Abstract

XML is a self-describing meta-language and fast emerging as a dominant standard for Web data exchange among various applications. With the tremendous growth of XML documents, an efficient storage system is required to manage them. The conventional databases, which require all data to adhere to an explicitly specified rigid schema, are unable to provide an efficient storage for tree-structured XML documents. A new data model that is specifically designed for XML documents is required. In this paper, we propose a new storage system, named Efficient Native XML Storage System (ENAXS), for large and complex XML documents. ENAXS stores all XML documents in its native format to overcome the deficiencies of the conventional databases, achieve optimal storage utilization and support efficient query processing. In addition, we propose a path-based indexing scheme which is embedded in ENAXS for fast data retrieval. We have implemented ENAXS and evaluated its performance with real data sets. Experimental results show the efficiency and scalability of the proposed system in utilizing storage space and executing various types of queries.KeywordsQuery ProcessingNode GroupQuery ExecutionPath QueryNode InfoThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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