Improving min/max aggregation over spatial objects
Proceedings of the 9th ACM international symposium on Advances in geographic information systems
Spatio-Temporal Aggregation Using Sketches
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Range Aggregate Processing in Spatial Databases
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
Optimizing spatial Min/Max aggregations
The VLDB Journal — The International Journal on Very Large Data Bases
Index structures for data warehouses
Index structures for data warehouses
Authenticated Index Structures for Aggregation Queries
ACM Transactions on Information and System Security (TISSEC)
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Different models to estimate the performance of tree-based index structures exist. Materialized aggregates in the inner nodes of such index structures are used to speed up range queries on aggregates. This is achieved by avoiding traversing the index tree down to the leaves through aggregates precomputed in the inner nodes. None of the existing models deals with these aggregated data. In this paper, we extend the existing models to take account of aggregated data. Our main contribution is a new generic performance model to estimate the Performance of Index Structures with and without Aggregated data (PISA) that covers both aspects. In addition, the PISA model is adaptable to the distribution of the data and the location of the query boxes (e. g. uniform, normal, and skewed distributions). Experiments confirm that in most cases the PISA model is more accurate than other models.