Spark Analysis Technology in Engineering Project Management Support in Big Data Scenarios

Engineering project management support plays a crucial role in modern engineering projects, improving the efficiency and level of project management, reducing project risks, and ensuring the smooth implementation and successful delivery of projects through planning, execution, monitoring, and analysis functions. However, traditional engineering project management support encounters many problems such as large amount of data, inefficiency, and data dispersion. In order to solve these problems, this paper uses Apache Spark technology to build a Spark-based big data analysis model to achieve the prediction of the project schedule, and data mining and analysis, etc. The experimental results show that the precision rate of the prediction of the project schedule reaches 92.76%, the recall rate reaches 92.54%, and the F1 value is 0.926, and the system's runtime is significantly higher than that of other algorithms, and although the speed gradually decreases with the increase of data volume, it always stays above 14GB/min.