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Analysis and evaluation of MapReduce solutions on an HPC cluster
(Pergamon Press, 2016-02)
[Abstract] 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 organizations are adopting High Performance ...
Enhancing in-memory Efficiency for MapReduce-based Data Processing
(Academic Press, 2018-10)
[Abstract] As the memory capacity of computational systems increases, the in-memory data management of Big Data processing frameworks becomes more crucial for performance. This paper analyzes and improves the memory ...
Flame-MR: An event-driven architecture for MapReduce applications
(Elsevier BV * North-Holland, 2016)
[Abstract] Nowadays, many organizations analyze their data with the MapReduce paradigm, most of them using the popular Apache Hadoop framework. As the data size managed by MapReduce applications is steadily increasing, the ...
Performance Evaluation of Big Data Frameworks for Large-Scale Data Analytics
(IEEE Computer Society, 2017-02-06)
[Abstract] The increasing adoption of Big Data analytics has led to a high demand for efficient technologies in order to manage and process large datasets. Popular MapReduce frameworks such as Hadoop are being replaced by ...
MREv: An Automatic MapReduce Evaluation Tool for Big Data Workloads
(Elsevier, 2015)
[Abstract]: The popularity of Big Data computing models like MapReduce has caused the emergence of many frameworks oriented to High Performance Computing (HPC) systems. The suitability of each one to a particular use case ...