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Spatial Data Indexing and Query Processing in GeoCloud
Published in ASTM International
2019
Volume: 47
   
Issue: 6
Abstract
GeoCloud is essential for spatial data management. This article depicts GeoCloud and SpatialHadoop, both of which are developed for spatial information, indexing, and query processing. It contains traditional spatial indexing that comprises R-tree, Hilbert R-tree, and improved Bloom filter tree. We enhance the query search by utilizing Spatial Join, Range Query, k-nearest neighbor (k-NN), and Max k-NN queries. By doing so, we implement the data structures and query evaluation performance of different spatial datasets in GeoCloud instances with SpatialHadoop. We show that our proposed system is more efficient in terms of data storage and retrieval in GeoCloud. © 2019 by ASTM International.
About the journal
JournalData powered by TypesetJournal of Testing and Evaluation
PublisherData powered by TypesetASTM International
ISSN0090-3973
Impact FactorNo
Open Access0
Citation Styleunsrt