期刊名称：International Journal of Grid and Distributed Computing
印刷版ISSN：2005-4262
出版年度：2016
卷号：9
期号：5
页码：229-240
DOI：10.14257/ijgdc.2016.9.5.20
出版社：SERSC
摘要：Big data analytical systems, such as MapReduce, have become main issues for many enterprises and research groups. Currently, multi-query which translated into MapReduce jobs is submitted repeatedly with similar tasks. So, exploiting these similar tasks can offer possibilities to avoid repeated computations of MapReduce jobs. Therefore, many researches have addressed the sharing opportunity to optimize multi- query processing. Consequently, the main goal of this work is to study and compare comprehensively two existed sharing opportunity techniques using predicate-based filters; MRShare and relaxed MRShare. The comparative study has been performed over TPC-H benchmark and confirmed that the relaxed MRShare technique significantly outperforms the MRShare for shared data in terms of predicate-based filters among multi-query.
