GreedyBigVis – A greedy approach for preparing large datasets to multidimensional visualization
Moustafa Sadek Kahil, Abdelkrim Bouramoul, Makhlouf Derdour · International Journal of Computers and Applications · 2021
Structured visualization offers an efficient way to explore and analyze data. Some of the latter need a hierarchical visualization to be more understandable. However, with a large amount of big heterogeneous data, several issues regarding visualization are challenged. The numerous patterns cannot be visualized simultaneously together, and they must be presented incrementally and in an effective manner. On the other hand, the visualization must be done in low latency, while respecting the real-time and scalability constraints. This paper proposes a new approach to prepare large data-sets for multidimensional interactive visualizations. Based on the greedy algorithm, it offers mechanisms to prioritize the potential hierarchical one, select the first patterns to be visualized, and manage the multidimensional visualization cases. The proposed approach was implemented using Apache Spark to ensure the parallel computing tasks. The experimentation shows its efficiency regarding the considered factors such as scalability constraints, complexity, multidimensionality, and hierarchy.