大数据背景下数据仓库架构的现状与展望

Lihua Sun, Mu Hu, K. Ren, Mingming Ren
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引用次数: 6

摘要

与传统的数据仓库应用相比,大数据分析具有数据量大、查询分析复杂的特点。为了设计适合大数据分析的数据仓库架构,本文对当前主流的实现平台——并行数据库、MapReduce以及基于上述两种架构的混合架构进行了分析和总结。并分别介绍了它们的优缺点,描述了大数据分析的各种研究和作者的努力,对未来的研究进行了展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Present Situation and Prospect of Data Warehouse Architecture under the Background of Big Data
Compared with the traditional data warehouse applications, the big data analysis is characterized by its large data size and complex query analysis. In order to design the data warehouse architecture suitable for the big data analysis, this paper analyzes and summarizes the current mainstream implementation platform-parallel database, MapReduce and the hybrid architecture based on the above-mentioned two architectures. Moreover, it presents respectively their advantages and disadvantages and describes various researches of and the author's efforts on the big data analysis to make prospects for the future study.
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