Abstract
The data volume and the multitude of sources have an exponential number of technical and application challenges. In the past, Big Data solutions have been presented as a replacement for the Parallel Database Management Systems. However, Big Data solutions can be seen as a complement to a RDBMS for analytical applications, because different problems require complex analysis capabilities provided by both technologies. The aim of his work is to integrate a Big Data solution and a classic DBMS, in a goal of queries optimization. We propose a model for OLAP queries process. Then, we valid the proposed optimized model through experiments showing the gain of the execution cost saved up.
Author supplied keywords
Cite
CITATION STYLE
Jemal, D., Faiz, R., Boukorca, A., & Bellatreche, L. (2015). MapReduce-DBMS: An integration model for big data management and optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9262, pp. 430–439). Springer Verlag. https://doi.org/10.1007/978-3-319-22852-5_36
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
