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DOI: 10.14569/IJACSA.2022.01308101
PDF

Straggler Mitigation in Hadoop MapReduce Framework: A Review

Author 1: Lukuman Saheed Ajibade
Author 2: Kamalrulnizam Abu Bakar
Author 3: Ahmed Aliyu
Author 4: Tasneem Danish

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 8, 2022.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Processing huge and complex data to obtain useful information is challenging, even though several big data processing frameworks have been proposed and further enhanced. One of the prominent big data processing frameworks is MapReduce. The main concept of MapReduce framework relies on distributed and parallel processing. However, MapReduce framework is facing serious performance degradations due to the slow execution of certain tasks type called stragglers. Failing to handle stragglers causes delay and affects the overall job execution time. Meanwhile, several straggler reduction techniques have been proposed to improve the MapReduce performance. This study provides a comprehensive and qualitative review of the different existing straggler mitigation solutions. In addition, a taxonomy of the available straggler mitigation solutions is presented. Critical research issues and future research directions are identified and discussed to guide researchers and scholars.

Keywords: Big data; blacklisting execution; Hadoop; MapReduce; spark; speculative execution; straggler

Lukuman Saheed Ajibade, Kamalrulnizam Abu Bakar, Ahmed Aliyu and Tasneem Danish, “Straggler Mitigation in Hadoop MapReduce Framework: A Review” International Journal of Advanced Computer Science and Applications(IJACSA), 13(8), 2022. http://dx.doi.org/10.14569/IJACSA.2022.01308101

@article{Ajibade2022,
title = {Straggler Mitigation in Hadoop MapReduce Framework: A Review},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.01308101},
url = {http://dx.doi.org/10.14569/IJACSA.2022.01308101},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {8},
author = {Lukuman Saheed Ajibade and Kamalrulnizam Abu Bakar and Ahmed Aliyu and Tasneem Danish}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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