Aggregated 2D Range Queries on Clustered Points
Abstract
Efficient processing of aggregated range queries on two-dimensional grids is a common requirement in information retrieval and data mining systems, for example in Geographic Information Systems and OLAP cubes. We introduce a technique to represent grids supporting aggregated range queries that requires little space when the data points in the grid are clustered, which is common in practice. We show how this general technique can be used to support two important types of aggregated queries, which are ranked range queries and counting range queries. Our experimental evaluation shows that this technique can speed up aggregated queries up to more than an order of magnitude, with a small space overhead.
Cite
@article{arxiv.1603.02063,
title = {Aggregated 2D Range Queries on Clustered Points},
author = {Nieves R. Brisaboa and Guillermo De Bernardo and Roberto Konow and Gonzalo Navarro and Diego Seco},
journal= {arXiv preprint arXiv:1603.02063},
year = {2016}
}
Comments
This research has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sk{\l}odowska-Curie Actions H2020-MSCA-RISE-2015 BIRDS GA No. 690941