XQuery is a query language under development by the W3C XML Query Working Group. The language contains constructs for navigating, searching, and restructuring XML data. With XML gaining importance as the standard for representing business data, XQuery must support the types of queries that are common in business analytics. One such class of queries is OLAP-style aggregation queries. Although these queries are expressible in XQuery Version 1, the lack of explicit grouping constructs makes the construction of these queries non-intuitive and places a burden on the XQuery engine to recognize and optimize the implicit grouping constructs. Furthermore, although the flexibility of the XML data model provides an opportunity for advanced forms of grouping that are not easily represented in relational systems, these queries are difficult to express using the current XQuery syntax. In this paper, we provide a proposal for extending the XQuery FLWOR expression with explicit syntax for grouping and for numbering of results. We show that these new XQuery constructs not only simplify the construction and evaluation of queries requiring grouping and ranking but also enable complex analytic queries such as moving-window aggregation and rollups along dynamic hierarchies to be expressed without additional language extensions.

XML languages, such as XQuery, XSLT and SQL/XML, employ XPath as the search and extraction language. XPath expressions often define complicated navigation, resulting in expensive query processing, especially when executed over large collections of documents. In this paper, we propose a framework for exploiting materialized XPath views to expedite processing of XML queries. We explore a class of materialized XPath views, which may contain XML fragments, typed data values, full paths, node references or any combination thereof. We develop an XPath matching algorithm to determine when such views can be used to answer a user query containing XPath expressions. We use the match information to identify the portion of an XPath expression in the user query which is not covered by the XPath view. Finally, we construct, possibly multiple, compensation expressions which need to be applied to the view to produce the query result. Experimental evaluation, using our prototype implementation, shows that the matching algorithm is very efficient and usually accounts for a small fraction of the total query compilation time.

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After a discussion of the theory of software agents, this book presents IMPACT (Interactive Maryland Platform for Agents Collaborating Together), an experimental agent infrastructure that translates formal theories of agency into a functional multiagent system that can extend legacy software code and application-specific or legacy data structures. Software agents are the latest advance in the trend toward smaller, modular pieces of code, where each module performs a well-defined, focused task or set of tasks. Programmed to interact with and provide services to other agents, including humans, software agents act autonomously with prescribed backgrounds, beliefs, and operations. Systems of agents can access and manipulate heterogeneously stored data such as that found on the Internet. After a discussion of the theory of software agents, this book presents IMPACT (Interactive Maryland Platform for Agents Collaborating Together), an experimental agent infrastructure that translates formal theories of agency into a functional multiagent system that can extend legacy software code and application-specific or legacy data structures. The book describes three sample applications: a store, a self-correcting auto-pilot, and a supply chain.

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