• DocumentCode
    739215
  • Title

    A survey of mapreduce based parallel processing technologies

  • Author

    Lu Jiamin ; Feng Jun

  • Author_Institution
    Coll. of Comput. & Inf., Hehai Univ., Nanjing, China
  • Volume
    11
  • Issue
    14
  • fYear
    2014
  • Firstpage
    146
  • Lastpage
    155
  • Abstract
    Along with the increasing Big Data challenges, the MapReduce based systems are extensively welcomed, because of their remarkable simplicity and scalability. However, from the first day MapReduce is proposed, its argument with parallel DBMSs never stops, as it over-focuses on the scalability but overlooks the efficiency. Accordingly, extended systems are proposed in order to improve the performance on the limited scale clusters. In the meantime, traditional RDBMS technologies like structured data model, transaction, SQL, etc. are also getting more attention. This paper reviews such systems, from Google and also the third parties, trying to indicate the directions for the future research.
  • Keywords
    parallel programming; relational databases; Big Data; Google; MapReduce based parallel processing technology; MapReduce based system; RDBMS technology; parallel DBMS; relational database management system; Computers; Data models; Distributed databases; Google; Parallel processing; Scalability; MapReduce; parallel processing; variants;
  • fLanguage
    English
  • Journal_Title
    Communications, China
  • Publisher
    ieee
  • ISSN
    1673-5447
  • Type

    jour

  • DOI
    10.1109/CC.2014.7085615
  • Filename
    7085615