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• W1567254235 abstract "Hadoop task schedulers like Fair Share and Capacity have been specially designed to share hardware resources among multiple organizations. The Capacity Scheduler provides a complex set of parameters to give fine control over resource allocation of a shared MapReduce cluster. Administrators and users often run into performance problems because they do not understand the performance influence of the task scheduler parameters on MapReduce workloads. Interaction between parameter settings is particularly problematic.In this paper, we implemented a Capacity Scheduler simulator component, integrated it into an existing simulator and then validated the simulator with small test cases, consisting of standard benchmark sort programs. We then studied the impact of Capacity Scheduler parameters on different MapReduce workload submission patterns with a more complex set of benchmark programs. Among other results, we found maxCapacity and minUser-LimitPCT to be influential parameters suggested by previous work and that using separate queues for short and long jobs provides the best performance in terms of response ratio, execution time and makespan compared to submitting both types of jobs in the same queue." @default.
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• W1567254235 date "2014-11-03" @default.
• W1567254235 modified "2023-09-26" @default.
• W1567254235 title "Simulation and performance evaluation of the hadoop capacity scheduler" @default.
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