An Expressive Hadoop MapReduce Framework
The traditional Hadoop MapReduce framework is a simple programming model for large scale parallel and distributed data processing. However, the model is not structured for semantic-oriented large data processing since it is not expressive. This paper presents a tree-oriented approach
to enable expressiveness in the traditional Hadoop MapReduce framework. The new tree based MapReduce structure provides for group based processing, level based processing, and traversal order based processing. Stand-alone or nested, these processing constructs provides the required expressivity
for semantic-oriented large data processing. This is accomplished yet preserving the fundamental benefit of traditional MapReduce framework—fault-tolerant processing.
Keywords: Expressive; Hadoop MapReduce; Parallel Trees
Document Type: Research Article
Affiliations: 1: Faculty of Computing and Informatics, Multimedia University, Cyberjaya 63100, Malaysia 2: School of Information Technology, Monash University, Victoria 3800, Australia
Publication date: 01 November 2017
- ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
- Editorial Board
- Information for Authors
- Subscribe to this Title
- Ingenta Connect is not responsible for the content or availability of external websites
- Access Key
- Free content
- Partial Free content
- New content
- Open access content
- Partial Open access content
- Subscribed content
- Partial Subscribed content
- Free trial content