ML-Powered Index Tuning: An Overview of Recent Progress and Open Challenges
T Siddiqui, W Wu - ACM SIGMOD Record, 2024 - dl.acm.org
The increasing scale and complexity of workloads in modern cloud services highlight a
crucial challenge in automated index tuning: recommending high-quality indexes while …
crucial challenge in automated index tuning: recommending high-quality indexes while …
The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto …
Existing machine learning (ML) approaches to automatically optimize database
management systems (DBMSs) only target a single configuration space at a time (eg, knobs …
management systems (DBMSs) only target a single configuration space at a time (eg, knobs …
TRAP: Tailored Robustness Assessment for Index Advisors via Adversarial Perturbation
Many index advisors have recently been proposed to build indexes automatically to improve
query performance. However, they mainly consider performance improvement in static …
query performance. However, they mainly consider performance improvement in static …
Wred: Workload Reduction for Scalable Index Tuning
Modern database systems offer index-tuning advisors that automatically identify a set of
indexes to improve workload performance. Advisors leverage the optimizer's what-if API to …
indexes to improve workload performance. Advisors leverage the optimizer's what-if API to …
Morphtree: a polymorphic main-memory learned index for dynamic workloads
Modern database systems rely on indexes to accelerate data access. The recently proposed
learned indexes can offer higher search performance with lower space costs than traditional …
learned indexes can offer higher search performance with lower space costs than traditional …
Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems
Autonomous database management systems (DBMSs) aim to optimize themselves
automatically without human guidance. They rely on machine learning (ML) models that …
automatically without human guidance. They rely on machine learning (ML) models that …
Breaking It Down: An In-Depth Study of Index Advisors
Index advisors aim to improve workload performance by judiciously selecting an appropriate
set of indexes. Various heuristic-based and learning-based methods have been proposed …
set of indexes. Various heuristic-based and learning-based methods have been proposed …
Automatic Database Index Tuning: A Survey
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 …
systems, which adjusts index settings to optimize the database performance. Recently, with …
Refactoring Index Tuning Process with Benefit Estimation
T Yu, Z Zou, W Sun, Y Yan - Proceedings of the VLDB Endowment, 2024 - dl.acm.org
Index tuning is a challenging task aiming to improve query performance by selecting the
most effective indexes for a database and a workload. Existing automatic index tuning …
most effective indexes for a database and a workload. Existing automatic index tuning …
MFIX: An Efficient and Reliable Index Advisor via Multi-Fidelity Bayesian Optimization
Indexes play a pivotal role in enhancing database performance. However, index selection
remains one of the most challenging problems in relational database management systems …
remains one of the most challenging problems in relational database management systems …