Back to Search
Start Over
MapReduce Scheduling Algorithms in Hadoop: A Systematic Study
- Publication Year :
- 2023
-
Abstract
- Hadoop is a framework for storing and processing huge volumes of data on clusters. It uses Hadoop Distributed File System (HDFS) for storing data and uses MapReduce to process that data. MapReduce is a parallel computing framework for processing large amounts of data on clusters. Scheduling is one of the most critical aspects of MapReduce. Scheduling in MapReduce is critical because it can have a significant impact on the performance and efficiency of the overall system. The goal of scheduling is to improve performance, minimize response times, and utilize resources efficiently. A systematic study of the existing scheduling algorithms is provided in this paper. Also, we provide a new classification of such schedulers and a review of each category. In addition, scheduling algorithms have been examined in terms of their main ideas, main objectives, advantages, and disadvantages.
Details
- Database :
- OAIster
- Notes :
- Hedayati, Soudabeh, Maleki, Neda, Olsson, Tobias, Ahlgren, Fredrik, Seyednezhad, Mahdi, Berahmand, Kamal
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1399995869
- Document Type :
- Electronic Resource