Abstract
A number of insertions, updates and deletions eventually deteriorate the structural efficiency of database storage, and then cause performance degradation. This phenomenon is called “aging.” In real-world database systems, aging often exhibits strong locality because of the inherent skewness of data access; specifically speaking, the cost of I/O operations is not uniform throughout the storage space. Potentially query execution cost is influenced by the aging. However, conventional query optimizers do not consider the aging locality; thus they cannot accurately estimate the cost of query execution plans at times. In this paper, we propose a novel method of cost estimation that has the key capability of accurately determining aging phenomena, even though such phenomena are non-uniformly incurred. Our experiment on PostgreSQL and TPC-H data sets showed that the proposed method can accurately estimate the query execution cost even if it is influenced by the aging.
Keywords
C. Kato — Currently, Fujitsu Laboratories.
The original version of this chapter was revised: The authors’ affiliations were incorrect. An erratum to this chapter can be found at 10.1007/978-3-319-44406-2_40
An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-3-319-44406-2_40
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Kato, C., Hayamizu, Y., Goda, K., Kitsuregawa, M. (2016). Aging Locality Awareness in Cost Estimation for Database Query Optimization. In: Hartmann, S., Ma, H. (eds) Database and Expert Systems Applications. DEXA 2016. Lecture Notes in Computer Science(), vol 9828. Springer, Cham. https://doi.org/10.1007/978-3-319-44406-2_32
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DOI: https://doi.org/10.1007/978-3-319-44406-2_32
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