使用NoSQL键值存储实现大数据智能的新方法

Abdelhak Khalil, Mustapha Belaïssaoui
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引用次数: 5

摘要

如今,NoSQL技术正在取得重大进展,并被认为是数据存储的未来,特别是当涉及到大量数据时,这就是数据仓库解决方案的情况。NoSQL数据库在关系型数据库中具有较高的可扩展性和良好的性能,但在关系型数据库中,NoSQL数据库非常耗时,无法处理大数据量。如今,NoSQL这个术语以及大数据等模糊相关的短语越来越受欢迎,这让我们开始考虑在决策支持系统中使用这项技术。本文的目的是研究在最流行和最不复杂的NoSQL数据库类型之一下实例化大数据集市的可能性;即键值存储,主要的挑战是在基于有利于数据完整性的传统数据库的老派数据仓库方法与新一代数据库管理系统提供的有趣机会之间建立良好的相关性。本文描述了从多维概念模式到逻辑模型的转换过程,并根据Oracle NoSQL数据库的实践经验,列出了每种方法的优缺点。
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New approach for implementing big datamart using NoSQL key-value stores
Nowadays, NoSQL technologies are gaining significant ground and considered as the future of data storage, especially when it comes to huge amount of data, which is the case of data warehouse solutions. NoSQL databases provide high scalability and good performance among relational ones, which are really time consuming and can’t handle large data volume. The growing popularity of the term NoSQL these days and vaguely related phrases like big data make us think about using this technology in decision support systems. The purpose of this paper is to investigate the possibility to instantiate a big data mart under one of the most popular and least complicated types of NoSQL databases; namely key-value store, the main challenge is to make a good correlation between the old-school approach of data warehousing based on traditional databases that favor data integrity, and interesting opportunities offered by new generation of database management systems. The paper describes the transformation process from multidimensional conceptual schema to the logical model following three approaches, and outlines a list of strengths and weaknesses for each one based on practical experience under Oracle NoSQL Database.
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