Affiliation:
1. Purdue University, West Lafayette, IN
2. Qatar Computing Research Institute, Qatar
Abstract
The widespread use of location-aware devices has led to countless location-based services in which a user query can be arbitrarily complex, i.e., one that embeds multiple spatial selection and join predicates. Amongst these predicates, the
k
-Nearest-Neighbor (
k
NN) predicate stands as one of the most important and widely used predicates. Unlike related research, this paper goes beyond the optimization of queries with single
k
NN predicates, and shows how queries with
two k
NN predicates can be optimized. In particular, the paper addresses the optimization of queries with: (i) two
k
NN-select predicates, (ii) two
k
NN-join predicates, and (iii) one
k
NN-join predicate and one
k
NN-select predicate. For each type of queries, conceptually correct query evaluation plans (QEPs) and new algorithms that optimize the query execution time are presented. Experimental results demonstrate that the proposed algorithms outperform the conceptually correct QEPs by orders of magnitude.
Subject
General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development
Cited by
12 articles.
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