Combining MapReduce and Serverless Computing for Efficient Word Frequency Statistics

Linxu Dai

2024

Abstract

Mapreduce is an important data processing model that can process massive data effectively and conveniently. Serverless computing is a new type of cloud computing technology with huge development potential, which aims to alleviate the limitations of centralized model training in traditional machine learning algorithms and can significantly protect data security and personal privacy. Inspired by the advantages of the aforementioned two technologies, this paper considers combining these two technologies together for efficient word frequency statistics. Specifically, this article first describes the basic principles and advantages of the MapReduce model and serverless computing technology, as well as their research and development direction and practical application in recent years. Then, this article details the proposed program framework for frequent statistical tasks based on the MapReduce model and serverless computing technology. Extensive experiments are conducted to demonstrate the effectiveness of proposed method by analyzing the results of the program operation and operation time. Finally, this article discusses ideas and directions that optimize the performance of MapReduce models based on serverless computing technology.

Paper Citation

in Harvard Style

Dai L. (2024). Combining MapReduce and Serverless Computing for Efficient Word Frequency Statistics. 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 506-510. DOI: 10.5220/0012957900004508

in Bibtex Style

@conference{emiti24,
author={Linxu Dai},
title={Combining MapReduce and Serverless Computing for Efficient Word Frequency Statistics},
booktitle={Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2024},
pages={506-510},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012957900004508},
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 - Combining MapReduce and Serverless Computing for Efficient Word Frequency Statistics
SN - 978-989-758-713-9
AU - Dai L.
PY - 2024
SP - 506
EP - 510
DO - 10.5220/0012957900004508
PB - SciTePress