Attribute Value Reordering For Efficient Hybrid OLAP

Details Attribute Value Reordering For Efficient Hybrid OLAP Attribute Value Reordering For Efficient Hybrid OLAP

2007-02-24

arxiv.org/abs/cs/0702143v1

Owen Kaser, Daniel Lemire, Attribute Value Reordering For Efficient Hybrid OLAP, Information Sciences, Volume 176, Issue 16, 2

Computer Science

Databases

Scientific paper

10.1016/j.ins.2005.09.005

The normalization of a data cube is the ordering of the attribute values. For large multidimensional arrays where dense and sparse chunks are stored differently, proper normalization can lead to improved storage efficiency. 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 dimensions are nearly statistically independent, we show that dimension-wise attribute frequency sorting is an optimal normalization and takes time O(d n log(n)) for data cubes of size n^d. When dimensions are not independent, we propose and evaluate several heuristics. The hybrid OLAP (HOLAP) storage mechanism is already 19%-30% more efficient than ROLAP, but normalization can improve it further by 9%-13% for a total gain of 29%-44% over ROLAP.

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