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The implemented programs in the MapReduce processing model are focused in the analysis of large volume of data in a distributed and parallel architecture. This architecture is automatically managed by the framework, so the developer could be focused in the program functionality regardless of infrastructure failures or resource allocation. However, the infrastructure state can cause…

Hadoop has certain issues that could be taken care to execute the job efficiently. These limitations are due to the locality of the data in the cluster, allocation of the jobs, scheduling of the tasks and resource allocations in Hadoop. Execution in the mapreduce remains a challenge in terms of efficiency. So, an improved Hadoop…

Cloud computing has become a compelling paradigm built on compute and storage virtualization technologies. The current virtualization solution in the Cloud widely relies on hypervisor-based technologies. Given the recent booming of the container ecosystem, the container-based virtualization starts receiving more attention for being a promising alternative. Although the container technologies are generally considered to be…

Cloud providers seek to maximize their market share. Traditionally, they deploy datacenters with sufficient capacity to accommodate their entire computing demand while maintaining geographical affinity to its customers. Achieving these goals by a single cloud provider is increasingly unrealistic from a cost of ownership perspective. Moreover, the carbon emissions from underutilized datacenters place an increasing…

Cloud computing is a power platform to deal with big data. Among several software frameworks used for the construction of cloud computing systems, Apache Hadoop, which is an open-source software, becomes a popular one. Hadoop supports for distributed data storage and the process of large data sets on computer clusters based on a MapReduce parallel…

With the rapid growth of financial markets, analyzers are paying more attention on predictions. Stock data are time series data, with huge amounts. Feasible solution for handling the increasing amount of data is to use a cluster for parallel processing, and Hadoop parallel computing platform is a typical representative. There are various statistical models for…

Big Data Analytics (BDA) is important to utilize data from hospital systems to reduce healthcare costs. BDA enable queries of large volumes of patient data in an interactively dynamic way for healthcare. The study objective was high performance establishment of interactive BDA platform of hospital system. A Hadoop/MapReduce framework was established at University of Victoria…