Lero: A learning-to-rank query optimizer
A recent line of works apply machine learning techniques to assist or rebuild cost-based
query optimizers in DBMS. While exhibiting superiority in some benchmarks, their …
query optimizers in DBMS. While exhibiting superiority in some benchmarks, their …
Eraser: Eliminating performance regression on learned query optimizer
Efficient query optimization is crucial for database management systems. Recently, machine
learning models have been applied in query optimizers to generate better plans, but the …
learning models have been applied in query optimizers to generate better plans, but the …
Real-time workload pattern analysis for large-scale cloud databases
Hosting database services on cloud systems has become a common practice. This has led
to the increasing volume of database workloads, which provides the opportunity for pattern …
to the increasing volume of database workloads, which provides the opportunity for pattern …
Machine learning for databases: Foundations, paradigms, and open problems
This tutorial delves into the burgeoning field of Machine Learning for Databases (ML4DB),
highlighting its recent progress and the challenges impeding its integration into industrial …
highlighting its recent progress and the challenges impeding its integration into industrial …
DACE: A Database-Agnostic Cost Estimator
Cost estimation is of great importance in query optimization. However, traditional optimizers
compute the cost based on heuristics, sacrificing accuracy for efficiency. In recent years …
compute the cost based on heuristics, sacrificing accuracy for efficiency. In recent years …
Lero: applying learning-to-rank in query optimizer
In recent studies, machine learning techniques have been employed to support or enhance
cost-based query optimizers in DBMS. Although these approaches have shown superiority …
cost-based query optimizers in DBMS. Although these approaches have shown superiority …
Join Order Selection with Deep Reinforcement Learning: Fundamentals, Techniques, and Challenges
Join Order Selection (JOS) is a fundamental challenge in query optimization, as it
significantly affects query performance. However, finding an optimal join order is an NP-hard …
significantly affects query performance. However, finding an optimal join order is an NP-hard …
[PDF][PDF] Dynamic materialized view management using graph neural network
Materialized views (MVs) are vital in DBMS to improve the query efficiency by reducing
redundant computations of shared subqueries in a workload. Traditional methods focus on …
redundant computations of shared subqueries in a workload. Traditional methods focus on …
QO-Insight: Inspecting Steered Query Optimizers
Steered query optimizers address the planning mistakes of traditional query optimizers by
providing them with hints on a per-query basis, thereby guiding them in the right direction …
providing them with hints on a per-query basis, thereby guiding them in the right direction …
[HTML][HTML] Learned Query Optimization by Constraint-Based Query Plan Augmentation
C Ye, H Duan, H Zhang, Y Wu, G Dai - Mathematics, 2024 - mdpi.com
Over the last decades, various cost-based optimizers have been proposed to generate
optimal plans for SQL queries. These optimizers are key to achieving good performance in …
optimal plans for SQL queries. These optimizers are key to achieving good performance in …