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【前端并发请求控制：必要性与实现策略】

news 来源：原创 2025/6/5 15:25:03

前端并发请求控制：必要性与实现策略

一、引言

在现代 Web 开发中，处理大量异步请求是一个常见场景。虽然浏览器和服务器都有其并发限制机制，但前端实现并发控制仍然具有其独特的价值和必要性。本文将深入探讨这个话题。

二、现有的并发限制机制

2.1 浏览器限制

浏览器对并发请求有默认的限制：

// 主流浏览器的并发限制（同一域名）
const browserLimits = {Chrome: 6,Firefox: '6-8',Safari: 6,Edge: 6
};// 但这个限制是按域名的
const requests = ['https://api1.example.com/data',  // 域名1：可以6个并发'https://api2.example.com/data',  // 域名2：可以6个并发'https://api3.example.com/data'   // 域名3：可以6个并发
];

2.2 服务器限制

服务器通常通过限流来控制并发：

// 典型的服务器限流响应
{status: 429,message: 'Too Many Requests',retry_after: 30
}

三、为什么需要前端并发控制

3.1 资源优化

// 不控制并发的问题
urls.forEach(async url => {try {await fetch(url);} catch (e) {if (e.status === 429) {// 1. 请求已经发出，消耗了资源// 2. 服务器已经处理了请求// 3. 网络带宽已经使用retry(url);}}
});// 控制并发的优势
await fetchWithLimit(urls, 5);
// 1. 预防性控制，避免资源浪费
// 2. 减少服务器压力
// 3. 优化网络资源使用

3.2 更好的用户体验

// 带进度反馈的并发控制
async function fetchWithProgress(urls, limit = 5) {let completed = 0;const total = urls.length;return fetchWithLimit(urls, limit, {onProgress: () => {completed++;updateUI(`进度：${completed}/${total}`);},onError: (error, url) => {showError(`请求失败：${url}`);}});
}

四、实现并发控制

4.1 基础实现

async function fetchWithLimit(urls, limit = 5) {const results = [];const executing = new Set();for (const url of urls) {const promise = fetch(url).then(response => {executing.delete(promise);return response;});executing.add(promise);results.push(promise);if (executing.size >= limit) {await Promise.race(executing);}}return Promise.all(results);
}

4.2 增强版实现

class RequestController {constructor(options = {}) {this.limit = options.limit || 5;this.timeout = options.timeout || 5000;this.retries = options.retries || 3;this.queue = [];this.executing = new Set();}async addRequest(url, options = {}) {const request = {url,priority: options.priority || 0,retryCount: 0};this.queue.push(request);this.processQueue();}async processQueue() {if (this.executing.size >= this.limit) {return;}// 按优先级排序this.queue.sort((a, b) => b.priority - a.priority);while (this.queue.length && this.executing.size < this.limit) {const request = this.queue.shift();this.executeRequest(request);}}async executeRequest(request) {const promise = this.fetchWithTimeout(request).catch(error => this.handleError(request, error));this.executing.add(promise);promise.finally(() => {this.executing.delete(promise);this.processQueue();});return promise;}async fetchWithTimeout(request) {const controller = new AbortController();const timeoutId = setTimeout(() => controller.abort(), this.timeout);try {const response = await fetch(request.url, {signal: controller.signal});clearTimeout(timeoutId);return response;} catch (error) {clearTimeout(timeoutId);throw error;}}async handleError(request, error) {if (request.retryCount < this.retries) {request.retryCount++;this.queue.unshift(request);await new Promise(resolve => setTimeout(resolve, Math.pow(2, request.retryCount) * 1000));} else {throw error;}}
}

五、实际应用场景

5.1 文件上传

class FileUploader {constructor(options = {}) {this.controller = new RequestController(options);this.chunkSize = options.chunkSize || 1024 * 1024;}async uploadFile(file) {const chunks = this.splitFile(file);const uploads = chunks.map((chunk, index) => ({url: '/upload',body: chunk,priority: chunks.length - index // 优先上传文件的前面部分}));return this.controller.addRequests(uploads);}
}

5.2 数据批量处理

class DataProcessor {constructor(options = {}) {this.controller = new RequestController(options);}async processDataset(items) {const batches = this.createBatches(items, 100);return this.controller.addRequests(batches.map(batch => ({url: '/process',body: batch,priority: batch.some(item => item.isUrgent) ? 1 : 0})));}
}

六、最佳实践建议

动态调整并发数：

function getOptimalConcurrency() {const connection = navigator.connection;if (!connection) return 5;switch (connection.effectiveType) {case '4g': return 6;case '3g': return 4;case '2g': return 2;default: return 3;}
}

实现优先级控制：

const priorities = {HIGH: 3,MEDIUM: 2,LOW: 1
};requests.sort((a, b) => b.priority - a.priority);

错误处理和重试策略：

async function retryWithBackoff(fn, maxRetries = 3) {for (let i = 0; i < maxRetries; i++) {try {return await fn();} catch (error) {if (i === maxRetries - 1) throw error;await delay(Math.pow(2, i) * 1000);}}
}