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http://dx.doi.org/10.6109/jkiice.2019.23.6.645

Implementation of query model of CQRS pattern using weather data  

Seo, Bomin (Department of Mobile Convergence Engineering, Hanbat National University)
Jeon, Cheolho (Department of Mobile Convergence Engineering, Hanbat National University)
Jeon, Hyeonsig (Department of Mobile Convergence Engineering, Hanbat National University)
An, Seyun (Department of Industrial Design, Hanbat National University)
Park, Hyun-ju (Department of Information and Communication Engineering, Hanbat National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.23, no.6, 2019 , pp. 645-651 More about this Journal
Abstract
At a time when large amounts of data are being poured out, there are many changes in software architecture or data storage patterns because of the nature of the data being written, rather more read-intensive than writing. Accordingly, in this paper, the query model of Command Query Responsibility Segmentation (CQRS) pattern separating the responsibilities of commands and queries is used to implement an efficient high-capacity data lookup system in users' requirements. This paper uses the 2018 temperature, humidity and precipitation data of the Korea Meteorological Administration Open API to store about 2.3 billion data suitable for RDBMS (PostgreSQL) and NoSQL (MongoDB). It also compares and analyzes the performance of systems with CQRS pattern applied from the perspective of the web server (Web Server) implemented and systems without CQRS pattern, the storage structure performance of each database, and the performance corresponding to the data processing characteristics.
Keywords
CQRS; RDBMS; NoSQL; Java; JSON;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 J. S. Oh, C. G. Song, "Transmission performance of improvements in mobile applications via XML and JSON data translation," Journal of Information Science Society, vol.39, no. 1, pp. 129-131, 2012.
2 json, www.json.org [Internet], Available : http://www.json.org/
3 P. Gomez, R. Casallas, and C. Roncancio, "Data schema does matter, even in NoSQL systems!," 2016 IEEE Tenth International Conference on Research Challenges in Information Science (RCIS), Grenoble, pp. 1-6, 2016.
4 DB-ENGINES, www.db-engines.com [Internet], Available : https://db-engines.com/en/ranking.
5 K. HAKIM, "Correctness for CQRS Systems," KTH Royal Institute of Technology, Stockholm, 2012.
6 M. Overeem, M. Spoor, and S. Jansen, "The dark side of event sourcing: Managing data conversion," 2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER), Klagenfurt, pp. 193-204, 2017.
7 C. B. Kyun, DDD START! Learn domain-driven design implementation and key concepts, 1th ed. Republic of Korea, KR : Seoul, 2016.
8 Public Data Portal, www.data.go.kr [Internet], Available: https://www.data.go.kr.
9 S. Y. Bang, H. D. Ha, C. J. Kim, "A Study on BigData-based Software Architecture Design for Utilizing Public Open Data," Journal of KIIT, vol. 13, no. 10, pp. 99-10, 2015.
10 B. H. Back, I. K. Ha, B. C. Ahn, "An Extraction Method of Sentiment Infromation from Unstructed Big Data on SNS," Journal of Korea Multimedia Society vol. 17, no. 6, pp. 671-680, Jun. 2014.   DOI