Implementing MapReduce Applications in Dynamic Cloud Environments

  • Fabrizio MarozzoEmail author
  • Domenico Talia
  • Paolo Trunfio
Part of the Computer Communications and Networks book series (CCN)


MapReduce is one of the most popular programming models for parallel data processing in Cloud environments. Standard MapReduce implementations are based on centralized master-slave architectures that do not cope well with dynamic Cloud environments in which nodes may join and leave the network at high rates. In this chapter we describe P2P-MapReduce, a framework that exploits a peer-to-peer (P2P) model to manage intermittent node participation, master failures, and MapReduce job recovery in a decentralized but effective way. Specifically, the chapter describes the P2P-MapReduce architecture, mechanisms, and implementation and provides an evaluation of its performance. The performance results confirm that P2P-MapReduce ensures a higher level of fault tolerance compared to a centralized implementation of MapReduce.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Fabrizio Marozzo
    • 1
    Email author
  • Domenico Talia
    • 1
  • Paolo Trunfio
    • 1
  1. 1.DIMESUniversity of CalabriaRendeItaly

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