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In order to solve the problem of complex event pattern in big data and strengthen research on key technologies of the Internet of Things and computer time matching algorithms, this paper studies the problem based on Hadoop clustering algorithm. Firstly, based on the subtype attribute of event type, the maximum value is selected as the final attribute value of the event after weighting the event. Secondly, cluster analysis is conducted on the Internet of Things flow dataset through the relationship between complex events. Finally, the simulation test is carried out on the simulation dataset of complex event relationship, and the simulation test of clustering algorithm comparison is carried out. The experimental results show that the clustering accuracy of different datasets is above 85%, and the clustering accuracy of causality reaches 96.07% when the dataset is 5G. Therefore, the algorithm proposed has high feasibility, good stability, and high speed and effectiveness for complex event processing. This study has certain practical significance for solving the problem of complex event pattern in big data. [ABSTRACT FROM AUTHOR]