云环境下大数据服务性能的测试与优化研究

Research on test and optimization of big data service performance in cloud environment

云环境取得了快速发展和普及,人们可以从云环境中租用所需要的资源,然后,按照租用的资源量进行精确计费,出现了一种大数据即服务概念(BDaaS),为了进一步提高BDaaS性能,现提出一套系统、完善的BDaaS on Openstack优化方案。首先,根据云环境、大数据计算框架、BDaaS等概念,探讨了BDaaS资源管理与使用策略;其次,从块设备以及Sahara接口优化、虚拟化性能瓶颈解决、数据源使用策略3个方面入手,提出行之有效的优化策略。结果表明文章所提出的优化方案具有较高的可靠性、可行性和正确性,可为技术人员提供有效的借鉴和参考。

Under the background of big data and cloud environment has achieved rapid development and popularization,people can resources you will need to rent from the cloud,and then,according to the lease resources accurately billing,in this context,there is a big data service concept(English abbreviation as “BDaaS”),in order to further improve the performance of BDaaS a systematic and perfect BDaaS on Openstack optimization scheme is proposed.First,based on cloud environment,big data computing framework,BDaaS and other related concepts,BDaaS resource management and usage strategies are discussed.Second,effective optimization strategies are proposed from three aspects:block device and Sahara interface optimization,virtualization performance bottleneck solution,and data source usage strategy.The results show that the optimization scheme proposed in this paper has high reliability,feasibility and correctness.Hope through this research,provide effective reference and reference for technical personnel.