Evaluation of Top-k OLAP Queries Using Aggregate R-Trees

Abstract. A top-k OLAP query groups measures with respect to some abstraction level of interesting dimensions and selects the k groups with the highest aggregate value. An example of such a query is “find the 10 combinations of product-type and month with the largest sum of sales”. Such queries may also be applied in a spatial database context, where objects are augmented with some measures that must be aggregated according to a spatial division. For instance, consider a map of objects (e.g., restaurants), where each object carries some nonspatial measure (e.g., the number of customers served during the last month). Given a partitioning of the space into regions (e.g., by a regular grid), the goal is to find the regions with the highest number of served customers. A straightforward method to evaluate a top-k OLAP query is to compute the aggregate value for each group and then select the groups with the highest aggregates. In this paper, we study the integration of the top-k opera...

• Type: Conference
• Year: 2005
• Where: SSD
• Authors: Nikos Mamoulis, Spiridon Bakiras, Panos Kalnis
• Keywords: Aggregate Value, OLAP Query Groups, SSD 2005, Top-k Olap Query