B Dong, Q Zheng, F Tian, KM Chao, N Godwin… - Journal of Systems and …, 2014 - Elsevier
Hadoop has emerged as a successful framework for large-scale data-intensive computing applications. However, there is no research on performance models for the Hadoop …
MapReduce is a programming model to process a massive amount of data on cloud computing. MapReduce processes data in two phases and needs to transfer intermediate …
Judging by the increasing impact of machine learning on large-scale data analysis in the last decade, one can anticipate a substantial growth in diversity of the machine learning …
V Sudhakaran, NP Chue Hong - … on Data intensive computing in the …, 2011 - dl.acm.org
Processing large volumes of scientific data requires an efficient and scalable parallel computing framework to obtain meaningful information quickly. In this paper, we evaluate a …
One of the most published programming models of cloud computing is MapReduce. Google MapReduce and Apache Hadoop MapReduce are various implementations of the model …
Geoinformation technologies require fast processing of high and quickly increasing volumes of all types of spatial data. Parallel computational approach and distributed systems …
Processing large volumes of scientific data requires an efficient and scalable parallel computing framework to obtain meaningful information quickly. MapReduce is a …
V Stojkovic, H Huo - Third International Conference on the Virtual …, 2009 - academia.edu
This paper presents and discusses the MapReduce programming model (MapReduce) and its implementations in functional programming languages such as Haskell, Cat, and F# …
Whenever a person or an automated system has to reason in uncertain domains, probability theory is necessary. Probabilistic graphical models allow us to build statistical models that …