A number of techniques have been developed to facilitate powerful data retrieval on the Web and Semantic Web. Three categories of Web query languages can be distinguished, according to the format of the data they can retrieve: XML, RDF and Topic Maps. This article introduces the spectrum of languages falling into these categories and summarises their salient aspects. The languages are introduced using common sample data and query types. Key aspects of the query languages considered are stressed in a conclusion.

/pdf/web-and-semantic-web-query-languages-a-survey-3uzduf3p8e.pdf

Web and semantic web query languages: a survey

An optimizer/normalizer is used to generate optimized intermediate language representation of an input query, such as an XML input query. A method of optimization of an input query in intermediate language form includes receiving the input query, examining the nodes in a left-depth first manner to identify code patterns and node types which are subjects for optimization, tagging the identified code patterns until the intermediate language representation of the input query has been examined in its entirety, searching from the top of the intermediate language representation for tagged code patterns, and adjusting the tagged code patterns with improved code patterns to form an optimal representation for an input query. The input to the optimizer/normalizer is assumed to be an input query transformed into an intermediate language representation containing code patterns and nodes, each node having a respective node type.

Query optimizer system and method

A data access architecture is provided that includes a mapping architecture for mapping data as may be used by an application to data as persisted in a database. The mapping architecture makes use of two types of mapping views—a query view that helps in translating queries and an update view that helps in translating updates. Incremental view maintenance can be used to translate data between the application and database.

Mapping architecture with incremental view maintenance

This paper addresses the question of updating relational databases through XML views. Using query trees to capture the notions of selection, projection, nesting, grouping, and heterogeneous sets found throughout most XML query languages, we show how XML views expressed using query trees can be mapped to a set of corresponding relational views. We then show how updates on the XML view are mapped to updates on the corresponding relational views. Existing work on updating relational views can then be leveraged to determine whether or not the relational views are updatable with respect to the relational updates, and if so, to translate the updates to the underlying relational database.

/pdf/from-xml-view-updates-to-relational-view-updates-old-1u0r3jd7zy.pdf

From XML view updates to relational view updates: old solutions to a new problem

This paper presents a study of Geography Markup Language (GML), the issues that arise from using GML for spatial applications, including storage, parsing, querying and visualization, as well as the use of GML for mobile devices and web services. GML is a modeling language developed by the Open Geospatial Consortium (OGC) as a medium of uniform geographic data storage and exchange among diverse applications. Many new XML-based languages are being developed as open standards in various areas of application. It would be beneficial to integrate such languages with GML during the developmental stages, taking full advantage of a non-proprietary universal standard. As GML is a relatively new language still in development, data processing techniques need to be refined further in order for GML to become a more efficient medium for geospatial applications.

Advances in GML for Geospatial Applications

Modern data sources, including structural and semi-structural sources, often export XML views over base data, and at times may materialize their views by storing the XML query result to provide faster data access. It is typically more efficient to maintain a view by incrementally propagating the base changes to the view than by re-computing it from scratch. Techniques for the incremental maintenance of relational views have been extensively studied in the literature. However, the maintenance of views created using XQuery is as of now unexplored. In this paper we propose an algebraic approach for incremental XQuery view maintenance. In our approach, an update to the XML source is transformed into a set of well defined update primitives which are propagated through the XML algebra tree. This algebraic update propagation process generates incremental update primitives to be applied to the result view. We briefly discuss our XQuery view maintenance system implementation. Our experiments confirm that incremental view maintenance is indeed faster than re-computation.

An algebraic approach for incremental maintenance of materialized XQuery views

XML data management using relational database systems has been intensively studied in the last few years. However, in order for such systems to be viable, they must support not only queries, but also updates over virtual XML views that wrap the relational data. While view updating is a long-standing difficult issue in the relational context, the flexible XML data model and nested XML query language both pose additional challenges for view updating.This paper addresses the question, if for a given update over an XML view, a correct relational update translation exists. First, we propose a clean extended-source theory as criteria for determining whether a given translation mapping is correct. To determine the existence of such a correct mapping, we classify a view update as either un-translatable, conditionally or unconditionally translatable under a given update translation policy. This classification depends on several features of the XML view and the update: (a) granularity of the update at the view side, (b) properties of the view construction, and (c) types of duplication appearing in the view. These features are represented in the Annotated Schema Graph. This is further utilized by our Schema-driven Translatability Reasoning algorithm (STAR) to classify a given update into one of the three above update categories. The correctness of the algorithm is proven using our clean extended-source theory. This technique represents a practical approach that can be applied by any existing view update system in industry and academia for analyzing the translatability of a given update statement before translation of it is attempted. To illustrate the working algorithm, we provide a concrete case study on the translatability of XML view updates.

/pdf/updating-xml-views-published-over-relational-databases-3cdogy2gdu.pdf

Updating XML views published over relational databases: towards the existence of a correct update mapping

Outlook. We present multiple XQuery optimization based on materialized XML view technology in the Rainbow system. In this demo we in particular show: (1) Rainbow’s support for defining and incrementally maintaining materialized XQuery views, (2) XQuery optimization by query rewriting to use materialized views, (3) Performing multiple query optimization by merging multiple XML queries (XATs) into one global access plan to decide upon materialization of intermediate results as views, and (4) Query processing of updates issued on XML views that wrap relational data by decomposing the updates into SQL update statements and consistency checks on the relational base data. The Rainbow System. We have extended Rainbow [1], our existing XML data management system, as shown in Figure 1. Rainbow accepts an XQuery query or an update request in an extended XQuery syntax from the user. The XQuery is parsed into an algebraic representation, called XML Algebra Tree (XAT) [3]. The XAT is then optimized by the global query optimizer using algebraic rewrite rules [2]. We have introduced a separate phase of XAT cleanup [2] which includes the XAT table schema cleanup and cutting of unnecessary XML operators. This optimization often significantly improves the query performance. The optimized XAT is then executed by the query manager.

Rainbow: multi-XQuery optimization using materialized XML views

Managing XML data using relational database systems, including query processing over virtual XML views that wrap relational sources, has been heavily studied in the last few years. Updating such virtual XML views, however, is not well studied, although it is essential for building a viable full-featured XML data management systems. XML view update is a challenging problem because of having to address the mismatch between the two rather different data models and distinct query paradigms. In this paper, we tackle the XQuery view update problem, in particular, we focus on the round-trip XML view update subproblem. This case, characterized by a pair of loading and extraction mappings that load XML data into the relational store and extract appropriate XML views, is very common in practice, as many applications utilize a relational engine for XML document storage. We discuss and prove the updatability of such views. We also present a decomposition-based update translation strategy for solving this problem. As evidence of feasibility, we have implemented the proposed strategies within the Rainbow XQuery system. Experimental studies are also given to assess the performance characteristics of our update system in different scenarios.

/pdf/updating-xquery-views-published-over-relational-data-a-round-icvpdsqtjv.pdf

Updating XQuery Views Published over Relational Data: A Round-Trip Case Study

Updates over virtual XML views that wrap the relational data have not been well supported by current XML data management systems. This paper studies the problem of the existence of a correct relational update translation for a given view update. First, we propose a clean extended-source theory to decide whether a translation mapping is correct. Then to answer the question of the existence of a correct mapping, we classify a view update as either un-translatable, conditionally or unconditionally translatable under a given update translation policy. We design a graph-based algorithm to classify a given update into one of the three update categories based on schema knowledge extracted from the XML view and the relational base. This now represents a practical approach that could be applied by any existing view update system in industry and in academic for analyzing the translatability of a given update statement before translation of it is attempted.

On the Updatability of XML Views Published over Relational Data

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