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29 December 2008 DPR-tree: a distributed parallel spatial index structure for high performance spatial databases
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Proceedings Volume 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA); 72853A (2008) https://doi.org/10.1117/12.815628
Event: International Conference on Earth Observation Data Processing and Analysis, 2008, Wuhan, China
Abstract
Parallelism of spatial index could significantly improve the performance of spatial queries, special for massive spatial databases, so the research of parallel spatial index takes a important role in high performance spatial databases. Existing parallel spatial index methods have two main shortcoming: one is accessing hotspot and bottleneck of index items located in main server, the other is high costs and complicated operations for maintaining index consistency. Aim at these, a distributed parallel spatial index structure called DPR-tree is proposed. It splits whole index region into partition sub-regions by using Hilbert space-filling curve grid and organizes index sub-regions according to locality of spatial objects, then maps index sub-regions to partition sub-regions and assigns these index sub-regions to different computer nodes by a appointed map function, Each computer node manages a multi-level distributed sub-Rtree which is built from a index sub-region. Our experimental results indicate that the proposed parallel spatial index can achieve speedup well and offer significant potential for reducing query response time.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yan Zhou, Qing Zhu, and Qiang Liu "DPR-tree: a distributed parallel spatial index structure for high performance spatial databases", Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72853A (29 December 2008); https://doi.org/10.1117/12.815628
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