• DocumentCode
    113563
  • Title

    Performance analysis of Hadoop MapReduce on an OpenNebula cloud with KVM and OpenVZ virtualizations

  • Author

    Magalhaes Vasconcelos, Pedro Roger ; Azevedo de Araujo Freitas, Gisele

  • Author_Institution
    Fed. Univ. of Ceara, Ceará, Brazil
  • fYear
    2014
  • fDate
    8-10 Dec. 2014
  • Firstpage
    471
  • Lastpage
    476
  • Abstract
    Cloud computing provides access to a set of resources such as virtual machines, storage and network as services. In this context, virtualization has been used as an platform for resource-intensive applications, like Hadoop, as it has brought features like server consolidation, scalability and better resources usage. OpenVZ and KVM are very popular and widely used virtualization platforms with distinct virtualization modes: containet-based and full-virtualization. In this work, we conducted benchmarks to measure the performance of a Hadoop cluster deployed on OpenNebula clouds with KVM and OpenVZ. Our results show that OpenVZ performs better than KVM in the CPU and I/O reading benchmarks. KVM achieves better performance in the I/O writing benchmarks.
  • Keywords
    cloud computing; data handling; operating system kernels; resource allocation; virtual machines; virtualisation; CPU; Hadoop MapReduce; Hadoop cluster; I/O reading benchmarks; I/O writing benchmarks; KVM; OpenNebula cloud computing; OpenVZ virtualizations; containet-based virtualization; kernel-based virtual machine; performance analysis; resource-intensive applications; Benchmark testing; Cloud computing; Hardware; Servers; Virtual machine monitors; Virtual machining; Virtualization; Big Data; KVM; MapReduce; OpenVZ; cloud computing; virtualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet Technology and Secured Transactions (ICITST), 2014 9th International Conference for
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1109/ICITST.2014.7038858
  • Filename
    7038858