A hybrid split strategy for k-d-tree based access structures G⃗
GIS '96 Proceedings of the 4th ACM international workshop on Advances in geographic information systems
Multimedia support for databases
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Efficient searching with linear constraints
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Balanced aspect ratio trees: combining the advantages of k-d trees and octrees
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
The SH-tree: A Super Hybrid Index Structure for Multidimensional Data
DEXA '01 Proceedings of the 12th International Conference on Database and Expert Systems Applications
A space-partitioning-based indexing method for multidimensional non-ordered discrete data spaces
ACM Transactions on Information Systems (TOIS)
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In recent years, various k-d-tree based multi-dimensional access structures have been proposed. All these structures share an average bucket utilization of at most ln 2 (about 69.3 %). In this paper we present two algorithms which perform local redistributions of objects to improve the storage utilization of these access structures. We show that under fair conditions a good improvement algorithm can save up to 20 % of space and up to 15 % of query processing time. On the other hand we also show that a local redistribution scheme designed without care, can improve the storage utilization and at the same time worsen the performance of range queries drastically. Furthermore we show the dependencies between split strategies and local redistribution schemes and the general limitations which can be derived from these dependencies.