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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。
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。
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.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: 102400
type: ""
[[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()
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。
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:
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。
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
}
- 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 4.5.13
vue 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-ui
import 'element-ui/lib/theme-chalk/index.css'
Vue.use(ElementUI);
Vue.config.productionTip = false
new 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
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?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
- 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
<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>
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
- 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。