垂直分布的云数据库中并行抓取和延迟抓取的性能比较

J. Kohler, Thomas Specht
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引用次数: 5

摘要

下面的工作主要关注SeDiCo框架的垂直数据分布方法带来的严重性能问题。SeDiCo(安全分布式云数据存储)是一个框架,它将数据库数据垂直分布在多个云上,以维护数据的安全性、保护和隐私。但是,这种垂直数据分布需要在任何客户机访问之前将数据连接在一起。这种连接非常耗时,因此,这种方法目前在实际使用场景中是不可行的。为了克服这些性能问题,本工作建议引入一个数据缓存架构和两个相应的获取过程,即延迟和并行获取。我们进一步实施了这两种策略,测量了它们的表现并相互比较。我们的结果表明,并行获取策略远远优于延迟获取策略。在此之上,本文概述了我们方法的整个缓存架构,并详细讨论了这两种策略。最后,本工作总结了测量结果,并讨论了SeDiCo框架背景下的进一步挑战,作为未来的工作任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A performance comparison between parallel and lazy fetching in vertically distributed cloud databases
The following work focuses on the severe performance issues that come along with the vertical data distribution approach of the SeDiCo framework. SeDiCo (A Secure and Distributed Cloud Data Store) is a framework that vertically distributes database data across several clouds in order to maintain data security, protection and privacy. However, this vertical data distribution requires joining data together before any client access. This join is extremely time-consuming and thus, this approach is currently not feasible in practical usage scenarios. In order to overcome those performance issues, this work proposes the introduction of a data cache architecture and two corresponding fetch procedures, i.e. lazy and parallel fetching. We further implemented both strategies, measured their performance and compared them to each other. Our results show that the parallel fetch strategy by far outperforms the lazy fetch strategy. Above that, this work outlines the entire caching architecture of our approach and discusses the two strategies in detail. Finally, this work concludes the measured results and discusses further challenges in the context of the SeDiCo framework as future work tasks.
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