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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 …
Data Management In Cloud Environments: Nosql And Newsql Data Stores, Katarina Grolinger, Wilson A. Higashino, Abhinav Tiwari, Miriam Am Capretz
Data Management In Cloud Environments: Nosql And Newsql Data Stores, Katarina Grolinger, Wilson A. Higashino, Abhinav Tiwari, Miriam Am Capretz
Electrical and Computer Engineering Publications
: Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the …
Knowledge As A Service Framework For Disaster Data Management, Katarina Grolinger, Emna Mezghani, Miriam Am Capretz, Ernesto Exposito
Knowledge As A Service Framework For Disaster Data Management, Katarina Grolinger, Emna Mezghani, Miriam Am Capretz, Ernesto Exposito
Electrical and Computer Engineering Publications
Each year, a number of natural disasters strike across the globe, killing hundreds and causing billions of dollars in property and infrastructure damage. Minimizing the impact of disasters is imperative in today’s society. As the capabilities of software and hardware evolve, so does the role of information and communication technology in disaster mitigation, preparation, response, and recovery. A large quantity of disaster-related data is available, including response plans, records of previous incidents, simulation data, social media data, and Web sites. However, current data management solutions offer few or no integration capabilities. Moreover, recent advances in cloud computing, big data, and …