Analysis and Application of Spark Fast Data Recommendation Algorithm Based on Hadoop Platform

With the rapid advancement of information technology, efficient management and precise formulation of personalized recommendations have become the focus of attention in many fields. This article explains the core principles of Hadoop architecture and Spark technology, as well as the mechanism of their joint operation. We analyzed the multi-level architecture of Spark technology and its parallel processing model's contribution to driving algorithm performance. In terms of algorithm construction, the implementation process of a recommendation algorithm based on collaborative filtering and content matching on the Spark platform was described in detail, and its excellent performance was confirmed through experimental methods. We discussed the application examples of Hadoop Spark platform in multiple fields such as e-commerce, social networks, financial services, and online teaching, demonstrating the effectiveness of the algorithm in improving recommendation accuracy and accelerating system feedback speed.