Master-client R-trees: a new parallel R-tree architecture

Master-client R-trees: a new parallel R-tree architecture
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DOI:
10.1109/ssdm.1999.787622
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发表时间:
1999-07
期刊:
Proceedings. Eleventh International Conference on Scientific and Statistical Database Management
影响因子:
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通讯作者:
Bernd Schnitzer;Scott T. Leutenegger
Bernd Schnitzer;Scott T. Leutenegger
中科院分区:
其他
文献类型:
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作者:
Bernd Schnitzer;Scott T. Leutenegger

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科学数据库必须能够有效地运行多维数据集的子集检索。如果数据集是非常大的,显着的检索加速可以通过并行获得。在本文中,我们提出了一种新的并行分布式无共享R树结构。我们提供的实验结果表明实际的加速几个合成和真实的数据集。此外,我们进行了实验研究,调查几个去聚类策略和通信参数的效果。
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.