Title :
A Cloud-Based Framework for Supporting Effective and Efficient OLAP in Big Data Environments
Author :
Cuzzocrea, Alfredo ; Moussa, Rim
Author_Institution :
ICAR, Univ. of Calabria, Cosenza, Italy
Abstract :
Inspired by the emerging Big Data challenge, in this paper we provide the description of OLAP*, a Cloud based framework for supporting effective and efficient OLAP in Big Data environments. OLAP* combines data warehouse partitioning techniques with Cloud Computing paradigms, and provides a suitable implementation on top of the well-known ROLAP server Mondrian where the main task consists in applying meaningful transformation of multidimensional database schemas. We complement our analytical contribution by mean of a case study showing the effectiveness of our framework in a practical setting.
Keywords :
Big Data; cloud computing; data mining; data warehouses; Big Data environments; OLAP; cloud computing paradigms; cloud-based framework; data warehouse partitioning techniques; online analytical processing; Benchmark testing; Big data; Business; Data warehouses; Databases; Parallel processing; Servers;
Conference_Titel :
Cluster, Cloud and Grid Computing (CCGrid), 2014 14th IEEE/ACM International Symposium on
Conference_Location :
Chicago, IL
DOI :
10.1109/CCGrid.2014.129