Querying Big Data: Bridging Theory and Practice  

作　　者：樊文飞 怀进鹏 

机构地区：[1]School of Informatics, University of Edinburgh,Edinburgh EH8 9AB, U.K. [2]International Research Center on Big Data, Beihang University [3]School of Computer Science and Engineering, Beihang University

出　　处：《Journal of Computer Science & Technology》2014年第5期849-869,共21页计算机科学技术学报（英文版）

基　　金：supported in part by the National Basic Research 973 Program of China under Grant No.2014CB340302;Fan is also supported in part by the National Natural Science Foundation of China under Grant No.61133002;the Guangdong Innovative Research Team Program under Grant No.2011D005;Shenzhen Peacock Program under Grant No.1105100030834361;the Engineering and Physical Sciences Research Council of UK under Grant No.EP/J015377/1;the National Science Foundation of USA under Grant No.III-1302212

摘　　要：Big data introduces challenges to query answering, from theory to practice. A number of questions arise. What queries are ＂tractable＂ on big data？ How can we make big data ＂small＂ so that it is feasible to find exact query answers？When exact answers are beyond reach in practice, what approximation theory can help us strike a balance between the quality of approximate query answers and the costs of computing such answers？ To get sensible query answers in big data,what else do we necessarily do in addition to coping with the size of the data？ This position paper aims to provide an overview of recent advances in the study of querying big data. We propose approaches to tackling these challenging issues,and identify open problems for future research.Big data introduces challenges to query answering, from theory to practice. A number of questions arise. What queries are ＂tractable＂ on big data？ How can we make big data ＂small＂ so that it is feasible to find exact query answers？When exact answers are beyond reach in practice, what approximation theory can help us strike a balance between the quality of approximate query answers and the costs of computing such answers？ To get sensible query answers in big data,what else do we necessarily do in addition to coping with the size of the data？ This position paper aims to provide an overview of recent advances in the study of querying big data. We propose approaches to tackling these challenging issues,and identify open problems for future research.

关 键 词：big data query answering TRACTABILITY APPROXIMATION data quality 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]