Hadoop MapReduce Job Scheduling Algorithms Survey and Use Cases

Alaa A. Abdallat, Arwa I. Alahmad, Duaa A. AlSahebAlT Amimi and Jaber A. AlWidian

Modern Applied Science, 2019, vol. 13, issue 7, 38

Abstract: Data is the fastest growing asset in the 21st century, extracting insights is becoming of the essence as the traditional ecosystems are incapable to process the resulting amounts, complying with different structural levels, and is rapidly produced. Along this paradigm, the need for processing mostly real time data among other factors highlights the need for optimized Job Scheduling Algorithms, which is the interest of this paper. It is one of the most important aspects to guarantee an efficient processing ecosystem with minimal execution time, while exploiting the available resources taking into consideration granting all the users a fair share of the dedicated resources. Through this work, we lay some needed background on the Hadoop MapReduce framework. We run a comparative analysis on different algorithms that are classified on different criteria. The light is shed on different classifications- Cluster Environment, Job Allocation Strategy, Optimization Strategy, and Metrics of Quality. We, also, construct use cases to showcase the characteristics of selected Job Scheduling Algorithms, then we present a comparative display featuring the details for the use cases.

Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://ccsenet.org/journal/index.php/mas/article/download/0/0/39863/40923 (application/pdf)
https://ccsenet.org/journal/index.php/mas/article/view/0/39863 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ibn:masjnl:v:13:y:2019:i:7:p:38

Access Statistics for this article

More articles in Modern Applied Science from Canadian Center of Science and Education Contact information at EDIRC.
Bibliographic data for series maintained by Canadian Center of Science and Education ().