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Design\n### 1-1. Flow Diagram\n![제목 없는 다이어그3램 drawio](https://github.com/user-attachments/assets/8ee0fb02-1bfc-49c3-846d-ea2f838cebce)\n\n1. Split MP4 files into chunks.\n2. Send chunk file from client to server\n3. Integrate chunk files\n\n### 1-2. Goal\n- Enhance the efficiency of processing and transferring large files by effectively splitting MP4 files into chunks for seamless transmission and integration.\n- Improve the user experience by allowing users to upload files without delays, ensuring a smooth and responsive interface.\n- Optimize server resources to maintain stable and efficient file processing, minimizing downtime and bottlenecks.\n\n### 1-3. Key Points\n1. Efficiently handle large volumes of data using a message broker for low overhead and increased throughput.\n2. Utilize asynchronous and non-blocking operations to achieve optimal speed and responsiveness.\n3. Implement sequence numbers in chunk files to guarantee the correct order during integration, preventing data integrity issues.\n\n## 2. Implementation\n### 2-1. Speed comparison between chunked and regular methods (Based on 2GB file)\n* **Chunked Upload(Promise parallel processing)**\n  \n    \u003cimg src=\"chunked-upload.png\" width=\"300px\"/\u003e\n\n    \u003eaverage latency : 19000 ms\n\n* **Non Chunked Upload**\n  \n    \u003cimg src=\"non-chunked-upload.png\" width=\"305px\"/\u003e\n\n    \u003eaverage latency : 25000 ms\n\n#### Conclusion\nTransmitting files in chunks uses less bandwidth compared to sending the entire file at once, and it also allows for parallel processing, resulting in faster speeds.\n\n\n## 3. Reference\n* frontend : https://github.com/KNU-K/large-file-processing-fe-demo","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fknu-k%2Flarge-file-processing-demo","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fknu-k%2Flarge-file-processing-demo","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fknu-k%2Flarge-file-processing-demo/lists"}