A functional clustering method for optimal access to complex domains in a relational DBMS

The authors present a clustering method for complex domains. The method is original in that tuples can be clustered using functions applied to complex domain values. Thus, tuples are organized according to a function result. Those functions most often applied to complex values and used in the restriction part of queries can be used as clustering predicates. Hence, they optimize the retrieval of tuples that would otherwise require processing the whole relation. In SABRINA, complex domain processing is made possible by a Lisp language processor designed as an integrated database management system processor. Clustering is determined by a set of predicates defining a recursive partitioning of the relation. These predicates are the Lisp functions, taken from the set of functions applicable to a given domain. The authors demonstrate that by using the same approach for a data manipulation language and a clustering strategy, few modifications of the DBMS program are required and the assertional power of the DBMS is upgraded while respecting performance considerations.<
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