更新版本至 0.0.37，优化文件上传功能，支持大文件分块上传，改用 SparkMD5 计算 Blob 哈希

query/query-resources/index.ts

@@ -71,23 +71,83 @@ export class QueryResources {
     // Blob 类型时 hashContent 返回 Promise
     const hash = hashResult instanceof Promise ? await hashResult : hashResult;
     url.searchParams.set('hash', hash);
+
+    // 判断是否需要分块上传（文件大于20MB）
+    const isBlob = content instanceof Blob;
+    const fileSize = isBlob ? content.size : new Blob([content]).size;
+    const CHUNK_THRESHOLD = 20 * 1024 * 1024; // 20MB
+
+    if (fileSize > CHUNK_THRESHOLD && isBlob) {
+      // 使用分块上传
+      return this.uploadChunkedFile(filepath, content, hash, opts);
+    }
+
     const formData = new FormData();
-    if (content instanceof Blob) {
+    if (isBlob) {
       formData.append('file', content);
     } else {
       formData.append('file', new Blob([content], { type }));
     }
     return adapter({
       url: url.toString(),
-      headers: { ...this.header(opts?.headers, false) },
-      params: {
-        hash: hash,
-      },
       isPostFile: true,
       method: 'POST',
       body: formData,
+      timeout: 5 * 60 * 1000, // 5分钟超时
+      ...opts,
+      headers: { ...opts?.headers, ...this.header(opts?.headers, false) },
+      params: {
+        hash: hash,
+        ...opts?.params,
+      },
     });
   }
+  async uploadChunkedFile(filepath: string, file: Blob, hash: string, opts?: DataOpts): Promise<Result<any>> {
+    const pathname = `${this.prefix}${filepath}`;
+    const filename = path.basename(pathname);
+    const url = new URL(pathname, window.location.origin);
+    url.searchParams.set('hash', hash);
+    url.searchParams.set('chunked', '1');
+    console.log(`url,`, url, hash);
+    // 预留 eventSource 支持（暂不处理）
+    // const createEventSource = opts?.createEventSource;
+
+    const chunkSize = 5 * 1024 * 1024; // 5MB
+    const totalChunks = Math.ceil(file.size / chunkSize);
+
+    for (let currentChunk = 0; currentChunk < totalChunks; currentChunk++) {
+      const start = currentChunk * chunkSize;
+      const end = Math.min(start + chunkSize, file.size);
+      const chunk = file.slice(start, end);
+
+      const formData = new FormData();
+      formData.append('file', chunk, filename);
+      formData.append('chunkIndex', currentChunk.toString());
+      formData.append('totalChunks', totalChunks.toString());
+      console.log(`Uploading chunk ${currentChunk + 1}/${totalChunks}`, url.toString());
+      try {
+        const res = await adapter({
+          url: url.toString(),
+          isPostFile: true,
+          method: 'POST',
+          body: formData,
+          timeout: 5 * 60 * 1000, // 5分钟超时
+          ...opts,
+          headers: { ...opts?.headers, ...this.header(opts?.headers, false) },
+          params: {
+            hash: hash,
+            ...opts?.params,
+          },
+        });
+        console.log(`Chunk ${currentChunk + 1}/${totalChunks} uploaded`, res);
+      } catch (error) {
+        console.error(`Error uploading chunk ${currentChunk + 1}/${totalChunks}`, error);
+        throw error;
+      }
+    }
+
+    return { code: 200, message: '上传成功' };
+  }
   async createFolder(folderpath: string, opts?: DataOpts): Promise<Result<any>> {
     const filepath = folderpath.endsWith('/') ? `${folderpath}keep.txt` : `${folderpath}/keep.txt`;
     return this.uploadFile(filepath, '文件夹占位，其他文件不存在，文件夹不存在，如果有其他文件夹，删除当前文件夹占位文件即可', opts);

query/query-resources/utils.ts

@@ -1,4 +1,5 @@
 import MD5 from 'crypto-js/md5';
+import SparkMD5 from 'spark-md5';
 
 export const hashContent = (str: string | Blob | Buffer): Promise<string> | string => {
   if (typeof str === 'string') {
@@ -12,57 +13,20 @@ export const hashContent = (str: string | Blob | Buffer): Promise<string> | stri
   return '';
 };
 
+// 直接计算整个 Blob 的 MD5
 export const hashBlob = (blob: Blob): Promise<string> => {
-  return new Promise((resolve, reject) => {
-    const reader = new FileReader();
-    reader.onload = async () => {
-      try {
-        const content = reader.result;
-        if (typeof content === 'string') {
-          resolve(MD5(content).toString());
-        } else if (content) {
-          const contentString = new TextDecoder().decode(content);
-          resolve(MD5(contentString).toString());
-        } else {
-          reject(new Error('Empty content'));
-        }
-      } catch (error) {
-        console.error('hashBlob error', error);
-        reject(error);
-      }
-    };
-    reader.onerror = (error) => reject(error);
-    reader.readAsArrayBuffer(blob);
-  });
-};
-export const hashFile = (file: File): Promise<string> => {
-  return new Promise((resolve, reject) => {
-    const reader = new FileReader();
-
-    reader.onload = async (event) => {
-      try {
-        const content = event.target?.result;
-        if (content instanceof ArrayBuffer) {
-          const contentString = new TextDecoder().decode(content);
-          const hashHex = MD5(contentString).toString();
-          resolve(hashHex);
-        } else if (typeof content === 'string') {
-          const hashHex = MD5(content).toString();
-          resolve(hashHex);
-        } else {
-          throw new Error('Invalid content type');
-        }
-      } catch (error) {
-        console.error('hashFile error', error);
-        reject(error);
-      }
-    };
-
-    reader.onerror = (error) => {
+  return new Promise(async (resolve, reject) => {
+    try {
+      const spark = new SparkMD5.ArrayBuffer();
+      spark.append(await blob.arrayBuffer());
+      resolve(spark.end());
+    } catch (error) {
+      console.error('hashBlob error', error);
       reject(error);
-    };
-
-    // 读取文件为 ArrayBuffer
-    reader.readAsArrayBuffer(file);
+    }
   });
 };
+
+export const hashFile = (file: File): Promise<string> => {
+  return hashBlob(file);
+};