APACHE SPARK-BASED DISTRIBUTED FRAMEWORK FOR SCALABLE EDI TRANSACTION PROCESSING.

Abstract

The article describes how to use Apache Spark to improve Electronic Data Interchange (EDI) transactions. Apache Spark has high potential to address scalability, performance, and integration issues that commonly occur during peak loads in traditional EDI systems, including retail and logistics settings. In this study, it was established that the distributed computing services offered by Spark minimise load, increase processing speed, and minimise resource utilisation. The research compares performance by developing a quantitative assessment of real-world data from EDI systems using Spark and traditional centralised systems. Analysis results indicate that Spark-based systems are quick at handling transaction processing, can be extended, and are cost-effective. The article is about modernising the business EDI infrastructure, and as a result, massive savings have been made. It also implies directions for future research to make the use of distributed systems even lighter in EDI applications, e.g., Apache Spark.