On supporting full-text retrievals in XML query

XML (Extensible Markup Language) has emerged as the standard data-exchange format for Internet-based business applications. These applications introduce a new set of data management requirements involving XML. However, for the foreseeable future, a significant amount of business data will continue to be stored in relational database systems. Thus, a bridge is needed to satisfy the requirements of these new XML-based applications while still using relational database technology. This paper describes the design and implementation of the XTABLES middleware system, which we believe achieves this goal. In particular, XTABLES provides a general framework to create XML views of relational data, query XML views, and store and query XML documents using a relational database system. Some of the novel features of the XTABLES architecture are that it 1) provides users with a single XML query language for creating and querying XML views of relational data, 2) executes queries efficiently by pushing most computation down to the relational database engine, c) allows users to query seamlessly over relational data and meta-data, and 4) allows users to write queries that span XML documents and XML views of relational data.

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 warehouses give decision-support systems a chance to use complicated data by giving them a place to start. But native-XML database management systems are slow right now, so it is important to look into ways to make them faster. This study presents two strategies to think about. To start, we suggest using a link index that was made with the fact that XML warehouses have a lot of dimensions in mind. The join procedures are taken out, but the data from the first warehouse stays the same. Second, we show how to choose XML materialized views by grouping the query load to show how this can be done. To prove that these ideas work, we built a set of decision support XQuery tools and ran them against an XML data warehouse. We compared the results obtained with and without our optimization methods. Our tests show that it works, even though the queries themselves are a little hard to understand and the datasets themselves are very big. XML has emerged as the widely accepted standard for transmitting data over mobile wireless networks. In these kinds of networks, mobile clients can use a wireless broadcast channel to send queries to get the XML data they need. Because mobile devices are so small and have so little storage space and a short battery life, it may be hard for customers to download the whole XML data set on one of these devices. To solve this problem, you need to index XML data so that mobile clients only have to download the parts of the file they need. Users who want to access only certain parts of the XML content in an XML stream could use one of several indexing methods. Still, the indexing methods that are used now add more data to an XML stream that is already very large. This research comes up with a new XML stream structure for broadcasting XML data by compressing and summarizing the information about how XML nodes are put together. This study was conducted in the United Kingdom. When data is summed up before being sent, the time it takes to get it in XML format over a wireless broadcast channel can be cut down. The recommended XML stream structure also has indexes that will help you skip over any data that is not important. So, it could make it less likely that XML query results will drain the batteries of mobile devices when they are being processed. We also found that our suggested XML stream design was better than its predecessors in terms of access and tuning times for processing XML queries over the XML data stream. So, our architecture can be used to answer a wide range of XML questions.

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 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

The exploitation of large volume of XML (eXtensible Markup Language) data with a limited storage space implies the development of a special and reliable treatment to compress data and query them. This work studies and treats these processes in order to combine them via a mediator while facilitating querying compressed XML data without recourse to the decompression process. We propose a new technique to compress, re-index and query XML data while improving XMill and B+Tree algorithms. We show the reliability and the speed up of the proposed querying system towards response time and answers' exactitude.

Digital broadcasting is a novel paradigm for the next generation broadcasting. It can offer a new opportunity for interactive services such as content-based browsing, non-linear navigation, usage of user preference, and history, etc. On the other hand, one of the important factors for this new broadcasting environment is the interoperability among providers and consumers since the environment is distributed. Therefore a standard metadata for digital broadcasting is required and TV-Anytime metadata is one of the metadata standards for digital broadcasting. It is defined using XML schema, so its instances are XML data. In order to fulfill interoperability, a standard query language is also required and XQuery, which is a forthcoming standard query language for XML data, is a natural choice. In this paper we propose an efficient XML data management system that supports TV-Anytime metadata, especially using XQuery as a query language. Since the volume of metadata would be very large in real situation, our system considers a relational database system as storage. We implement a prototype system and test performance for various typical queries by comparing our system with other general-purpose systems.KeywordsPath ExpressionXPath ExpressionRelational Database SystemDigital BroadcastingMetadata GeneratorThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

In a relational database system, cursors provide a mechanism for traversal of a set of query results. The existing cursor defined in the SQL or JDBC, which is targeted for navigating results in the relational form, is inadequate for traversing or fetching XML query results. In this paper, we propose a mechanism for efficient and flexible cursor operations on XML data sets stored in an XML repository based on a relational database system. We first define a cursor interface for traversal of XML query result, which also provides a positioned update function. To demonstrate the feasibility of the cursor interface, we then propose and examine three different implementations in a relational database system: multi-cursor, outer union, and hybrid. Our experiments using XMach [23] benchmark data sets show that the hybrid approach has the best performance among the three in a mixed workload with both sequential and structure-aware cursor traversals.

The problem of efficiently evaluating XPath and XQuery queries has become increasingly significant since more and more XML data is stored in its native form. We propose a novel optimisation technique for XML queries that is based on the semantic properties exhibited by XML data. In sharp contrast to previous studies on selectivity estimation we propose to specify bounds on the number of element nodes in an XML tree that form the root of isomorphic subtrees. It turns out that efficient reasoning about these constraints provides effective means to predict the number of XPath and XQuery query answers, to predict the number of updates using the XQuery update facility, to predict the number of en(de)cryptions using XML encryption, and to optimise XML queries.

The China-America Digital Academic Library (CADAL) project aims to create a searchable collection of one million digital books freely available over the Internet. For this, a terabyte text retrieval system is required. This paper presents a cache-based, distributed terabyte text retrieval system, with fulltext retrieval, distributed computing and caching techniques. By distributing data by subject on different index servers, query searching is limited to specific index servers. With cache servers, response time is reduced. When queried, the system returns only highly relevant search results, to reduce the workload on the network. The prototype system shows the effectiveness of our design.

With the wide adoption of XML as a standard data representation and exchange format querying XML documents becomes increasingly important. However relational database systems constitute a much more mature technology than what is available for native storage of XML. To bridge the gap one way to manage XML data is to use a commercial relational database system. In this approach users typically first ``shred'' their documents by isolating what they predict to be meaningful fragments then store the individual fragments according to some relational schema and later translate each XML query (e.g. expressed in W3C's XQuery) to SQL queries expressed against the shredded documents.In this paper we propose an alternative approach that builds on relational database technology but shreds XML documents dynamically. This avoids many of the problems in maintaining document order and reassembling compound data from its fragments. We then present an algorithm to translate a significant subset of XQuery into an extended relational algebra that includes operators defined for the structured text datatype. This algorithm can be used as the basis of a sound translation from XQuery to SQL and the starting point for query optimization which is required for XML to be supported by relational database technology.

Data on the Internet are usually represented and transfered as XML. The XML data is represented as a tree and therefore, object repositories are well-suited to store and query them due to their modeling power. XML queries are represented as regular path expressions and evaluated by traversing each object of the tree in object repositories. Several indexes are proposed to fast evaluate regular path expressions. However, in some cases they may not cover all possible paths because they require a great amount of disk space. In order to efficiently evaluate the queries in such cases, we propose an signature based block traversing which combines the signature method and block traversing. The signature approach shrink the search space by using the signature information attached to each object, which hints the existence of a certain label in the sub-tree. The block traversing reduces disk I/O by early evaluating the reachable objects in a page. We conducted diverse experiments to show that the hybrid approach achieves a better performance than the other naive ones.KeywordsSearch SpaceState NodeQuery ProcessingPath SignatureQueue SizeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

We are addressing the efficient processing of continuous XML streams, in which the server broadcasts XML data to multiple clients concurrently through a multicast data stream, while each client is fully responsible for processing the stream. In our framework, a server may disseminate XML fragments from multiple documents in the same stream, can repeat or replace fragments, and can introduce new fragments or delete invalid ones. A client uses a light-weight database based on our proposed XML algebra to cache stream data and to evaluate XML queries against these data. The synchronization between clients and servers is achieved through annotations and punctuations transmitted along with the data streams. We are presenting a framework for processing XML queries in XQuery form over continuous XML streams. Our framework is based on a novel XML algebra and a new algebraic optimization framework based on query decorrelation, which is essential for non-blocking stream processing.

From Tree Patterns to Generalized Tree Patterns: On Efficient Evaluation of XQuery

It is an important part to determine the structural relationship of nodes in XML queries. With a numbering scheme for XML data, the structural relationships of nodes can be quickly determined. Most of the numbering schemas for XML data are static and they cannot number XML data which are updated frequently. Some numbering schemas that are dynamic consume more storage space. So it is a challenging research area to design an efficient dynamic numbering schema. This paper presents an efficient dynamic region code, called DRC, for XML tree numbering based on decimal. The experimental results show that DRC consumes less storage space and is more steady than other dynamic numbering schemes.