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A Performance Prediction Model for Database Environments: A Preliminary Analysis

机译:数据库环境的性能预测模型:初步分析

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摘要

Properly addressing the performance issues presented in database systems is and has been a significant technological challenge, this due to the uncontrolled fluctuation of user requests. Being able to predict the behaviour of such systems can greatly improve their performance. Several prediction methods, such as linear regression and autoregressive moving average, among others, have extensively been used to predict performance in shared environments where a workload is involved. However, not all them produce accurate predictions when the system is working under different workloads. In this paper, we present our preliminary results on exploring the accuracy of two different approaches (exact and approximate methods) used to predict the response time of a database system subject to different workloads in a controlled environment. Our results show that approximate methods present better prediction accuracy when compared to exact methods. Hence, we consider the main contributions of this work the following: (a) the results obtained from comparing exact and approximate methods, since they can be used as a basis for further works addressing similar problems, and (b) a preliminary prediction model also based on our findings.
机译:正确解决数据库系统中存在的性能问题已经成为一项重大技术挑战,这是由于用户请求的不受控制的波动所致。能够预测此类系统的行为可以大大提高其性能。几种预测方法(例如线性回归和自回归移动平均值)已广泛用于预测涉及工作负载的共享环境中的性能。但是,当系统在不同的工作负载下工作时,并非所有这些工具都能产生准确的预测。在本文中,我们提供了关于探索两种不同方法(精确方法和近似方法)的准确性的初步结果,这些方法可用来预测数据库系统在受控环境中承受不同工作负载时的响应时间。我们的结果表明,与精确方法相比,近似方法具有更好的预测准确性。因此,我们认为这项工作的主要贡献如下:(a)通过比较精确方法和近似方法获得的结果,因为它们可以用作解决类似问题的进一步工作的基础,并且(b)初步预测模型根据我们的发现。

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