MapReduce operations with WS-VLAM workflow management system

被引：3
|
作者：
Baranowski, Mikolaj [1 ]
Belloum, Adam [1 ]
Bubak, Marian [1 ]
机构：
[1] Univ Amsterdam, Inst Informat, NL-1098 XH Amsterdam, Netherlands
来源：
2013 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE | 2013年 / 18卷
关键词：
scientific workflow; Ruby; MapReduce; Hadoop; parallel processing;
D O I：
10.1016/j.procs.2013.05.449
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Workflow management systems are widely used to solve scientific problems as they enable orchestration of remote and local services such as database queries, job submission and running an application. To extend the role that workflow systems play in data-intensive science, we propose a solution that integrates WMS and MapReduce model. In this paper, we discuss possible solution of combining MapReduce and workflow applications, we describe the implementation of chosen solution based on metaprogramming approach in Ruby programming language and evaluate it with an example of word count application.
引用
收藏
页码：2599 / 2602
页数：4
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