期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2013
卷号：48
期号：2
页码：1253-1257
出版社：Journal of Theoretical and Applied
摘要：Scientific workflows produce huge 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
