Abstract
The multi-tenant jobs scheduling problem based on MapReduce framework has become more and more significant in contemporary society. Existing scheduling approach or algorithm no longer fit well in scenario that numerous jobs were submitted by multiple users at the same time. Therefore, taken enlarging jobs’ throughput for MapReduce into account, we firstly propose an MRScheduling which focuses on meeting job’s respective deadline. Considering the various parameters which are related to job execution time of a MapReduce’s job, we present a simply time-cost model, for the aim that quantifying the number of job’s assigned map slots and reduce slots. Then, an MRScheduling algorithm is discussed in details. Finally, we perform our approach on both real data and synthetic data on real distributed cluster to verify its effectiveness and efficiency.
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