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-O_CM, 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-O_CM using the CM-OPL methodology and its underlying language. The benefits of Tun-O_CM are discussed by instantiating it in a real scenario.

数据库调优是数据库管理员（DBA）根据他们的实际经验和调优系统执行的任务，它支持DBA采取行动来提高数据库系统的性能。众所周知，这是一项复杂的任务，需要有关可能的数据库配置的精确域知识。理想情况下，DBA应该跟踪多个数据库管理系统（DBMS）参数，配置数据结构，并且必须了解多个数据库（DB）配置之间可能存在的干扰。我们声称自动调整系统是决策支持系统，数据库调整也可以看作是配置管理任务。因此，我们可以借助正式的域概念化来表征它，这得益于配置管理域中现有的控制实践和计算支持。_CM，一种表示为基础良好的本体的概念模型，其中包含对数据库调整域的新颖表征，作为支持决策制定的配置管理概念。我们使用CM-OPL方法及其基础语言开发并代表Tun-O _CM。通过在实际场景中实例化Tun-O _CM的好处来进行讨论。