Title :
Master-client R-trees: a new parallel R-tree architecture
Author :
Schnitzer, Bernd ; Leutenegger, Scott T.
Author_Institution :
Dept. of Comput. Sci. IV, Erlangen-Nurnberg Univ., Germany
Abstract :
Scientific databases must be able to efficiently run subset retrievals of multidimensional data sets. If the data sets are very large, significant retrieval speedups can be obtained via parallelism. In this paper, we present a new parallel distributed shared-nothing R-tree architecture. We provide experimental results demonstrating actual speedups for several synthetic and real data sets. In addition, we conduct experimental studies to investigate the effect of several declustering strategies and communication parameters
Keywords :
parallel architectures; parallel databases; scientific information systems; software performance evaluation; tree data structures; communication parameters; declustering strategies; distributed shared-nothing architecture; master-client R-trees; multidimensional data sets; parallel R-tree architecture; retrieval speedup; scientific databases; subset retrievals; Computer architecture; Computer science; Data visualization; Databases; Indexing; Information retrieval; Numerical simulation; Parallel processing; Round robin; Supercomputers;
Conference_Titel :
Scientific and Statistical Database Management, 1999. Eleventh International Conference on
Conference_Location :
Cleveland, OH
Print_ISBN :
0-7695-0046-3
DOI :
10.1109/SSDM.1999.787622
