AI RESEARCH
DOT: Dynamic Knob Selection and Online Sampling for Automated Database Tuning
arXiv CS.AI
•
ArXi:2603.15540v1 Announce Type: cross Database Management Systems (DBMS) are crucial for efficient data management and access control, but their administration remains challenging for Database Administrators (DBAs). Tuning, in particular, is known to be difficult. Modern systems have many tuning parameters, but only a subset significantly impacts performance. Focusing on these influential parameters reduces the search space and optimizes performance. Current methods rely on costly warm-up phases and human expertise to identify important tuning parameters.