Parallelism in relational data base systems: Architectural issues and design approaches

Abstract

The issues and solutions relation to intra-query parallelism in a relational DBMS (database management systems) supporting SQL are addressed. Instead of focusing on only a few algorithms for a subset of the problems, a broad framework for the study of the numerous issues that need to be addressed in supporting parallelism efficiently and flexibly is provided. The impact that parallelization of complex queries has on short transactions which have stringent response time constraints is discussed. The advantages and disadvantages of the shared nothing, shared disks, and shared everything architectures for parallelism are enumerated. The impact of parallelism on a number of components of an industrial-strength DBMS are pointed out. The different stages of query processing during which parallelism may be gainfully used are identified. The interactions between parallelism and the traditional systems' pipelining technique are analyzed. Finally, the performance implications of parallelizing a specific complex query are studied. This gives a range of sample points for different parameters of a parallel system architecture, namely I/O and communication bandwidth as a function of aggregate MIPS (million instruction per second).