Ad Hoc Aggregation Query Processing Algorithms Based on Bit-Store in Data Intensive Cloud

Donghua Yang, Jianzhong Li, Xixian Han, Jinbao Wang
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引用次数: 2

Abstract

Ad-hoc Aggregation query is extremely important for data-intensive applications in the cloud which extracts valuable summary information on massive datasets to help decision-maker make right decisions. Current data storage schemes (row-store and column-store) cannot efficiently answer ad-hoc aggregation on massive data sets in the cloud. A new data storage structure (bit vector storage structure, bit-store for short) is proposed in the paper, which partitions tables vertically by bit position and stores all bit values in the same positions into a separate bit file. This paper focuses on proposing ad-hoc aggregation query algorithms based on bit-store. Firstly, the storage model of bit-store including its attribute encoding and bit file organization is introduced. Then, the implementation of different aggregation operations using different encoding schemes is presented. Finally, analytical and experimental results show the effectiveness and efficiency of the proposed approach.
数据密集型云中基于位存储的自组织聚合查询处理算法
Ad-hoc聚合查询对于云中的数据密集型应用程序非常重要,它可以从海量数据集中提取有价值的汇总信息,帮助决策者做出正确的决策。当前的数据存储方案(行存储和列存储)不能有效地响应云中海量数据集的临时聚合。本文提出了一种新的数据存储结构(bit - vector storage structure,简称bit-store),它按位垂直划分表,并将相同位置的所有位值存储在一个单独的位文件中。提出了一种基于位存储的自组织聚合查询算法。首先,介绍了位存储的存储模型,包括其属性编码和位文件组织。然后,给出了使用不同编码方案实现不同聚合操作的方法。最后,分析和实验结果表明了该方法的有效性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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