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dc.contributor.authorDeWitt, David J.en_US
dc.contributor.authorRobinson, Ericen_US
dc.contributor.authorShankar, Srinathen_US
dc.contributor.authorPaulson, Eriken_US
dc.contributor.authorNaughton, Jeffreyen_US
dc.contributor.authorRoyalty, Joshuaen_US
dc.contributor.authorKrioukov, Andrewen_US
dc.date.accessioned2012-03-15T17:23:27Z
dc.date.available2012-03-15T17:23:27Z
dc.date.created2007en_US
dc.date.issued2007
dc.identifier.citationTR1637en_US
dc.identifier.urihttp://digital.library.wisc.edu/1793/60638
dc.description.abstractThis paper introduces Clustera, an integrated computation and data management system. In contrast to traditional cluster-management systems that target specific types of workloads, Clustera is designed for extensibility, enabling the system to be easily extended to handle a wide variety of job types ranging from computationally-intensive, long-running jobs with minimal I/O requirements to complex SQL queries over massive relational tables. Another unique feature of Clustera is the way in which the system architecture exploits modern software building blocks including application servers and relational database systems in order to realize important performance, scalability, portability and usability benefits. Finally, experimental evaluation suggests that Clustera has good scale-up properties for SQL processing, that Clustera delivers performance comparable to Hadoop for MapReduce processing and that Clustera can support higher job throughput rates than previously published results for the Condor and CondorJ2 batch computing systems.en_US
dc.format.mimetypeapplication/pdfen_US
dc.publisherUniversity of Wisconsin-Madison Department of Computer Sciencesen_US
dc.titleClustera: An Integrated Computation And Data Management Systemen_US
dc.typeTechnical Reporten_US


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    Technical Reports Archive for the Department of Computer Sciences at the University of Wisconsin-Madison

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