Exploiting Hadoop Topology in Virtualized Environments

 Exploiting Hadoop Topology in Virtualized Environments

Exploiting Hadoop Topology in Virtualized Environments.Virtualization is a key technique to make an environment easier to manage in terms of resource allocation. MapReduce is a programming model that provides an abstraction to perform distributed computation for large datasets. Hadoop is a well-known framework that offers an open source implementation for this model. Combining Hadoop and virtualization techniques in cloud-computing environments can unveil great potential, especially for big data context.

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However, running MapReduce jobs on virtual machines has indicated performance issues not solved yet. In this paper we present and discuss three scenarios regarding Hadoop topology in a cloud infrastructure. The first scenario proposes to allocate Hadoop daemons in a fully virtualized environment, the second scenario presents a hybrid environment, and the third scenario suggests to virtualize only MapReduce daemons.We also report results from a series of tests allocating Hadoop daemons in a fully virtualized environment. Results show that adding virtual machines to the cluster causes an overhead, decreases the efficiency of CPU utilization, and shortens the time slots for the MapReduce jobs.

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