Abstract
This paper adresses the problem of clustering complex data on disk to minimize the number of I/O in data intensive applications. It describes the clustering strategies adopted in the O2 system. As clustering depends on both structural aspects (composition hierarchy of the classes) and dynamic aspects (the methods associated with the classes) the paper details a cost model in order to evaluate the benefits of the clustering strategies. This model will permit to automatically derive new clustering strategies. To this end, a derivation algorithm which builds an optimal strategy in linear time is presented.
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© 1990 Springer-Verlag Berlin Heidelberg
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Benzaken, V. (1990). An evaluation model for clustering strategies in the O2 object-oriented database system. In: Abiteboul, S., Kanellakis, P.C. (eds) ICDT '90. ICDT 1990. Lecture Notes in Computer Science, vol 470. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-53507-1_74
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DOI: https://doi.org/10.1007/3-540-53507-1_74
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