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ABSTRACT
Generic database replication algorithms do not scale linearly in throughput as all update, deletion and insertion (UDI) queries must be applied to every database replica. The throughput is therefore limited to the point where the number of UDI queries alone is sufficient to overload one server. In such scenarios, partial replication of a database can help, as UDI queries are executed only by a subset of all servers. In this paper we propose GlobeTP, a system that employs partial replication to improve database throughput. GlobeTP exploits the fact that a Web application's query workload is composed of a small set of read and write templates. Using knowledge of these templates and their respective execution costs, GlobeTP provides database table placements that produce significant improvements in database throughput. We demonstrate the efficiency of this technique using two different industry standard benchmarks. In our experiments, GlobeTP increases the throughput by 57% to 150% compared to full replication, while using identical hardware configuration. Furthermore, adding a single query cache improves the throughput by another 30% to 60%.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 4
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Zhou Wei , Jiang Dejun , Guillaume Pierre , Chi-Hung Chi , Maarten van Steen, Service-oriented data denormalization for scalable web applications, Proceeding of the 17th international conference on World Wide Web, April 21-25, 2008, Beijing, China
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