The exponential growth of scientific and business data has resulted in the evolution of the
cloud computing environments and the MapReduce parallel programming model. The focus …

In the last decade, the increased use and growth of social media, unconventional web
technologies, and mobile applications, have all encouraged development of a new breed of …

As the size of Big Data workloads keeps increasing, the evaluation of distributed frameworks
becomes a crucial task in order to identify potential performance bottlenecks that may delay …

The progressive transition in the nature of both scientific and industrial datasets has been
the driving force behind the development and research interests in the NoSQL model …

This paper reviews the Ogre classification of Big Data application with 50 facets divided into
four groups or views. These four correspond to Problem Architecture, Execution mode, Data …

MapReduce has since its inception been steadily gaining ground in various scientific
disciplines ranging from space exploration to protein folding. The model poses a challenge …

The exponential growth of scientific and business data has resulted in the evolution of the
cloud computing and the MapReduce parallel programming model. Cloud computing …

The ever growing needs of Big Data applications are demanding challenging capabilities
which cannot be handled easily by traditional systems, and thus more and more …

MapReduce is increasingly becoming a popular programming model. However, the widely
used implementation, Apache Hadoop, uses the Hadoop Distributed File System (HDFS) …

Evaluating the performance of Big Data systems is the usual way of getting information
about the expected execution time of analytics applications. These applications are …