Opportunistic Prioritised Clustering Framework (OPCF)

Ever since the `early days' of database management systems, clustering has proven to be one of the most effective performance enhancement techniques for object oriented database management systems. The bulk of the work in the area has been on static clustering algorithms which re-cluster the object base when the database is off-line. However, this type of re-clustering cannot be used when 24-hour database access is required. In such situations on-line clustering is required, which allows the object base to be reclustered while the database is in operation. We believe that most existing on-line clustering algorithms lack three important properties. These include: the use of opportunism to imposes the smallest I/O footprint for re-organisation; the re-use of prior research on static clustering algorithms; and the prioritisation of re-clustering so that the worst clustered pages are re-clustered first. In this paper, we present OPCF, a framework in which any existing off-line cluste...

• Type: Conference
• Year: 2000
• Where: OODBS
• Authors: Zhen He, Alonso Marquez, Stephen Blackburn
• Keywords: Clustering Algorithms, Database, On-line Clustering, On-line Clustering Algorithms, OODBS 2000