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Building an Efficient Hadoop Workflow Engine Using BPEL

  • Jie Liu
  • Qiyuan Li
  • Feng Zhu
  • Jun Wei
  • Dan Ye
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8295)

Abstract

Big data processing and analysis techniques can guide enterprises to make correct decisions, and will play an important role in the enterprise business process. The Hadoop platform has become the basis of big data processing and analysis. To satisfy the needs of enterprises to develop data-intensive workflow based on Hadoop and integrate them into existing business processes, we build a Hadoop workflow engine named Pony based on BPEL model. The mapping method from Hadoop Workflow to BPEL process in three levels of the semantic model, deployment model, and execution model is presented. Pony uses a matured and stable BPEL engine to orchestrate Hadoop services. Pony implements a Hadoop job scheduler to collaborate with a BPEL engine to online schedule multiple workflows at runtime. This paper describes the design and implementation of Pony, and the experiment results demonstrate Pony can provide improved performance.

Keywords

MapReduce Hadoop workflow BPEL Data intensive computing Service oriented architecture 

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Jie Liu
    • 1
  • Qiyuan Li
    • 1
  • Feng Zhu
    • 1
  • Jun Wei
    • 1
  • Dan Ye
    • 1
  1. 1.Technology Center of Software Engineering, Institute of SoftwareChinese Academy of SciencesBeijingChina

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