Non-work-conserving effects in MapReduce: diffusion limit and criticality

@inproceedings{Tan2014NonworkconservingEI,
  title={Non-work-conserving effects in MapReduce: diffusion limit and criticality},
  author={Jian Tan and Yandong Wang and Weikuan Yu and Li Zhang},
  booktitle={SIGMETRICS},
  year={2014}
}
Sequentially arriving jobs share a MapReduce cluster, each desiring a fair allocation of computing resources to serve its associated map and reduce tasks. The model of such a system consists of a processor sharing queue for the MapTasks and a multi-server queue for the ReduceTasks. These two queues are dependent through a constraint that the input data of each ReduceTask are fetched from the intermediate data generated by the MapTasks belonging to the same job. A more generalized form of… CONTINUE READING