Natjam: Eviction Policies For Supporting Priorities and Deadlines in Mapreduce Clusters
Author(s)
Gupta, Indranil
Cho, Brian
Rahman, Muntasir Raihan
Chajed, Tej
Abad, Cristina L.
Roberts, Nathan
Lin, Philbert
Issue Date
2013-06-06
Keyword(s)
Cloud Computing
Mapreduce
Scheduling
Date of Ingest
2013-06-07T16:53:22Z
Abstract
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) 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. 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! commercial cluster, using both synthetic traces as well as Hadoop cluster traces we obtained from Yahoo!. Our results reveal that Natjam incurs overheads of under 7%. Under real Hadoop workloads, Natjam performs better than existing techniques.
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