Applying OLAP Pre-Aggregation Techniques to ... - Jacobs University

5.6 Summary 101
we considered non-uniform distributions including Poisson, peak, and step. For 2D
datasets, we showed that our algorithm performs better than that of image pyramids.
In particular, for non-uniform data distributions, our pre-aggregation selection algorithm
not only provides a lower average query cost, but makes a much more efficient
use of storage space. This is because our algorithm considers the frequency of the
query, and the cost savings (benefit) this provides for computing the workload. Nevertheless,
the major advantage of our algorithm over that of image pyramids is not the
improved average query cost, but the reduced amount of storage space required for
the pre-aggregates, especially for non-uniform distributions.
In our experiments with 3D and 4D datasets, we showed the effect of the available
storage space for pre-aggregation on average query costs. We observed that a small
amount of storage overhead is sufficient to dramatically reduce average query costs.
Since there are no similar techniques against which we can compare our results, we
compared our results against the average query costs obtained by using the original
data.