or segmented (distributed) on cluster nodes. The key challenges involved in projection design are picking appropriate column sets, sort orders, cluster data distributions and column encodings. To achieve the desired trade-off between query performance and storage footprint, DBD operates under three different design policies: (a) load-optimized, (b) query-optimized or (c) balanced. These policies indirectly control the number of projections proposed and queries optimized to achieve the desired balance. To cater to query workloads that evolve over time, DBD also operates in a comprehensive and incremental design mode. In addition, DBD lets users override specific features of projection design based on their intimate knowledge about the data and query workloads. We present the complete physical design algorithm, describing in detail how projection candidates are efficiently explored and evaluated using optimizer´s cost and benefit model. Our experimental results show that DBD produces good physical designs that satisfy a variety of customer use cases.
  • Keywords
    parallel databases; query processing; DBD; DBDesigner tool; Vertica analytic database; balanced design policy; customer requirements; customer use case; customizable physical design tool; distributed massively parallel columnar database; fault recovery; fault tolerance; incremental design mode; load-optimized design policy; projection candidates; projection design; query performance; query workloads; query-optimized design policy; storage footprint; Algorithm design and analysis; Cities and towns; Distributed databases; Encoding; Fault tolerance; Fault tolerant systems;
  • 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.2014.6816725
  • Filename
    6816725