Improvement and implementation of job scheduling algorithm for MapReduce in Hadoop platform
Jie Huijuan College of Applied Science and technology, Hainan University
Based on the MapReduce architecture of Hadoop, this paper analyzes the existing three job scheduling algorithms, and proposes a fair scheduling algorithm (FSVQ) based on variable length queue for the current algorithm without considering the disadvantage of server load status and data locality, and the algorithm analyzes the idle node rate, And it satisfies the consideration of data locality by adopting the method of waiting. Experiments show that the algorithm can increase the efficiency of server cluster and reduce network delay, which has practical application significance.
Improvement and implementation of job scheduling algorithm for MapReduce in Hadoop platform
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