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- Miyazaki Reina
- Graduate School of Engineering, Kochi University of Technology
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- Matsuzaki Kiminori
- School of Information, Kochi University of Technology
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- Sato Shigeyuki
- School of Information, Kochi University of Technology
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Abstract
<p>MapReduce is a framework for large-scale data processing proposed by Google, and its open-source implementation, Hadoop MapReduce, is now widely used. Several language systems have been proposed to make developing MapReduce programs easier, for instance, Sawzall, FlumeJava, Pig, Hive, and Crunch. These language systems mainly target applications that can be naturally solved by using a MapReduce-like programming model. In this study, we propose a new MapReduce-program generator that accepts programs manipulating one-dimensional arrays. By using the proposed generator, users only need to write sequential programs to generate Hadoop MapReduce programs automatically. We applied some program optimization techniques to the generation of Hadoop MapReduce programs. In this paper, we also report our experiment results that compare programs generated by the proposed generator with hand-written MapReduce programs.</p>
Journal
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- Journal of Information Processing
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Journal of Information Processing 25 (0), 841-851, 2017
Information Processing Society of Japan
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Details 詳細情報について
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- CRID
- 1390282680272625792
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- NII Article ID
- 130005990949
- 170000148795
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- NII Book ID
- AA11464814
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- ISSN
- 18827802
- 18826652
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- Text Lang
- en
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- Data Source
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- JaLC
- IRDB
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed