Theses and Dissertations from UMD

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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM

More information is available at Theses and Dissertations at University of Maryland Libraries.

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Author: search.filters.author.Zhou, YifanSubject: search.filters.subject.Database Systems

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    Extensions of an Empirical Automated Tuning Framework
    (2013) Zhou, Yifan; Hollingsworth, Jeffery K; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Empirical auto-tuning has been successfully applied to scientific computing applications and web-based cluster servers over the last few years. However, few studies are focused on applying this method on optimizing the performance of database systems. In this thesis, we present a strategy that uses Active Harmony, an empirical automated tuning framework to optimize the throughput of PostgreSQL server by tuning its settings such as memory and buffer sizes. We used Nelder-Mead simplex method as the search engine, and we showed how our strategy performs compared to the hand-tuned and default results. Another part of this thesis focuses on using data from prior runs of auto-tuning. Prior data has been proved to be useful in many cases, such as modeling the search space or finding a good starting point for hill-climbing. We present several methods that were developed to manage the prior data in Active Harmony. Our intention was to provide tuners a complete set of information for their tuning tasks.