1,418 research outputs found
Relational Approach to Logical Query Optimization of XPath
To be able to handle the ever growing volumes of XML documents, effective and efficient data management solutions are needed. Managing XML data in a relational DBMS has great potential. Recently, effective relational storage schemes and index structures have been proposed as well as special-purpose join operators to speed up querying of XML data using XPath/XQuery. In this paper, we address the topic of query plan construction and logical query optimization. The claim of this paper is that standard relational algebra extended with special-purpose join operators suffices for logical query optimization. We focus on the XPath accelerator storage scheme and associated staircase join operators, but the approach can be generalized easily
Classification of index partitions to boost XML query performance
XML query optimization continues to occupy considerable
research effort due to the increasing usage of XML data. Despite many innovations over recent years, XML databases struggle to compete with more traditional database systems. Rather than using node indexes, some efforts have begun to focus on creating partitions of nodes within indexes. The motivation is to quickly eliminate large sections of the XML tree based on the partition they occupy. In this research, we present one such partition index that is unlike current approaches in how it determines size and number of these partitions. Furthermore, we provide a process for compacting the index and reducing the number of node access operations in order to optimize XML queries
Reasoning & Querying ā State of the Art
Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF
Pattern based processing of XPath queries
As the popularity of areas including document storage and
distributed systems continues to grow, the demand for high
performance XML databases is increasingly evident. This
has led to a number of research eorts aimed at exploiting
the maturity of relational database systems in order to in-
crease XML query performance. In our approach, we use an
index structure based on a metamodel for XML databases
combined with relational database technology to facilitate
fast access to XML document elements. The query process
involves transforming XPath expressions to SQL which can
be executed over our optimised query engine. As there are
many dierent types of XPath queries, varying processing
logic may be applied to boost performance not only to indi-
vidual XPath axes, but across multiple axes simultaneously.
This paper describes a pattern based approach to XPath
query processing, which permits the execution of a group of
XPath location steps in parallel
Boosting XML Filtering with a Scalable FPGA-based Architecture
The growing amount of XML encoded data exchanged over the Internet increases
the importance of XML based publish-subscribe (pub-sub) and content based
routing systems. The input in such systems typically consists of a stream of
XML documents and a set of user subscriptions expressed as XML queries. The
pub-sub system then filters the published documents and passes them to the
subscribers. Pub-sub systems are characterized by very high input ratios,
therefore the processing time is critical. In this paper we propose a "pure
hardware" based solution, which utilizes XPath query blocks on FPGA to solve
the filtering problem. By utilizing the high throughput that an FPGA provides
for parallel processing, our approach achieves drastically better throughput
than the existing software or mixed (hardware/software) architectures. The
XPath queries (subscriptions) are translated to regular expressions which are
then mapped to FPGA devices. By introducing stacks within the FPGA we are able
to express and process a wide range of path queries very efficiently, on a
scalable environment. Moreover, the fact that the parser and the filter
processing are performed on the same FPGA chip, eliminates expensive
communication costs (that a multi-core system would need) thus enabling very
fast and efficient pipelining. Our experimental evaluation reveals more than
one order of magnitude improvement compared to traditional pub/sub systems.Comment: CIDR 200
On Region Algebras, XML Databases, and Information Retrieval
This paper describes some new ideas on developing a logical algebra for databases that manage textual data and support information retrieval functionality. We describe a first prototype of such a system
Four Lessons in Versatility or How Query Languages Adapt to the Web
Exposing not only human-centered information, but machine-processable data on the Web is one of the commonalities of recent Web trends. It has enabled a new kind of applications and businesses where the data is used in ways not foreseen by the data providers. Yet this exposition has fractured the Web into islands of data, each in different Web formats: Some providers choose XML, others RDF, again others JSON or OWL, for their data, even in similar domains. This fracturing stifles innovation as application builders have to cope not only with one Web stack (e.g., XML technology) but with several ones, each of considerable complexity. With Xcerpt we have developed a rule- and pattern based query language that aims to give shield application builders from much of this complexity: In a single query language XML and RDF data can be accessed, processed, combined, and re-published. Though the need for combined access to XML and RDF data has been recognized in previous work (including the W3Cās GRDDL), our approach differs in four main aspects: (1) We provide a single language (rather than two separate or embedded languages), thus minimizing the conceptual overhead of dealing with disparate data formats. (2) Both the declarative (logic-based) and the operational semantics are unified in that they apply for querying XML and RDF in the same way. (3) We show that the resulting query language can be implemented reusing traditional database technology, if desirable. Nevertheless, we also give a unified evaluation approach based on interval labelings of graphs that is at least as fast as existing approaches for tree-shaped XML data, yet provides linear time and space querying also for many RDF graphs. We believe that Web query languages are the right tool for declarative data access in Web applications and that Xcerpt is a significant step towards a more convenient, yet highly efficient data access in a āWeb of Dataā
Desirable properties for XML update mechanisms
The adoption of XML as the default data interchange format and the standardisation of the XPath and XQuery languages has resulted in significant research in the development and implementation of XML databases capable of processing queries efficiently. The ever-increasing deployment of XML in industry and the real-world requirement to support efficient updates to XML documents has more recently prompted research in dynamic XML labelling schemes. In this paper, we provide an overview of the recent research in dynamic XML labelling schemes. Our motivation is to define a set of properties that represent a more holistic dynamic labelling scheme and present our findings through an evaluation matrix for most of the existing schemes that provide update functionality
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