XPath

Abstract: This article describes XRel, a novel approach for storage and retrieval of XML documents using relational databases. In this approach, an XML document is decomposed into nodes on the basis of its tree structure and stored in relational tables according to the node type, with path information from the root to each node. XRel enables us to store XML documents using a fixed relational schema without any information about DTDs and also to utilize indices such as the B 1 -tree and the R-tree supported by database management systems. Thus, XRel does not need any extension of relational databases for storing XML documents. For processing XML queries, we present an algorithm for translating a core subset of XPath expressions into SQL queries. Finally, we demonstrate the effectiveness of this approach through several experiments using actual XML documents.

Abstract: Our experimental analysis of several popular XPath processors reveals a striking fact: Query evaluation in each of the systems requires time exponential in the size of queries in the worst case. We show that XPath can be processed much more efficiently, and propose main-memory algorithms for this problem with polynomial-time combined query evaluation complexity. Moreover, we show how the main ideas of our algorithm can be profitably integrated into existing XPath processors. Finally, we present two fragments of XPath for which linear-time query processing algorithms exist and another fragment with linear-space/quadratic-time query processing.

Abstract: With the advent of native and XML enabled database systems, techniques for efficiently storing, indexing and querying large collections of XML documents have become an important research topic. This paper presents the storage, indexing and query processing architecture of eXist, an Open Source native XML database system. eXist is tightly integrated with existing tools and covers most of the native XML database features. An enhanced indexing scheme at the architecture's core supports quick identification of structural node relationships. Based on this scheme, we extend the application of path join algorithms to implement most parts of the XPath query language specification and add support for keyword search on element and attribute contents.

Abstract: The emergence of the Web has increased interests in XML data. XML query languages such as XQuery and XPath use label paths to traverse the irregularly structured data. Without a structural summary and efficient indexes, query processing can be quite inefficient due to an exhaustive traversal on XML data. To overcome the inefficiency, several path indexes have been proposed in the research community. Traditional indexes generally record all label paths from the root element in XML data. Such path indexes may result in performance degradation due to large sizes and exhaustive navigations for partial matching path queries start with the self-or-descendent axis("//").In this paper, we propose APEX, an adaptive path index for XML data. APEX does not keep all paths starting from the root and utilizes frequently used paths to improve the query performance. APEX also has a nice property that it can be updated incrementally according to the changes of query workloads. Experimental results with synthetic and real-life data sets clearly confirm that APEX improves query processing cost typically 2 to 54 times better than the existing indexes, with the performance gap increasing with the irregularity of XML data.