Online Tuning of Aggregation Tables for OLAP

Materializing results from complex aggregation queries helps to significantly improve response times in OLAP servers. This problem is known as the view selection problem: choosing the optimal set of aggregation tables (called configuration) for a given workload. In this paper we present an online approach for adjusting the configuration dynamically to the current workload. This approach is implemented as part of an open source OLAP server and acts on the level of multidimensional MDX queries. The work presents the details of cost estimation and optimization of the system demonstrated in [10] and extends it by an online tuning strategy.