一种云环境下的大数据Top-K查询方法  

Method for Top-K Query on Big Data in Cloud

作　　者：慈祥[1] 马友忠[1] 孟小峰[1] 

机构地区：[1]中国人民大学信息学院,北京100872

出　　处：《软件学报》2014年第4期813-825,共13页Journal of Software

基　　金：国家自然科学基金(61379050;91224008);国家高技术研究发展计划(863)(2013AA013204);高等学校博士学科点专项科研基金(20130004130001)

摘　　要：Top-K查询在搜索引擎、电子商务等领域有着广泛的应用.Top-K查询从海量数据中返回最符合用户需求的前K个结果,主要目的是消除信息过载带来的负面影响.大数据背景下的Top-K查询,给数据管理和分析等方面带来新的挑战.结合MapReduce的特点,从数据划分、数据筛选等方面对云环境下的大数据Top-K查询问题进行深入研究.实验结果表明,该方法具有良好的性能和扩展性.Top-K query has been widely used in lots of modern applications such as search engine and e-commerce. Top-K query returns the most relative results for user from massive data, and its main purpose is to eliminate the negative effect of information overload. Top-K query on big data has brought new challenges to data management and analysis. In light of features of MapReduce, this paper presents an in-depth study of Top-K query on big data from the perspective of data partitioning and data filtering. Experimental results show that the proposed approaches have better performance and scalability.

关 键 词：TOP-K查询 云计算 MAPREDUCE 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]