Abstract
Under the background of informatization, physical education in colleges and universities in our country is facing a new revolution. Informatization is the key point of this change. Based on this, this paper studies college students’ physical health data mining from the perspective of cloud data. First of all, this paper analyzes the unified scheduling of students’ physical health data resources in the cloud environment. Secondly, the paper focuses on the Yam system, and designs a new data mining and scheduling model Luna Scheduler based on the DRF algorithm. The model is optimized from Yam’s native Capacity Scheduler, including scheduling algorithms, fine-grained resource allocation, etc. Finally, the paper tests the algorithm and the model, and proposes a parameter configuration suggestion that is beneficial to improve the Yarn throughput’s verification.
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