再也不用等！Spring Boot 3.3 搞定大文件分塊上傳 + 文件“秒傳”，速度飛起！
作者：編程疏影
通過本文，我們構建了一個完整的支持大文件上傳系統(tǒng)，具備高效、穩(wěn)定、可擴展的特性，適用于企業(yè)級系統(tǒng)中的文檔上傳、視頻管理、素材收集等場景。
- 在現(xiàn)代化的文件上傳場景中，用戶往往會面臨上傳大文件、網(wǎng)絡中斷、重復上傳浪費帶寬等挑戰(zhàn)。為了解決這些問題，本文基于 Spring Boot 3.3 搭建一個高性能、可擴展的文件上傳系統(tǒng)，支持：結合前后端完整示例，本文將帶你從零構建一套實用的上傳方案，助力各類業(yè)務系統(tǒng)高效接入大文件處理能力。
文件秒傳（通過 MD5 實現(xiàn)）
分塊上傳（支持大文件斷點續(xù)傳）
分塊合并（支持服務端合并）
構建 Spring Boot 3.3 項目
pom.xml 關鍵依賴配置如下：
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>cn.hutool</groupId>
<artifactId>hutool-all</artifactId>
<version>5.8.25</version>
</dependency>
</dependencies>定義文件信息實體類 FileInfo
package com.icoderoad.model;
import cn.hutool.core.util.IdUtil;
public class FileInfo {
private String id = IdUtil.fastUUID();
private String fileName;
private String fileMd5;
private Long fileSize;
private String filePath;
public FileInfo(String fileName, String fileMd5, Long fileSize, String filePath) {
this.fileName = fileName;
this.fileMd5 = fileMd5;
this.fileSize = fileSize;
this.filePath = filePath;
}
}核心服務類 FileService
package com.icoderoad.service;
import cn.hutool.crypto.digest.DigestUtil;
import com.icoderoad.model.FileInfo;
import org.springframework.stereotype.Service;
import org.springframework.web.multipart.MultipartFile;
import java.io.*;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
@Service
public class FileService {
private final Map<String, FileInfo> fileStore = new ConcurrentHashMap<>();
private final String tempDir = System.getProperty("java.io.tmpdir") + File.separator + "chunks";
public FileInfo findByMd5(String md5) {
return fileStore.get(md5);
}
public FileInfo saveFile(String fileName, String fileMd5, Long fileSize, String filePath) {
FileInfo info = new FileInfo(fileName, fileMd5, fileSize, filePath);
fileStore.put(fileMd5, info);
return info;
}
public String calculateMD5(MultipartFile file) throws IOException {
return DigestUtil.md5Hex(file.getInputStream());
}
public void saveChunk(MultipartFile chunk, String identifier, int index) throws IOException {
File dir = new File(tempDir + File.separator + identifier);
if (!dir.exists()) dir.mkdirs();
chunk.transferTo(new File(dir, index + ".part"));
}
public File mergeChunks(String identifier, int totalChunks, String fileName) throws IOException {
File dir = new File(tempDir + File.separator + identifier);
File merged = new File(System.getProperty("java.io.tmpdir"), fileName);
try (FileOutputStream out = new FileOutputStream(merged)) {
for (int i = 0; i < totalChunks; i++) {
File chunk = new File(dir, i + ".part");
try (FileInputStream in = new FileInputStream(chunk)) {
byte[] buffer = new byte[1024 * 1024];
int len;
while ((len = in.read(buffer)) > 0) {
out.write(buffer, 0, len);
}
}
}
}
return merged;
}
}通用返回結構 Result
package com.icoderoad.common;
public class Result {
private boolean success;
private Object data;
private String message;
public Result(boolean success, Object data, String message) {
this.success = success;
this.data = data;
this.message = message;
}
public static Result success(Object data) {
return new Result(true, data, "成功");
}
public static Result error(String message) {
return new Result(false, null, message);
}
}控制器 FileController
package com.icoderoad.controller;
import com.icoderoad.common.Result;
import com.icoderoad.model.FileInfo;
import com.icoderoad.service.FileService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.*;
import org.springframework.web.multipart.MultipartFile;
import java.io.File;
@RestController
@RequestMapping("/api/file")
public class FileController {
@Autowired
private FileService fileService;
@PostMapping("/check")
public Result check(@RequestParam("md5") String md5) {
FileInfo exist = fileService.findByMd5(md5);
return Result.success(exist);
}
@PostMapping("/upload")
public Result upload(@RequestParam("file") MultipartFile file) {
try {
String md5 = fileService.calculateMD5(file);
FileInfo exist = fileService.findByMd5(md5);
if (exist != null) return Result.success(exist);
String path = System.getProperty("java.io.tmpdir") + File.separator + file.getOriginalFilename();
file.transferTo(new File(path));
FileInfo saved = fileService.saveFile(file.getOriginalFilename(), md5, file.getSize(), path);
return Result.success(saved);
} catch (Exception e) {
return Result.error("上傳失敗: " + e.getMessage());
}
}
@PostMapping("/chunk")
public Result uploadChunk(@RequestParam("chunk") MultipartFile chunk,
@RequestParam("identifier") String identifier,
@RequestParam("index") int index) {
try {
fileService.saveChunk(chunk, identifier, index);
return Result.success("分塊上傳成功");
} catch (Exception e) {
return Result.error("上傳分塊失敗: " + e.getMessage());
}
}
@PostMapping("/merge")
public Result mergeChunks(@RequestParam("identifier") String identifier,
@RequestParam("total") int total,
@RequestParam("fileName") String fileName) {
try {
File merged = fileService.mergeChunks(identifier, total, fileName);
String md5 = DigestUtil.md5Hex(merged);
FileInfo info = fileService.saveFile(fileName, md5, merged.length(), merged.getAbsolutePath());
return Result.success(info);
} catch (Exception e) {
return Result.error("合并失敗: " + e.getMessage());
}
}
}前端: 基于 Bootstrap + SparkMD5 + Axios 實現(xiàn)分塊上傳與秒傳功能
<!DOCTYPE html>
<html lang="zh-CN">
<head>
<meta charset="UTF-8">
<title>大文件上傳 Demo</title>
<link rel="stylesheet">
<script src="https://cdn.jsdelivr.net/npm/axios/dist/axios.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/spark-md5/spark-md5.min.js"></script>
</head>
<body class="container py-5">
<div class="card shadow-lg">
<div class="card-header bg-primary text-white">
<h4>大文件分塊上傳 + 秒傳 Demo</h4>
</div>
<div class="card-body">
<div class="mb-3">
<input type="file" class="form-control" id="fileInput">
</div>
<button class="btn btn-success" onclick="upload()">開始上傳</button>
<div class="mt-3">
<div class="progress">
<div id="progressBar" class="progress-bar" role="progressbar" style="width: 0%">0%</div>
</div>
</div>
</div>
</div>
<script>
constCHUNK_SIZE=2*1024*1024;// 每塊 2MB
let file =null;
document.getElementById('fileInput').addEventListener('change',function(e){
file = e.target.files[0];
});
asyncfunctionupload(){
if(!file)returnalert('請選擇文件');
const fileMD5 =awaitcalculateMD5(file);
const chunkCount =Math.ceil(file.size/CHUNK_SIZE);
const checkRes =await axios.get('/api/file/check',{
params:{md5: fileMD5,fileName: file.name}
});
if(checkRes.data.code===200&& checkRes.data.data.exists){
alert('服務器已存在該文件，已秒傳成功！');
updateProgressBar(100);
return;
}
for(let i =0; i < chunkCount; i++){
const start = i *CHUNK_SIZE;
const end =Math.min(file.size, start +CHUNK_SIZE);
const chunk = file.slice(start, end);
const formData =newFormData();
formData.append('file', chunk);
formData.append('md5', fileMD5);
formData.append('chunk', i);
formData.append('total', chunkCount);
formData.append('fileName', file.name);
await axios.post('/api/file/chunk', formData);
updateProgressBar(Math.round(((i +1)/ chunkCount)*100));
}
await axios.post('/api/file/merge',null,{
params:{md5: fileMD5,fileName: file.name}
});
alert('上傳并合并完成！');
}
asyncfunctioncalculateMD5(file){
returnnewPromise((resolve, reject)=>{
const chunkSize =CHUNK_SIZE;
const chunks =Math.ceil(file.size/ chunkSize);
let currentChunk =0;
const spark =newSparkMD5.ArrayBuffer();
const fileReader =newFileReader();
fileReader.onload=e=>{
spark.append(e.target.result);
currentChunk++;
if(currentChunk < chunks){
loadNext();
}else{
resolve(spark.end());
}
};
fileReader.onerror=()=>reject('讀取失敗');
functionloadNext(){
const start = currentChunk * chunkSize;
const end =Math.min(start + chunkSize, file.size);
fileReader.readAsArrayBuffer(file.slice(start, end));
}
loadNext();
});
}
functionupdateProgressBar(percent){
const bar =document.getElementById('progressBar');
bar.style.width= percent +'%';
bar.innerText= percent +'%';
}
</script>
</body>
</html>結語
通過本文，我們構建了一個完整的支持大文件上傳系統(tǒng)，具備高效、穩(wěn)定、可擴展的特性，適用于企業(yè)級系統(tǒng)中的文檔上傳、視頻管理、素材收集等場景。其核心優(yōu)勢在于：
- ?? 秒傳機制：避免重復上傳，節(jié)省資源
- ?? 分塊傳輸：支持大文件，提升上傳穩(wěn)定性
- ?? 擴展性強：可進一步結合 Redis、MQ 等組件提升并發(fā)處理能力
責任編輯：武曉燕
來源：
路條編程
