| 摘要 |
An apparatus and method for efficiently compressing contents of a database system to support ad hoc querying and OLAP type aggregation queries. This invention consists of a new compressed representation of the data cube that (a) drastically reduces storage requirements, (b) does not require the discretization hierarchy along each query dimension to be fixed beforehand and (c) treats each dimension as a potential target measure and supports multiple aggregation functions without additional storage costs. The tradeoff is approximate, yet relatively accurate, answers to queries. The basic method relies on representing the contents of the database by a probability distribution consisting of a mixture of Gaussians. Aggregation queries, be they multi-dimensional, conjunctive, or disjunctive, can be answered by performing integration over the probability distribution. We augment the basic model with a collection of (possibly compressed) outliers rows from the data to further enhance accuracy if more system memory is available for this task.
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