tailieunhanh - The LRU-K Page Replacement Algorithm For Database Disk Buffering

As detection of relationships improves with more samples and better methodology, families and super- families can become more populated. At present, structur- al relationships provide the highest level of classification, and structure-based databases classify proteins with similar ‘folds’. These classifications reveal that whenever structures are known for two proteins that are considered members of the same family or superfamily, the structures are similar, whereas the converse is often not true. Therefore, significant sequence similarity can be used to infer common structure (and common ancestry); however, similar structures that lack detectable sequence similarity may have resulted fromeither divergence beyond detection or convergence to a similar divergence froma common ancestor can occur with retention of. | The LRU-K Page Replacement Algorithm For Database Disk Buffering Elizabeth J. O Neil 1 Patrick E. O Neil 1 Gerhard Weikum 1 Department of Mathematics and Computer Science 2 Department of Computer Science University of Massachussetts at Boston ETH Zurich Harbor Campus CH-8092 Zurich Boston MA 02125-3393 Switzeriand E-mail eoneil@ poneil@ weikum@ ABSTRACT This paper introduces a new approach to database disk buffering called the LRƯ-K method. The basic idea of LRƯ-K is to keep track of the times of the last K references to popular database pages using this information to statistically estimate the interarrival times of references on a page by page basis. Although the LRU-K approach performs optimal statistical inference under relatively standard assumptions it is fairly simple and incurs little bookkeeping overhead. As we demonstrate with simulation experiments the LRU-K algorithm surpasses conventional buffering algorithms in discriminating between frequently and infrequently referenced pages. In fact LRU-K can approach the behavior of buffering algorithms in which page sets with known access frequencies are manually assigned to different buffer pools of specifically tuned sizes. Unlike such customized buffering algorithms however the LRU-K method is self-tuning and does not rely on external hints about workload characteristics. Furthermore the LRU-K algorithm adapts in real time to changing patterns of access. 1. Introduction Problem Statement All database systems retain disk pages in memory buffers for a period of time after they have been read in from disk and accessed by a particular application. The purpose is to keep popular pages memory resident and reduce disk I O. In their Five Minute Rule Gray and Putzolu pose the following tradeoff We are willing to pay more for memory buffers up to a certain point in order to reduce the cost of disk arms for a system GRAYPUT see also CKS . The critical buffering decision arises when a .