At present, artificial intelligence-based methods have been able to achieve good results in radar emitter recognition task. However, with the development of electronic information technology, there will be more and more unknown emitters whose characteristic distribution and categories are unknown. In the absence of prior knowledge, it is difficult to fully train the artificial intelligence model, which makes most of the existing methods unable to well complete the recognition of unknown radar emitters. This paper proposes a big electromagnetic data solution that can be used for the recognition of unknown radar emitters, and then focuses on the Flink-based fast comparison retrieval and recognition algorithm for unknown radar emitters. Finally, a comparative experiment proves the effectiveness of the proposed method, and its recognition accuracy can reach 87.2%. When the parallelism is set to 6, the entire Mutual Information- K-Nearest Neighbor(MI-KNN) parallelization algorithm takes only 4.7 s.