Event based forecasting of database workloads
It is well known that analysis of database workloads recorded in the past can be used to improve performance of a database system in the future. This work investigates a problem how to use information extracted from the audit trails to predict the characteristics and levels of future workloads in a database system. The paper describes a new approach to a database workload forecasting based on the identification of periodically repeated instances of events and association of workload related information with the events. The proposed approach creates the new workload forecasts from the analysis of audit trails in the periods of times related to the earlier determined instances of events. A system of operations on the workload forecasts defined in this work can be used to derive the new workload forecasts from the already existing ones. An event based approach to workload forecasting that associates the specific types of database workloads with the instances of events allows for more precise the forecasting of such workloads in the future data processing.