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Bringing SQL databases to key-based NoSQL databases: a canonical approach

机译:将SQL数据库引入基于密钥的NoSQL数据库:一种规范方法

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Big Data management has brought several challenges to data-centric applications, like the support to data heterogeneity, rapid data growth and huge data volume. NoSQL databases have been proposed to tackle Big Data challenges by offering horizontal scalability, schemaless data storage and high availability, among others. However, NoSQL databases do not have a standard query language, which bring on a steep learning curve for developers. On the other hand, traditional relational databases and SQL are very popular standards for storing and manipulating critical data, but they are not suitable to Big Data management. One solution for relational-based applications to move to NoSQL databases is to offer a way to access NoSQL databases through SQL instructions. Several approaches have been proposed for translating relational database schemata and operations to equivalent ones in NoSQL databases in order to improve scalability and availability. However, these approaches map relational databases only to a single NoSQL data model and, sometimes, to a specific NoSQL database product. This paper presents a canonical approach, called SQLToKeyNoSQL, that translates relational schemata as well as SQL instructions to equivalent schemata and access methods of any key-oriented NoSQL database. We present the architecture of our layer focusing on the mapping strategies as well as experiments that evaluate the benefits of our approach against some state-of-art baselines.
机译:大数据管理给以数据为中心的应用程序带来了一些挑战,例如对数据异构性的支持,快速的数据增长和巨大的数据量。已提出通过提供水平可伸缩性,无模式数据存储和高可用性等方式来解决大数据挑战的NoSQL数据库。但是,NoSQL数据库没有标准的查询语言,这为开发人员带来了陡峭的学习曲线。另一方面,传统的关系数据库和SQL是用于存储和处理关键数据的非常流行的标准,但是它们不适用于大数据管理。基于关系的应用程序迁移到NoSQL数据库的一种解决方案是提供一种通过SQL指令访问NoSQL数据库的方法。为了提高可伸缩性和可用性,已经提出了几种将关系数据库模式和操作转换为NoSQL数据库中的等效方法的方法。但是,这些方法仅将关系数据库映射到单个NoSQL数据模型,有时还映射到特定的NoSQL数据库产品。本文提出了一种称为SQLToKeyNoSQL的规范方法,该方法将关系架构以及SQL指令转换为等效的架构和任何面向键的NoSQL数据库的访问方法。我们介绍了该层的体系结构,重点是映射策略以及针对某些最新基准评估了我们方法的好处的实验。

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