Intelligent agents based improved map-reduce method for multiple databases

M. Muntean, Raul Boldea
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引用次数: 1

Abstract

Big Data became in the last years a key basis of competition and innovation. But it is difficult to process the whole amount of data using traditional database and software techniques. To overcome this issue, search methods were developed to faster achieve information from large databases. In this paper, we propose an approach based on the use of agent technology and big data concept in order to improve the process time of Map-Reduce programming model. Finally, the approach is validated by a case study in which we achieved a 1.7x speedup comparing to traditional Map-Reduce technique for 26Mb of data.
基于智能代理的改进多数据库地图约简方法
过去几年,大数据成为竞争和创新的关键基础。但是利用传统的数据库和软件技术很难处理全部的数据量。为了克服这个问题,人们开发了搜索方法来更快地从大型数据库中获取信息。为了提高Map-Reduce编程模型的处理时间,本文提出了一种基于agent技术和大数据概念的方法。最后,通过一个案例研究验证了该方法,在26Mb数据下,与传统Map-Reduce技术相比,我们实现了1.7倍的加速。
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