Tun-OCM: A model-driven approach to support database tuning decision making

Database tuning is a task executed by Database Administrators (DBAs) based on their practical experience and on tuning systems, which support DBA actions towards improving the performance of a database system. It is notoriously a complex task that requires precise domain knowledge about possible database configurations. Ideally, a DBA should keep track of several Database Management Systems (DBMS) parameters, configure data structures, and must be aware about possible interferences among several database (DB) configurations. We claim that an automatic tuning system is a decision support system and DB tuning may also be seen as a configuration management task. Therefore, we may characterize it by means of a formal domain conceptualization, benefiting from existing control practices and computational support in the configuration management domain. This work presents Tun-OCM, a conceptual model represented as a well-founded ontology, that encompasses a novel characterization of the database tuning domain as a configuration management conceptualization to support decision making. We develop and represent Tun-OCM using the CM-OPL methodology and its underlying language. The benefits of Tun-OCM are discussed by instantiating it in a real scenario.

Automated summary

Database tuning is a task executed by Database Administrators based on practical experience and domain knowledge, requiring precise configurations and awareness of possible interferences. An automatic tuning system can be seen as a decision support system, aiding in improving database performance and configuration management tasks.