计算机工程与应用2016，Vol.52Issue(22)：22-25,4.DOI:10.3778/j.issn.1002-8331.1604-0388
Hadoop云平台MapReduce模型优化研究
Research on optimized MapReduce model of Hadoop cloud plat-form
摘要
Abstract
Sequential control of running mechanism of MapReduce model on Hadoop platform can lead to waste of com-puting resources. From the perspective of the fine-grained parallel data processing of each node, combined with multi-threads technique of Java shared memory, this paper optimizes MapReduce model and puts forward a MapReduce+OpenMP framework. This model is a distributed and parallel computing architecture based on Hadoop cloud platform, which combines computing resources of coarse and fine granularity. After programming and realizing on the GPS trajectory data of the taxi in the Hadoop distributed cluster environment, the results show that this distributed parallel computing model can really improve the computing efficiency of processing big data set, and it is an effective optimization and improvement to the MapReduce model of big data processing.关键词
Hadoop/MapReduce/OpenMP/分布式/并行Key words
Hadoop/MapReduce/OpenMP/distributed/parallel分类
信息技术与安全科学引用本文复制引用
张红,王晓明,曹洁,马彦宏,郭义戎,王慜..Hadoop云平台MapReduce模型优化研究[J].计算机工程与应用,2016,52(22):22-25,4.基金项目
甘肃省自然科学基金（No.148RJZA019）；甘肃省科技支撑计划基金（No.1304GKCA023）。 （）
