Abstract
Small, medium and large companies all face three well-identified problems, precisely: (i) the data deluge, (ii) the large number of interacted exploratory queries and (iii) the economic crisis. Hence, it becomes a real necessity to consider those problems and develop low-cost database deployment solutions. Data parallel architectures are one of the relevant deployment platforms that may manage efficiently this deluge of data. The process of designing such architecture has to integrate the interaction that may exist between queries. Although, the state-of-art on parallel data warehouses is quite rich, to the best of our knowledge, the query interaction is not highlighted. Amazingly, the queries are in the core of the parallel design. Ignoring their interaction may impact the quality of the final design. In this paper, we propose a new scalable hyper-graph approach, called HYPAD, for designing cluster warehouses by considering concurrent analytical highly interacted queries. Our approach is validated through a data warehouse cluster simulator. The obtained results show the effectiveness and efficiency of our proposal.