文献类型：期刊文献

英文题名：Scientific data processing framework for Hadoop MapReduce

作者：Kong, Xiangsheng[1]; Chen, Jianbiao[1]

第一作者：孔祥盛

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：2950-2954

外文期刊名：Journal of Chemical and Pharmaceutical Research

收录：EI(收录号：20151000598169);Scopus(收录号：2-s2.0-84923922704)

语种：英文

外文关键词：Medicine - Pharmacodynamics

摘要：Scientific workflows produce large amounts of scientific data. Hadoop MapReduce has been widely adopted for data-intensive processing of large datasets. The Kepler system can support scientific workflows, high–performance and high-throughput applications, which can be data-intensive and compute-intensive. The paper presented a "Kepler + Hadoop" framework for executing MapReduce-based scientific workflows on Hadoop. ? 2014, Journal of Chemical and Pharmaceutical Research. All rights reserved.