Clustering Algorithms for Object-Oriented Databases

Jérôme Darmont (1) , Le Gruenwald (1)

1 Computer Science Department- University of Oklahoma

It is widely acknowledged that good object clustering is critical to the performance of OODBs. Clustering means storing related objects close together on secondary storage so that when one object is accessed from disk, all its related objects are also brought into memory. Then access to these related objects is a main memory access that is much faster than a disk access. The aim of this paper is to compare the performance of three clustering algorithms: Cactis, CK and ORION. Simulation experiments we performed showed that the Cactis algorithm is better than the ORION algorithm and that the CK algorithm totally outperforms both other algorithms in terms of response time and clustering overhead.

Mots clés: Cactis; CK; Clustering; Object-Oriented Databases; ORION; Simulation

Domaines: Base de données [cs.DB]

Jérôme Darmont, Le Gruenwald. Clustering Algorithms for Object-Oriented Databases. 1996 Symposium on Object-Oriented Database Management Systems, ASME Engineering Systems Design and Analysis Conference (ESDA 1996), ASME International, Jul 1996, Montpellier, France. pp.115-123. ⟨hal-01773441⟩