Exploiting inheritance and structure semantics for effective clustering and buffering in an object-oriented DBMS

Abstract

Object-oriented databases provide new kinds of data semantics in terms of inheritance and structural relationships. This paper examines how to use these additional semantics to obtain more effective object buffering and clustering. We use the information collected from real-world object-oriented applications, the Berkeley CAD Group's OCT design tools, as the basis for a simulation model with which to investigate alternative buffering and clustering strategies. Observing from our measurements that real CAD applications exhibit high data read to write ratios, we propose a run-time clustering algorithm whose initial evaluation indicates that system response time can be improved by a factor of 200% when the read/write ratio is high. We have also found it useful to limit the amount of I/O allowed to the clustering algorithm as it examines candidate pages for clustering at run-time. Basically, there is little performance distinction between limiting reclustering to a few I/Os or many, so a low limit on I/O appears to be acceptable. We also examine, under a variety of workload assumptions, context-sensitive buffer replacement policies with alternative prefetching policies.