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MapReduce Scheduler by Characterizing Performance Interference
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DOI：10.1109/CC.2016.7733049.png)
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摘要
En 中文
Recently, virtualization has become more and more important in the cloud computing to support efficient flexible resource provisioning. However, performance interference among virtual machines (VMs) has become a challenge which may affect the effectiveness of resource provisioning. In a virtual cluster which runs the MapReduce applications, the performance interference can also affect the performance of the Map and Reduce tasks and thus cause a performance degradation of the MapReduce job. Accordingly, this paper presents a MapReduce scheduling framework to mitigate this performance degradation caused by the performance interference. The framework includes a performance interference prediction module and an interference aware scheduling algorithm. To verify its effectiveness, we have done a set of experiments on a 24-node virtual MapReduce cluster. The experiments illustrate that the proposed framework can achieve a performance improvement in the virtualized environment compared with other MapReduce schedulers.
Keyword:
MapReduce
scheduler
performance interference
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