Performance analysis of a relational data base management system

Abstract

The effect on the performance of data management systems of the use of extended storage devices, multiple processors and prefetching data blocks is analyzed with respect to one system, INGRES. Benchmark query streams, derived from user queries, were run on the INGRES system and their CPU usage and data reference patterns traced. The results show that the performance characteristics of two query types: data-intensive queries and overhead-intensive queries, are so different that it may be difficult to design a single architecture to optimize the performance of both types. It is shown that the random access model of data references holds only for overhead-intensive queries, and then only if references to system catalogs are not considered data references. Significant sequentiality of reference was found in the data-intensive queries. It is shown that back-end data management machines that distribute processing toward the data may be cost effective only for data-intensive queries. It is proposed that the best method of distributing the processing of the overhead-intensive query is through the use of intelligent terminals. A third benchmark set, multi-relation queries, was devised, and proposals are made for taking advantage of the locality of reference which was found.