User-Centric Approach for Benchmark RDF Data Generator in Big Data Performance Analysis

Changes in data generation sources such as social networks, mobile devices, and process automation, along with an increase in the number of instruments generating observational data have pushed beyond the boundaries of current day data analysis systems. New algorithms, specialized hardware systems, and computing paradigms are designed to solve problems exhibited by large datasets, but at the same time there is a dearth of flexible and easy to use tools to assess the effectiveness of these proposed solutions. Benchmarking tools are required to compare the performance and the cost associated with any Big Data system. This research focuses on a user-centric approach of building such tools and proposes a flexible, extensible, and easy to use framework to support performance analysis of Big Data systems. Finally, case studies from two different domains are presented to validate the framework.