Today, consumers request virtual resources like CPU, RAM, disk (etc.) supplied by the service providers (like Amazon) and they pay on a "pay-as-you-go" basis. Generally, the supervisors adopt virtualization technologies, which optimize resources usage and limit the operating cost. The virtualization technologies are classified in two categories. The first one concerns the heavy virtualization. Each virtual machines (VM) emulates hardware and embeds its own operating system (OS) that is completely isolated from the host OS. The second one concerns the light virtualization, which is based on the management of containers. The containers share the host OS kernel [5] while ensuring isolation. In this paper, we benchmark the performance and the energy consumption of an infrastructure that is based on the software Hadoop regarding the two technologies of virtualization. At first, we will identify the points to be improved concerning Hadoop performances and then we will reduce the deployment cost on the cloud. Second, the Hadoop community finds an in-depth study of the resources consumption depending on the environment of deployment. Our experiments are based on the comparison of the Docker technology (light virtualization) and VMware technology® (heavy virtualization). We come to the point that in most experiments the light technology offers better performances in completion time of workloads and it is more adapted to be used with the Hadoop software.
['Aymen Jlassi', 'Patrick Martineau']
Virtualization technologies for the big data environment