大数据基础理论与系统关键技术浅析

A Brief Review of Theory and System Technologies for Big Data

【目的】本文主要就大数据基础理论及系统相关研究背景、技术架构和关键技术展开介绍,并结合技术发展趋势提出未来研究和技术发展方向。【方法】本文在简要介绍大数据处理基础理论的基础上,从面向数据并行的大数据处理技术、RDF(Resource Description Framework)图数据的查询与匹配、大数据分析技术三个方面简要介绍了大数据系统的关键技术。【结果】未来数据产生的速度将进一步提高,在这种应用背景下,如何在设备端进行快速的数据处理成为一种趋势。【结论】未来,我们将在继续关注大数据基础理论与系统关键技术的基础上,引入边缘计算、雾计算等场景,研究物联网环境下的大数据处理。

[Objective]The article mainly gives a brief review for big data theory and systems,including the research background,the technical architecture and the key technologies following by estimating future research directions.[Method]On the basis of the brief introduction of the big data processing theory,this paper introduces the key technologies for big data systems by the three aspects:the data parallel processing methods,the Resource Description Framework(RDF)graph data query and matching,and the big data analysis technologies.[Results]The speed of data generation will be accelerated further more in near future,thus how to quickly process the data on the edge side would lead a research trend.[Conclusion]In future,we will continue to focus on the basic theory and system technologies of big data.At the same time,we will also try to introduce some new research directions,such as edge computing,fog computing,and big data processing in the Internet of Things.