Abstract: Aggregation queries are performed by first identifying outlier values, aggregating the outlier values, and sampling the remaining data after pruning the outlier values. The sampled data is extrapolated and added to the aggregated outlier values to provide an estimate for each aggregation query. Outlier values are identified by selecting values outside of a selected sliding window of data having the lowest variance. An index is created for the outlier values. The outlier data is removed from the window of data, and separately aggregated. The remaining data without the outliers is then sampled to provide a statistically relevant sample that is then aggregated and extrapolated to provide an estimate for the remaining data. This sampled estimate is combined with the outlier aggregate to form an estimate for the entire set of data.

Abstract: In a relational database system, a set of physical design structures is enumerated that optimizes database performance over a given workload consisting of workload entries that include queries and updates that have been executed against the database. An individual benefit is calculated for each candidate structure relevant to a given workload entry and these individual benefits are summed over the entries in the workload examined thus far. A workload entry is selected from the workload and a set of candidate structures relevant to the workload entry is identified.