MapReduce Scheduler: A 360-degree view

TL;DR

This paper provides a comprehensive overview of MapReduce scheduling algorithms, analyzing their characteristics, limitations, and potential future directions to improve large-scale distributed computing efficiency.

Contribution

It systematically presents the state-of-the-art MapReduce scheduling algorithms and discusses issues and future possibilities in heterogeneous environments.

Findings

Analysis of various scheduling algorithms

Identification of shortcomings in current approaches

Discussion on future research directions

Abstract

Undoubtedly, the MapReduce is the most powerful programming paradigm in distributed computing. The enhancement of the MapReduce is essential and it can lead the computing faster. Therefore, here are many scheduling algorithms to discuss based on their characteristics. Moreover, there are many shortcoming to discover in this field. In this article, we present the state-of-the-art scheduling algorithm to enhance the understanding of the algorithms. The algorithms are presented systematically such that there can be many future possibilities in scheduling algorithm through this article. In this paper, we provide in-depth insight on the MapReduce scheduling algorithm. In addition, we discuss various issues of MapReduce scheduler developed for large-scale computing as well as heterogeneous environment.