• DocumentCode
    2182313
  • Title

    Partitioning real-time ETL workflows

  • Author

    Simitsis, Alkis ; Gupta, Chetan ; Wang, Song ; Dayal, Umeshwar

  • Author_Institution
    HP Labs., Palo Alto, CA, USA
  • fYear
    2010
  • fDate
    1-6 March 2010
  • Firstpage
    159
  • Lastpage
    162
  • Abstract
    Many organizations are aiming to move away from traditional batch processing ETL to real-time ETL (RT-ETL). This move is motivated by a need to analyze and take decisions on as fresh a data as possible. The RT-ETL engines operate on the abstraction of data flow executed on parallel architectures. For high throughput and low response times, there is a need for partitioning the data over the large number of nodes in the engine. In this paper, we consider the problem of partitioning realtime ETL flows and we propose a high level architecture for that.
  • Keywords
    batch processing (computers); data flow computing; workflow management software; batch processing; data flow execution; high level architecture; parallel architectures; real-time ETL workflows; Costs; Data warehouses; Decision making; Delay; Design optimization; Fault tolerance; Humans; Maintenance; Merging; Real time systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering Workshops (ICDEW), 2010 IEEE 26th International Conference on
  • Conference_Location
    Long Beach, CA
  • Print_ISBN
    978-1-4244-6522-4
  • Electronic_ISBN
    978-1-4244-6521-7
  • Type

    conf

  • DOI
    10.1109/ICDEW.2010.5452754
  • Filename
    5452754