在一起的路上-数据库和机器学习的性能调优

Cherry Khosla, B. Saini
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引用次数: 0

摘要

数据库管理系统是数据密集型应用程序的关键组件。为了有效地处理和分析数据,数据库系统应该在性能方面达到同等水平。调优数据库是目前改善DBMS操作的主要目标。优化数据库以提高性能并满足应用程序的需求已经超出了人类的能力。因此,研究人员已经探索了如何使用机器学习来自动调优数据库。在本文中,我们回顾并讨论了数据库调优的各个领域,以及如何使用机器学习来自动调优配置。我们还讨论了可用于将机器学习与数据库系统集成的各种方法。最后,我们讨论了调优数据库系统中的开放问题。
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On a Way Together - Database and Machine Learning for Performance Tuning
Database Management systems are the crucial components in data intensive applications. For efficiently processing and analyzing the data, the database systems should be at par in terms of performance. Tuning the database is nowadays the major goal to improve DBMS's operations. Optimizing the databases to increase the performance and to meet the needs of an application has surpassed the abilities of the humans. Therefore, the researchers have explored how machine learning can be used to tune the databases automatically. In this paper, we have reviewed and discussed various areas of the database tuning, and how machine learning is used to automatically tune the configurations. We have also discussed the various approaches that can be used to integrate the machine learning with database systems. Lastly, we discussed the open problem in tuning database systems.
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