Abstract
Autonomic databases are intended to reduce the total cost of ownership for a database system by providing self-management functionality. The self-management decisions heavily depend on the database workload, as the workload influences both the physical design and the DBMS configuration. In particular, a database reconfiguration is required whenever there is a significant change, i.e. shift, in the workload.
In this paper we present an approach for continuous, light-weight workload monitoring in autonomic databases. Our concept is based on a workload model, which describes the typical workload of a particular DBS using n-Gram-Models. We show how this model can be used to detect significant workload changes. Additionally, a processing model for the instrumentation of the workload is proposed. We evaluate our approach using several workload shift scenarios.
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Holze, M., Ritter, N. (2008). Autonomic Databases: Detection of Workload Shifts with n-Gram-Models. In: Atzeni, P., Caplinskas, A., Jaakkola, H. (eds) Advances in Databases and Information Systems. ADBIS 2008. Lecture Notes in Computer Science, vol 5207. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85713-6_10
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DOI: https://doi.org/10.1007/978-3-540-85713-6_10
Publisher Name: Springer, Berlin, Heidelberg
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