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.