Generating SQL/XML query and update statements

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

Indexing XML Data Stored in a Relational Database

Having a database design that avoids redundant information and update anomalies is the main goal of normalization techniques. Ideally, data as well as constraints should be preserved. However, this is not always achievable: while BCNF eliminates all redundancies, it may not preserve constraints, and 3NF, which achieves dependency preservation, may not always eliminate all redundancies. Our first goal is to investigate how much redundancy 3NF tolerates in order to achieve dependency preservation. We apply an information-theoretic measure and show that only prime attributes admit redundant information in 3NF, but their information content may be arbitrarily low. Then we study the possibility of achieving both redundancy elimination and dependency preservation by a hierarchical representation of relational data in XML. We provide a characterization of cases when an XML normal form called XNF guarantees both. Finally, we deal with dependency preservation in XML and show that like in the relational case, normalizing XML documents to achieve non-redundant data can result in losing constraints. By modifying the definition of XNF, we define another normal form for XML documents, X3NF, that generalizes 3NF for the case of XML and achieves dependency preservation.

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.

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.

Recently, ontology-based data access is more and more employed in the context of data integration. That is, to the usual data layer of an information system we superimpose a conceptual layer to be exposed to the client. In this paper, we discuss a way to query XML data over conceptual layer using Description Logics. Given a XML data file, we first map the XML DTD to a corresponding relational schema preserving the original semantics of the XML DTD, and at the meantime, we store the XML data into the relational database. After that, we create an ontology described in Description Logics with respect to the relational schema. When a Description Logic query is posted to the ontology TBox, we map it to SQL query with respect to the relational database. In this way, we can query XML data using Description Logics. The main contribution of this thesis can be seen as the following two parts: 1. We proposed a mapping from XML DTD to relational schema with constraints preserving the original XML DTD semantics. 2. We described a framework of querying XML data using Description Logics, more precisely, the DL-LiteA logic.

Chapter 72 - DTD-Directed Publishing with Attribute Translation Grammars

As Web applications are time vulnerable, the increasing size of XML documents and the complexity of evaluating XML queries pose new performance challenges to existing information retrieval technologies. This paper introduces a new approach for developing a purpose-built XML data management system to improve the system performance of a Web site with XML support by using parallel data processing techniques. To improve the system performance, we propose a parallelisation model for XML data processing, where the data storage strategies, data placement methods and query evaluation techniques have been studied. Other related issues are also presented.

To implement a XML data warehouse system, a key issue is how to efficiently maintain materialized views, to preserve their consistency with data sources when base data changes. Self-maintenance of views has been shown to dramatically improve performance for view maintenance, and studied extensively in the context of the relational data model. But for XML database, there are still lots of work left to be done. In this paper, we give a preliminary result on self-maintainability of deletions of views over XML data. We give a necessary and sufficient condition of self-maintainability of deletions, and an algorithm to implement self-maintenance of deletions of views for XML data.

This paper proposes a new benchmark, Renda-RX, for evaluating XML-Relational database management systems which can store and process both relational and XML data. To our knowledge, it is the first time to consider a performance benchmark on mixed data, although there are TPC series for relational data, and XBench, XMark, TPoX etc. for XML data. We summarize the requirements of a benchmark for database systems, and describe the construction of our benchmark. It includes scenario selection, data storage, transaction design and result report etc. Based on the benchmark design, we also develop a test tool and successfully get some performance results on a commercial XRDBMS, System-X.

Semantic and pragmatic processing in FIDO: A flexible interface for data-base operations

As cloud computing continues to evolve, organizations are finding new ways to store the massive amounts of big data that are collected. Big data storage often require greater flexibility and scalability which can be provided by incorporating NoSQL technologies. NoSQL (Not Only SQL) is quickly becoming a popular approach to store large and unstructured data. This paper looks at the various classifications of NoSQL technologies as well as many of the notable characteristics of the technologies. The authors also describe some deficiencies of using NoSQL and give some explanation to why companies are adopting the technology. The paper concludes with suggestions for future research of NoSQL technologies and a content analysis of current articles in database management is provided in the appendix. Keywords: big data, cloud computing, document databases, MongoDB, NoSQL, Not Only SQL, unstructured database INTRODUCTION Since NoSQL database technologies entered the market in 1998, these technologies have challenged the widely-accepted relational structures and database management practices supported by traditional SQL databases. Despite this trend, the perception that NoSQL seeks to eliminate the use of relational databases is a common misconception. NoSQL is best considered with the acronym NOSQL - Not Only SQL - which more accurately represents an approach that combines non-relational databases with the use of relational ones. This approach seeks to leverage both NoSQL and SQL technologies in order to balance the demands of performance, scalability, and schema flexibility with data integrity and consistency (Purdue, 2014; Penchikala, 2013). The rise of web-scale applications creates performance, scalability, and schema flexibility demands that present significant challenges for traditional SQL / relational databases. Thus, a variety of new entrants have entered the market, each seeking to address specific challenges, including (Kent, 2012): * The need to store large volumes of data about users, objects and products * The need to provide near-real-time transaction processing * The need to provide high-speed analytics on large volumes of data (big data) * The need to support flexible data schemas for evolving business environments * The need to scale applications horizontally with predictable hardware and licensing cost structures Each NoSQL solution seeks to address one or more of the above issues, often by providing alternative approaches to long-established relational database norms. Traditional relational databases were not designed to cope with the scalability and flexibility challenges facing modern applications. Older databases were not designed to take advantage of the inexpensive storage and excess processing power available today. The defining characteristics of NoSQL technologies, as well as the relative advantages and disadvantages of NoSQL, and the subsequent influence on adoption of NoSQL technologies are each the subject of a small, yet growing body of research. This paper provides a literature review of that research and proposes potential areas where future research may focus. REVIEW OF LITERATURE NoSQL database technology is a relatively recent innovation and much of the research surrounding it is of an emerging nature. For the purpose of this literature review Galileo was primarily used for identifying the articles. Articles were selected that focused directly on NoSQL database technologies (unstructured / semi-structured databases, document databases, etc.) and articles that focused on relational databases. The contrasting articles provided the researchers with the ability to compare the features that are offered with a greater degree of variability in NoSQL databases (for example, an article on SQL scalability provided a foundation for comparing newer horizontal scaling techniques used in certain NoSQL databases). …

Traditional approaches for data anonymization consider relational data and textual data independently. We propose rx-anon, an anonymization approach for heterogeneous semi-structured documents composed of relational and textual attributes. We map sensitive terms extracted from the text to the structured data. This allows us to use concepts like k-anonymity to generate a joint, privacy-preserved version of the heterogeneous data input. We introduce the concept of redundant sensitive information to consistently anonymize the heterogeneous data. To control the influence of anonymization over unstructured textual data versus structured data attributes, we introduce a modified, parameterized Mondrian algorithm. We evaluate our approach with two real-world datasets using a Normalized Certainty Penalty score, adapted to the problem of jointly anonymizing relational and textual data. The results show that our approach is capable of reducing information loss by using the tuning parameter to control the Mondrian partitioning while guaranteeing k-anonymity. As rx-anon is a framework approach, it can be reused and extended by other anonymization algorithms, privacy models, and textual similarity metrics.

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.

In this paper, we propose a new structure-based approach, called Xregion, to store XML data in relational databases. Our approach first partitions an XML document into several disjoint regions according to the cardinality of element nodes, and then maps these regions into separate relations. Our experimental results demonstrate that the proposed approach dramatically improves the performance of queries on the XML data over the existing approaches.