Ad-hoc aggregate query processing algorithms based on bit-store for query intensive applications in cloud computing

  • Authors:

  • Donghua Yang;Yuqiang Feng;Ye Yuan;Xixian Han;Jinbao Wang;Jianzhong Li

  • Affiliations:

  • The Academy of Fundamental and Interdisciplinary Sciences, Harbin Institute of Technology, Harbin 150001, China and School of Management, Harbin Institute of Technology, Harbin 150001, China;School of Management, Harbin Institute of Technology, Harbin 150001, China;The Academy of Fundamental and Interdisciplinary Sciences, Harbin Institute of Technology, Harbin 150001, China;School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China;School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China;School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China

  • Venue:
  • Future Generation Computer Systems
  • Year:
  • 2013

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Abstract

Ad-hoc Aggregate query is extremely important for query intensive applications in cloud computing which extracts valuable summary information on massive datasets to help the decision-maker make right decisions. Current data storage schemes (row-store and column-store) cannot efficiently answer ad-hoc aggregate query on massive data sets in cloud computing. A new data storage structure (bit vector storage structure, bit-store for short) is proposed in this paper. The paper focuses on proposing ad-hoc aggregate query algorithms based on bit-store. Firstly, the storage model of bit-store including its attribute encoding schemes and bit file organization is introduced. Secondly, different aggregate operations for query processing are presented based on different encoding schemes. Thirdly, cost analysis for different aggregate operations is presented. Finally, the effectiveness and efficiency of the proposed algorithms is showed by the analytical and experimental results.