30 0

Jargon of Hadoop MapReduce Scheduling Techniques: A Scientific Categorization

Title
Jargon of Hadoop MapReduce Scheduling Techniques: A Scientific Categorization
Author
이춘화
Issue Date
2019-03
Publisher
CAMBRIDGE UNIV PRESS
Citation
KNOWLEDGE ENGINEERING REVIEW, v. 34 , Page. 1-33
Abstract
Recently, valuable knowledge that can be retrieved from a huge volume of datasets (called Big Data) set in motion the development of frameworks to process data based on parallel and distributed computing, including Apache Hadoop, Facebook Corona, and Microsoft Dryad. Apache Hadoop is an open source implementation of Google MapReduce that attracted strong attention from the research community both in academia and industry. Hadoop MapReduce scheduling algorithms play a critical role in the management of large commodity clusters, controlling QoS requirements by supervising users, jobs, and tasks execution. Hadoop MapReduce comprises three schedulers: FIFO, Fair, and Capacity. However, the research community has developed new optimizations to consider advances and dynamic changes in hardware and operating environments. Numerous efforts have been made in the literature to address issues of network congestion, straggling, data locality, heterogeneity, resource under-utilization, and skew mitigation in Hadoop scheduling. Recently, the volume of research published in journals and conferences about Hadoop scheduling has consistently increased, which makes it difficult for researchers to grasp the overall view of research and areas that require further investigation. A scientific literature review has been conducted in this study to assess preceding research contributions to the Apache Hadoop scheduling mechanism. We classify and quantify the main issues addressed in the literature based on their jargon and areas addressed. Moreover, we explain and discuss the various challenges and open issue aspects in Hadoop scheduling optimizations.
URI
https://www.cambridge.org/core/journals/knowledge-engineering-review/article/jargon-of-hadoop-mapreduce-scheduling-techniques-a-scientific-categorization/AD1710CECC4AF123B8AB8BD56EB85813http://repository.hanyang.ac.kr/handle/20.500.11754/110281
ISSN
0269-8889; 1469-8005
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE