MapReduce optimization using regulated dynamic prioritization

Abstract

We present a system for allocating resources in shared data and compute clusters that improves MapReduce job scheduling in three ways. First, the system uses regulated and user-assigned priorities to offer different service levels to jobs and users over time. Second, the system dynamically adjusts resource allocations to fit the requirements of different… (More)
DOI: 10.1145/1555349.1555384

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