A High Performance System for Processing Queries on Distributed Geospatial Data Sets

The size of many geospatial databases has grown exponentially in recent years. This increase in size brings with it an increased requirement for additional CPU and I/O resources to handle the querying and retrieval of this data. A number of proprietary systems could be ideally suited for such tasks,...

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Published inHigh Performance Computing for Computational Science - VECPAR 2004 pp. 119 - 128
Main Authors Abdelguerfi, Mahdi, Mahadevan, Venkata, Challier, Nicolas, Flanagin, Maik, Shaw, Kevin, Ratcliff, Jay
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture Notes in Computer Science
Subjects
Applied sciences
Beowulf cluster
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Exact sciences and technology
Geospatial database
Parallel and distributed computing
Software
Performance evaluation
High performance
Database query
Query processing
Distributed database
Geographic information system
Database
Feasibility
Distributed computing
Online AccessGet full text
ISBN9783540254249
3540254242
ISSN0302-9743
1611-3349
DOI10.1007/11403937_10

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Abstract The size of many geospatial databases has grown exponentially in recent years. This increase in size brings with it an increased requirement for additional CPU and I/O resources to handle the querying and retrieval of this data. A number of proprietary systems could be ideally suited for such tasks, but are impractical in many situations because of their high cost. On the other hand, Beowulf clusters have gained popularity for providing such resources in a cost-effective manner. In this paper, we present a system that uses the compute nodes of a Beowulf cluster to store fragments of a large geospatial database and allows for the seamless viewing, querying, and retrieval of desired geospatial data in a parallel fashion i.e. utilizing the compute and I/O resources of multiple nodes in the cluster. Experimental results are provided to quantify the performance of the system and ascertain its feasibility versus traditional GIS architectures.
AbstractList The size of many geospatial databases has grown exponentially in recent years. This increase in size brings with it an increased requirement for additional CPU and I/O resources to handle the querying and retrieval of this data. A number of proprietary systems could be ideally suited for such tasks, but are impractical in many situations because of their high cost. On the other hand, Beowulf clusters have gained popularity for providing such resources in a cost-effective manner. In this paper, we present a system that uses the compute nodes of a Beowulf cluster to store fragments of a large geospatial database and allows for the seamless viewing, querying, and retrieval of desired geospatial data in a parallel fashion i.e. utilizing the compute and I/O resources of multiple nodes in the cluster. Experimental results are provided to quantify the performance of the system and ascertain its feasibility versus traditional GIS architectures.
Author Abdelguerfi, Mahdi
Shaw, Kevin
Challier, Nicolas
Flanagin, Maik
Mahadevan, Venkata
Ratcliff, Jay
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Hernández, Vicente
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Palma, José M. L. M.
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Keywords Performance evaluation
High performance
Database query
Query processing
Distributed database
Geographic information system
Database
Feasibility
Distributed computing
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Snippet The size of many geospatial databases has grown exponentially in recent years. This increase in size brings with it an increased requirement for additional CPU...
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StartPage 119
SubjectTerms Applied sciences
Beowulf cluster
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Exact sciences and technology
Geospatial database
Parallel and distributed computing
Software
Title A High Performance System for Processing Queries on Distributed Geospatial Data Sets
URI http://link.springer.com/10.1007/11403937_10
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