使用容量调度器增强Hadoop集群虚拟化

A. Raj, K. Kaur, U. Dutta, V. K. Sandeep, S. Rao
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引用次数: 27

摘要

我们提供了一个Hadoop集群的虚拟化设置,它可以用更少的资源提供更大的计算能力,因为虚拟化集群需要更少的物理机器。集群的主节点设置在物理机上,从节点设置在虚拟机(vm)上,这些虚拟机可能位于普通物理机上。Hadoop配置的虚拟机镜像是通过克隆虚拟机来创建的,这样可以在不增加太多开销的情况下快速添加和删除集群中的节点。此外,我们还配置了Hadoop虚拟化集群来使用容量调度器,而不是默认的FIFO调度器。容量调度器在分配任何作业之前,根据从节点中RAM和虚拟内存(VMEM)的可用性来调度任务。因此,不是让作业排队,而是根据可用内存在vm上有效地分配作业。分析Hadoop的各种配置参数,并对虚拟化集群进行微调,以确保最佳性能和最大可伸缩性。
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Enhancement of Hadoop Clusters with Virtualization Using the Capacity Scheduler
We present a virtualized setup of a Hadoop cluster that provides greater computing capacity with lesser resources, since a virtualized cluster requires fewer physical machines. The master node of the cluster is set up on a physical machine, and slave nodes are set up on virtual machines (VMs) that may be on a common physical machine. Hadoop configured VM images are created by cloning of VMs, which facilitates fast addition and deletion of nodes in the cluster without much overhead. Also, we have configured the Hadoop virtualized cluster to use capacity scheduler instead of the default FIFO scheduler. The capacity scheduler schedules tasks based on the availability of RAM and virtual memory (VMEM) in slave nodes before allocating any job. So instead of queuing up the jobs, they are efficiently allocated on the VMs based on the memory available. Various configuration parameters of Hadoop are analyzed and the virtualized cluster is fine-tuned to ensure best performance and maximum scalability.
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