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CLQLMRS: improving cache locality in MapReduce job...
Journal article

CLQLMRS: improving cache locality in MapReduce job scheduling using Q-learning

Abstract

Scheduling of MapReduce jobs is an integral part of Hadoop and effective job scheduling has a direct impact on Hadoop performance. Data locality is one of the most important factors to be considered in order to improve efficiency, as it affects data transmission through the system. A number of researchers have suggested approaches for improving data locality, but few have considered cache locality. In this paper, we present a state-of-the-art …

Authors

Ghazali R; Adabi S; Rezaee A; Down DG; Movaghar A

Journal

Journal of Cloud Computing, Vol. 11, No. 1,

Publisher

Springer Nature

DOI

10.1186/s13677-022-00322-5

ISSN

2192-113X