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Nearest Neighbor Queries in Shared-Nothing Environments
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IEEE Transactions on Knowledge and Data Engineering
Asymptotically Optimal Declustering Schemes for Range Queries
ICDT '01 Proceedings of the 8th International Conference on Database Theory
Study of Scalable Declustering Algorithms for Parallel Grid Files
IPPS '96 Proceedings of the 10th International Parallel Processing Symposium
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IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
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VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
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DEXA '01 Proceedings of the 12th International Conference on Database and Expert Systems Applications
Optimal Parallel I/O for Range Queries through Replication
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Hierarchical Declustering Schemes for Range Queries
EDBT '00 Proceedings of the 7th International Conference on Extending Database Technology: Advances in Database Technology
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IEEE Transactions on Knowledge and Data Engineering
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Asymptotically optimal declustering schemes for 2-dim range queries
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IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
Disk Allocation for Fast Range and Nearest-Neighbor Queries
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(Almost) Optimal parallel block access for range queries
Information Sciences—Informatics and Computer Science: An International Journal
One torus to rule them all: multi-dimensional queries in P2P systems
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Optimizing Reduction Computations In a Distributed Environment
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Replicated declustering of spatial data
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Optimal data-space partitioning of spatial data for parallel I/O
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Design of a next generation sampling service for large scale data analysis applications
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Efficient parallel processing of range queries through replicated declustering
Distributed and Parallel Databases
Improved bounds and schemes for the declustering problem
Theoretical Computer Science
Data space mapping for efficient I/O in large multi-dimensional databases
Information Systems
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Divide-and-conquer scheme for strictly optimal retrieval of range queries
ACM Transactions on Storage (TOS)
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ADVIS'04 Proceedings of the Third international conference on Advances in Information Systems
Online balancing of ar-tree indexed distributed spatial data warehouse
PPAM'05 Proceedings of the 6th international conference on Parallel Processing and Applied Mathematics
Generalized Optimal Response Time Retrieval of Replicated Data from Storage Arrays
ACM Transactions on Storage (TOS)
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We propose a method to achieve declustering for cartesian product files on M units. The focus is on range queries, as opposed to partial match queries that older declustering methods have examined. Our method uses a distance-preserving mapping, namely, the Hilbert curve, to impose a linear ordering on the multidimensional points (buckets); then, it traverses the buckets according to this ordering, assigning buckets to disks in a round-robin fashion. Thanks to the good distance-preserving properties of the Hilbert curve, the end result is that each disk contains buckets that are far away in the K-d address space. This is exactly the goal of declustering. Experiments show that these intuitive arguments lead indeed to good performance: the proposed method performs at least as well or better than older declustering schemes.