Enhancing query processing on stock market cloud-based database

Hagger Essam, Ahmed Gamal, Essam M. Shaaban
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Abstract

Cloud computing is rapidly expanding because it allows users to save the development and implementation time on their work. It also reduces the maintenance and operational costs of the used systems. Furthermore, it enables the elastic use of any resource rather than estimating workload, which may be inaccurate, as database systems can benefit from such a trend. In this paper, we propose an algorithm that allocates the materialized view over cloudbased replica sets to enhance the database system's performance in stock market using a Peerto-Peer architecture. The results show that the proposed model (MVCRS) improves the query processing time and network transfer cost by distributing the materialized views over cloudbased replica sets. Also, it has a significant effect on decision-making and achieving economic returns.
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加强股票市场云数据库的查询处理
云计算正在迅速扩展,因为它允许用户节省开发和实现工作的时间。它还降低了使用系统的维护和操作成本。此外,它允许弹性地使用任何资源,而不是估计工作负载,这可能是不准确的,因为数据库系统可以从这种趋势中受益。在本文中,我们提出了一种基于点对点架构的算法,该算法将物化视图分配到基于云的副本集上,以提高数据库系统在股票市场中的性能。结果表明,该模型(MVCRS)通过将物化视图分布在基于云的副本集上,提高了查询处理时间和网络传输成本。此外,它对决策和实现经济回报也有显著的影响。
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