원문정보
초록
영어
This paper designed the learning resource storage model mainly based on Hadoop platform, and the system structure was optimized on the basis of the original system against the problems of inefficient storage of massive small files, high memory overhead on the Hadoop platform. The PBL teaching resources are classified to improve the utilization ratio of resources and access efficiency of resources according to the file size and file correlation. When processing the small files, small files are merged according to the knowledge point, and then storage processing is conducted with the method of handling large files, giving full play to the advantages of processing files in the Hadoop. Simulation experiment is conducted in the laboratory environment, to compare the integrated storage space with the time required for resources storage. The result is that the model can reduce the storage space of the file, and improve the integrated storage efficiency on the basis of not affecting file storage.
목차
1. Introduction
2. Learning Resource Storage Model Structure and Function Design
2.1. Learning Resources Analysis
2.2. Learning Resource Storage Model Structure Design
2.3. PBL Teaching Process
2.4. Distributed Storage Design of Learning Resources
3. Simulation Experiment Analysis
3.1. Storage Space Test
3.2. Storage Time Test
4. Conclusion
References