The Resource Description Framework (RDF) is a flexible model for representing information about resources in the web. With the increasing amount of RDF data which is becoming available, ecient and scalable management of RDF data has become a fundamental challenge to achieve the Semantic Web vision. The RDF model has attracted a lot of attentions in the database community and many researchers have proposed diff erent solutions to store and query RDF data eciently . In this paper, we focus on evaluating the state-of-the-art of the approaches which are relying on the relational infrastructure to provide scalable engines to store and query RDF data. Our experimental evaluation is done on top of recently introduced SP2Bench performance benchmark for RDF query engines. The results of our experiments shows that there is still room for optimization in the proposed generic relational RDF storage schemes and thus new techniques for storing and querying RDF data are still required to bring forward the Semantic Web vision.

Publish/subscribe-based messaging systems are used increasingly often as a communication mechanism in data-oriented web applications. Such applications often pose serious performance and scalability challenges. To address these challenges, it is important that systems are tested using benchmarks to evaluate their performance and scalability before they are put into production. In this paper, we present jms2009-PS, a new benchmark for publish/subscribe-based messaging systems built on top of the SPECjms2007 standard workload. We introduce the benchmark and discuss its con guration parameters showing how the workload can be customized to evaluate various aspects of publish/subscribe communication. Finally, we present a case study illustrating how the benchmark can be used for performance analysis of messaging servers.

In recent years, many approaches to XML twig pattern query processing have been developed. Holistic approaches are particularly significant in that they provide a theoretical model for optimal processing of some query classes and have very low main memory complexity. Holistic algorithms are supported by a stream abstract data type. This data type is usually implemented using inverted list or special purpose data structure. In this article, we focus on an efficient implementation of a stream ADT. We utilize previously proposed fast decoding algorithms for some prefix variable-length codes, like Elias-delta, Fibonacci of order 2 and 3 as well as Elias-Fibonacci codes. We compare the efficiency of the access to a stream using various decompression algorithms. These results are compared with the result of data structures where any compression is not used. We show that the compression improves the efficiency of XML query processing.

Hybrid XML storage offers a large number of alternative shredding choices. In order to automatically determine optimal shredding strategies it is crucial to have an insight into how the structure of a XML data set affects the performance. Since the structure can take many forms and the number of possible mappings is huge it is important to gain insights on the relation between structure and performance for formats that are actually used. By taking real-world data sets and modify the structure in steps you can see how the performance and other measurable properties change. We describe how a data generator can be used to produce a synthetic data set based on an existing data set, by using four different models. We compare the performance on the original data set with the performance on the different synthetic models.

This paper aims to introduce Analyzer - a complete framework for performing statistical analyses of real-world documents. Exploitation of results of these analyses is a classical way how data processing in many areas can be optimized. Although this intent is legitimate, ad hoc and dedicated analyses soon become obsolete, they are usually built on insufficiently extensive collections and are difficult to repeat. \emph{Analyzer} represents an easily extensible framework, which helps the user gathering documents, managing analyses and browsing computed reports. This paper particularly attempts to discuss proposed analyses model, standard application usage and features, and also basic aspects of the framework architecture and implementation.