Performance Analysis of Hadoop MapReduce on an OpenNebula Cloud with KVM and OpenVZ Virtualizations

被引：0

作者：

Magalhaes Vasconcelos, Pedro Roger ^{[1
]}

de Araujo Freitas, Gisele Azevedo ^{[1
]}

机构：

[1] Univ Fed Ceara, Fortaleza, Ceara, Brazil

来源：

2014 9TH INTERNATIONAL CONFERENCE FOR INTERNET TECHNOLOGY AND SECURED TRANSACTIONS (ICITST) | 2014年

关键词：

Big Data; MapReduce; cloud computing; virtualization; KVM; OpenVZ;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Cloud computing provides access to a set of resources such as virtual machines, storage and network as services. In this context, virtualization has been used as an platform for resource-intensive applications, like Hadoop, as it has brought features like server consolidation, scalability and better resources usage. OpenVZ and KVM are very popular and widely used virtualization platforms with distinct virtualization modes: containet-based and full-virtualization. In this work, we conducted benchmarks to measure the performance of a Hadoop cluster deployed on OpenNebula clouds with KVM and OpenVZ. Our results show that OpenVZ performs better than KVM in the CPU and I/O reading benchmarks. KVM achieves better performance in the I/O writing benchmarks.

引用

页码：471 / 476

页数：6