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In recent years, many researchers and vendors have proposed their XML storage approaches based on relational databases (RDB), which are called XML-relational databases (XRDB). To manipulate XML data in XRDB, many excellent model-mapping schemas were proposed to provide schema definitions to translate various XML documents with different structures into relational tables. Such an approach can support any sophisticated applications and well-formed XML documents. When XML data stored in an XRDB, the user query must be translated into the corresponding SQL commands, then executed in the relational database. However, most model-mapping-schema-based approaches have a potential performance problem for retrieving XML data from an XRDB, because a large number of join operations are needed. In this paper, a novel query preprocessing technique will be proposed to reduce the number of join operations from the corresponding SQL commands. The rationale behind our approach is to replace join operations by predefined constant-mapping selection operations. By reducing the number of join operations, the performance of query processing can be greatly improved. The capability of our proposed approach was verified by experiments, for which we have some encouraging results.

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A large-scaled RFID application often needs a highly efficient database system in data processing. This research is motivated by the strong demand of an efficient index structure design for main-memory database systems of RFID applications. In this paper, a signature-based grid index structure is proposed for efficient data queries and storage. An efficient methodology is proposed to locate duplicates and to execute batch deletions and range queries based on application domain knowhow. The capability of the design is implemented in an open source main-memory database system H2 and evaluated by realistic workloads of RFID applications.