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An under-appreciated tuning principle asserts start-up costs are high; running costs are low. When applied to the application level, this principle suggests performance of a few bulk operations that manipulate and transport a lot of data rather than many small operations that act on small amounts of data. To make this concrete, this entry discusses several examples and draws lessons from each.
Historical Background
Application-level tuning is about changing the way a task is performed. This entails finding a better algorithm or finding a better way to handle the database. The first is difficult to automate, but the latter goes back to the very first use of the relational databases. Whether on disk or in main memory, databases have generally always performed best when a single statement accesses all and exactly the data needed for a task.
Foundations
Application-level tuning has the nice property that it often is a pure...
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Recommended Reading
Celko J. Joe celko’s SQL for smarties: advanced SQL programming. 3rd ed. San Francisco: Morgan Kaufmann; 2005.
Shasha D, Bonnet P. Database tuning: principles, experiments and troubleshooting techniques. San Francisco: Morgan Kaufmann; 2002.
Tow D. SQL tuning. Beijing: O’Reilly; 2003.
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Bonnet, P., Shasha, D. (2016). Application-Level Tuning. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_805-2
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DOI: https://doi.org/10.1007/978-1-4899-7993-3_805-2
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Publisher Name: Springer, New York, NY
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