Pattern based processing of XPath queries

As the popularity of areas including document storage and distributed systems continues to grow, the demand for high performance XML databases is increasingly evident. This has led to a number of research eorts aimed at exploiting the maturity of relational database systems in order to in- crease XML query performance. In our approach, we use an index structure based on a metamodel for XML databases combined with relational database technology to facilitate fast access to XML document elements. The query process involves transforming XPath expressions to SQL which can be executed over our optimised query engine. As there are many dierent types of XPath queries, varying processing logic may be applied to boost performance not only to indi- vidual XPath axes, but across multiple axes simultaneously. This paper describes a pattern based approach to XPath query processing, which permits the execution of a group of XPath location steps in parallel

A Bi-Labeling Based XPath Processing System

We present BLAS, a Bi-LAbeling based XPath processing System. BLAS uses two labeling schemes to speed up query processing: P-labeling for processing consecutive child (or parent) axis traversals, and D-labeling for processing descendant (or ancestor) axis traversals. XML data are stored in labeled form and indexed. Algorithms are presented for translating XPath queries to SQL expressions. BLAS reduces the number of joins in the SQL query translated from a given XPath query and reduces the number of disk accesses required to execute the SQL query compared with the traditional XPath processing using D-labeling alone. We also propose an approximate P-labeling scheme and the corresponding query translation algorithm to handle XML data trees that contain a large number of distinct tag names, and/or are very deep. This extension captures a spectrum of XPath-to-SQL query translation schemes, ranging from existing schemes that do not use P-labels to the one that uses exact P-labels. Experimental results demonstrate the efficiency of the BLAS system

SMOQE: A System for Providing Secure Access to XML

XML views have been widely used to enforce access control, support data integration, and speed up query answering. In many applications, e.g., XML security enforcement, it is prohibitively expensive to materialize and maintain a large number of views. Therefore, views are necessarily virtual. An immediate question then is how to answer queries on XML virtual views. A common approach is to rewrite a query on the view to an equivalent one on the underlying document, and evaluate the rewritten query. This is the approach used in the Secure MOdular Query Engine (SMOQE). The demo presents SMOQE, the first system to provide efficient support for answering queries over virtual and possibly recursively defined XML views. We demonstrate a set of novel techniques for the specification of views, the rewriting, evaluation and optimization of XML queries. Moreover, we provide insights into the internals of the engine by a set of visual tools. 1

Querying XML data streams from wireless sensor networks: an evaluation of query engines

As the deployment of wireless sensor networks increase and their application domain widens, the opportunity for effective use of XML filtering and streaming query engines is ever more present. XML filtering engines aim to provide efficient real-time querying of streaming XML encoded data. This paper provides a detailed analysis of several such engines, focusing on the technology involved, their capabilities, their support for XPath and their performance. Our experimental evaluation identifies which filtering engine is best suited to process a given query based on its properties. Such metrics are important in establishing the best approach to filtering XML streams on-the-fly

TypEx : a type based approach to XML stream querying

We consider the topic of query evaluation over semistructured information streams, and XML data streams in particular. Streaming evaluation methods are necessarily eventdriven, which is in tension with high-level query models; in general, the more expressive the query language, the harder it is to translate queries into an event-based implementation with finite resource bounds

Reasoning & Querying – State of the Art

Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF