678 research outputs found
A Framework for Developing Real-Time OLAP algorithm using Multi-core processing and GPU: Heterogeneous Computing
The overwhelmingly increasing amount of stored data has spurred researchers
seeking different methods in order to optimally take advantage of it which
mostly have faced a response time problem as a result of this enormous size of
data. Most of solutions have suggested materialization as a favourite solution.
However, such a solution cannot attain Real- Time answers anyhow. In this paper
we propose a framework illustrating the barriers and suggested solutions in the
way of achieving Real-Time OLAP answers that are significantly used in decision
support systems and data warehouses
Hybrid approach for XML access control (HyXAC)
While XML has been widely adopted for sharing and managing information over the Internet, the need for efficient XML access control naturally arise. Various access control models and mechanisms have been proposed in the research community, such as view-based approaches and preprocessing approaches. All categories of solutions have their inherent advantages and disadvantages. For instance, view based approach provides high performance in query evaluation, but suffers from the view maintenance issues. To remedy the problems, we propose a hybrid approach, namely HyXAC: Hybrid XML Access Control. HyXAC provides efficient access control and query processing by maximizing the utilization of available (but constrained) resources. HyXAC uses pre-processing approach as a baseline to process queries and define sub-views. It dynamically allocates the available resources (memory and secondary storage) to materialize sub-views to improve query performance. Dynamic and fine-grained view management is introduced to utilize cost-effectiveness analysis for optimal query performance. Fine-grained view management also allows sub-views to be shared across multiple roles to eliminate the redundancies in storage
Materialized View Selection in XML Databases
Materialized views, a rdbms silver bullet, demonstrate its
efficacy in many applications, especially as a data warehousing/decison support system tool. The pivot of playing materialized views efficiently is view selection. Though studied for over thirty years in rdbms, the
selection is hard to make in the context of xml databases, where both the semi-structured data and the expressiveness of xml query languages add challenges to the view selection problem. We start our discussion on producing minimal xml views (in terms of size) as candidates for a given workload (a query set). To facilitate intuitionistic view selection, we present a view graph (called vcube) to structurally maintain all generated views. By basing our selection on vcube for materialization, we propose two view selection strategies, targeting at space-optimized and space-time tradeoff, respectively. We built our implementation on
top of Berkeley DB XML, demonstrating that significant performance improvement could be obtained using our proposed approaches
Contributions Ă lâOptimisation de RequĂȘtes Multidimensionnelles
Analyser les donnĂ©es consiste Ă choisir un sous-ensemble des dimensions qui les dĂ©criventafin d'en extraire des informations utiles. Or, il est rare que l'on connaisse a priori les dimensions"intĂ©ressantes". L'analyse se transforme alors en une activitĂ© exploratoire oĂč chaque passe traduit par une requĂȘte. Ainsi, il devient primordiale de proposer des solutions d'optimisationde requĂȘtes qui ont une vision globale du processus plutĂŽt que de chercher Ă optimiser chaque requĂȘteindĂ©pendamment les unes des autres. Nous prĂ©sentons nos contributions dans le cadre de cette approcheexploratoire en nous focalisant sur trois types de requĂȘtes: (i) le calcul de bordures,(ii) les requĂȘtes dites OLAP (On Line Analytical Processing) dans les cubes de donnĂ©es et (iii) les requĂȘtesde prĂ©fĂ©rence type skyline
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