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Towards Scalability in Systems with Write Operations in Relational Databases

机译:在关系数据库中具有写入操作的系统中的可扩展性

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The scalability of systems is essential in scenarios where there is a lot of concurrent users. Some systems have peak access during certain times, others have a lot of concurrent users regularly. Thus, these systems must be able to perform equally as a growing number of requests. The study of system scalability that manipulate database considers read operations in database systems. However, in this paper we present an approach for horizontal scalability on systems that perform write database operations. The proposed approach uses queuing theory and differs from commonly developed solutions like clustering databases and elasticity in the cloud. A case study was conducted with an application of persistent logs, and two versions of the application have been implemented in order to compare the efficiency of the use of queues. Results show the efficiency of the use of queuing theory implemented to allow scalability for applications with a large amount of writing database operations.
机译:系统的可扩展性在有很多并发用户的情况下是必不可少的。有些系统在某些时候有峰值访问,其他系统定期有很多并发用户。因此,这些系统必须能够同样地执行作为越来越多的请求。操纵数据库的系统可伸缩性研究考虑数据库系统中的读取操作。然而,在本文中,我们在执行写入数据库操作的系统上介绍了一种水平可伸缩性的方法。该方法采用排队理论,与云中的聚类数据库和云中的弹性等常见开发的解决方案不同。在应用持久性日志的应用中进行了案例研究,已经实施了两个版本的应用程序,以比较队列使用的效率。结果显示使用排队理论的使用效率,以允许具有大量写入数据库操作的应用程序的可扩展性。

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