Mining periodic workload patterns in database audit trails
Information about periodic processing of database operations has a pivotal importance for continuous physical database design and automated performance tuning of database systems. This work shows how to detect the oscillations of database workloads caused by the periodical invocations of user applications. In particular, we present an algorithm for discovering periodic patterns in the histories of processing of complex and elementary database operations. In our approach, information collected from the database audit trails is transformed into a sequence of syntax trees and later on it is compressed in a syntax tree table. The periodic patterns are discovered through nested iterations over a four dimensional space of syntax trees and positional parameters of the patterns. Transformations of the patterns are used to discover the overlaping periodic patterns.