Renda-RX: A Benchmark for Evaluating XML-Relational Database System

The XML data is a typical kind of tree-data. However, the XML research community has given little attention to the traditional Relational database Management System(RDBMS) based encoding schemes for tree-data. In this paper, we will investigate one of the traditional RDBMS-based encoding schemes, called Nested Interval, for storage and retrieval of XML data. Especially, our approach is very robust for updating XML data, including insertion of new nodes. In fact, the existing RDBMS-based XML storage and indexing techniques work very poorly against XML data updates because they should be rebuilt from the scratch when any update occurs in XML data. In contract, our scheme does not require re-encoding. In this respect, our approach is a viable option for storing and querying update-intensive XML applications.

Although the native (tree-like) storage of XML data becomes more and more important there will be an enduring demand to manage XML data in its textual representation, for instance in relational structures or file systems. XML data has to be wellformed by definition and additionally, in many cases, it has to be valid according to a given XML schema. Because the XML column types are often derived from text types (e.g. CLOBs) guaranteeing well-formedness as well as validity is not trivial. And even worse, for frequently modified data it is usually too expensive to re-validate the whole XML data after each update - but waiving re-validation may lead to inconsistencies and malfunctions of applications. In this paper we present a schema-aware pushdown automaton (i.e. a stack machine) that validates an XML string/stream. Using an element/state-index, the pushdown automaton is able to re-validate local modifications of the data while guaranteeing overall validity. Update operations (e.g. SQLXML, XQuery updates) are validated before executing them.

The XML support in relational databases and the SQL/XML language are still relatively new as compared to purely relational databases and traditional SQL. Today, most database users have a strong relational and SQL background. SQL/XML enables users to perform queries and updates across XML and relational data, but many struggle with writing SQL/XML statements or XQuery update expressions. One reason is the novelty of SQL/XML and of the XQuery expressions that must be included. Another problem is that the tree structure of the XML data may be unknown or difficult to understand for the user. Evolving XML Schemas as well as hybrid XML/relational schemas make it even harder to write SQL/XML statements. Also, legacy applications use SQL but may require access to XML data without costly code changes. Motivated by these challenges, we developed a method to generate SQL/XML query and update statements automatically. The input is either a GUI or a regular SQL statement that uses logical data item names irrespective of their actual location in relational or XML columns in the database. The output is a SQL/XML statement that queries or updates relational and XML data as needed to carry out the original user statement. This relieves the user and simplifies schema evolution and integration. We have prototyped and tested the proposed method on top of DB2 9.5.

The presence of a schema offers many advantages in processing, translating, querying, and storage of XML data. Basic decision problems like equivalence, inclusion, and non-emptiness of intersection of schemas form the basic building blocks for schema optimization and integration, and algorithms for static analysis of transformations. It is thereby paramount to establish the exact complexity of these problems. Most common schema languages for XML can be adequately modeled by some kind of grammar with regular expressions at right-hand sides. In this paper, we observe that apart from the usual regular operators of union, concatenation and Kleene-star, schema languages also allow numerical occurrence constraints and interleaving operators. Although the expressiveness of these operators remain within the regular languages, their presence or absence has significant impact on the complexity of the basic decision problems. We present a complete overview of the complexity of the basic decision problems for DTDs, XSDs and Relax NG with regular expressions incorporating numerical occurrence constraints and interleaving. We also discuss chain regular expressions and the complexity of the schema simplification problem incorporating the new operators.

As Extensible Markup Language (XML) [5] is emerging as the data format of the internet era, there are increasing needs to effciently store and query XML data. One way towards this goal is using relational database by transforming XML data into relational format. In this paper, we argue that existing transformation algorithms are not complete in the sense that they focus only on structural aspects and ignoring semantic aspects. We present the semantic knowledge that needs to be captured during the transformation to ensure a correct relational schema. Further, we show a simple algorithm that can 1) derive such semantic knowledge from the given XML Document Type Definition (DTD) and 2) preserve the knowledge by representing them in terms of semantic constraints in relational database terms. By combining the existing transformation algorithms and our constraints-preserving algorithm, one can transform XML DTD to relational schema where correct semantics and behaviors are guaranteed by the preserved constraints. Experimental results are also presented.

XML data is likely to be widely used as a data exchange format but users also need to store and query XML data. The purpose of this panel is to explore whether and how to best provide this functionality.

Because of increasing use of XML data on the internet, the need for an efficient method of storing and querying XML data is vital. So far, two major types of system for XML data management have been introduced: XML Enabled systems and XML native systems. The former uses relational database system for storing and querying XML data and the latter is a special XML database system which is based on XML data model. Since relational database systems are more mature than XML native systems, it seems that the use of abilities and efficiencies of relational systems is more economical. In this article, we have introduced a new relational schema named XLight for storing and processing XML data, and we have compared it with some similar methods.

In this chapter, we discuss the design and implementation of join algorithms for data streaming systems, wherememory is often limited relative to the data that needs to be processed.We first focus on progressive join algorithms for various data models. We introduce a framework for progressive join processing, called the Result Rate based Progressive Join (RRPJ) framework which can be used for join processing for various data models, and discuss its various instantiations for processing relational, high-dimensional, spatial and XML data.

As XML data storage and interchange become ubiquitous, analysts and data engineers increasingly need tools to model their data and map it to XML schemas and to reverse engineer XML documents and schemas in support of evolution and integration activities. For effective data management, model transformations require guarantees of properties of interest including guarantees of information and constraintpreservation, redundancy-free and compactness guarantees, and assurances about readability and maintainability. In this paper, we make foundational observations about XML data management, including conceptual modeling for XML data, transformations to and from XML Schema and XML data models, and transformation guarantees concerning properties of interest, and we provide resolutions for conceptual mismatches between XML data management and more traditional data management. Our implemented prototype tools show that these observations and insights can provide a strong foundation for XML data engineering.

The Extensible Markup Language (XML) is emerging as the dominant data format for data exchange between applications. Many translation techniques have been devised to publish large amounts of existing conventional relational data in XML format. There also exists a need to be able to represent imprecise data in both relational databases and XML. This paper describes a fuzzy XML schema model for representing a fuzzy relational database in XML format. It also outlines a translation algorithm to include fuzzy relations and similarity matrices with their associated conventional relations. We also describe how the proposed fuzzy XML schema and the conversion process from fuzzy relational data into fuzzy XML have been integrated into VIREX, which is a prototype with powerful visual tool for transforming relational data into XML.KeywordsFuzzy XMLFuzzy Relational DatabaseSchema ConversionVisual Interface

Independent XML storage based on XSD (XML Schema Document) is adopted in NXD (Native XML Database), XML storage structure based on tree-structure disassemble and the algorithm used in dynamically updating XML document are provided in this paper. The main idea is that in term of data model of XML document, XML document is parsed to Document Structure-Tree with Hierarchical Model and Leaf-Data with Relation Model for storage. Simulataneously Proxy node is imported in order to solve the problem that XML data store in cross-blocks. And with XSD model information, sparse index is constructed to save storage space. It is proved that this storage structure could improve efficiency of XML document operation.

This paper describes Sucxent, a novel system for the storage and querying of XML data using a relational database system (RDBMS). The relational schema proposed under Sucxent does not require the knowledge of the DTDs of the XML documents being stored. In this approach we store only the leaf nodes and their text values together with their ancestor list. Doing so will eliminate θ ( )-joins to answer XPath-expression based queries. θ-joins account for a major performance bottleneck in current approaches for storing XML data in an RDBMS. We also compare the performance of our system to two existing approaches for relational storage of XML documents, XRel and XParent, to demonstrate the effectiveness of our approach. We show that our system performs significantly better than XRel and XParent in terms of insertion, extraction and querying of XML documents.

XML data update management in XML-enabled database

B2B 전자상거래와 같이 XML.을 이용한 정보교환이 확산되고 있으며 이에 따라 상호 교환되는 정보에 대하여 체계적이며 안정적인 저장관리가 요구되고 있다. 이를 위해 XML 응용과 데이터베이스 연계를 위한 다양한 연구가 관계형 데이터베이스를 중심으로 수행되었다. 그러나 계층구조를 갖는 XML 데이터를 2차원 테이블의 집합인 관계형 정보로 표현하는 관계형 데이터베이스로의 저장에는 본질적인 한계가 있어, 계층구조를 지원하는 객체지향 데이터베이스로의 저장이 요망된다. 이에 따라 계층구조를 갖는 XML 데이터를 객체지향 데이터 베이스로 지장하기 위한 모델링 방안이 요구된다. 본 논문에서는 객체모델을 토대로 DTD를 객체 지향 데이터베이스 스키마로 변환하기 위한 방법을 제안한다. 이를 위하여 먼저 DTD를 객체모델로 변환시키기 위한 객체변환 방안을 제시하고, 변환된 객체모델을 객체지향 데이터베이스 스키마로 변경시키기 위한 스키마 변환 방법을 제안했다. Information exchange on XML such as B2B electronic commerce is spreading. Therefore the systematic and stable management mechanism for storing the exchanged information is needed. For this goal there are many research activities for connection between XML application and relational database. But because XML data have hierarchical structures and relational database can store only flat-structured data, we need to store XML data in object-oriented database that support hierarchical structure. Accordingly the modeling methodology for storing XML data in object-oriented database is needed. In this parer, the transforming methods based on object model from XML DTD to object-oriented database schema is proposed. For this, we first introduce mapping methods that map XML DTD to object model and then we propose soem methods that transform from the object model to object-oriented database schema.

Data forms the key success enabler for any business organization. Structured collection and organized data along with this analytical enablement will provide more insights to the organization's existing operations and ways for better improvement. In order to do efficient data collection, integration of data from various sources forms the vital role. Many of the vital business initiatives for an organization requires the data to integrate. Such initiatives performed by creating a customized solution across every data source. In such given architecture, the complexity to integrate data source is proportionate to the increase in data sources. Use of eXtensible Markup Language (XML) for standardizing the information exchange across several sources is an industry standard implementation. It is the technology used to implement and deliver an enterprise-level data integration solution using heterogeneous data sources. The transformation capability of XML is capable of handling very complex and big documents and can do processing of ~thousands of real-time transactions using message bus or Web Services methods. The XML provided solutions are flexible and easily adaptable, thus enabling them to incorporate into a broader range of organizational solutions. This paper discusses in detail, the data integration methods and their challenges and processing of XML data using Extraction, Transformation and Load method. The paper also provides the several ways to parse the XML data as part of the data processing with the case study for an On Line Transaction Process (OLTP) system of a manufacturing company.