ACM Transactions on Database Systems (TODS)
The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
A general solution of the n-dimensional B-tree problem
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
The SR-tree: an index structure for high-dimensional nearest neighbor queries
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Multidimensional binary search trees used for associative searching
Communications of the ACM
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
M-tree: An Efficient Access Method for Similarity Search in Metric Spaces
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Multiple Query Processing in Deductive Databases using Query Graphs
VLDB '86 Proceedings of the 12th International Conference on Very Large Data Bases
The R+-Tree: A Dynamic Index for Multi-Dimensional Objects
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
The Universal B-Tree for Multidimensional Indexing: general Concepts
WWCA '97 Proceedings of the International Conference on Worldwide Computing and Its Applications
Multiple Range Query Optimization in Spatial Databases
ADBIS '98 Proceedings of the Second East European Symposium on Advances in Databases and Information Systems
SEA-CNN: Scalable Processing of Continuous K-Nearest Neighbor Queries in Spatio-temporal Databases
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Relational Database Index Design and the Optimizers
Relational Database Index Design and the Optimizers
Foundations of Multidimensional and Metric Data Structures (The Morgan Kaufmann Series in Computer Graphics and Geometric Modeling)
Efficient Processing of Narrow Range Queries in Multi-dimensional Data Structures
IDEAS '06 Proceedings of the 10th International Database Engineering and Applications Symposium
Physical Database Design: the database professional's guide to exploiting indexes, views, storage, and more
Database Systems: The Complete Book
Database Systems: The Complete Book
Expert Oracle Database 11g Administration
Expert Oracle Database 11g Administration
Storing semi-structured data on disk drives
ACM Transactions on Storage (TOS)
Construction of tree-based indexes for level-contiguous buffering support
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Optimization of disk accesses for multidimensional range queries
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part I
Multiple k nearest neighbor query processing in spatial network databases
ADBIS'06 Proceedings of the 10th East European conference on Advances in Databases and Information Systems
Expert Performance Indexing for SQL Server 2012
Expert Performance Indexing for SQL Server 2012
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Multidimensional data are commonly utilized in many application areas like electronic shopping, cartography and many others. These data structures support various types of queries, e.g. point or range query. The range query retrieves all tuples of a multidimensional space matched by a query rectangle. Processing range queries in a multidimensional data structure has some performance issues, especially in the case of a higher space dimension or a lower query selectivity. As result, these data are often stored in an array or one-dimensional index like B-tree and range queries are processed with a sequence scan. Many real world queries can be transformed to a multiple range query: the query including more than one query rectangle. In this article, we aim our effort to processing of this type of the range query. First, we show an algorithm processing a sequence of range queries. Second, we introduce a special type of the multiple range query, the Cartesian range query. We show optimality of these algorithms from the IO and CPU costs point of view and we compare their performance with current methods. Although we introduce these algorithms for the R-tree, we show that these algorithms are appropriate for all multidimensional data structures with nested regions.