Knowledge and Information Systems

, Volume 41, Issue 2, pp 531–557 | Cite as

Tuple MapReduce and Pangool: an associated implementation

  • Pedro Ferrera
  • Ivan De Prado
  • Eric Palacios
  • Jose Luis Fernandez-MarquezEmail author
  • Giovanna Di Marzo Serugendo
Regular Paper


This paper presents Tuple MapReduce, a new foundational model extending MapReduce with the notion of tuples. Tuple MapReduce allows to bridge the gap between the low-level constructs provided by MapReduce and higher-level needs required by programmers, such as compound records, sorting, or joins. This paper shows as well Pangool, an open-source framework implementing Tuple MapReduce. Pangool eases the design and implementation of applications based on MapReduce and increases their flexibility, still maintaining Hadoop’s performance. Additionally, this paper shows: pseudo-codes for relational joins, rollup, and the PageRank algorithm; a Pangool’s code example; benchmark results comparing Pangool with existing approaches; reports from users of Pangool in industry; and the description of a distributed database exploiting Pangool. These results show that Tuple MapReduce can be used as a direct, better-suited replacement of the MapReduce model in current implementations without the need of modifying key system fundamentals.


MapReduce Hadoop Big Data Distributed systems Scalability 


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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Pedro Ferrera
    • 1
  • Ivan De Prado
    • 1
  • Eric Palacios
    • 1
  • Jose Luis Fernandez-Marquez
    • 2
    Email author
  • Giovanna Di Marzo Serugendo
    • 2
  1. 1.Datasalt Systems S.L.BarcelonaSpain
  2. 2.CUIUniversity of GenevaCarougeSwitzerland

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