2PTS: A Two-Phase Task Scheduling Algorithm for MapReduce
- Authors
- Lim, Byungnam; Shim, Yeeun; Chung, Yon Dohn
- Issue Date
- 9월-2016
- Publisher
- IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
- Keywords
- MapReduce; task scheduling algorithm; data locality
- Citation
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E99D, no.9, pp.2377 - 2380
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
- Volume
- E99D
- Number
- 9
- Start Page
- 2377
- End Page
- 2380
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/87716
- DOI
- 10.1587/transinf.2016EDL8075
- ISSN
- 1745-1361
- Abstract
- For an efficient processing of large data in a distributed system, Hadoop MapReduce performs task scheduling such that tasks are distributed with consideration of the data locality. The data locality, however, is limitedly exploited, since it is pursued one node at a time basis without considering the global optimality. In this paper, we propose a novel task scheduling algorithm that globally considers the data locality. Through experiments, we show our algorithm improves the performance of MapReduce in various situations.
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Collections - Graduate School > Department of Computer Science and Engineering > 1. Journal Articles
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