On efficient storing and processing of long aggregate lists

  • Authors:
  • Marcin Gorawski;Rafal Malczok

  • Affiliations:
  • Institute of Computer Science, Silesian University of Technology, Gliwice, Poland;Institute of Computer Science, Silesian University of Technology, Gliwice, Poland

  • Venue:
  • DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
  • Year:
  • 2005

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper we present a solution called Materialized Aggregate List designed for the efficient storing and processing of long aggregate lists. An aggregate list contains aggregates, calculated from the data stored in the database. In our approach, once created, the aggregates are materialized for further use. The list structure contains a table divided into pages. We present three different page-filling algorithms used when the list is browsed. We present test results and we use them for estimating the best combination of the configuration parameters: number of pages, size of a single page and number of available database connections. The Materialized Aggregate List can be applied on every aggregation level in various indexing structures, such as, an aR-tree.