On a Way Together - Database and Machine Learning for Performance Tuning

被引：0

作者：

Khosla, Cherry ^{[1
]}

Saini, Baljit Singh ^{[1
]}

机构：

[1] Lovely Profess Univ, Sch Comp Sci & Engn, Phagwara, India

来源：

2021 INTERNATIONAL CONFERENCE ON COMPUTING SCIENCES (ICCS 2021) | 2021年

关键词：

Database Tuning; Machine Learning; Tuning methods; Performance tuning;

D O I：

10.1109/ICCS54944.2021.00032

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：123 / 128

页数：6

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