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Resource Efficient Parallel VLDB with Customizable Degree of Redundancy
Xiong, Fanfan
Xiong, Fanfan
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Thesis/Dissertation
Date
2009
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Computer and Information Science
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http://dx.doi.org/10.34944/dspace/3847
Abstract
This thesis focuses on the practical use of very large scale relational databases. It leverages two recent breakthroughs in parallel and distributed computing: a) synchronous transaction replication technologies by Justin Y. Shi and Suntain Song; and b) Stateless Parallel Processing principle pioneered by Justin Y. Shi. These breakthroughs enable scalable performance and reliability of database service using multiple redundant shared-nothing database servers. This thesis presents a Functional Horizontal Partitioning method with customizable degree of redundancy to address practical very large scale database applications problems. The prototype VLDB implementation is designed for transparent non-intrusive deployments. The prototype system supports Microsoft SQL Servers databases. Computational experiments are conducted using industry-standard benchmark (TPC-E).
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