Events Sourcing and Command Query Responsibility Segregation Based Fast Data Architecture  

作　　者：Gérard Behou N’guessan Odilon Yapo Achiepo Jérôme Diako Gérard Behou N’guessan;Odilon Yapo Achiepo;Jérôme Diako(Research and Digital Expertise Unit (UREN), Virtual University of Cô,te d’Ivoire (UVCI), Abidjan, Ivory Coast;Lastic, ESATIC, Abidjan, Ivory Coast)

机构地区：[1]Research and Digital Expertise Unit (UREN), Virtual University of Cô,te d’Ivoire (UVCI), Abidjan, Ivory Coast [2]Lastic, ESATIC, Abidjan, Ivory Coast

出　　处：《Open Journal of Applied Sciences》2023年第2期198-206,共9页应用科学（英文）

摘　　要：With the advent of Big Data, the fields of Statistics and Computer Science coexist in current information systems. In addition to this, technological advances in embedded systems, in particular Internet of Things technologies, make it possible to develop real-time applications. These technological developments are disrupting Software Engineering because the use of large amounts of real-time data requires advanced thinking in terms of software architecture. The purpose of this article is to propose an architecture unifying not only Software Engineering and Big Data activities, but also batch and streaming architectures for the exploitation of massive data. This architecture has the advantage of making possible the development of applications and digital services exploiting very large volumes of data in real time;both for management needs and for analytical purposes. This architecture was tested on COVID-19 data as part of the development of an application for real-time monitoring of the evolution of the pandemic in Côte d’Ivoire using PostgreSQL, ELasticsearch, Kafka, Kafka Connect, NiFi, Spark, Node-Red and MoleculerJS to operationalize the architecture.With the advent of Big Data, the fields of Statistics and Computer Science coexist in current information systems. In addition to this, technological advances in embedded systems, in particular Internet of Things technologies, make it possible to develop real-time applications. These technological developments are disrupting Software Engineering because the use of large amounts of real-time data requires advanced thinking in terms of software architecture. The purpose of this article is to propose an architecture unifying not only Software Engineering and Big Data activities, but also batch and streaming architectures for the exploitation of massive data. This architecture has the advantage of making possible the development of applications and digital services exploiting very large volumes of data in real time;both for management needs and for analytical purposes. This architecture was tested on COVID-19 data as part of the development of an application for real-time monitoring of the evolution of the pandemic in Côte d’Ivoire using PostgreSQL, ELasticsearch, Kafka, Kafka Connect, NiFi, Spark, Node-Red and MoleculerJS to operationalize the architecture.

关 键 词：Architecture Software Engineering Big Data Data Engineering Real Time 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]