Using Horizontal-Vertical Decompositions to Improve Query Evaluation

Abstract

We investigate how relational restructuring may be used to improve query performance. Our approach parallels recent research extending semantic query optimization (SQO), which uses knowledge about the instance to achieve more efficient query processing. Our approach differs, however, in that the instance does not govern whether the optimization may be applied; rather, the instance governs whether the optimization yields more efficient query processing. It also differs in that it involves an explicit decomposition of the relation instance. We use approximate functional dependencies as the conceptual basis for this decomposition and develop query rewriting techniques to exploit it. We present experimental results using both synthetic and real-world data. These results lead to a characterization of a well-defined class of queries for which improved processing time is observed.