java实现文件分片上传并且断点续传

朴灿烈づ我的快乐病毒、 2023-10-13 10:54 17阅读 0赞

## 一、简单的分片上传 ##

针对第一个问题，如果文件过大，上传到一半断开了，若重新开始上传的话，会很消耗时间，并且你也并不知道距离上次断开时，已经上传到哪一部分了。因此我们应该先对大文件进行分片处理，防止上面提到的问题。

### 前端代码： ###

<!DOCTYPE html>
    <html>
    <head>
        <title>文件上传示例</title>
        <meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
    </head>
    <body>
    <form>
        <input type="file" id="fileInput" multiple>
        <button type="button" onclick="upload()" >上传</button>
    </form>
    <script>
        function upload() {
          
            var fileInput = document.getElementById('fileInput');
            var fileName = document.getElementById("fileInput").files[0].name;
            var files = fileInput.files;
            var chunkSize = 1024 * 10; // 每个块的大小为10KB
            var totalChunks = Math.ceil(files[0].size / chunkSize); // 文件总块数
            var currentChunk = 0; // 当前块数
    
            // 分片上传文件
            function uploadChunk() {
          
                var xhr = new XMLHttpRequest();
                var formData = new FormData();
    
                // 将当前块数和总块数添加到formData中
                formData.append('currentChunk', currentChunk);
                formData.append('totalChunks', totalChunks);
                formData.append('fileName',fileName);
    
                // 计算当前块在文件中的偏移量和长度
                var start = currentChunk * chunkSize;
                var end = Math.min(files[0].size, start + chunkSize);
                var chunk = files[0].slice(start, end);
    
                // 添加当前块到formData中
                formData.append('chunk', chunk);
    
                // 发送分片到后端
                xhr.open('POST', '/file/upload');
                xhr.send(formData);
    
                xhr.onload = function() {
          
                    // 更新当前块数
                    currentChunk++;
    
                    // 如果还有未上传的块，则继续上传
                    if (currentChunk < totalChunks) {
          
                        uploadChunk();
                    } else {
          
                        // 所有块都上传完毕，进行文件合并
                        mergeChunks(fileName);
                    }
                }
            }
    
            // 合并所有分片
            function mergeChunks() {
          
                var xhr = new XMLHttpRequest();
                xhr.open("POST", "/file/merge", true);
                xhr.setRequestHeader("Content-type", "application/x-www-form-urlencoded");
                xhr.onreadystatechange = function() {
          
                    if (xhr.readyState === 4) {
          
                        if (xhr.status === 200) {
          
                            console.log("文件上传完成：", xhr.responseText);
                        } else {
          
                            console.error(xhr.responseText);
                        }
                    }
                };
                xhr.send("fileName=" + fileName);
            }
    
            // 开始上传
            uploadChunk();
        }
    </script>
    </body>
    </html>

> ps：以上代码使用了html+js完成，请求是使用了xhr来发送请求。其中xhr.open的地址为自己本地的接口地址。由于平时测试并不需要真正上传大型文件，所以每个分片的大小定义为10KB，以此模拟大文件上传。

#### 后端代码： ####

@RestController
    @RequestMapping("/file")
    public class FileController {
        
        @Autowired
        private ResourceLoader resourceLoader;
    
        @Value("${my.config.savePath}")
        private String uploadPath;
    
        private Map<String, List<File>> chunksMap = new ConcurrentHashMap<>();
    
        @PostMapping("/upload")
        public void upload(@RequestParam int currentChunk, @RequestParam int totalChunks,
                           @RequestParam MultipartFile chunk,@RequestParam String fileName) throws IOException {
        
    
            // 将分片保存到临时文件夹中
            String chunkName = chunk.getOriginalFilename() + "." + currentChunk;
            File chunkFile = new File(uploadPath, chunkName);
            chunk.transferTo(chunkFile);
    
            // 记录分片上传状态
            List<File> chunkList = chunksMap.get(fileName);
            if (chunkList == null) {
        
                chunkList = new ArrayList<>(totalChunks);
                chunksMap.put(fileName, chunkList);
            }
            chunkList.add(chunkFile);
        }
    
        @PostMapping("/merge")
        public String merge(@RequestParam String fileName) throws IOException {
        
    
            // 获取所有分片，并按照分片的顺序将它们合并成一个文件
            List<File> chunkList = chunksMap.get(fileName);
            if (chunkList == null || chunkList.size() == 0) {
        
                throw new RuntimeException("分片不存在");
            }
    
            File outputFile = new File(uploadPath, fileName);
            try (FileChannel outChannel = new FileOutputStream(outputFile).getChannel()) {
        
                for (int i = 0; i < chunkList.size(); i++) {
        
                    try (FileChannel inChannel = new FileInputStream(chunkList.get(i)).getChannel()) {
        
                        inChannel.transferTo(0, inChannel.size(), outChannel);
                    }
                    chunkList.get(i).delete(); // 删除分片
                }
            }
    
            chunksMap.remove(fileName); // 删除记录
            // 获取文件的访问URL
            Resource resource = 
            			resourceLoader.getResource("file:" + uploadPath + fileName); //由于是本地文件，所以开头是"file"，如果是服务器，请改成自己服务器前缀
            return resource.getURI().toString();
        }
    }

> ps: 使用一个map记录上传了哪些分片，这里将分片存在了本地的文件夹，等到分片都上传完成后合并并删除分片。用ConcurrentHashMap代替HashMap是因为它在多线程下是安全的。  
> 以上只是一个简单的文件上传代码，但是只要在这上面另做修改就可以解决上面提到的问题。

## 二、解决问题 ##

### 1. 怎么避免大量的硬盘读写 ###

上面代码有一个弊端，就是将分片的内容存在了本地的文件夹里。而且在合并的时候判断上传是否完全也是从文件夹读取文件的。对磁盘的大量读写操作不仅速度慢，还会导致服务器崩溃，因此下面代码使用了redis来存储分片信息，避免对磁盘过多读写。（你也可以使用mysql或者其他中间件来存储信息，由于读写尽量不要在mysql，所以我使用了redis）。

### 2.目标文件过大，如果在上传过程中断开了怎么办 ###

使用redis来存储分片内容，当断开后，文件信息还是存储在redis中，用户再次上传时，检测redis是否有该分片的内容，如果有则跳过。

### 3. 前端页面上传的文件数据与原文件数据不一致该如何发现 ###

前端在调用上传接口时，先计算文件的校验和，然后将文件和校验和一并传给后端，后端对文件再计算一次校验和，两个校验和进行对比，如果相等，则说明数据一致，如果不一致则报错，让前端重新上传该片段。  
**js计算校验和代码：**

// 计算文件的 SHA-256 校验和
        function calculateHash(fileChunk) {
        
            return new Promise((resolve, reject) => {
        
                const blob = new Blob([fileChunk]);
                const reader = new FileReader();
                reader.readAsArrayBuffer(blob);
                reader.onload = () => {
        
                    const arrayBuffer = reader.result;
                    const crypto = window.crypto || window.msCrypto;
                    const digest = crypto.subtle.digest("SHA-256", arrayBuffer);
                    digest.then(hash => {
        
                        const hashArray = Array.from(new Uint8Array(hash));
                        const hashHex = hashArray.map(b => b.toString(16).padStart(2, '0')).join('');
                        resolve(hashHex);
                    });
                };
                reader.onerror = () => {
        
                    reject(new Error('Failed to calculate hash'));
                };
            });
        }

public static String calculateHash(byte[] fileChunk) throws Exception {
        
            MessageDigest md = MessageDigest.getInstance("SHA-256");
            md.update(fileChunk);
            byte[] hash = md.digest();
            ByteBuffer byteBuffer = ByteBuffer.wrap(hash);
            StringBuilder hexString = new StringBuilder();
            while (byteBuffer.hasRemaining()) {
        
                hexString.append(String.format("%02x", byteBuffer.get()));
            }
            return hexString.toString();
        }

**注意点:**

*  这里前端和后端计算校验和的算法一定要是一致的，不然得不到相同的结果。
 *  在前端中使用了crypto对文件进行计算,需要引入相关的js。 你可以使用script引入也可以直接下载js

[crypto的下载地址][crypto] 如果github打不开，可能需要使用npm下载了

### 4. 上传过程中如果断开了应该如何判断哪些分片没有上传 ###

对redis检测哪个分片的下标不存在，若不存在则存入list，最后将list返回给前端

boolean allChunksUploaded = true;
    	List<Integer> missingChunkIndexes = new ArrayList<>();
    	 for (int i = 0; i < hashMap.size(); i++) {
        
    	     if (!hashMap.containsKey(String.valueOf(i))) {
        
    	         allChunksUploaded = false;
    	         missingChunkIndexes.add(i);
    	     }
    	 }
    	 if (!allChunksUploaded) {
        
    	     return ResponseEntity.status(HttpStatus.BAD_REQUEST).body(missingChunkIndexes);
    	 }

## 三、完整代码 ##

### 1、引入依赖 ###

<dependency>
      	<groupId>io.lettuce</groupId>
        <artifactId>lettuce-core</artifactId>
        <version>6.1.4.RELEASE</version>
    </dependency>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-data-redis</artifactId>
    </dependency>

lettuce是一个Redis客户端，你也可以不引入，直接使用redisTemplat就行了

### 2、前端代码 ###

<!DOCTYPE html>
    <html lang="en">
    <head>
        <meta charset="UTF-8">
        <title>File Upload Demo</title>
    </head>
    <body>
    <input type="file" id="fileInput" multiple>
    <button type="button" onclick="uploadFile()" >上传</button>
    <div id="progressBar"></div>
    <script src="https://cdn.bootcss.com/crypto-js/3.1.9-1/crypto-js.min.js"></script>
    <script>
        var fileId = "";
        var fileName = null;
        var file;
        const chunkSize = 1024 * 10; // 每个分片的大小10KB
    
        async function uploadFile() {
          
            var fileInput = document.getElementById('fileInput');
            file = fileInput.files[0];
            fileName = document.getElementById("fileInput").files[0].name;
            // 分片上传文件
            const chunks = Math.ceil(file.size / chunkSize);
            for (let i = 0; i < chunks; i++) {
          
                try {
          
                    await uploadChunk(file, i);
                } catch (error) {
          
                    console.error('Failed to upload chunk', i, error);
                    // 如果上传失败，则尝试恢复上传
                    try {
          
                        await uploadChunk(file, i);
                    } catch (error) {
          
                        console.error('Failed to resume upload', i, error);
                        return;
                    }
                }
            }
            // 合并文件
            try {
          
                const fileUrl = await mergeFile();
                console.log('File URL:', fileUrl);
            } catch (error) {
          
                console.error('Failed to merge file', error);
            }
        }
        function uploadChunk(file, chunkIndex) {
          
            return new Promise((resolve, reject) => {
          
                let fileTemp = file.slice(chunkIndex * chunkSize, (chunkIndex + 1) * chunkSize);
                var myPromise = calculateHash(fileTemp);
                myPromise.then(result =>{
          
                    const formData = new FormData();
                    formData.append('chunk',fileTemp);
                    formData.append('chunkIndex', chunkIndex);
                    formData.append('chunkChecksum', result);
                    formData.append('chunkSize', chunkSize);
                    formData.append('fileId',fileId);
                    const xhr = new XMLHttpRequest();
                    xhr.open('POST', '/hospital/file2/upload', true);
    
                    xhr.onload = () => {
          
                        if (xhr.status === 200) {
          
                            resolve(xhr.response);
                            fileId = xhr.responseText
                        } else {
          
                            reject(xhr.statusText);
                        }
                    };
    
                    xhr.onerror = () => {
          
                        reject(xhr.statusText);
                    };
                    xhr.send(formData);
                })
            });
        }
    
        function mergeFile() {
          
            return new Promise((resolve, reject) => {
          
                const xhr = new XMLHttpRequest();
                const formData = new FormData();
                formData.append('fileId',fileId);
                formData.append('fileName',fileName);
                xhr.open('POST', '/hospital/file2/merge', true);
    
                xhr.onload = () => {
          
                    if (xhr.status === 200) {
          
                        resolve(xhr.response);
                    } else {
          
                        reject(xhr.statusText);
                        resume(xhr.response.replace(/\[|]/g,'').split(','));
                    }
                };
    
                xhr.onerror = () => {
          
                    reject(xhr.statusText);
    
                };
    
                xhr.send(formData);
            });
        }
        async function resume(list){
          
            for (let i = 0; i < list.length; i++) {
          
                try {
          
                    await uploadChunk(file, i);
                } catch (error) {
          
                    console.error('Failed to upload chunk', i, error);
                    // 如果上传失败，则尝试恢复上传
                    try {
          
                        await uploadChunk(file, i);
                    } catch (error) {
          
                        console.error('Failed to resume upload', i, error);
                        return;
                    }
                }
            }
            // 合并文件
            try {
          
                const fileUrl = await mergeFile();
                console.log('File URL:', fileUrl);
            } catch (error) {
          
                console.error('Failed to merge file', error);
            }
        }
    
        // 计算文件的 SHA-256 校验和
        function calculateHash(fileChunk) {
          
            return new Promise((resolve, reject) => {
          
                const blob = new Blob([fileChunk]);
                const reader = new FileReader();
                reader.readAsArrayBuffer(blob);
                reader.onload = () => {
          
                    const arrayBuffer = reader.result;
                    const crypto = window.crypto || window.msCrypto;
                    const digest = crypto.subtle.digest("SHA-256", arrayBuffer);
                    digest.then(hash => {
          
                        const hashArray = Array.from(new Uint8Array(hash));
                        const hashHex = hashArray.map(b => b.toString(16).padStart(2, '0')).join('');
                        resolve(hashHex);
                    });
                };
                reader.onerror = () => {
          
                    reject(new Error('Failed to calculate hash'));
                };
            });
        }
    
    </script>
    </body>
    </html>

### 3、后端接口代码 ###

@RestController
    @RequestMapping("/file2")
    public class File2Controller {
        
    
        private static final String FILE_UPLOAD_PREFIX = "file_upload:";
    
        @Autowired
        private ResourceLoader resourceLoader;
    
        @Value("${my.config.savePath}")
        private String uploadPath;
        @Autowired
        private ThreadLocal<RedisConnection> redisConnectionThreadLocal;
        
    //    @Autowired
    //    private RedisTemplate redisTemplate;
    
        @PostMapping("/upload")
        public ResponseEntity<?> uploadFile(@RequestParam("chunk") MultipartFile chunk,
                                            @RequestParam("chunkIndex") Integer chunkIndex,
                                            @RequestParam("chunkSize") Integer chunkSize,
                                            @RequestParam("chunkChecksum") String chunkChecksum,
                                            @RequestParam("fileId") String fileId) throws Exception {
        
            if (StringUtils.isBlank(fileId) || StringUtils.isEmpty(fileId)) {
        
                fileId = UUID.randomUUID().toString();
            }
            String key = FILE_UPLOAD_PREFIX + fileId;
            byte[] chunkBytes = chunk.getBytes();
            String actualChecksum = calculateHash(chunkBytes);
            if (!chunkChecksum.equals(actualChecksum)) {
        
                return ResponseEntity.status(HttpStatus.BAD_REQUEST).body("Chunk checksum does not match");
            }
    //        if(!redisTemplate.opsForHash().hasKey(key,String.valueOf(chunkIndex))) {
        
    //            redisTemplate.opsForHash().put(key, String.valueOf(chunkIndex), chunkBytes);
    //        }
            RedisConnection connection = redisConnectionThreadLocal.get();
    
            Boolean flag = connection.hExists(key.getBytes(), String.valueOf(chunkIndex).getBytes());
            if (flag==null || flag == false) {
        
                connection.hSet(key.getBytes(), String.valueOf(chunkIndex).getBytes(), chunkBytes);
            }
    
            return ResponseEntity.ok(fileId);
    
        }
    
        public static String calculateHash(byte[] fileChunk) throws Exception {
        
            MessageDigest md = MessageDigest.getInstance("SHA-256");
            md.update(fileChunk);
            byte[] hash = md.digest();
            ByteBuffer byteBuffer = ByteBuffer.wrap(hash);
            StringBuilder hexString = new StringBuilder();
            while (byteBuffer.hasRemaining()) {
        
                hexString.append(String.format("%02x", byteBuffer.get()));
            }
            return hexString.toString();
        }
    
        @PostMapping("/merge")
        public ResponseEntity<?> mergeFile(@RequestParam("fileId") String fileId, @RequestParam("fileName") String fileName) throws IOException {
        
            String key = FILE_UPLOAD_PREFIX + fileId;
            RedisConnection connection = redisConnectionThreadLocal.get();
            try {
        
                Map<byte[], byte[]> chunkMap = connection.hGetAll(key.getBytes());
    //            Map chunkMap = redisTemplate.opsForHash().entries(key);
                if (chunkMap.isEmpty()) {
        
                    return ResponseEntity.status(HttpStatus.NOT_FOUND).body("File not found");
                }
    
                Map<String,byte[]> hashMap = new HashMap<>();
                for(Map.Entry<byte[],byte[]> entry :chunkMap.entrySet()){
        
                    hashMap.put((new String(entry.getKey())),entry.getValue());
                }
                // 检测是否所有分片都上传了
                boolean allChunksUploaded = true;
                List<Integer> missingChunkIndexes = new ArrayList<>();
                for (int i = 0; i < hashMap.size(); i++) {
        
                    if (!hashMap.containsKey(String.valueOf(i))) {
        
                        allChunksUploaded = false;
                        missingChunkIndexes.add(i);
                    }
                }
                if (!allChunksUploaded) {
        
                    return ResponseEntity.status(HttpStatus.BAD_REQUEST).body(missingChunkIndexes);
                }
    
                File outputFile = new File(uploadPath, fileName);
                boolean flag = mergeChunks(hashMap, outputFile);
                Resource resource = resourceLoader.getResource("file:" + uploadPath + fileName);
    
    
                if (flag == true) {
        
                    connection.del(key.getBytes());
    //                redisTemplate.delete(key);
                    return ResponseEntity.ok().body(resource.getURI().toString());
                } else {
        
                    return ResponseEntity.status(555).build();
                }
            } catch (Exception e) {
        
                e.printStackTrace();
                return ResponseEntity.status(HttpStatus.INTERNAL_SERVER_ERROR).body(e.getMessage());
            }
        }
    
        private boolean mergeChunks(Map<String, byte[]> chunkMap, File destFile) {
        
            try (FileOutputStream outputStream = new FileOutputStream(destFile)) {
        
                // 将分片按照顺序合并
                for (int i = 0; i < chunkMap.size(); i++) {
        
                    byte[] chunkBytes = chunkMap.get(String.valueOf(i));
                    outputStream.write(chunkBytes);
                }
                return true;
            } catch (IOException e) {
        
                e.printStackTrace();
                return false;
            }
        }
    }

### 4、redis配置 ###

@Configuration
    public class RedisConfig {
        
        @Value("${spring.redis.host}")
        private String host;
    
        @Value("${spring.redis.port}")
        private int port;
    
        @Value("${spring.redis.password}")
        private String password;
    
        @Bean
        public RedisConnectionFactory redisConnectionFactory() {
        
            RedisStandaloneConfiguration config = new RedisStandaloneConfiguration();
            config.setHostName(host);
            config.setPort(port);
            config.setPassword(RedisPassword.of(password));
            return new LettuceConnectionFactory(config);
        }
        @Bean
        public ThreadLocal<RedisConnection> redisConnectionThreadLocal(RedisConnectionFactory redisConnectionFactory) {
        
            return ThreadLocal.withInitial(() -> redisConnectionFactory.getConnection());
        }
    }

**使用 redisConnectionThreadLocal 是为了避免多次建立连接，很耗时间**

## 总结 ##

以上就是该功能的完整代码。使用代码记得修改uploadPath，避免代码找不到目录路径。在代码最后，可以使用mysql对整个文件计算校验和，将校验和结果和文件名、文件大小、文件类型存入数据库中，在下次大文件上传前先判断是否存在。若存在就不要上传避免占用空间。

[crypto]: https://github.com/brix/crypto-js/releases/tag/4.1.0