This paper presents Natjam, a system that supports arbitrary job priorities, hard real-time scheduling, and efficient preemption for Mapreduce clusters that are resource-constrained. Our contributions include: i) exploration and evaluation of smart eviction policies for jobs and for tasks, based on resource usage, task runtime, and job deadlines; and ii) a work-conserving task preemption mechanism for Mapreduce. We incorporated Natjam into the Hadoop YARN scheduler framework (in Hadoop 0.23). We present experiments from deployments on a test cluster, Emulab and a Yahoo! Inc. commercial cluster, using both synthetic workloads as well as Hadoop cluster traces from Yahoo!. Our results reveal that Natjam incurs overheads as low as 7%, and is preferable to existing approaches.<\/p>\n","protected":false},"excerpt":{"rendered":"
This paper presents Natjam, a system that supports arbitrary job priorities, hard real-time scheduling, and efficient preemption for Mapreduce clusters that are resource-constrained. 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