Managing Multiuser Database Buffers Using Data Mining Techniques

In this paper, we propose a data-mining-based approach to public buffer management for a multiuser database system, where database buffers are organized into two areas – <i>public</i> and <i>private</i>. While the private buffer areas contain pages to be updated by particular users, the public buffer area contains pages shared among different users. Unlike traditional buffer management strategies where limited knowledge of user access patterns is used, the proposed approach discovers knowledge from page access sequences of user transactions and uses it to guide public buffer <i>placement</i> and <i>replacement</i>. A <i>prefetch</i> strategy is exploited based on the discovered page access knowledge. In practice, to make such a data-mining-based buffer management approach tractable, we present a soft variation to approximate our absolute best buffer replacement solution. The knowledge to be discovered and the discovery methods are discussed in the paper. The effectiveness of the proposed approach was investigated through a simulation study. The results indicate that with the help of the discovered knowledge, the public buffer hit ratio can be improved significantly, while the added computational complexity, compared to the achievement in buffer hit ratio, is less. In some situations, the time cost of the data-mining-based buffer management policy is even lower than that of the simplest buffer management policy.