计算机应用与软件2025，Vol.42Issue(9)：38-43,6.DOI:10.3969/j.issn.1000-386x.2025.09.006
基于双通道深度强化学习的数据库索引推荐技术
INDEX RECOMMENDATION BASED ON DUAL CHANNEL DQN
摘要
Abstract
Aiming at the problems such as unused the characteristics of SQL workload and the mechanical rule method during index recommendation,we propose a DQN-based dual channel index recommendation model(Dual Channel Deep Q-Network,DC-DQN).The index selectivity and SQL query type features wre trained independently through two separate channels and the information fusion was carried out through the full connection layer,so as to select the candidate index that better matches three-star index.The experimental results on TPC-H dataset show that DC-DQN performs as good as having all indexes and under the construction of specific query workload,DC-DQN performs better than the previous method.关键词
索引推荐/深度强化学习/三星索引/索引选择问题Key words
Index recommendation/Deep reinforcement learning/Three-star index/Index select problem分类
信息技术与安全科学引用本文复制引用
蒋忠强,时家幸,王宝晗,蔡敦波..基于双通道深度强化学习的数据库索引推荐技术[J].计算机应用与软件,2025,42(9):38-43,6.基金项目
中国移动通信集团有限公司应用基础研究项目"云计算前沿技术研究"(R22100TE). （R22100TE）
