实现大文件上传和断点续传实践经验总结
共 33818字,需浏览 68分钟
·
2022-07-13 07:58
原文:https://juejin.cn/post/7118671489615790094
实现文件上传,大文件,以及如何断点续传等技术实现细节,我会每个细节,每个代码都写出来,一起调试,一起跟着步骤一一实现。
大文件上传技术要点分析
技术要点分析:
e6
文件对象,ajax
上传,async await promise
,后台文件存储,流操作(写入到服务器里面去)。一个文件传统上传
8M
,现在文件上传一般很大的文件,就要考虑切片问题,实现大文件上传。js
在es6
文件对象file node stream
有所增强。任何文件都是二进制,分隔blob
(文件的一种类型)。一个大的文件可以分解为从哪个位置开始
start
,每一块多小size,offset
。http
请求,n
个切片可以并发上传。核心利用Blob.prototype.slice
方法,调用的slice
方法可以返回 原文件的某个切片。(速度更快,改善了体验)预先设置好的切片最大数量将文件切分为一个个切片,然后借助
http
的可并发性,同时上传多个切片,这样从原本传一个大文件,变成了同时传多个小的文件切片,可以大大减少上传时间。由于是并发,传输到服务器的顺序可能会发生变化,所以我们还需要给每个切片记录顺序。(前端的切片上传,让
http
并发带来上传大文件的快感。
大文件上传前端
创建big_file_upload
目录文件,初始化node
的项目:npm init -y
,生成package.json
文件。创建file_slice.html
文件,模拟文件上传,切片的过程,以及说明代码的意义。
live-server
启动一下我们本地的服务器,它是npm
的一个包,可以下载npm i -g live-server
。也可以下载vs code
里live server
插件。启动.html
文件。
file_slice文件
file_slice.html
代码:
<!DOCTYPE html><html>
<head>
<meta charset="utf-8">
<title></title>
</head>
<body>
<input type="file" id="file">
<script>
document.getElementById('file')
.addEventListener('change', (event) => { const file = event.target.files[0]; // es6 文件对象
// console.log(file);
// console.log(Object.prototype.toString.call(file)); // [object File]
// console.log(Object.prototype.toString.call(file.slice(0, 102400))); // [object Blob]
let cur = 0, size = 1024*1024; // 1M
// blob等待上传的对象,所有的切片上传完
const fileChunkList = []; // blob数组
while(cur < file.size) {
fileChunkList.push({ // cur start offset end
file: file.slice(cur, cur + size)
});
cur += size;
} console.log(fileChunkList)
}) </script>
</body></html>
file.slice
完成切片,blob
类型文件切片,js
二进制文件类型的blob
协议。在文件上传到服务器之前就可以提前预览。
返回文档最后修改的日期和时间 lastModified: xxxx891269598
返回文档最后修改的日期和时间 lastModifiedDate: Tue Feb 15 xxxx 10:14:29 GMT+0800 (中国标准时间) {}
名字 name: "JavaScript高级程序设计(第4版).pdf"大小 size: 14355650类型 type: "application/pdf"网络工具包相对路径 webkitRelativePath: ""
size: 102400type: ""[[Prototype]]: Blob
(14) [{…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}, {…}]0: {file: Blob}1: {file: Blob}2: {file: Blob}3: {file: Blob}4: {file: Blob}5: {file: Blob}6: {file: Blob}7: {file: Blob}8: {file: Blob}9: {file: Blob}10: {file: Blob}11: {file: Blob}12: {file: Blob}13: {file: Blob}length: 14
Blob.slice
Blob.slice()
方法用于创建一个包含源 Blob
的指定字节范围内的数据的新 Blob
对象。
返回值
一个新的 Blob
对象,它包含了原始 Blob
对象的某一个段的数据。
blob文件
同目录下创建 blob.html
文件,代码:
<!DOCTYPE html><html>
<head>
<meta charset="utf-8">
<title></title>
</head>
<body>
<img src="" alt="" id="pic" width="350px">
<input type="file" id="file" />
<script>
// es6 file对象 blob blob:// 在文件上传解决的问题。
// 传统es5时代文件只有上传到服务器后,静态服务提供一个远程地址给我们,才能够看到我们上传的这张图片。
// es6在本地客户端操作文件的能力 file对象。
// blob 协议在本地就把它立马显示出来,配上上传进度,更好的用户体验。
document.getElementById('file').addEventListener('change', (e) => { const file = e.target.files[0]; const URL = window.URL; const objectUrl = URL.createObjectURL(file); console.log(objectUrl); const pic = document.getElementById('pic');
pic.src = objectUrl;
pic.onload = function() {
URL.revokeObjectURL(objectUrl); // 协议地址 释放
}
}) </script>
</body></html>
预览效果:
思路步骤
切片,target
目标后端文件下以名字为目录的文件;服务器端,如恶化将这些切片,合并成一个,并且显示原来的图片,对于服务器端node
流 stream
的概念。
开始在big_file_upload
文件下创建server
目录,初始化一下npm init -y
,生成package.json
文件,添加一下我们的入口文件,index.js
文件。
创建文件目录:
说明:server
后端服务,target
存储文件,某文件下等
server
目录下的index.js
文件代码:
const path = require('path'); // 路径const fse = require('fs-extra'); // fs扩展包// 上传目录const UPLOAD_DIR = path.resolve(__dirname, ".", "target"); // server/target// console.log(UPLOAD_DIR);const filename = 'da';const filePath = path.resolve(UPLOAD_DIR, '..', `${filename}.mp3`); // 路径console.log(filePath); // 根目录下const pipeStream = (path, writeStream) =>
new Promise(resolve => { const readStream = fse.createReadStream(path);
readStream.on('end',() => {
fse.unlinkSync(path); // 移除
resolve();
})
readStream.pipe(writeStream);
})const mergeFileChunk = async (filePath, filename, size) => { // console.log(filePath, filename, size)
// 大文件上传时,设计后端思想时每个要上传的文件,先以文件名,
// 为target目录名,把分文件blob,放入这个目录
// 文件blob上传前要加上index
// node 文件合并肯定可以的,stream
const chunkDir = path.resolve(UPLOAD_DIR, filename); // console.log(chunkDir);
const chunkPaths = await fse.readdir(chunkDir); // console.log(chunkPaths); // 路径下的数组文件名
chunkPaths.sort((a, b) => a.split('-')[1] - b.split('-')[1]); // console.log(chunkPaths, '++');
// 每块内容写入最后的文件,promise
await Promise.all(
chunkPaths.map((chunkPath, index) =>
pipeStream( // 回流的方法
path.resolve(chunkDir, chunkPath),
fse.createWriteStream(filePath, { start: index * size, end: (index + 1) * size
})
)
)
) // console.log('文件合并成功');
fse.rmdirSync(chunkDir); // 删除}
mergeFileChunk(filePath, filename, 0.5*1024*1024);
fs
提供文件的读写,删除,文件的移动,文件的目录,文件的目录查看等等yarn add fs-extra
yarn global add nodemon
stream
流可读流,可写流
chunk
都是一个二进制流文件Promise.all
来包装每个chunk
的写入start end
fse createWriteStream
每个
chunk
写入 先创建可读流,再pipe
给可写流的过程。
思路:以原文件做为文件夹的名字,在上传blobs
到这个文件夹,前且每个blob
都以文件-index
的命名方式来存储。
http并发上传大文件切片
修改file_slice.html
文件:
<!DOCTYPE html><html>
<head>
<meta charset="utf-8">
<title></title>
</head>
<body>
<input type="file" id="file">
<script>
// 请求封装
// http并发文件上传 blob上传 chunk POST
// 当blob Promise.All 再发送一个merge的请求 /merge
function request({
url,
method = 'POST',
data,
headers = {},
requestList // 上传的文件列表
}) { return new Promise(resolve => { const xhr = new XMLHttpRequest(); // js ajax 对象
xhr.open(method, url); // 请求
Object.keys(headers).forEach(key => {
xhr.setRequestHeader(key, headers[key]) // 请求加头信息
})
xhr.send(data);
xhr.onload = e => { // 事件监听
resolve({ data: e.target.response
})
}
})
} document.getElementById('file')
.addEventListener('change', async (event) => { const file = event.target.files[0]; // es6 文件对象
// console.log(file);
const file_name = file.name.split('.')[0]; // console.log(Object.prototype.toString.call(file)); // [object File]
// console.log(Object.prototype.toString.call(file.slice(0, 102400))); // [object Blob]
let cur = 0, size = 1024*1024; // 1M
// blob等待上传的对象,所有的切片上传完
const fileChunkList = []; // blob数组
while(cur < file.size) {
fileChunkList.push({ // cur start offset end
file: file.slice(cur, cur + size)
});
cur += size;
} console.log(fileChunkList) const requestList = fileChunkList.map(({file}, index) => { // 请求的数组
const formData = new FormData(); // js post form
formData.append('chunk', file);
formData.append('filename', `${file_name}-${index}`); return {
formData
};
})
.map(async ({ formData }) => request({ url: 'http://localhost:3000', // 前后端的api
data: formData
})) await Promise.all(requestList); // 并发吧
// console.log(requestList);
}) </script>
</body></html>
server
目录下,创建main.js
文件,处理提交:
下载
yarn add multiparty
const http = require('http');const path = require('path');const multiparty = require('multiparty');const fse = require('fs-extra');const server = http.createServer();const UPLOAD_DIR = path.resolve(__dirname, '.', 'target');
server.on('request', async (req, res) => {
res.setHeader("Access-Control-Allow-Origin", "*");
res.setHeader("Access-Control-Allow-Headers", "*"); // res.end("hello");
if (req.url == '/') { // chunk, name
const multipart = new multiparty.Form(); // console.log(multipart)
multipart.parse(req, async (err, fields, files) => { if (err) { return;
} // console.log(files);
const [chunk] = files.chunk; // 拿到了文件块
const [filename] = fields.filename; // 文件名
// 块名
// console.log(filename);
const dir_name = filename.split('-')[0]; const chunkDir = path.resolve(UPLOAD_DIR, dir_name); if (!fse.existsSync(chunkDir)) { await fse.mkdirs(chunkDir)
} // chunk.path
// 把chunk放入目录
await fse.move(chunk.path, `${chunkDir}/${filename}`);
})
} else if (req.url == '/merge/') { // 合并
res.end('OK');
}
})
server.listen(3000, () => console.log('正在监听3000端口'))
Form { _writableState: WritableState { objectMode: false, highWaterMark: 16384, finalCalled: false, needDrain: false, ending: false, ended: false, finished: false, destroyed: false, decodeStrings: true, defaultEncoding: 'utf8', length: 0, writing: false, corked: 0, sync: true, bufferProcessing: false, onwrite: [Function: bound onwrite], writecb: null, writelen: 0, afterWriteTickInfo: null, buffered: [], bufferedIndex: 0, allBuffers: true, allNoop: true, pendingcb: 0, prefinished: false, errorEmitted: false, emitClose: false, autoDestroy: true, errored: null, closed: false
}, _events: [Object: null prototype] { newListener: [Function (anonymous)] }, _eventsCount: 1, _maxListeners: undefined, error: null, autoFields: false, autoFiles: false, maxFields: 1000, maxFieldsSize: 2097152, maxFilesSize: Infinity, uploadDir: 'C:\\Users\\xxx\\xxx\\Local\\xxx', encoding: 'utf8', bytesReceived: 0, bytesExpected: null, openedFiles: [], totalFieldSize: 0, totalFieldCount: 0, totalFileSize: 0, flushing: 0, backpressure: false, writeCbs: [], emitQueue: [],
[Symbol(kCapture)]: false}
断点续传
服务器端返回,告知我从那开始
浏览器端自行处理
缓存处理
在切片上传的
axios
成功回调中,存储已上传成功的切片在切片上传前,先看下
localstorage
中是否存在已上传的切片,并修改uploaded
构造切片数据时,过滤掉
uploaded
为true
的
垃圾文件清理
前端在localstorage设置缓存时间,超过时间就发送请求通知后端清理碎片文件,同时前端也要清理缓存。
前后端都约定好,每个缓存从生成开始,只能存储12小时,12小时后自动清理
为每个文件切割块添加不同的标识,
hash
当上传成功后,记录上传成功的标识
当我们暂停或者发送失败后,可以重新发送没有上传成功的切割文件
创建vue项目:vue create vue-upload-big-file
.
$ vue --version
@vue/cli 4.5.13vue create vue-upload-big-file
$ vue create vue-upload-big-file
? Please pick a preset: (Use arrow keys)
? Please pick a preset: Manually select features
? Check the features needed for your project: (Press <space> to select, <a> to t
? Check the features needed for your project: Choose Vue version, Babel
? Choose a version of Vue.js that you want to start the project with (Use arrow
? Choose a version of Vue.js that you want to start the project with 2.x
? Where do you prefer placing config for Babel, ESLint, etc.? (Use arrow keys)
> In dedicated config files
? Where do you prefer placing config for Babel, ESLint, etc.? In package.json
? Save this as a preset for future projects? (y/N) n
yarn add element-ui
在main.js
中引入element-ui
,代码如下:
import Vue from 'vue
import App from './App.vue'
import ElementUI from 'element-uiimport 'element-ui/lib/theme-chalk/index.css'Vue.use(ElementUI);
Vue.config.productionTip = falsenew Vue({ render: h => h(App),
}).$mount('#app')
App.vue
代码清理如下:
<template> <div id="app">
</div></template><script>export default { name: 'app', components: {
}
}</script>
App.vue
代码实现:
async calculateHash (fileChunkList) { return new Promise(resolve => { // 需要花时间的任务
// web workers
// js 单线程的 UI 线程
// html5 web workers 单独开一个线程 独立于 worker
// 回调
this.container.worker = new Worker('/hash.js'); this.container.worker.postMessage({ fileChunkList }); this.container.worker.onmessage = e => { console.log(e.data);
}
})
}async handleUpload (e) { // 大量的任务
if (!this.container.file) return; this.status = Status.uploading; const fileChunkList = this.createFileCHunk(this.container,file); this.container.hash = await this.calculateHash(fileChunkList);
}
createFileCHunk (file, size = SIZE) { const fileChunkList = []; let cur = 0; while (cur < file.size) {
fileChunkList.push({ file: file.slice(cur, cur + size)
});
cur += size;
} return fileChunkList;
}handleFileChange(e) { // 分隔文件
const [ file ] = e.target.files; // 拿到第一个文件
// console.log(e.target.files);
this.container.file = file;
}
无论时前端还是后端,要考虑传输文件,特别是大文件,有可能发生丢失文件的情况,网速卡顿,服务器超时,如何避免丢失的情况。hash
当点击上传按钮时候,调用createFileChunk
将文件进行切片,切片数量通过文件大小控制,这里设置默认值大小,进行默认值大小的进行切片
createFileChunk
内使用while
循环和slice
方法将切片放入fileChunkList
数组中返回
在生成文件切片时,需要给每个切片一个标识作为hash
,这里使用文件名+下标,这样后端可以知道切片是第几个切片,用于之后的合并切片
FormData.append()
发送数据用到了 FormData
formData.append(name, value, filename)
,其中 filename
为可选参数,是传给服务器的文件名称, 当一个 Blob 或 File
被作为第二个参数的时候, Blob
对象的默认文件名是 "blob"
。
什么叫hash呢
什么叫hash
呢?文件名,并不是唯一的,1.jpg
图片,1.jpg
图片,或 2.jpg
图片 一样的内容。- 不同名的图片,内容是一样的。针对文件内容进行 hash
计算。丢失重传。
随后调用uploadChunks
上传所有的文件切片,将文件切片,切片hash
,以及文件名放入FormData
中,再调用上一步的 request
函数返回一个 promise
,最后调用 Promise.all
并发上传所有的切片
spark-md5.min.js
:
(function(factory){if(typeof exports==="object"){module.exports=factory()}else if(typeof define==="function"&&define.amd){define(factory)}else{var glob;try{glob=window}catch(e){glob=self}glob.SparkMD5=factory()}})(function(undefined){"use strict";var add32=function(a,b){return a+b&4294967295},hex_chr=["0","1","2","3","4","5","6","7","8","9","a","b","c","d","e","f"];function cmn(q,a,b,x,s,t){a=add32(add32(a,q),add32(x,t));return add32(a<<s|a>>>32-s,b)}function md5cycle(x,k){var a=x[0],b=x[1],c=x[2],d=x[3];a+=(b&c|~b&d)+k[0]-680876936|0;a=(a<<7|a>>>25)+b|0;d+=(a&b|~a&c)+k[1]-389564586|0;d=(d<<12|d>>>20)+a|0;c+=(d&a|~d&b)+k[2]+606105819|0;c=(c<<17|c>>>15)+d|0;b+=(c&d|~c&a)+k[3]-1044525330|0;b=(b<<22|b>>>10)+c|0;a+=(b&c|~b&d)+k[4]-176418897|0;a=(a<<7|a>>>25)+b|0;d+=(a&b|~a&c)+k[5]+1200080426|0;d=(d<<12|d>>>20)+a|0;c+=(d&a|~d&b)+k[6]-1473231341|0;c=(c<<17|c>>>15)+d|0;b+=(c&d|~c&a)+k[7]-45705983|0;b=(b<<22|b>>>10)+c|0;a+=(b&c|~b&d)+k[8]+1770035416|0;a=(a<<7|a>>>25)+b|0;d+=(a&b|~a&c)+k[9]-1958414417|0;d=(d<<12|d>>>20)+a|0;c+=(d&a|~d&b)+k[10]-42063|0;c=(c<<17|c>>>15)+d|0;b+=(c&d|~c&a)+k[11]-1990404162|0;b=(b<<22|b>>>10)+c|0;a+=(b&c|~b&d)+k[12]+1804603682|0;a=(a<<7|a>>>25)+b|0;d+=(a&b|~a&c)+k[13]-40341101|0;d=(d<<12|d>>>20)+a|0;c+=(d&a|~d&b)+k[14]-1502002290|0;c=(c<<17|c>>>15)+d|0;b+=(c&d|~c&a)+k[15]+1236535329|0;b=(b<<22|b>>>10)+c|0;a+=(b&d|c&~d)+k[1]-165796510|0;a=(a<<5|a>>>27)+b|0;d+=(a&c|b&~c)+k[6]-1069501632|0;d=(d<<9|d>>>23)+a|0;c+=(d&b|a&~b)+k[11]+643717713|0;c=(c<<14|c>>>18)+d|0;b+=(c&a|d&~a)+k[0]-373897302|0;b=(b<<20|b>>>12)+c|0;a+=(b&d|c&~d)+k[5]-701558691|0;a=(a<<5|a>>>27)+b|0;d+=(a&c|b&~c)+k[10]+38016083|0;d=(d<<9|d>>>23)+a|0;c+=(d&b|a&~b)+k[15]-660478335|0;c=(c<<14|c>>>18)+d|0;b+=(c&a|d&~a)+k[4]-405537848|0;b=(b<<20|b>>>12)+c|0;a+=(b&d|c&~d)+k[9]+568446438|0;a=(a<<5|a>>>27)+b|0;d+=(a&c|b&~c)+k[14]-1019803690|0;d=(d<<9|d>>>23)+a|0;c+=(d&b|a&~b)+k[3]-187363961|0;c=(c<<14|c>>>18)+d|0;b+=(c&a|d&~a)+k[8]+1163531501|0;b=(b<<20|b>>>12)+c|0;a+=(b&d|c&~d)+k[13]-1444681467|0;a=(a<<5|a>>>27)+b|0;d+=(a&c|b&~c)+k[2]-51403784|0;d=(d<<9|d>>>23)+a|0;c+=(d&b|a&~b)+k[7]+1735328473|0;c=(c<<14|c>>>18)+d|0;b+=(c&a|d&~a)+k[12]-1926607734|0;b=(b<<20|b>>>12)+c|0;a+=(b^c^d)+k[5]-378558|0;a=(a<<4|a>>>28)+b|0;d+=(a^b^c)+k[8]-2022574463|0;d=(d<<11|d>>>21)+a|0;c+=(d^a^b)+k[11]+1839030562|0;c=(c<<16|c>>>16)+d|0;b+=(c^d^a)+k[14]-35309556|0;b=(b<<23|b>>>9)+c|0;a+=(b^c^d)+k[1]-1530992060|0;a=(a<<4|a>>>28)+b|0;d+=(a^b^c)+k[4]+1272893353|0;d=(d<<11|d>>>21)+a|0;c+=(d^a^b)+k[7]-155497632|0;c=(c<<16|c>>>16)+d|0;b+=(c^d^a)+k[10]-1094730640|0;b=(b<<23|b>>>9)+c|0;a+=(b^c^d)+k[13]+681279174|0;a=(a<<4|a>>>28)+b|0;d+=(a^b^c)+k[0]-358537222|0;d=(d<<11|d>>>21)+a|0;c+=(d^a^b)+k[3]-722521979|0;c=(c<<16|c>>>16)+d|0;b+=(c^d^a)+k[6]+76029189|0;b=(b<<23|b>>>9)+c|0;a+=(b^c^d)+k[9]-640364487|0;a=(a<<4|a>>>28)+b|0;d+=(a^b^c)+k[12]-421815835|0;d=(d<<11|d>>>21)+a|0;c+=(d^a^b)+k[15]+530742520|0;c=(c<<16|c>>>16)+d|0;b+=(c^d^a)+k[2]-995338651|0;b=(b<<23|b>>>9)+c|0;a+=(c^(b|~d))+k[0]-198630844|0;a=(a<<6|a>>>26)+b|0;d+=(b^(a|~c))+k[7]+1126891415|0;d=(d<<10|d>>>22)+a|0;c+=(a^(d|~b))+k[14]-1416354905|0;c=(c<<15|c>>>17)+d|0;b+=(d^(c|~a))+k[5]-57434055|0;b=(b<<21|b>>>11)+c|0;a+=(c^(b|~d))+k[12]+1700485571|0;a=(a<<6|a>>>26)+b|0;d+=(b^(a|~c))+k[3]-1894986606|0;d=(d<<10|d>>>22)+a|0;c+=(a^(d|~b))+k[10]-1051523|0;c=(c<<15|c>>>17)+d|0;b+=(d^(c|~a))+k[1]-2054922799|0;b=(b<<21|b>>>11)+c|0;a+=(c^(b|~d))+k[8]+1873313359|0;a=(a<<6|a>>>26)+b|0;d+=(b^(a|~c))+k[15]-30611744|0;d=(d<<10|d>>>22)+a|0;c+=(a^(d|~b))+k[6]-1560198380|0;c=(c<<15|c>>>17)+d|0;b+=(d^(c|~a))+k[13]+1309151649|0;b=(b<<21|b>>>11)+c|0;a+=(c^(b|~d))+k[4]-145523070|0;a=(a<<6|a>>>26)+b|0;d+=(b^(a|~c))+k[11]-1120210379|0;d=(d<<10|d>>>22)+a|0;c+=(a^(d|~b))+k[2]+718787259|0;c=(c<<15|c>>>17)+d|0;b+=(d^(c|~a))+k[9]-343485551|0;b=(b<<21|b>>>11)+c|0;x[0]=a+x[0]|0;x[1]=b+x[1]|0;x[2]=c+x[2]|0;x[3]=d+x[3]|0}function md5blk(s){var md5blks=[],i;for(i=0;i<64;i+=4){md5blks[i>>2]=s.charCodeAt(i)+(s.charCodeAt(i+1)<<8)+(s.charCodeAt(i+2)<<16)+(s.charCodeAt(i+3)<<24)}return md5blks}function md5blk_array(a){var md5blks=[],i;for(i=0;i<64;i+=4){md5blks[i>>2]=a[i]+(a[i+1]<<8)+(a[i+2]<<16)+(a[i+3]<<24)}return md5blks}function md51(s){var n=s.length,state=[1732584193,-271733879,-1732584194,271733878],i,length,tail,tmp,lo,hi;for(i=64;i<=n;i+=64){md5cycle(state,md5blk(s.substring(i-64,i)))}s=s.substring(i-64);length=s.length;tail=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0];for(i=0;i<length;i+=1){tail[i>>2]|=s.charCodeAt(i)<<(i%4<<3)}tail[i>>2]|=128<<(i%4<<3);if(i>55){md5cycle(state,tail);for(i=0;i<16;i+=1){tail[i]=0}}tmp=n*8;tmp=tmp.toString(16).match(/(.*?)(.{0,8})$/);lo=parseInt(tmp[2],16);hi=parseInt(tmp[1],16)||0;tail[14]=lo;tail[15]=hi;md5cycle(state,tail);return state}function md51_array(a){var n=a.length,state=[1732584193,-271733879,-1732584194,271733878],i,length,tail,tmp,lo,hi;for(i=64;i<=n;i+=64){md5cycle(state,md5blk_array(a.subarray(i-64,i)))}a=i-64<n?a.subarray(i-64):new Uint8Array(0);length=a.length;tail=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0];for(i=0;i<length;i+=1){tail[i>>2]|=a[i]<<(i%4<<3)}tail[i>>2]|=128<<(i%4<<3);if(i>55){md5cycle(state,tail);for(i=0;i<16;i+=1){tail[i]=0}}tmp=n*8;tmp=tmp.toString(16).match(/(.*?)(.{0,8})$/);lo=parseInt(tmp[2],16);hi=parseInt(tmp[1],16)||0;tail[14]=lo;tail[15]=hi;md5cycle(state,tail);return state}function rhex(n){var s="",j;for(j=0;j<4;j+=1){s+=hex_chr[n>>j*8+4&15]+hex_chr[n>>j*8&15]}return s}function hex(x){var i;for(i=0;i<x.length;i+=1){x[i]=rhex(x[i])}return x.join("")}if(hex(md51("hello"))!=="5d41402abc4b2a76b9719d911017c592"){add32=function(x,y){var lsw=(x&65535)+(y&65535),msw=(x>>16)+(y>>16)+(lsw>>16);return msw<<16|lsw&65535}}if(typeof ArrayBuffer!=="undefined"&&!ArrayBuffer.prototype.slice){(function(){function clamp(val,length){val=val|0||0;if(val<0){return Math.max(val+length,0)}return Math.min(val,length)}ArrayBuffer.prototype.slice=function(from,to){var length=this.byteLength,begin=clamp(from,length),end=length,num,target,targetArray,sourceArray;if(to!==undefined){end=clamp(to,length)}if(begin>end){return new ArrayBuffer(0)}num=end-begin;target=new ArrayBuffer(num);targetArray=new Uint8Array(target);sourceArray=new Uint8Array(this,begin,num);targetArray.set(sourceArray);return target}})()}function toUtf8(str){if(/[\u0080-\uFFFF]/.test(str)){str=unescape(encodeURIComponent(str))}return str}function utf8Str2ArrayBuffer(str,returnUInt8Array){var length=str.length,buff=new ArrayBuffer(length),arr=new Uint8Array(buff),i;for(i=0;i<length;i+=1){arr[i]=str.charCodeAt(i)}return returnUInt8Array?arr:buff}function arrayBuffer2Utf8Str(buff){return String.fromCharCode.apply(null,new Uint8Array(buff))}function concatenateArrayBuffers(first,second,returnUInt8Array){var result=new Uint8Array(first.byteLength+second.byteLength);result.set(new Uint8Array(first));result.set(new Uint8Array(second),first.byteLength);return returnUInt8Array?result:result.buffer}function hexToBinaryString(hex){var bytes=[],length=hex.length,x;for(x=0;x<length-1;x+=2){bytes.push(parseInt(hex.substr(x,2),16))}return String.fromCharCode.apply(String,bytes)}function SparkMD5(){this.reset()}SparkMD5.prototype.append=function(str){this.appendBinary(toUtf8(str));return this};SparkMD5.prototype.appendBinary=function(contents){this._buff+=contents;this._length+=contents.length;var length=this._buff.length,i;for(i=64;i<=length;i+=64){md5cycle(this._hash,md5blk(this._buff.substring(i-64,i)))}this._buff=this._buff.substring(i-64);return this};SparkMD5.prototype.end=function(raw){var buff=this._buff,length=buff.length,i,tail=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],ret;for(i=0;i<length;i+=1){tail[i>>2]|=buff.charCodeAt(i)<<(i%4<<3)}this._finish(tail,length);ret=hex(this._hash);if(raw){ret=hexToBinaryString(ret)}this.reset();return ret};SparkMD5.prototype.reset=function(){this._buff="";this._length=0;this._hash=[1732584193,-271733879,-1732584194,271733878];return this};SparkMD5.prototype.getState=function(){return{buff:this._buff,length:this._length,hash:this._hash}};SparkMD5.prototype.setState=function(state){this._buff=state.buff;this._length=state.length;this._hash=state.hash;return this};SparkMD5.prototype.destroy=function(){delete this._hash;delete this._buff;delete this._length};SparkMD5.prototype._finish=function(tail,length){var i=length,tmp,lo,hi;tail[i>>2]|=128<<(i%4<<3);if(i>55){md5cycle(this._hash,tail);for(i=0;i<16;i+=1){tail[i]=0}}tmp=this._length*8;tmp=tmp.toString(16).match(/(.*?)(.{0,8})$/);lo=parseInt(tmp[2],16);hi=parseInt(tmp[1],16)||0;tail[14]=lo;tail[15]=hi;md5cycle(this._hash,tail)};SparkMD5.hash=function(str,raw){return SparkMD5.hashBinary(toUtf8(str),raw)};SparkMD5.hashBinary=function(content,raw){var hash=md51(content),ret=hex(hash);return raw?hexToBinaryString(ret):ret};SparkMD5.ArrayBuffer=function(){this.reset()};SparkMD5.ArrayBuffer.prototype.append=function(arr){var buff=concatenateArrayBuffers(this._buff.buffer,arr,true),length=buff.length,i;this._length+=arr.byteLength;for(i=64;i<=length;i+=64){md5cycle(this._hash,md5blk_array(buff.subarray(i-64,i)))}this._buff=i-64<length?new Uint8Array(buff.buffer.slice(i-64)):new Uint8Array(0);return this};SparkMD5.ArrayBuffer.prototype.end=function(raw){var buff=this._buff,length=buff.length,tail=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],i,ret;for(i=0;i<length;i+=1){tail[i>>2]|=buff[i]<<(i%4<<3)}this._finish(tail,length);ret=hex(this._hash);if(raw){ret=hexToBinaryString(ret)}this.reset();return ret};SparkMD5.ArrayBuffer.prototype.reset=function(){this._buff=new Uint8Array(0);this._length=0;this._hash=[1732584193,-271733879,-1732584194,271733878];return this};SparkMD5.ArrayBuffer.prototype.getState=function(){var state=SparkMD5.prototype.getState.call(this);state.buff=arrayBuffer2Utf8Str(state.buff);return state};SparkMD5.ArrayBuffer.prototype.setState=function(state){state.buff=utf8Str2ArrayBuffer(state.buff,true);return SparkMD5.prototype.setState.call(this,state)};SparkMD5.ArrayBuffer.prototype.destroy=SparkMD5.prototype.destroy;SparkMD5.ArrayBuffer.prototype._finish=SparkMD5.prototype._finish;SparkMD5.ArrayBuffer.hash=function(arr,raw){var hash=md51_array(new Uint8Array(arr)),ret=hex(hash);return raw?hexToBinaryString(ret):ret};return SparkMD5});
('/hash.js') // 放在根目录 public
web workers
优化我们的前端性能,将要花大量时间的,复杂的,放到一个新的线程中去计算,文件上传通过hash
计算。
hash.js
代码:
// 通过内容计算md5值self.importScripts('/spark-md5.min.js')
self.onmessage = e => { // self.postMessage({
// "msg": "您好"
// })
const { fileChunkList } = e.data; const spark = new self.SparkMD5.ArrayBuffer(); let percentage = 0; let count = 0; // console.log(fileChunkList, 'worker fileChunkList');
// 计算出hash
const loadNext = index => { const reader = new FileReader(); // 文件阅读对象
reader.readAsArrayBuffer(fileChunkList[index].file);
reader.onload = e => { // 事件
count++;
spark.append(e.target.result); if (count === fileChunkList.length)
{
self.postMessage({ percentage: 100, hash: spark.end()
});
self.close(); // 关闭当前线程
} else { // 还没读完
percentage += 100/fileChunkList.length;
self.postMessage({
percentage
});
loadNext(count);
}
}
}
loadNext(0)
} // this 当前的线程
大文件上传
将大文件转换为二进制流的格式
利用流可以切割的属性,将二进制流切割成多份
组装和分割块同等数量的请求块,并行或串行的形式发出请求
再给服务器端发出一个合并的信息
App.vue
<template> <div id="app">
<div>
<input type="file" :disabled="status !== Status.wait" @change="handleFileChange" />
<el-button @click="handleUpload" :disabled="uploadDisabled">上传</el-button>
<el-button @click="handleResume" v-if="status === Status.pause">恢复</el-button>
<el-button v-else :disabled="status !== Status.uploading || !container.hash" @click="handlePause">暂停 </el-button>
</div>
<div>
<div>计算文件hash</div>
<el-progress :percentage="hashPercentage"></el-progress>
<div>总进度</div>
<!-- 每个blob 进度 计算出来?
1. 每块blob 上传 值percentage 变的, watch
2. 计算属性 computed -->
<el-progress :percentage="fakeUploadPercentage"></el-progress>
</div>
<!-- 多个切片 -->
<!-- [{a:1}] -->
<el-table :data="data">
<el-table-column prop="hash" label="切片hash" align="center">
</el-table-column>
<el-table-column label="大小(kb)" align="center" width="120">
<template v-slot="{row}">
{{row.size | transformByte}} </template>
</el-table-column>
<el-table-column label="进度" align="center">
<template v-slot="{row}">
<el-progress :percentage="row.percentage" color="#909399">
</el-progress>
</template>
</el-table-column>
</el-table>
</div></template><script>
const SIZE = 10 * 1024 * 1024; // 切片大小
const Status = { wait: "wait", pause: "pause", uploading: "uploading"
}; export default { name: 'app', filters: { transformByte(val) { return Number((val / 1024).toFixed(0))
}
}, computed: { uploadDisabled() { return (
!this.container.file || [Status.pause, Status.uploading].includes(this.status)
);
}, uploadPercentage() { if (!this.container.file || !this.data.length) return 0; const loaded = this.data
.map(item => item.size * item.percentage)
.reduce((acc, cur) => acc + cur); return parseInt((loaded / this.container.file.size).toFixed(2));
}
}, watch: { uploadPercentage(now) { if (now > this.fakeUploadPercentage) { this.fakeUploadPercentage = now;
}
}
}, data: () => ({
Status, container: { file: null, hash: "", worker: null
}, hashPercentage: 0, data: [], requestList: [], status: Status.wait, // 当暂停时会取消 xhr 导致进度条后退
// 为了避免这种情况,需要定义一个假的进度条
fakeUploadPercentage: 0
}), methods: { async handleResume() { this.status = Status.uploading; const {
uploadedList
} = await this.verifyUpload( this.container.file.name, this.container.hash
) await this.uploadChunks(uploadedList);
}, handlePause() { this.status = Status.pause; // 状态停
this.resetData();
}, resetData() { this.requestList.forEach(xhr => xhr.abort()) this.requestList = []; if (this.container.worker) { //hash 计算过程中
this.container.worker.onmessage = null;
}
}, // xhr
request({
url,
method = "post",
data,
headers = {},
onProgress = e => e,
requestList
}) { return new Promise(resolve => { const xhr = new XMLHttpRequest();
xhr.upload.onprogress = onProgress;
xhr.open(method, url); Object.keys(headers).forEach(key =>
xhr.setRequestHeader(key, headers[key])
);
xhr.send(data);
xhr.onload = e => { // 将请求成功的 xhr 从列表中删除
if (requestList) { const xhrIndex = requestList.findIndex(item => item === xhr);
requestList.splice(xhrIndex, 1);
}
resolve({ data: e.target.response
});
}; // 暴露当前 xhr 给外部
requestList?.push(xhr);
});
}, async calculateHash(fileChunkList) { return new Promise(resolve => { // 封装花时间的任务
// web workers
// js 单线程的 UI 主线程
// html5 web workers 单独开一个线程 独立于 worker
// 回调 不会影响原来的UI
// html5 带来的优化,
this.container.worker = new Worker("/hash.js"); this.container.worker.postMessage({
fileChunkList
}); this.container.worker.onmessage = e => { // console.log(e.data);
const {
percentage,
hash
} = e.data; console.log(percentage, '----'); this.hashPercentage = percentage; if (hash) {
resolve(hash);
}
}
})
}, async handleUpload(e) { // 大量的任务
if (!this.container.file) return; this.status = Status.uploading; const fileChunkList = this.createFileChunk(this.container.file); console.log(fileChunkList); this.container.hash = await this.calculateHash(fileChunkList); // 文件 hash 没必要上传同一个文件多次
const {
shouldUpload,
uploadedList
} = await this.verifyUpload( //上传, 验证
this.container.file.name, this.container.hash
); console.log(shouldUpload, uploadedList); if (!shouldUpload) { this.$message.success("秒传:上传成功"); this.status = Status.wait; return;
} this.data = fileChunkList.map(({
file
}, index) => ({ fileHash: this.container.hash, //文件的hash
index, hash: this.container.hash + "-" + index, //每个块都有自己的index 在内的hash, 可排序, 可追踪
chunk: file, size: file.size, percentage: uploadedList.includes(index) ? 100 : 0 //当前切片是否已上传过
})); await this.uploadChunks(uploadedList); //上传切片
}, // 上传切片,同时过滤已上传的切片
async uploadChunks(uploadedList = []) { // console.log(this.data);
// 数据数组this.data => 请求数组 =》 并发
const requestList = this.data
.filter(({
hash
}) => !uploadedList.includes(hash))
.map(({
chunk,
hash,
index
}) => { const formData = new FormData();
formData.append("chunk", chunk);
formData.append("hash", hash);
formData.append("filename", this.container.file.name);
formData.append("fileHash", this.container.hash); return {
formData,
index
};
})
.map(async ({
formData,
index
}) => this.request({ url: "http://localhost:3000", data: formData, onProgress: this.createProgressHandler(this.data[index]), requestList: this.requestList
})); await Promise.all(requestList); // 之前上传的切片数量+本次上传的切片数量=所有切片数量
if (uploadedList.length + requestList.length == this.data.length) { await this.mergeRequest();
} console.log('可以发送合并请求了');
}, async mergeRequest() { await this.request({ url: 'http://localhost:3000/merge', headers: { "content-type": "application/json"
}, data: JSON.stringify({ size: SIZE, fileHash: this.container.hash, filename: this.container.file.name
})
}) this.$message.success('上传成功'); this.status = Status.wait;
}, // 用闭包保存每个 chunk 的进度数据
createProgressHandler(item) { return e => {
item.percentage = parseInt(String((e.loaded / e.total) * 100)); console.log(e.loaded, e.total, '----------');
}
}, // 根据 hash 验证文件是否曾经已经被上传过
// 没有才进行上传
async verifyUpload(filename, fileHash) { const {
data
} = await this.request({ url: 'http://localhost:3000/verify', headers: { "content-type": "application/json"
}, data: JSON.stringify({ // 字符串化
filename,
fileHash
})
}) return JSON.parse(data);
}, // es6的特性你和代码是如何结合的?少传这个参数
createFileChunk(file, size = SIZE) { const fileChunkList = []; let cur = 0; while (cur < file.size) {
fileChunkList.push({ file: file.slice(cur, cur + size)
})
cur += size;
} return fileChunkList;
}, handleFileChange(e) { const [file] = e.target.files; if (!file) return; this.resetData(); Object.assign(this.$data, this.$options.data()); this.container.file = file;
},
}, components: {
}
}</script><style>
#app { font-family: 'Avenir', Helvetica, Arial, sans-serif;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale; text-align: center; color: #2c3e50; margin-top: 60px;
}</style>
秒传
原理:计算整个文件的hash
,在执行上传操作前,向服务端发送请求,传递MD5
值,后端进行文件检索。若服务器中已存在该文件,便不进行后续的任何操作,上传也便直接结束。
大文件上传 + 断点续传的解决方案就完成了
总结
前端上传大文件时使用
Blob.prototype.slice
将文件切片,并发上传多个切片,最后发送一个合并的请求通知服务端合并切片后端进行合并到最终文件, 原生
XMLHttpRequest
的upload.onprogress
对切片上传进度的监听使用
spark-md5
根据文件内容算出文件hash
, 通过hash
可以判断服务端是否已经上传该文件,从而直接提示用户上传成功(秒传)前端在计算文件hash时,能否异步并实现进度响应
文件切片使用持久化或者内存存储导致溢出怎么办?
“继续下载”方案是否还有优化空间?
分片上传、接收、存储、合并,这些步骤抽象成一个文件上传协议是否更理想
上传状态由服务端动态获取,前端只做两个事:hash和切片。这个前提下,多切片并发上传、多文件并发上传,复杂度会提高很多,当然主要是后端复杂度。
源代码
file-breakpoint-continue