Spatio-temporal data services in a shared-nothing environment
Spatio-temporal data services in a shared-nothing environment
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DOI：
10.1109/ssdbm.2004.65
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发表时间：
2004-06
期刊：
影响因子：
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通讯作者：
Marios Hadjieleftheriou;V. Kriakov;Yangui Tao;G. Kollios;A. Delis;V. Tsotras
中科院分区：
文献类型：
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作者：
Marios Hadjieleftheriou;V. Kriakov;Yangui Tao;G. Kollios;A. Delis;V. Tsotras
最近，已经有一个激增的应用程序，产生时空数据，必须进行有效的处理，存储和查询。这些应用程序需要执行数百万次更新，以保持底层数据库最新。因此，需要能够支持这种更新密集型操作的时空数据管理系统。此外，这些系统应使用户能够以联机方式审查目前和过去的（历史）数据版本。我们提出了一个系统，利用了固有的并行性的无共享的计算环境存储和索引的时空数据。我们描述了我们提出的系统架构，数据组织和大纲技术，以确保在过度的查询负载和高更新率的鲁棒性和可扩展性。
Recently, there has been a proliferation of applications that produce spatiotemporal data that has to be processed, stored and queried efficiently. These applications necessitate the execution of millions of updates in order to keep the underlying database up-to-date. Consequently, there is a need for spatiotemporal data management systems that are able to support such update intensive operations. Moreover, these systems should offer users the capability to examine present as well as past (historical) data versions in an on-line fashion. We propose a system that exploits the inherent parallelism of a shared-nothing computing environment for storing and indexing the spatiotemporal data. We describe our proposed system architecture, data organization, and outline techniques for ensuring robustness and scalability under excessive query loads and high update rates.