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

fYear

1999

fDate

36373

Firstpage

68

Lastpage

77

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Scientific and Statistical Database Management, 1999. Eleventh International Conference on

Conference_Location

Cleveland, OH

Print_ISBN

0-7695-0046-3

Type

conf

DOI

10.1109/SSDM.1999.787622

Filename

787622