Soumia Benkrid

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In this paper, a comprehensive methodology for designing and querying Parallel Rational Data Warehouses (PRDW) over database clusters, called Fragmentation & Allocation (F&A) is proposed. F&A assumes that cluster nodes are heterogeneous in processing power and storage capacity, contrary to traditional design approaches that assume that cluster nodes are(More)
Data fragmentation and allocation in distributed and parallel Database Management Systems (DBMS) have been extensively studied in the past. Previous work tackled these two problems separately even though they are dependent on each other. We recently developed a combined algorithm that handles the dependency issue between fragmentation and allocation. A(More)
The process of designing a parallel data warehouse has two main steps: (1) fragmentation and (2) allocation of generated fragments at various nodes. Usually, fragmentation and allocation tasks are used iteratively (we first split the warehouse horizontally and then allocate fragments over the nodes). The main drawback of such design approach (called(More)
This paper complements our previous results in the context of effectively and efficient designing Parallel Relational Data Warehouses (PRDW) over heterogeneous database clusters, which are represented by the proposal of a methodology called Fragmentation & Allocation (F& A). The main merit of F& A is that of combining the fragmentation and the(More)
Résumé. Traditionnellement, concevoir un entrepôt de données parallèle consiste d’abord à partitionner son schéma ensuite allouer les fragments générés sur les noeuds d’une machine parallèle. L’inconvénient majeur d’une telle approche est son ignorance de l’interdépendance entre les processus de fragmentation et d’allocation. Une des entrées du problème(More)