文献类型：期刊文献

英文题名：Scientific data mining and processing using MapReduce in cloud environments

作者：Kong, Xiangsheng[1]

第一作者：孔祥盛

通讯作者：Kong, Xiangsheng

机构：[1] Department of Computer and Information, Xinxiang University, Xinxiang, China

第一机构：新乡学院计算机与信息工程学院

年份：2014

卷号：6

期号：6

起止页码：1270-1276

外文期刊名：Journal of Chemical and Pharmaceutical Research

收录：EI(收录号：20151100648081);Scopus(收录号：2-s2.0-84924662499)

语种：英文

外文关键词：Cloud computing - Data mining - Distributed computer systems - Real time systems - Social networking (online) - Throughput

摘要：High-performance processing scientific data has enabled the development of digital resources and web-based services that facilitate uses of data beyond those that may have been envisioned by the original data producers. Scientific data processing systems must handle scientific data coming from real-time, high-throughput applications. Timely processing of scientific data is important and requires sufficient available resources to achieve high throughput and deliver accurate output results. Cloud Computing provides a low-priced way for small and medium sized enterprises to process scientific data. Based on Hadoop MapReduce of cloud computing, we propose the detailed procedure of scientific data processing algorithm which can improve the overall performance under the shared environment while retaining compatibility with the native Hadoop MapReduce in this paper. ? 2014, Journal of Chemical and Pharmaceutical Research, All rights reserved.