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JS 实现请求调度器

作者：孟陬　　发布时间：2024-04-22 22:37:24　

标签：js,请求,调度器

const ids = [1001, 1002, 1003, 1004, 1005];
const urlPrefix = 'http://opensearch.example.com/api/apps';

// fetch 函数发送 HTTP 请求，返回 Promise
const appPromises = ids.map(id => `${urlPrefix}/${id}`).map(fetch);

Promise.all(appPromises)
// 通过 reduce 做累加
.then(apps => apps.reduce((initial, current) => initial + current.pv, 0))
.catch((error) => console.log(error));

上面的代码在应用个数不多的情况下，可以运行正常。当应用个数达到成千上万时，对支持并发数不是很好的系统，你的「压测」会把第三放服务器搞挂，暂时无法响应请求：

<html>
<head><title>502 Bad Gateway</title></head>
<body bgcolor="white">
<center><h1>502 Bad Gateway</h1></center>
<hr><center>nginx/1.10.1</center>
</body>
</html>

如何解决呢？

一个很自然的想法是，既然不支持这么多的并发请求，那就分割成几大块，每块为一个 chunk，chunk 内部的请求依然并发，但块的大小（chunkSize）限制在系统支持的最大并发数以内。前一个 chunk 结束后一个 chunk 才能继续执行，也就是说 chunk 内部的请求是并发的，但 chunk 之间是串行的。思路其实很简单，写起来却有一定难度。总结起来三个操作：分块、串行、聚合

难点在如何串行执行 Promise，Promise 仅提供了并行（Promise.all）功能，并没有提供串行功能。我们从简单的三个请求开始，看如何实现，启发式解决问题（heuristic）。

// task1, task2, task3 是三个返回 Promise 的工厂函数，模拟我们的异步请求
const task1 = () => new Promise((resolve) => {
setTimeout(() => {
resolve(1);
console.log('task1 executed');
}, 1000);
});

const task2 = () => new Promise((resolve) => {
setTimeout(() => {
resolve(2);
console.log('task2 executed');
}, 1000);
});

const task3 = () => new Promise((resolve) => {
setTimeout(() => {
resolve(3);
console.log('task3 executed');
}, 1000);
});

// 聚合结果
let result = 0;

const resultPromise = [task1, task2, task3].reduce((current, next) =>
current.then((number) => {
console.log('resolved with number', number); // task2, task3 的 Promise 将在这里被 resolve
result += number;

return next();
}),

Promise.resolve(0)) // 聚合初始值

.then(function(last) {
console.log('The last promise resolved with number', last); // task3 的 Promise 在这里被 resolve

result += last;

console.log('all executed with result', result);

return Promise.resolve(result);
});

运行结果如图 1：

代码解析：我们想要的效果，直观展示其实是 fn1().then(() => fn2()).then(() => fn3())。上面代码能让一组 Promise 按顺序执行的关键之处就在 reduce 这个“引擎”在一步步推动 Promise 工厂函数的执行。

难点解决了，我们看看最终代码：

/**
* 模拟 HTTP 请求
* @param {String} url
* @return {Promise}
*/
function fetch(url) {
console.log(`Fetching ${url}`);
return new Promise((resolve) => {
setTimeout(() => resolve({ pv: Number(url.match(/\d+$/)) }), 2000);
});
}

const urlPrefix = 'http://opensearch.example.com/api/apps';

const aggregator = {
/**
* 入口方法，开启定时任务
*
* @return {Promise}
*/
start() {
return this.fetchAppIds()
.then(ids => this.fetchAppsSerially(ids, 2))
.then(apps => this.sumPv(apps))
.catch(error => console.error(error));
},

/**
* 获取所有应用的 ID
*
* @private
*
* @return {Promise}
*/
fetchAppIds() {
return Promise.resolve([1001, 1002, 1003, 1004, 1005]);
},

promiseFactory(ids) {
return () => Promise.all(ids.map(id => `${urlPrefix}/${id}`).map(fetch));
},

/**
* 获取所有应用的详情
*
* 一次并发请求 `concurrency` 个应用，称为一个 chunk
* 前一个 `chunk` 并发完成后一个才继续，直至所有应用获取完毕
*
* @private
*
* @param {[Number]} ids
* @param {Number} concurrency 一次并发的请求数量
* @return {[Object]} 所有应用的信息
*/
fetchAppsSerially(ids, concurrency = 100) {
// 分块
let chunkOfIds = ids.splice(0, concurrency);
const tasks = [];

while (chunkOfIds.length !== 0) {
tasks.push(this.promiseFactory(chunkOfIds));
chunkOfIds = ids.splice(0, concurrency);
}

// 按块顺序执行
const result = [];
return tasks.reduce((current, next) => current.then((chunkOfApps) => {
console.info('Chunk of', chunkOfApps.length, 'concurrency requests has finished with result:', chunkOfApps, '\n\n');
result.push(...chunkOfApps); // 拍扁数组
return next();
}), Promise.resolve([]))
.then((lastchunkOfApps) => {
console.info('Chunk of', lastchunkOfApps.length, 'concurrency requests has finished with result:', lastchunkOfApps, '\n\n');

result.push(...lastchunkOfApps); // 再次拍扁它
console.info('All chunks has been executed with result', result);
return result;
});
},

/**
* 聚合所有应用的 PV
*
* @private
*
* @param {[]} apps
* @return {[type]} [description]
*/
sumPv(apps) {
const initial = { pv: 0 };

return apps.reduce((accumulator, app) => ({ pv: accumulator.pv + app.pv }), initial);
}
};

// 开始运行
aggregator.start().then(console.log);

运行结果如图 2：

抽象和复用

目的达到了，因具备通用性，下面开始抽象成一个模式以便复用。

串行

先模拟一个 http get 请求。

/**
* mocked http get.
* @param {string} url
* @returns {{ url: string; delay: number; }}
*/
function httpGet(url) {
const delay = Math.random() * 1000;

console.info('GET', url);

return new Promise((resolve) => {
setTimeout(() => {
resolve({
url,
delay,
at: Date.now()
})
}, delay);
})
}

串行执行一批请求。

const ids = [1, 2, 3, 4, 5, 6, 7];

// 批量请求函数，注意是 delay 执行的『函数』对了，否则会立即将请求发送出去，达不到串行的目的
const httpGetters = ids.map(id =>
() => httpGet(`https://jsonplaceholder.typicode.com/posts/${id}`)
);

// 串行执行之
const tasks = await httpGetters.reduce((acc, cur) => {
return acc.then(cur);

// 简写，等价于
// return acc.then(() => cur());
}, Promise.resolve());

tasks.then(() => {
console.log('done');
});

注意观察控制台输出，应该串行输出以下内容：

GET https://jsonplaceholder.typicode.com/posts/1
GET https://jsonplaceholder.typicode.com/posts/2
GET https://jsonplaceholder.typicode.com/posts/3
GET https://jsonplaceholder.typicode.com/posts/4
GET https://jsonplaceholder.typicode.com/posts/5
GET https://jsonplaceholder.typicode.com/posts/6
GET https://jsonplaceholder.typicode.com/posts/7

分段串行，段中并行

重点来了。本文的请求调度器实现

/**
* Schedule promises.
* @param {Array<(...arg: any[]) => Promise<any>>} factories
* @param {number} concurrency
*/
function schedulePromises(factories, concurrency) {
/**
* chunk
* @param {any[]} arr
* @param {number} size
* @returns {Array<any[]>}
*/
const chunk = (arr, size = 1) => {
return arr.reduce((acc, cur, idx) => {
const modulo = idx ％ size;

if (modulo === 0) {
acc[acc.length] = [cur];
} else {
acc[acc.length - 1].push(cur);
}

return acc;
}, [])
};

const chunks = chunk(factories, concurrency);

let resps = [];

return chunks.reduce(
(acc, cur) => {
return acc
.then(() => {
console.log('---');
return Promise.all(cur.map(f => f()));
})
.then((intermediateResponses) => {
resps.push(...intermediateResponses);

return resps;
})
},

Promise.resolve()
);
}

测试下，执行调度器：

// 分段串行，段中并行
schedulePromises(httpGetters, 3).then((resps) => {
console.log('resps:', resps);
});

控制台输出：

---
GET https://jsonplaceholder.typicode.com/posts/1
GET https://jsonplaceholder.typicode.com/posts/2
GET https://jsonplaceholder.typicode.com/posts/3
---
GET https://jsonplaceholder.typicode.com/posts/4
GET https://jsonplaceholder.typicode.com/posts/5
GET https://jsonplaceholder.typicode.com/posts/6
---
GET https://jsonplaceholder.typicode.com/posts/7

resps: [
{
"url": "https://jsonplaceholder.typicode.com/posts/1",
"delay": 733.010980640727,
"at": 1615131322163
},
{
"url": "https://jsonplaceholder.typicode.com/posts/2",
"delay": 594.5056229848931,
"at": 1615131322024
},
{
"url": "https://jsonplaceholder.typicode.com/posts/3",
"delay": 738.8230109146299,
"at": 1615131322168
},
{
"url": "https://jsonplaceholder.typicode.com/posts/4",
"delay": 525.4604386109747,
"at": 1615131322698
},
{
"url": "https://jsonplaceholder.typicode.com/posts/5",
"delay": 29.086379722201183,
"at": 1615131322201
},
{
"url": "https://jsonplaceholder.typicode.com/posts/6",
"delay": 592.2345027398272,
"at": 1615131322765
},
{
"url": "https://jsonplaceholder.typicode.com/posts/7",
"delay": 513.0684467560949,
"at": 1615131323284
}
]

总结

如果并发请求的数量太大，可以考虑分块串行，块中请求并发。
问题看似复杂，不放先简化之，然后一步步推导出关键点，最后抽象，就能找到解决方案。
本文的精髓在于使用 reduce 作为串行推动的引擎，故掌握其对我们日常开发遇到的迷局破解可提供新思路，reduce 精通见上篇你终于用 Reduce 了 🎉。

来源：https://juejin.cn/post/6936859831060037668

投稿

JS 实现请求调度器

目录

抽象和复用

串行

分段串行，段中并行

总结

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