A Study on Speeding up Spark with Big Data Compression through Xeon/FPGA in VMware Virtualization Communication Model

R.Prem Kumar
2017 International Journal for Research in Applied Science and Engineering Technology  
Cloud computing provides a promising platform for big sensing data processing and storage as it provides a flexible stack of massive computing, storage, and software services in a scalable manner. Due to the high volume and velocity of big sensing data, traditional data compression techniques lack sufficient efficiency and scalability for data processing. Based on specific on-Cloud data compression requirements, In addition to different compression technologies and methodologies, selection of a
more » ... good data compression tool is most important. There is a complete range of different data compression techniques available both online and offline working such that it becomes really difficult to choose which technique serves the best. In this survey, we characterize the Spark framework and also discuss the open issues and challenges raised on parallel data compression analysis with Spark. We propose a novel scalable Apache Spark with Xeon/FPGA data compression approach in VMware virtualization communication model.
doi:10.22214/ijraset.2017.9236 fatcat:2hx3pq3kmvfhzccgoe7i43y7me