计算机工程2025，Vol.51Issue(7)：31-46,16.DOI:10.19678/j.issn.1000-3428.0068808
基于机器学习的数据库多表连接顺序选择研究综述
Review of Multi-table Join Order Selection in Databases Based on Machine Learning
摘要
Abstract
Multi-table join order selection refers to the process of determining the optimal join sequence among the tables involved in a query during query optimization,to improve execution performance.In complex queries,different join orders can significantly affect query efficiency.In the era of big data,traditional join order selection algorithms,which typically based on heuristic rules,are challenged by massive datasets,diverse application scenarios,and complex query workloads.Their inability to dynamically adapt to environmental changes or to self-improve through learning affects the generalizability of these models,often resulting in suboptimal join orders that can severely degrade query performance.With the rapid advancement of machine learning,Artificial Intelligence for Databases(AI4DB)has emerged as a transformative approach to query optimization.Machine learning-based techniques address the limitations of traditional methods by enabling self-learning and context-aware adaptations.This study first reviews classical join order selection algorithms and then analyzes their inherent limitations.Next,state-of-the-art machine learning models for multi-table join optimization are systematically summarized,detailing their core technical designs.A comparative analysis is provided in terms of effectiveness and applicable scenarios,offering valuable insights for future research in this field.关键词
数据库/查询优化/机器学习/连接顺序/面向数据库的人工智能Key words
database/query optimization/machine learning/join order/Artificial Intelligence for Databases(AI4DB)分类
信息技术与安全科学引用本文复制引用
王浩,高锦涛,王杰..基于机器学习的数据库多表连接顺序选择研究综述[J].计算机工程,2025,51(7):31-46,16.基金项目
国家自然科学基金(62102201) （62102201）
宁夏回族自治区自然科学基金(2022AAC05010,2021BEB04054,2021AAC03034). （2022AAC05010,2021BEB04054,2021AAC03034）
