Word Frequency Counting Based on Serverless MapReduce

Hanzhe Li, Bingchen Lin, Mengyuan Xu

2024

Abstract

With the increasing demand for high-performance and high-efficiency computing, cloud computing, especially serverless computing, has gradually become a research hotspot in recent years, attracting numerous research attention. Meanwhile, MapReduce, which is a popular big data processing model in the industry, has been widely applied in various fields. Inspired by the serverless framework of Function as a Service and the high concurrency and robustness of MapReduce programming model, this paper focus on combining them to reduce the time span and increase the efficiency when executing the word frequency counting task. In this case, the paper use a MapReduce programming model based on a serverless computing platform to figure out the most optimized number of Map functions and Reduce functions for a particular task. For the same amount of workload, extensive experiments show both execution time reduces and the overall efficiency of the program improves at different rates as the number of map functions and reduce functions increases. This paper suppose the discovery of the most optimized number of map and reduce functions can help cooperations and programmers figure out the most optimized solutions.

Paper Citation

in Harvard Style

Li H., Lin B. and Xu M. (2024). Word Frequency Counting Based on Serverless MapReduce. In Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-713-9, SciTePress, pages 40-45. DOI: 10.5220/0012897600004508

in Bibtex Style

@conference{emiti24,
author={Hanzhe Li and Bingchen Lin and Mengyuan Xu},
title={Word Frequency Counting Based on Serverless MapReduce},
booktitle={Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2024},
pages={40-45},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012897600004508},
isbn={978-989-758-713-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - Word Frequency Counting Based on Serverless MapReduce
SN - 978-989-758-713-9
AU - Li H.
AU - Lin B.
AU - Xu M.
PY - 2024
SP - 40
EP - 45
DO - 10.5220/0012897600004508
PB - SciTePress