.png){kind=icon}
返回
Automatic Index Tuning: A Survey
.png){kind=icon}
PRE
AI
DOI：10.1109/TKDE.2024.3422006.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Index tuning plays a crucial role in facilitating the efficiency of data retrieval within database systems, which adjusts index settings to optimize the database performance. Recently, with the growth of data volumes, the complexity of workloads, and the diversification of database applications, various Automatic Index Tuning (AIT) methods have been proposed to address these challenges. In this paper, we provide a comprehensive survey on Automatic Index Tuning. First, we overview the AIT techniques from multiple aspects, including i) problem definition, ii) workflow, iii) framework, iv) index types, v) index interaction, vi) changing factors, vii) automation level, and show the development history. Second, we summarize techniques in the main modules of AIT, including preprocessing, index benefit estimation, and index selection. Preprocessing involves workload compression, index candidate generation, feature representation of workloads and databases, and workload reduction. Index benefit estimation approaches are categorized into empirical methods and machine learning based methods. Index selection involves algorithms of offline AIT and online AIT. Moreover, we summarize the commonly-used datasets in AIT and discuss the applications of index tuning in commercial and opensource database products. Finally, we outline potential future research directions. Our survey aims to enhance both general knowledge and in-depth insights into AIT, and inspire researchers to address the ongoing challenges.
Keyword:
Indexes
Tuning
Databases
Surveys
Estimation
Costs
Machine learning algorithms
Automatic index tuning
machine learning
index selection
index benefit estimation
reinforcement learning
期刊
IF:
10.4
论文数:
6.8K
被引数:
3.2W
机构
引用论文
Management of Peritonitis After Minimally Invasive Colorectal Surgery: Can We Stick to Laparoscopy?
PREAI
分享收藏
Research progress on the relationship between sex hormone‐binding globulin and male reproductive system diseases.png)
Andrologia
OAAI
AndrologiaIF0
OAAI分享收藏The index selection problem with configurations and memory limitation: A scatter search approach
PREAI
分享收藏
查看更多内容