Advertisement
Published in:
2005 | OriginalPaper | Chapter
On Efficient Storing and Processing of Long Aggregate Lists
Authors : Marcin Gorawski, Rafal Malczok
Published in: Data Warehousing and Knowledge Discovery
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
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.