数据一致性是分布式系统研究领域的经典问题,大数据时代数据来源和业务需求的多样性及复杂性又为一致性研究带来了诸多新的挑战,同时也推动着这方面研究不断前进。目前关于分布式系统一致性的综述文章大多集中于介绍各种一致性模型的概念、定义,忽视了对模型在实际应用中的分析。论文在阐述现有一致性模型的基础上,结合实际系统进行案例分析,总结不同模型的适用范围;同时针对目前大数据技术的发展趋势,归纳一致性问题未来研究的发展方向,为读者进行一致性方面的研究提供一定的借鉴意义。
Data consistency is an important research branch in the distributed system community, and the complexity and variety of data sources and businesses in Big Data times makes it increasingly challenging, which also propels this area to advance in return. Considering the fact that most of surveys on consistency are merely focused on introducing various consis- tency models while ignoring to explore their suitable application scenarios, in this paper case studies of real distributed stor- age systems are combined with theories of consistency models to provide more empirical analysis for readers. Additionally, based on the development situation of Big Data technology, some suggestions on the future study of consistency are given that are helpful for readers to conduct their researches.