The W3C XQuery language recommendation, based on a hierarchical and ordered document model, supports a wide variety of constructs and use cases. There is a diversity of approaches and strategies for evaluating XQuery expressions, in many cases only dealing with limited subsets of the language. In this paper we describe an implementation approach that handles XQuery with arbitrarily-nested FLWR expressions, element constructors and built-in functions (including structural comparisons). Our proposal maps an XQuery expression to a single equivalent SQL query using a novel dynamic interval encoding of a collection of XML documents as relations, augmented with information tied to the query evaluation environment. The dynamic interval technique enables (suitably enhanced) relational engines to produce predictably good query plans that do not restrict the use of sort-merge join query operators. The benefits are realized despite the challenges presented by intermediate results that create arbitrary documents and the need to preserve document order as prescribed by semantics of XQuery. Finally, our experimental results demonstrate that (native or relational) XML systems can benefit from the above technique to avoid a quadratic scale up penalty that e#ectively prevents the evaluation of nested FLWR expressions for large documents.

Several alternatives to manage large XML document collections exist, ranging from file systems over relational or other database systems to specifically tailored XML repositories. In this paper we give a tour of Natix, a database management system designed from scratch for storing and processing XML data. Contrary

We have developed a new approach for reliably multicasting timecritical data to heterogeneous clients over mesh-based overlay networks. To facilitate intelligent content pruning, data streams are comprised of a sequence of XML packets and forwarded by application-level XML routers. XML routers perform contentbased routing of individual XML packets to other routers or clients based upon queries that describe the information needs of downstream nodes. Our PC-based XML router prototype can route an 18 Mbit per second XML stream. Our routers use

Relational database systems may be turned into efficient XML and XPath processors if the system is provided with a suitable relational tree encoding. This paper extends this relational XML processing stack and shows that an RDBMS can also serve as a highly efficient XQuery runtime environment. Our approach is purely relational: XQuery expressions are compiled into SQL code which operates on the tree encoding. The core of the compilation procedure trades XQuery’s notions of variable scopes and nested iteration (FLWOR blocks) for equi-joins. The resulting relational XQuery processor closely adheres to the language semantics, e.g., it respects node identity as well as document and sequence order, and can support XQuery’s full axis feature. The system exhibits quite promising performance figures in experiments. Somewhat unexpectedly, we will also see that the XQuery compiler can make good use of SQL’s OLAP functionality. 1

XML documents are typically queried with a combination of value search and structure search. While querying by values can leverage traditional database technologies, evaluating structural relationship, specifically parent-child or ancestor-descendant relationship, between XML element sets has imposed a great challenge on efficient XML query processing. This paper proposes XR-tree, namely, XML Region Tree, which is a dynamic external memory index structure specially designed for strictly nested XML data. The unique feature of XR-tree is that, for a given element, all its ancestors (or descendants) in an element set indexed by an XRtree can be identified with optimal worst case I/O cost. We then propose a new structural join algorithm that can evaluate the structural relationship between two XR-tree indexed element sets by effectively skipping ancestors and descendants that do not participate in the join. Our extensive performance study shows that the XR-tree based join algorithm significantly outperforms previous algorithms. 1.

Finding all the occurrences of a twig pattern specified by a selection predicate on multiple elements in an XML document is a core operation for e#cient evaluation of XML queries. Holistic twig join algorithms were proposed recently as an optimal solution when the twig pattern only involves ancestordescendant relationships. In this paper, we address the problem of e#cient processing of holistic twig joins on all/partly indexed XML documents. In particular, we propose an algorithm that utilizes available indices on element sets. While it can be shown analytically that the proposed algorithm is as e#cient as the existing state-of-the-art algorithms in terms of worst case I/O and CPU cost, experimental results on various datasets indicate that the proposed index-based algorithm performs significantly better than the existing ones, especially when binary structural joins in the twig pattern have varying join selectivities.

This article is a proposal for a database index structure, the XPath accelerator, that has been specifically designed to support the evaluation of XPath path expressions. As such, the index is capable to support all XPath axes (including ancestor, following, preceding-sibling, descendant-or-self, etc.). This feature lets the index stand out among related work on XML indexing structures which had a focus on the child and descendant axes only. The index has been designed with a close eye on the XPath semantics as well as the desire to engineer its internals so that it can be supported well by existing relational database query processing technology: the index (a) permits set-oriented (or, rather, sequence-oriented) path evaluation, and (b) can be implemented and queried using well-established relational index structures, notably B-trees and R-trees

Like HTML, many XML documents are resident on native file systems. Since XML data is irregular and verbose, the disk space and the network bandwidth are wasted. To overcome the verbosity problem, the research on compressors for XML data has been conducted. However, some XML compressors do not support querying compressed data, while other XML compressors which support querying compressed data blindly encode tags and data values using predefined encoding methods. Thus, the query performance on compressed XML data is degraded. In this paper, we propose XPRESS, an XML compressor which supports direct and efficient evaluations of queries on compressed XML data. XPRESS adopts a novel encoding method, called reverse arithmetic encoding, which is intended for encoding label paths of XML data, and applies diverse encoding methods depending on the types of data values. Experimental results with real-life data sets show that XPRESS achieves significant improvements on query performance for compressed XML data and reasonable compression ratios. On the average, the query performance of XPRESS is 2.83 times better than that of an existing XML compressor and the compression ratio of XPRESS is 73%. 1.

XML is the W3C standard document format for writing and exchanging information on the Web. RDF is the W3C standard model for describing the semantics and reasoning about information on the Web. Unfortunately, RDF and XML---although very close to each other---are based on two different paradigms. We argue that in order to lead the Semantic Web to its full potential, the syntax and the semantics of information needs to work together. To this end, we develop a model theory for the XML XQuery 1.0 and XPath 2.0 Data Model, which provides a unified model for both XML and RDF. This unified model can serve as the basis for Web applications that deal with both data and semantics. We illustrate the use of this model on a concrete information integration scenario. Our approach enables each side of the fence to benefit from the other, notably, we show how the RDF world can take advantage of XML query languages, and how the XML world can take advantage of the reasoning capabilities available for RDF.

Most proposals for XML query languages are based on the data-centric view on XML and do not support uncertainty and vagueness, thus being insuitable for information retrieval (IR) of XML documents. Based on the document-centric view, we present the query language XIRQL which implements IR-related features such as weighting and ranking, relevance-oriented search, datatypes with vague predicates, and structural relativism. XIRQL integrates these features by using ideas from logic-based probabilistic IR models, in combination with concepts from the database area. For processing XIRQL queries, a path algebra is presented which also serves as a starting point for query optimization.