Eliminate inefficiency in form of some extra data downloaded in sync for large files
維護者通常 1 天內回覆
還沒有人認領這個 Issue。
評估
- 難度
- 4/5
- 預估耗時
- 3-5 天
- 新手友好度
- 25/100
- Issue 類型
- 功能
- 描述清晰度
- 需要釐清
- 活躍度
- 停滯
- 技術堆疊
- python
- 領域
- performance
研究方向
No files or tests are named in the payload. Start by locating the Synchronizer class and the downloader it drives in the b2-sdk-python codebase, then trace where a sync download sets the Range header for the first part. The linked B2 integration checklist explains multithreaded downloads. Done means the sync downloader receives the file size and opens the first part with an exact range, avoiding the extra bytes.
由索引模型根據 Issue 內容生成。
描述
Large files are downloaded in parts in parallel by all compliant clients, as specified by B2 integration checklist.
The extra data cost is there because when we start streaming the file, we don't (usually) know the size, so we are not requesting an exact range for the download of the first part, but we are sort of requesting the entire file. As soon as the headers come we realize that it's actually a big file, so we start a download session for the further parts of the file. When the data stream for the first part will emit enough data for us to satisfy the first part of the download range, we close the socket HOWEVER because there is some latency on the network, the server has already managed to send us some extra data which is being transmitted from the server to the client while the connection close request is transmitted from the client to the server. These few extra KB are lost.
When in context of sync we do know the file size. Synchronizer could communicate the file size to a specialized implementation of downloader which would then set a clean download part size using the Range header even for the first part.
- 主要語言
- Python
- 星號
- 214
- 分支
- 68
- 平均合併
- 51 分鐘
- 30 天內合併 PR
- 6
環境準備
- 沒有 Dockerfile 或 Docker Compose 檔案
- 沒有 Pull Request 範本
- 閱讀貢獻指南
從這裡開始
- 先讀完整個 Issue，再讀專案的貢獻指南。
- 在 Issue 下留言說明你要接手 —— 這能避免兩個人做同樣的事。
- Fork 儲存庫，在一個分支上完成修改。
- 送出 Pull Request，並在描述裡引用這個 Issue 編號。
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