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Much of business XML data has accompanying XSD specifications. In many scenarios "shredding" such XML data into a relational storage is a popular paradigm. Optimizing evaluation of XPath queries overmuch XML data requires paying careful attention to both the logical and physical designs of the relational database where XML data is shredded. None of the existing solutions has taken into account physical design of the generated relational database. In this paper, we study the interplay of logical and physical design and conclude that 1) solving them independently leads to suboptimal performance and 2) there is substantial overlap between logical and physical designs: some well-known logical design transformations generate the same mappings as physical design. Furthermore, existing search algorithms are inefficient to search the extremely large space of logical and physical design combinations. We propose a search algorithm that carefully avoids searching duplicated mappings and utilizes the workload information to further prune the search space. Experimental results confirm the effectiveness of our approach.