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目录
- 背景
-
实现小文件整体上传
- 搭建前端环境
- 搭建服务端环境
-
如何实现大文件分片上传
- 客户端实现分片
- 客户端计算 hash
- 客户端上传分片
- 服务端实现校验接口
- 服务端实现分片上传接口
- 服务端实现合并接口
- 客户端实现暂停 / 复原性能
- 客户端实现进度条性能
- 客户端实现文件秒传
- bingo
- 总结
背景
工作中如果有负责开放平台,那么往往会有上传文件的诉求。个别 10M 内大小的图片,咱们能通过一个上传接口即可,但如果文件大小超过 100M 或者 1G 甚至更大,通过一个接口在人机交互上显然不敌对,冀望为用户提供进度条,实时告知上传进度;而且用户能够抉择暂停,比方断网或上传了谬误文件,用户也能随时复原上传;若用户反复上传雷同文件时,零碎能提醒秒传胜利。也就是实现相似于百度网盘的上传性能。
- 小文件整体上传效果图
- 大文件分片上传效果图
上面将从零搭建前端和服务端,实现小文件上传再循序渐进到上传大文件。
技术栈次要是前端:React、AntD、Typescript
;服务端:TS-Node、Express...
。
文章首发于 @lan-react/upload,转载请注明起源。客户端代码寄存、服务端代码寄存。
实现小文件整体上传
搭建前端环境
通过 create-react-app --template typescript
创立我的项目
引入 antdyarn add antd
而后 yarn start
运行我的项目
编写上传的组件
import React, {ChangeEvent, useState, useEffect} from 'react';
import {Row, Col, Input} from 'antd';
interface UploadProps {width?: number;}
interface CurrentFile {
file: File;
dataUrl?: string;
type?: string;
}
const isImage = (type: string = ''): boolean => type.includes('image');
const Upload: React.FC<UploadProps> = (props) => {
const {width = 300,} = props;
const [currentFile, setCurrentFile] = useState<CurrentFile>();
const onFileChange = (event: ChangeEvent<HTMLInputElement>) => {const file: File = event.target.files![0];
if (file) {const reader = new FileReader();
reader.addEventListener('load', () => {
setCurrentFile({
file: file,
dataUrl: reader.result as string,
type: file.type,
})
});
reader.readAsDataURL(file);
}
}
return (
<div>
<Input type="file" style={{width: width}} onChange={onFileChange} />
{isImage(currentFile?.type) ? <img src={currentFile?.dataUrl} style={{width: 100}} alt={currentFile?.file.name} /> : null }
</div>
)
}
export default Upload;
小文件上传应用FormData
return (
<div>
<Input type="file" style={{width: width}} onChange={onFileChange} />
+ <Button type="primary" onClick={() => onFileUpload(UploadType.WHOLE)}> 小文件整体上传 </Button>
</div>
)
编写一个按钮而后解决上传
// 上传类型
enum UploadType {
WHOLE,
PART,
}
// 大小检测
const checkSize = (size: number = 0, maxSize: number = 2 * 1024 * 1024 * 1024): boolean => {if (size > maxSize) {message.error(` 文件大小不能超过 2G`)
return false
}
return true
}
const onFileUpload = (type: UploadType = UploadType.WHOLE) => {if (!currentFile?.file) {message.error('请抉择文件~')
return
}
if (!checkSize(currentFile?.file?.size)) return
switch (type) {
case UploadType.WHOLE:
wholeUpload();
break;
}
}
// 整体上传
const wholeUpload = async () => {const formData = new FormData()
formData.append('file', currentFile?.file as File)
formData.append('name', currentFile?.file.name as string)
const res = await request({
url: '/wholeUpload',
method: 'POST',
data: formData,
})
message.success('上传胜利');
}
而后简略封装下 request
export interface Config {
baseUrl?: string;
url?: string;
method?: string;
headers?: any;
data?: any;
}
export const request = (conf: Config): Promise<any> => {
const config: Config = {
method: 'GET',
baseUrl: 'http://localhost:8000',
headers: {},
data: {},
...conf
}
return new Promise((resolve, reject) => {const xhr = new XMLHttpRequest();
xhr.open(config.method as string, `${config.baseUrl}${config.url}`);
for (const key in config.headers) {if (Object.prototype.hasOwnProperty.call(config.headers, key)) {const value = config.headers[key];
xhr.setRequestHeader(key, value);
}
}
xhr.responseType = 'json';
xhr.onreadystatechange = () => {if (xhr.readyState === 4) {if (xhr.status === 200) {resolve(xhr.response);
} else {reject(xhr.response);
}
}
}
xhr.send(config.data);
})
}
搭建服务端环境
应用 nodemon
和ts-node
"scripts": {"dev": "cross-env PORT=8000 nodemon --exec ts-node --files ./src/www.ts"},
借助 http
模块起服务编写./src/www.ts
import app from './app'
import http from 'http'
const port = process.env.PORT || 8000
const server = http.createServer(app)
const onError = (error: any) => {console.error(error)
}
const onListening = () => {console.log(`Listening on port ${port}`)
}
server.listen(port)
server.on('error', onError)
server.on('listening', onListening)
而后编写app.ts
import express, {Request, Response, NextFunction} from 'express'
import path from 'path'
import fs from 'fs-extra'
import logger from 'morgan'
import cors from "cors"
import multiparty from 'multiparty'
import createError from 'http-errors'
import {INTERNAL_SERVER_ERROR} from 'http-status-codes'
const app = express()
const PUBLIC_DIR = path.resolve(__dirname, 'public')
app.use(logger('dev'))
app.use(express.json())
app.use(express.urlencoded({ extended: true}))
app.use(cors())
app.use(express.static(PUBLIC_DIR))
app.post('/upload', async (req: Request, res: Response, next: NextFunction) => {const form = new multiparty.Form()
form.parse(req, async (err: any, fields, files) => {if (err) return next(err)
const name = fields.name[0]
const file = files.file[0]
await fs.move(file.path, path.resolve(PUBLIC_DIR, name), {overwrite: true})
res.json({success: true})
})
})
app.use((_req: Request, _res: Response, next: NextFunction) => {next(createError(404))
})
app.use((error: any, _req: Request, res: Response, _next: NextFunction) => {res.status(error.status || INTERNAL_SERVER_ERROR)
res.json({
succuess: false,
error,
})
})
export default app
将文件寄存到本地,即服务端我的项目根目录的 public
目录。
而后启动服务npm run dev
再如下操作,实现上传小文件。
接下来将实现大文件的分片上传
如何实现大文件分片上传
大文件分片上传的思路
- 客户端将大文件进行宰割。(这里粒度为 10M,宰割后文件按
fileName-${index}
进行排序以便服务端合并) - 为了实现秒传性能,须要对文件内容计算出 hash 值。(计算 hash 比拟耗时,借助 worker 实现,并提供进度条)
- 客户端对宰割后的小文件顺次调用接口上传。
- 服务端提供上传接口。(将所有小文件寄存到长期目录)
- 客户端上传所有分片文件后,调用申请合并的接口。
- 服务端提供合并接口。(按上述已排序的文件名进行合并,合并成大文件后寄存本地)
- 客户端提供暂停 / 复原性能。(暂停即调用
xhr.abort()
,复原即从新上传) - 特地的:在上传之前客户端会调用校验接口。(得悉文件是否已上传?文件上传了哪一部分?)
- 服务端提供校验接口。(依据文件名在长期目录下读取分片,如果有则将分片信息返回客户端)
- 客户端依据返回内容进行解决。(有成品文件即为秒传、有分片文件则只上传残余局部)
- 上传完毕
上述大抵实现思路,上面将介绍实现细节和留神点。
客户端实现分片
const onFileUpload = (type: UploadType = UploadType.WHOLE) => {
// ...
switch (type) {
case UploadType.WHOLE:
wholeUpload();
break;
+ case UploadType.PART:
+ partUpload()
+ break;
}
}
interface Part {
chunk: Blob;
size: number;
fileName?: string;
chunkName?: string;
loaded?: number;
percent?: number;
xhr?: XMLHttpRequest;
}
const partUpload = async () => {setUploadStatus(UploadStatus.UPLOADING);
// 1. 对文件进行分片
// 2. 依据分片计算文件 hash
// 3. 分片上传
const partList = createChunks(currentFile?.file as File);
const fileHash = await generateHash(partList);
console.log(fileHash, 'fileHash');
const lastDotIdx = currentFile?.file.name.lastIndexOf('.');
const extName = currentFile?.file.name.slice(lastDotIdx);
const fileName = `${fileHash}${extName}`;
partList.forEach((part: Part, index: number) => {
part.fileName = fileName;
part.chunkName = `${fileName}-${index}`;
part.loaded = 0;
part.percent = 0;
})
setFileName(fileName);
setPartList(partList);
await uploadParts(partList, fileName)
}
再顺次实现 createChunks
和generateHash
两个外围办法
const createChunks = (file: File, size: number = DEAFULT_SIZE): Part[] => {
let current: number = 0;
const partList: Part[] = [];
while (current < file.size) {const chunk: Blob = file.slice(current, current + size);
partList.push({
chunk,
size: chunk.size,
})
current += size
}
return partList;
}
客户端计算 hash
const generateHash = (partList: Part[]): Promise<any> => {return new Promise((resolve, reject) => {const worker = new Worker('/generateHash.js');
worker.postMessage({partList});
worker.onmessage = (event) => {const { percent, hash} = event.data;
setHashPercent(percent);
if (hash) {resolve(hash);
}
}
worker.onerror = error => {reject(error);
}
})
}
次要借助 Worker
在public
下新建 generateHash.js
文件
self.importScripts('https://cdn.bootcss.com/spark-md5/3.0.0/spark-md5.js');
self.onmessage = async (event) => {const { partList} = event.data;
const spark = new self.SparkMD5.ArrayBuffer();
let percent = 0;
const perSize = 100 / partList.length;
const buffers = await Promise.all(partList.map(({ chunk}) => new Promise((resolve, reject) => {const reader = new FileReader();
reader.readAsArrayBuffer(chunk);
reader.onload = (e) => {
percent += perSize;
self.postMessage({percent: Number(percent.toFixed(2)) });
resolve(e.target.result);
}
})));
buffers.forEach(buffer => spark.append(buffer));
self.postMessage({percent: 100, hash: spark.end() });
self.close();}
将每一个分片的计算进度 postMessage
给generateHash
,而后实时同步进度setHashPercent
客户端上传分片
const uploadParts = async (partList: Part[], fileName: string) => {
const res = await request({url: `/verify/${fileName}`,
})
if (res.code === 200) {if (!res.data.needUpload) {message.success('秒传胜利');
setPartList(partList.map((part: Part) => ({
...part,
loaded: DEAFULT_SIZE,
percent: 100,
})))
reset()
return
}
try {const { uploadedList} = res.data
const requestList = createRequestList(partList, uploadedList, fileName);
const partsRes = await Promise.all(requestList);
if (partsRes.every(item => item.code === 200)) {
const mergeRes = await request({url: `/merge/${fileName}`,
})
if (mergeRes.code === 200) {message.success('上传胜利');
reset()} else {message.error('上传失败,请稍后重试~');
}
} else {message.error('上传失败,请稍后重试~');
}
} catch (error) {message.error('上传失败或暂停');
console.error(error);
}
}
}
- 在上传之前客户端会调用校验接口。(得悉文件是否已上传?文件上传了哪一部分?)
- 客户端对宰割后的小文件顺次调用接口上传。
- 客户端上传所有分片文件后,调用申请合并的接口。
服务端实现校验接口
export const PUBLIC_DIR = path.resolve(__dirname, 'public')
export const TEMP_DIR = path.resolve(__dirname, 'temp')
const DEAFULT_SIZE = 1024 * 1024 * 10;
// ...
app.get('/verify/:fileName', async (req: Request, res: Response, _next: NextFunction) => {const { fileName} = req.params
const filePath = path.resolve(PUBLIC_DIR, fileName)
const existFile = await fs.pathExists(filePath)
if (existFile) {
res.json({
code: 200,
msg: 'success',
data: {needUpload: false,},
})
return
}
const folderPath = path.resolve(TEMP_DIR, fileName)
const existFolder = await fs.pathExists(folderPath)
let uploadedList: any[] = []
if (existFolder) {uploadedList = await fs.readdir(folderPath)
uploadedList = await Promise.all(uploadedList.map(async (fileName: string) => {const stat = await fs.stat(path.resolve(folderPath, fileName))
return {
fileName,
size: stat.size,
}
}))
}
res.json({
code: 200,
msg: 'success',
data: {
needUpload: true,
uploadedList,
}
})
})
服务端实现分片上传接口
app.post('/partUpload/:fileName/:start/:chunkName', async (req: Request, res: Response, _next: NextFunction) => {const { fileName, chunkName, start} = req.params
const folderPath = path.resolve(TEMP_DIR, fileName)
const existFolder = await fs.pathExists(folderPath)
if (!existFolder) {await fs.mkdirs(folderPath)
}
const filePath = path.resolve(folderPath, chunkName)
const ws = fs.createWriteStream(filePath, {start: Number(start),
flags: 'a',
})
req.on('end', () => {ws.close()
res.json({
code: 200,
msg: 'success',
data: true,
})
})
req.on('error', () => {ws.close()
})
req.on('close', () => {ws.close()
})
req.pipe(ws)
})
fileName
依据文件名创立长期目录寄存分片文件chunkName
分片名,命名格局为fileName-${index}
start
记录分片上传了多少
服务端实现合并接口
app.get('/merge/:fileName', async (req: Request, res: Response, _next: NextFunction) => {const { fileName} = req.params
try {await mergeChunks(fileName)
res.json({
code: 200,
msg: 'success',
data: true,
})
} catch (error) {
res.json({
code: 1,
msg: 'error',
data: false,
})
}
})
与客户端绝对应,合并规定与宰割规定相同。
const getIndex = (str: string) => {const matched = str.match(/-(\d{1,})$/)
return matched ? Number(matched[1]) : 0
}
const pipeStream = (filePath: string, ws: WriteStream) => new Promise((resolve, _reject) => {const rs = fs.createReadStream(filePath)
rs.on('end', async () => {await fs.unlink(filePath)
resolve()})
rs.pipe(ws)
})
export const mergeChunks = async (fileName: string, size: number = DEAFULT_SIZE) => {const filePath = path.resolve(PUBLIC_DIR, fileName)
const folderPath = path.resolve(TEMP_DIR, fileName)
const folderFiles = await fs.readdir(folderPath)
folderFiles.sort((a, b) => getIndex(a) - getIndex(b))
await Promise.all(folderFiles.map((chunk: string, index: number) => pipeStream(path.resolve(folderPath, chunk),
fs.createWriteStream(filePath, {start: index * size})
)))
await fs.rmdir(folderPath)
}
应用流而非间接写文件的形式
客户端实现暂停 / 复原性能
<Row>
<Col span={24}>
{uploadStatus === UploadStatus.INIT && <Button type="primary" onClick={() => onFileUpload(UploadType.PART)}> 大文件分片上传 </Button>
}
{uploadStatus === UploadStatus.UPLOADING && <Button type="primary" onClick={() => onFilePause()}> 暂停 </Button>
}
{uploadStatus === UploadStatus.PAUSE && <Button type="primary" onClick={() => onFileResume()}> 复原 </Button>
}
</Col>
</Row>
实现暂停即调用 xhr.abort
办法,须要先在 request.ts
中为其提供可挂载
// request.ts
if (config.setXhr) {config.setXhr(xhr);
}
// upload.tsx
const onFilePause = () => {partList.forEach((part: Part) => part.xhr && part.xhr.abort())
setUploadStatus(UploadStatus.PAUSE)
}
在此之前还需欠缺 createRequestList
办法
const createRequestList = (partList: Part[], uploadedList: Uploaded[], fileName: string): Promise<any>[] => {return partList.filter((part: Part) => {const uploadedFile = uploadedList.find(item => item.fileName === part.chunkName);
if (!uploadedFile) { // 此 chunk 还没上传过
part.loaded = 0;
part.percent = 0;
return true;
}
if (uploadedFile.size < part.chunk.size) { // 此 chunk 上传了一部分
part.loaded = uploadedFile.size;
part.percent = Number((part.loaded / part.chunk.size * 100).toFixed(2));
return true;
}
// 上传过了
return false;
}).map((part: Part) => request({url: `/partUpload/${fileName}/${part.loaded}/${part.chunkName}`,
method: 'POST',
headers: {'Content-Type': 'application/octet-stream',},
setXhr: (xhr: XMLHttpRequest) => { // + 挂载
part.xhr = xhr;
},
onProgress: (event: ProgressEvent) => { // + 进度条
part.percent = Number(((part.loaded! + event.loaded) / part.chunk.size * 100).toFixed(2));
console.log('part percent:', part.percent)
setPartList([...partList])
},
data: part.chunk.slice(part.loaded),
}))
}
再实现复原性能,即从新申请一次
const onFileResume = async () => {await uploadParts(partList, fileName)
setUploadStatus(UploadStatus.UPLOADING)
}
客户端实现进度条性能
如下面的办法 createRequestList
代码,在 onProgress
中实时获取到上传进度
const columns = [
{
title: '分片名',
dataIndex: 'chunkName',
key: 'chunkName',
width: '20%',
},
{
title: '进度条',
dataIndex: 'percent',
key: 'percent',
width: '80%',
render: (value: number) => {return <Progress percent={value} />
}
}
]
const totalPercent = partList.length > 0
? partList.reduce((memo: number, curr: Part) => memo + curr.percent!, 0) / partList.length
: 0
{ uploadStatus !== UploadStatus.INIT ? (
<>
<Row>
<Col span={4}>
Hash 进度条
</Col>
<Col>
<Progress percent={hashPercent} />
</Col>
</Row>
<Row>
<Col span={4}>
Total 进度条
</Col>
<Col>
<Progress percent={totalPercent} />
</Col>
</Row>
<Table
columns={columns}
dataSource={partList}
rowKey={row => row.chunkName as string}
/>
</>
) : null }
客户端实现文件秒传
在下面 uploadParts
办法中曾经实现
const uploadParts = async (partList: Part[], fileName: string) => {
const res = await request({url: `/verify/${fileName}`,
})
if (res.code === 200) {if (!res.data.needUpload) {message.success('秒传胜利');
setPartList(partList.map((part: Part) => ({
...part,
loaded: DEAFULT_SIZE,
percent: 100,
})))
reset()
return
}
// ...
}
}
bingo
效果图如下
总结
- 小文件上传应用 FormData,大文件上传设置
'Content-Type': 'application/octet-stream'
。FormData
可携带参数,octet-stream
参数可设置在 url 中。
formData.append('file', currentFile?.file as File)
formData.append('name', currentFile?.file.name as string)
request({url: `/partUpload/${fileName}/${part.loaded}/${part.chunkName}` })
- 因为 File 继承自
Blob
,客户端可应用 Blob.slice 对大文件进行宰割;服务端对分片文件存储,提供合并接口按切割程序进行合并(应用createWriteStream/createReadStream
)。 -
为了实现秒传性能,须要对文件进行惟一标识,服务端校验为已上传文件间接返回胜利和拜访地址。
- 应用 Worker 创立后台任务计算大文件惟一标识,防止页面卡死。
- 应用 Spark-md5 计算文件惟一标识
MD5
-
提供进度条性能
- 计算
MD5
时可借助Worker.postMessage
按分片粒度告诉前端计算进度 - 上传分片可借助 xhr.upload.onprogress 实时告诉前端上传进度
- 前端借助
Antd-Progress/Table
展现进度条
- 计算
-
提供暂停 / 复原性能
- 暂停借助 xhr.abort()终止申请
- 从新上传获取上传状况,再只上传未上传局部。在服务端读取上传分片状况,客户端上传时再次借助
Blob.slice(part.loaded)
。服务端存储时按fs.createWriteStream(filePath, { start: Number(start), flags: 'a' })
进行追加文件。