From XML schema to relations: A cost-based approach to XML storage

As Web applications manipulate an increasing amount of XML, there is a growing interest in storing XML data in re-lational databases. Due to the mismatch between the com-plexity of XML’s tree structure and the simplicity of flat re-lational tables, there are many ways to store the same doc-ument in an RDBMS, and a number of heuristic techniques have been proposed. These techniques typically define fixed mappings and do not take application characteristics into account. However, a fixed mapping is unlikely to work well for all possible applications. In contrast, LegoDB is a cost-based XML storage mapping engine that explores a space of possible XML-to-relational mappings and selects the best mapping for a given application. LegoDB leverages cur-rent XML and relational technologies: 1) it models the tar-get application with an XML Schema, XML data statistics, and an XQuery workload; 2) the space of configurations is generated through XML-Schema rewritings; and 3) the best among the derived configurations is selected using cost es-timates obtained through a standard relational optimizer. In this paper, we describe the LegoDB storage engine and pro-vide experimental results that demonstrate the effectiveness of this approach.