IA2: A Deep Reinforcement Learning-Based Index Advisor for Optimizing Database Performance Across Diverse Workloads
IA2 is a novel deep reinforcement learning-based approach that efficiently selects optimal index configurations to enhance database workload performance, outperforming existing index advisors by leveraging adaptive action masking and comprehensive workload modeling.
Genetic Algorithm for Optimizing Materialized Views in Data Warehouses to Improve Query Performance and Reduce Maintenance Costs
A genetic algorithm approach that intelligently selects an optimal set of materialized views to maximize query performance, minimize maintenance costs, and satisfy storage constraints in data warehousing environments.
Spanning Tree-based Query Plan Enumeration: Optimizing Query Plans with Spanning Trees
Optimizing query plans using spanning trees for efficient query optimization.
Improving Query Performance with GenRewrite Using Large Language Models
Leveraging Large Language Models for query rewriting can significantly improve performance and reduce manual effort.
Spanning Tree-based Query Plan Enumeration: Optimizing Query Plans with Spanning Trees
The authors propose a novel approach to query optimization by framing it as finding spanning trees with low costs, utilizing Prim's and Kruskal's algorithms to enhance the robustness of the query optimizer.