Michael Rys

Database and XML Technologies

XML Twig Queries.- Ordered Backward XPath Axis Processing against XML Streams.- BPI-TWIG: XML Twig Query Evaluation.- On the Efficiency of a Prefix Path Holistic Algorithm.- Query Execution.- KSRQuerying: XML Keyword with Recursive Querying.- The XML-? XPath Processor: Benchmarking and Results.- XPath+: A Tool for Linked XML Documents Navigation.- XML Document Parsing and Compression.- A Data Parallel Algorithm for XML DOM Parsing.- Optimizing XML Compression.- XML Lossy Text Compression: A Preliminary Study.- XQuery.- XQuery Full Text Implementation in BaseX.- Recommending XMLTable Views for XQuery Workloads.- An Encoding of XQuery in Prolog.- Universal XForms for Dynamic XQuery Generation.- XML Transaction Management and Schema Design.- From Entity Relationship to XML Schema: A Graph-Theoretic Approach.- Atomicity for XML Databases.

XML and relational database management systems: inside Microsoft® SQL Server™ 2005

Microsoft® SQL Server™ has a long history of XML support dating back to 1999. While first concentrating on enabling the transport of relational data via XML with the SQL Server 2000 release, SQL Server 2005 now additionally provides native XML storage and query support. This part of the tutorial will provide an insight into how SQL Server 2005 fits XML functionality into its core relational database management framework.

Spatial indexing in microsoft SQL server 2008

Microsoft SQL Server 2008 adds built-in support for 2-dimensional spatial data types for both planar and geodetic geometries to address the increasing demands for managing location-aware data. SQL Server 2008 also adds indexing capabilities that, together with the necessary plan selections done by the query optimizer, provide efficient processing of spatial queries. This paper will present an overview of the spatial indexing implementation in SQL Server 2008 and outline how the indexing is implemented and how the cost-based query optimizer chooses among the different plans.

XML and relational database management systems: the inside story

As XML has evolved from a document markup language to a widely-used format for exchange of structured and semistructured data, managing large amounts of XML data has become increasingly important. A number of companies, including both established database vendors and startups, have recently announced new XML database systems or new XML functionality integrated into existing database systems. This tutorial will provide an insight into how XML functionality fits into relational database management systems as seen by three major relational vendors: IBM, Microsoft and Oracle.

Scalable SQL

How do large-scale sites and applications remain SQL-based?

Bringing the Internet to your database: using SQL server 2000 and XML to build loosely-coupled systems

Loosely-coupled, distributed system architectures need to be flexible enough to allow individual components to join or leave the heterogeneous conglomerate of services and components and to change their internal design and data models without jeopardizing the whole architecture. A well-established approach is to use XML as the lingua franca for the integration layer that hides the heterogeneity among the components and provides the glue that allows the individual components to take part in the loosely integrated system. The article focuses on how to provide the basic technology to enable a relational database to become a component in such loosely-coupled systems and it provides an overview of the features that are needed to provide access via HTTP and XML.

Mapping XML to a Wide Sparse Table

XML is commonly supported by SQL database systems. However, existing mappings of XML to tables can only deliver satisfactory query performance for limited use cases. In this paper, we propose a novel mapping of XML data into one wide table whose columns are sparsely populated. This mapping provides good performance for document types and queries that are observed in enterprise applications but are not supported efficiently by existing work. XML queries are evaluated by translating them into SQL queries over the wide sparsely-populated table. We show how to translate full XPath 1.0 into SQL. Based on the characteristics of the new mapping, we present rewriting optimizations that dramatically reduce the number of joins. Experiments demonstrate that query evaluation over the new mapping delivers considerable improvements over existing techniques for the target use cases.

Bringing the Internet to Your Database: Using SQL Server 2000 and XML to Build Loosely-Coupled Systems

Loosely-coupled, distributed system architectures need to be flexible enough to allow individual components to join or leave the heterogeneous conglomerate of services and components and to change their internal design and data models without jeopardizing the whole architecture. A well-established approach is to use XML as the lingua franca for the integration layer that hides the heterogeneity among the components and provides the glue that allows the individual components to take part in the loosely integrated system. The article focuses on how to provide the basic technology to enable a relational database to become a component in such loosely-coupled systems and it provides an overview of the features that are needed to provide access via HTTP and XML.

Full-Text Search with XQuery: A Status Report

XML [45] has become one of the most important data representation formats. One of the major reasons for this success is that XML is well-suited not only for representing marked-up documents – as its heritage based on SGML indicates – but also highly-structured hierarchical data such as object hierarchies or relational data and semistructured data (see Fig. 3.1). Even data that traditionally has been represented in binary format such as graphics is now being represented using XML (e.g., SVG).

Optimizing runtime XML processing in relational databases

XML processing performance in database systems depends on static optimizations such as XML query rewrites, cost-based optimizations such as choosing appropriate XML indices, and the efficiency of runtime tasks like XML parsing and serialization. This paper discusses some of the runtime performance aspects of XML processing in relational database systems using Microsoft® SQL ServerTM 2005s approach as an example. It also motivates a non-textual storage as the preferred choice for storing XML natively. A performance evaluation of these techniques shows XML query performance improvements of up to 6 times.