Development of an interactive platform for searching bus tickets using distributed big data processing technologies

Abstract

In the modern context of digital transformation, the passenger transportation sector requires innovative solutions capable of ensuring high speed, accuracy, and scalability in route planning and fare calculation processes. Traditional ticket search services are often characterized by significant query processing delays and limited flexibility in forming pricing proposals. This highlights the need for new information systems oriented toward the integration of distributed data processing technologies. This work presents the development of a web application for searching bus tickets across multi-segment connections with a built-in fare recommendation module. The system combines fast route search functionality, support for complex queries with transfers, and automated fare calculation. Apache Spark is used as the computational core, enabling distributed processing of large data sets. The server-side is built using Flask, while PostgreSQL is employed for data storage. The user interface is implemented using HTML, CSS, and JavaScript, ensuring accessibility and ease of interaction. Analysis of existing analogs demonstrated the absence of comprehensive solutions that simultaneously optimize route search and automate fare calculation. The proposed system overcomes these limitations through integration with carrier APIs to collect upto-date information and the implementation of big data processing mechanisms. Experimental testing confirmed the effectiveness of the approach: system response time was reduced to 300–500 ms, and recommendation accuracy reached 92–95%. In cluster mode, the system can process over 1 million records per hour, indicating high performance and scalability. The practical significance of this development lies in its potential application as a standalone tool for carriers or as part of comprehensive transportation platforms. The system contributes to cost optimization, increased transparency of pricing polici es, and improved user experience, making it a promising solution for modern transportation logistics.