Industrial track: Architecting railway KPIs data processing with Big Data technologies

In our conducted research we have built the data processing pipeline for storing railway KPIs data based on Big Data open-source technologies - Apache Hadoop, Kafka, Kafka HDFS Connector, Spark, Airflow and PostgreSQL. Created methodology for data load testing allowed to iteratively perform data load tests with increased data size and evaluate needed cluster software and hardware resources and, finally, detected bottlenecks of solution. As a result of the research we proposed architecture for data processing and storage, gave recommendations on data pipeline optimization. In addition, we calculated approximate cluster machines sizing for current dataset volume for data processing and storage services.