基于dbaas的大数据处理协同系统设计

Yean-Woo Jung, Jong-Yong Lee, Kyedong Jung
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引用次数: 0

摘要

随着近年来云计算的发展,大数据处理和企业之间的协作正在成为IT行业的新范式。在SNS等实时产生大量数据的环境中,大数据处理技术在提取有效数据方面非常有用。MapReduce是在大数据提取中使用这种编程模型的一个很好的例子。随着企业间协作的日益频繁,新旧信息存储系统的集成带来了数据的重复和异构问题。这些问题的出现是因为不同公司的现有数据库存在差异。然而,这些问题可以通过实现MapReduce技术来消除。本文提出了一个基于数据库即服务(Database as a Service, DBaaS)的协作系统,以解决企业间协作中的数据集成问题。该系统可用于结构化和非结构化数据,减少了数据集成的开销。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Design of DBaaS-Based Collaboration System for Big Data Processing
With the recent growth in cloud computing, big data processing and collaboration between businesses are emerging as new paradigms in the IT industry. In an environment where a large amount of data is generated in real time, such as SNS, big data processing techniques are useful in extracting the valid data. MapReduce is a good example of such a programming model used in big data extraction. With the growing collaboration between companies, problems of duplication and heterogeneity among data due to the integration of old and new information storage systems have arisen. These problems arise because of the differences in existing databases across the various companies. However, these problems can be negated by implementing the MapReduce technique. This paper proposes a collaboration system based on Database as a Service, or DBaaS, to solve problems in data integration for collaboration between companies. The proposed system can reduce the overhead in data integration, while being applied to structured and unstructured data.
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