Multi User Scheduling Strategy Research based on Mapreduce Cluster
Yu Liping, Yang Li-shen, Liang Zhu · Journal of Convergence Information Technology · 2013
With the development of Internet, it brings the data rapid expansion and the numbers of file continue to increase. More and more enterprises begin to use cluster computing system with data intensive, for example Hadoop, Dryad. Hadoop cluster can reduce the unnecessary expenses for independent cluster through sharing of the large data sets resources between multiple users. On the basis of MapReduce cluster, this paper analyses the strategy of job scheduling on the platform of Hadoop, and introduces an improved scheduling strategy in detail. Finally, we verify the feasibility and superiority of the improved strategy through the experiment.