Let's say you need to fetch and process a lot of data from a remote server. It might be any REST API endpoint, but for demonstration purposes I'll take JSONPlaceholder. I'll use Node.js, but the same principles are applicable for a browser.

JSONPlaceholder has photos endpoint which returns a simple json data by photo id:

{
  "albumId": 1,
  "id": 1,
  "title": "accusamus beatae ad facilis cum similique qui sunt",
  "url": "https://via.placeholder.com/600/92c952",
  "thumbnailUrl": "https://via.placeholder.com/150/92c952"
}

I'll use helper function getIdList to generate array with required amount of IDs.

const getIdList = n => [...new Array(n)].map((item, i) => i + 1);
getIdList(5); // [1,2,3,4,5]

axios will help to fetch the data:

function fetchPhoto(id) {
  const url = `https://jsonplaceholder.typicode.com/photos/${id}`;
  return axios.get(url)
    .then(res => res.data)
}

All at once

My first intention to solve the problem of handling thousands of requests was to start all requests in parallel and process the result when all requests are completed.

function all(items, fn) {
  const promises = items.map(item => fn(item));
  return Promise.all(promises);
}

It works great for small amount of items. Making 10, 50, 100 requests at the same time seems like a good idea. Fetching 10 items in parallel on a good connection takes less than a second.
But what about 2000 items?
Chances are that you'll hit the problem
(node:6740) UnhandledPromiseRejectionWarning: Error: read ECONNRESET
or
(node:3808) UnhandledPromiseRejectionWarning: Error: connect ETIMEDOUT
or
(node:7052) UnhandledPromiseRejectionWarning: Error: Client network socket disconnected before secure TLS connection was established

The point is that Node can't handle a lot of connections at the same time and we need to rethink the solution.

One by one

Other option is to solve the problem step by step. Let's start next request only after previous has been resolved.

function series(items, fn) {
  let result = [];
  return items.reduce((acc, item) => {
    acc = acc.then(() => {
      return fn(item).then(res => result.push(res));
    });
    return acc;
  }, Promise.resolve())
    .then(() => result);
}

Now it takes 4-5 seconds to fetch 10 items instead of one second in the previous example. But requesting 2000 items will not fail, so kinda success here. But how can we improve the algorithm completion time?

Divide and conquer

Let's take the best parts of both solutions and combine them together. We'll split all requests into chunks and fetch these chunks one by one. Feel free to experiment with the chunk size, I think for this example 50 requests per chunk would be fine.

function splitToChunks(items, chunkSize = 50) {
  const result = [];
  for (let i = 0; i < items.length; i+= chunkSize) {
    result.push(items.slice(i, i + chunkSize));
  }
  return result;
}

function chunks(items, fn, chunkSize = 50) {
  let result = [];
  const chunks = splitToChunks(items, chunkSize);
  return series(chunks, chunk => {
    return all(chunk, fn)
      .then(res => result = result.concat(res))
  })
    .then(() => result);
}

Awesome! Now we can handle a lot of requests with managable amount of time.

Conclusion

Results for fetching 2000 items:
all: ❌ Fetch error
series: ✅ 11 min 35 s
chunks: ✅ 1 min 12 s

Code on github