Introduction
Virtualization is a foundational technology applicable to cloud computing and big data implementation. It provides the basis for many platform attributes required to access, store, analyze, and manage the distributed computing components in big data environments. Virtualization — using computer resources to imitate other resources — is valued for its capability to increase IT resource utilization, efficiency, and scalability. One primary application of virtualization is server consolidation, which helps organizations improve the utilization of physical servers and potentially save on infrastructure costs. However, you find many benefits to virtualization. Companies that initially focused solely on server virtualization now recognize that it can be applied across IT infrastructure, including software, storage, and networks.
Importance of Virtualization
Solving big data challenges typically requires the management of large data volumes of highly distributed data stores and computing- and data-active applications. Therefore, one needs a highly efficient IT environment to support big data. Virtualization provides the additional efficiency level to make big data platforms a reality. Although virtualization is technically not a requirement for big data analysis, software frameworks such as MapReduce, used in big data environments, are more efficient in a virtualized environment. If you need your big data environment to scale — almost without bounds — you should virtualize elements of your environment.
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