Configuration knobs of database systems are essential to achieve high throughput and low
latency. Recently, automatic tuning systems using machine learning methods (ML) have …

Knob tuning plays an important role in database optimization, which tunes knob settings to
optimize the database performance or improve resource utilization. However, there are …

Modern database management systems (DBMS) expose hundreds of configurable knobs to
control system behaviours. Determining the appropriate values for these knobs to improve …

DB-BERT is a database tuning tool that exploits information gained via natural language
analysis of manuals and other relevant text documents. It uses text to identify database …

Recently, using automatic configuration tuning to improve the performance of modern
database management systems (DBMSs) has attracted increasing interest from the …

Query optimization has long been a fundamental yet challenging topic in the database field.
With the prosperity of machine learning (ML), some recent works have shown the …

Machine learning techniques have been proposed to optimize the databases. For example,
traditional empirical database optimization techniques (eg, cost estimation, join order …

Tuning a database system to achieve optimal performance on a given workload is a long-
standing problem in the database community. A number of recent works have leveraged ML …

Recently, using machine learning for performance tuning of cloud database (CDB) service
has shown great potentials. However, facing personalized requirements such as various …

Database management systems (DBMSs) are notoriously difficult to deploy and administer.
Self-driving DBMSs seek to remove these impediments by managing themselves …