Attribute Value Reordering for Efficient Hybrid OLAP

Kaser, Owen et Lemire, Daniel (2003). « Attribute Value Reordering for Efficient Hybrid OLAP », dans ACM Sixth International Workshop on Data Warehousing and OLAP (DOLAP 2003, Louisiana, USA) pp. 1-8.

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The normalization of a data cube is the process of choosing an ordering for the attribute values, and the chosen ordering will affect the physical storage of the cube's data. For large multidimensional arrays, proper normalization can lead to more efficient storage in hybrid OLAP contexts that store dense and sparse chunks differently. We show that it is NP-hard to compute an optimal normalization even for 1x3 chunks, although we find an exact algorithm for 1x2 chunks. When attributes are nearly statistically independent, we show that an optimal normalization is given by dimension-wise attribute frequency sorting, which can be done in time O(d n log(n)) for data cubes of size n^d. When attributes are not independent, we propose and evaluate a number of heuristics. Our optimized hybrid OLAP storage mechanism was observed to be 44% more storage efficient than ROLAP and the gains due to normalization alone accounted for 45% of this increase in efficiency.

Type: Communication, article de congrès ou colloque
Mots-clés ou Sujets: Multidimensional Databases, Data Cubes, Multidimensional Binary Arrays, OLAP, MOLAP, HOLAP, Normalization, Chunking
Unité d'appartenance: Télé-université > UER Science et Technologie
Déposé par: Daniel Lemire
Date de dépôt: 27 août 2007
Dernière modification: 01 nov. 2014 02:03
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