Abstract
In this paper, we present a new clustering algorithm called the High Fan Out algorithm and then give the performance comparison of the High Fan Out (HFO) algorithm, Kemighan-Lin based algorithms, and the Probability Ranking Partitioning algorithm for a persistent C++(C**) implementation in a single user environment where the global request stream follows a pattern most of the time. The global request stream is obtained through OO7 Benchmark. It is shown than HFO algorithm performs the best when object sizes are uniform and the cache sizes are relatively large. We conclude with a table that indicates the best clustering algorithm to be used depending on the characteristics of the database application at hand and the restrictions imposed by the computer system. It is also indicated that, the performance of a clustering algorithm can not be based solely on the communication cost, or on the amount of internal fragmentation. On the contrary both of the measures should be taken into account to predict the number of cache misses.
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© 1995 Springer-Verlag Berlin Heidelberg
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Koc, K., Dogac, A., Evrendilek, C. (1995). Comparison of Clustering Algorithms in a Single User Environment through OO7 Benchmark. In: Eder, J., Kalinichenko, L.A. (eds) East/West Database Workshop. Workshops in Computing. Springer, London. https://doi.org/10.1007/978-1-4471-3577-7_6
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DOI: https://doi.org/10.1007/978-1-4471-3577-7_6
Publisher Name: Springer, London
Print ISBN: 978-3-540-19946-5
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