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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 7, 2023.
Abstract: This case study examines Riot Games' use of Apache Spark and its effects on data processing and analytics. Riot Games is a well-known game production studio. The developer Riot Games, best known for the well-liked online multiplayer game League of Legends, manages enormous volumes of data produced daily by millions of players. Riot Games handled and analyzed this data quickly using Apache Spark, a distributed computing technology that made insightful findings and improved user experiences. This case study explores Riot Games' difficulties, the company's adoption of Apache Spark, its implementation, and the advantages of utilizing Spark's capabilities. We evaluated the drawbacks and advantages of adopting Spark in the gaming sector and offered suggestions for game creators wishing to embrace Spark for their data processing and real-time analytics requirements. Our study adds to the increasing body of knowledge on the use of Spark in the gaming sector and offers suggestions and insights for both game producers and researchers.
Kanhaiya Sharma, Firdous Hussain Mohammad and Deepak Parashar, “Apache Spark in Riot Games: A Case Study on Data Processing and Analytics” International Journal of Advanced Computer Science and Applications(IJACSA), 14(7), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140704
@article{Sharma2023,
title = {Apache Spark in Riot Games: A Case Study on Data Processing and Analytics},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140704},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140704},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {7},
author = {Kanhaiya Sharma and Firdous Hussain Mohammad and Deepak Parashar}
}
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.