Multiple query optimization with depth-first branch-and-bound and dynamic query ordering

In certain database applications such as deductive databases, batch query processing, and recursive query processing etc., a single query can be transformed into a set of closely related database queries. Great benefits can be obtained by executing a group of related queries all together in a single unified multi-plan instead of executing each query separately. In order to achieve this, Multiple Query Optimization (MQO) identifies common task(s) (e.g. common subexpressions, joins, etc.) among a set of query plans and creates a single unified plan (multiplan) which can be executed to obtain the required outputs for all queries at once. In this paper, a new heuristic function (f_c), dynamic query ordering heuristics, and Depth-First Branch-and-Bound (DFBB) are defined and experimentally evaluated, and compared with existing methods which use A* and static query ordering. Our experiments show that all three of f_c, DFBB, and dynamic query ordering help to improve the performance of our MQO algorithm.