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.
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Gorawski, M., Malczok, R. (2005). On Efficient Storing and Processing of Long Aggregate Lists. In: Tjoa, A.M., Trujillo, J. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2005. Lecture Notes in Computer Science, vol 3589. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11546849_19
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DOI: https://doi.org/10.1007/11546849_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28558-8
Online ISBN: 978-3-540-31732-6
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