| Author(s) |
Dunstan, Neil
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| Publication Date |
2013
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| Abstract |
The datacube is a conceptual data structure to support On-Line Analytical Processing (OLAP). It is essentially a series of tables organized according to attributes (called dimensions). Table rows (or cells) contain aggregated information for collections of records that satisfy value constraints for each dimension. The Statistics Tree (ST) uses a tree structure for storing the datacube in memory in order to optimize cell lookup time and handle a variety of types of cell-based queries. An Augmented ST (AST) is proposed with additional list structures within the ST. The additional lists link together the cells that comprise the tables of the datacube. An algorithm that builds table lists requires only a single traversal of the ST. Thus the AST supports both cell-level and table-level queries. Algorithms to build and update datacubes stored as ASTs are shown. A web-based wireless sensor network OLAP server based on the AST is described.
|
| Citation |
Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2013 International Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Golden Coast, QLD, Australia, April 14-17, 2013, Revised Selected Papers, p. 26-35
|
| ISBN |
9783642403194
9783642403187
|
| Link | |
| Language |
en
|
| Publisher |
Springer
|
| Series |
Lecture Notes in Computer Science
|
| Title |
An OLAP Server for Sensor Networks Using Augmented Statistics Trees
|
| Type of document |
Conference Publication
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| Entity Type |
Publication
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