Parallel bulk-loading of spatial data

被引：23

作者：

Papadopoulos, A ^{[1
]}

Manolopoulos, Y ^{[1
]}

机构：

[1] Aristotle Univ Thessaloniki, Dept Informat, GR-54006 Thessaloniki, Greece

来源：

PARALLEL COMPUTING | 2003年 / 29卷 / 10期

关键词：

parallel databases; spatial access methods; bulk-loading; query processing;

D O I：

10.1016/j.parco.2003.05.003

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Spatial database systems have been introduced in order to support non-traditional data types and more complex queries. Although bulk-loading techniques for access methods have been studied in the spatial database literature, parallel bulk-loading has not been addressed in a parallel spatial database context. Therefore, we study the problem of parallel bulk-loading, assuming that an R-tree like access method need to be constructed, from a spatial relation that is distributed to a number of processors. Analytical cost models and experimental evaluation based on real-life and synthetic datasets demonstrate that the index construction time can be reduced considerably by exploiting parallelism. I/O costs, CPU time and communication costs are taken into consideration in order to investigate the efficiency of the proposed algorithm. (C) 2003 Elsevier B.V. All rights reserved.

引用

页码：1419 / 1444

页数：26

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