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Full-Text Articles in Computer Sciences
Challenges For Mapreduce In Big Data, Katarina Grolinger, Michael Hayes, Wilson Higashino, Alexandra L'Heureux, David Allison, Miriam Capretz
Challenges For Mapreduce In Big Data, Katarina Grolinger, Michael Hayes, Wilson Higashino, Alexandra L'Heureux, David Allison, Miriam Capretz
Wilson A Higashino
In the Big Data community, MapReduce has been seen as one of the key enabling approaches for meeting continuously increasing demands on computing resources imposed by massive data sets. The reason for this is the high scalability of the MapReduce paradigm which allows for massively parallel and distributed execution over a large number of computing nodes. This paper identifies MapReduce issues and challenges in handling Big Data with the objective of providing an overview of the field, facilitating better planning and management of Big Data projects, and identifying opportunities for future research in this field. The identified challenges are grouped …
Challenges For Mapreduce In Big Data, Katarina Grolinger, Michael Hayes, Wilson A. Higashino, Alexandra L'Heureux, David S. Allison, Miriam A.M. Capretz
Challenges For Mapreduce In Big Data, Katarina Grolinger, Michael Hayes, Wilson A. Higashino, Alexandra L'Heureux, David S. Allison, Miriam A.M. Capretz
Electrical and Computer Engineering Publications
In the Big Data community, MapReduce has been seen as one of the key enabling approaches for meeting continuously increasing demands on computing resources imposed by massive data sets. The reason for this is the high scalability of the MapReduce paradigm which allows for massively parallel and distributed execution over a large number of computing nodes. This paper identifies MapReduce issues and challenges in handling Big Data with the objective of providing an overview of the field, facilitating better planning and management of Big Data projects, and identifying opportunities for future research in this field. The identified challenges are grouped …