On Efficient Storing and Processing of Long Aggregate Lists

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...

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Bibliographic Details
Published inData Warehousing and Knowledge Discovery pp. 190 - 199
Main Authors Gorawski, Marcin, Malczok, Rafal
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture Notes in Computer Science
Subjects
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Data Warehouse
Exact sciences and technology
Indexing Structure
Information systems. Data bases
Memory organisation. Data processing
Page Size
Single Page
Software
Table Page
Data analysis
List processing
Database
Knowledge discovery
Materialized view
Autoregressive model
Filling
Regression analysis
Data mining
Data warehouse
Indexing
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Summary: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.
ISBN:354028558X
9783540285588
ISSN:0302-9743
1611-3349
DOI:10.1007/11546849_19