Energy Efficiency for MapReduce Workloads: An In-depth Study

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Provided by: Australian Computer Society
Topic: Data Management
Format: PDF
The energy efficiency has emerged as a crucial optimization goal in data centers. MapReduce has become a popular and even fashionable distributed processing model for parallel computing in data centers. Hadoop is an open-source implementation of MapReduce, which is widely used for short jobs requiring low response time. In this paper, the authors conduct an in-depth study of the energy efficiency for MapReduce workloads. They identify four factors that affect the energy efficiency of MapReduce.
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