I'm guessing from Google's point of view, that parallel processing two tasks (for example, that simply had Utilities.sleep(3000)
) would require multiple threads to run in the server cpu, which may not be manageable and may be easy to abuse.
Whereas parallel processing on the client or other companies server (e.g., Node.js) is up to that developer or user. (If they don't scale well it's not Google's problem)
However there are some things that use parallelism
UrlFetchApp.fetchAll
UrlFetchApp.fetchAll() will asynchronously fetch many urls. Although this is not what you're truly looking for, fetching urls is a major reason to seek parallel processing.
I'm guessing Google is reasoning this is ok since fetchall
is using a web client and its own resources are already protected by quota.
FirebaseApp getAllData
Firebase I have found is very fast compared to using a spreadsheet for data storage. You can get many things from the database at once using FirebaseApp
's getAllData
:
function myFunction() {
var baseUrl = "https://samplechat.firebaseio-demo.com/";
var secret = /* your secret */;
var database = FirebaseApp.getDatabaseByUrl(baseUrl, secret);
// paths of 3 different user profiles
var path1 = "users/jack";
var path2 = "users/bob";
var path3 = "users/jeane";
Logger.log(database.getAllData([path1, path2, path3]));
}
HtmlService - IFrame mode
HtmlService - IFrame mode allows full multi-tasking by going out to client script where promises are truly supported and making parallel calls back into the server. You can initiate this process from the server, but since all the parallel tasks' results are returned in the client, it's unclear how to get them back to the server. You could make another server call and send the results, but I'm thinking the goal would be to get them back to the script that called HtmlService
in the first place, unless you go with a beginRequest
and endRequest
type architecture.
tanaikech/RunAll
This is a library for running the concurrent processing using only native Google Apps Script (GAS). This library claims full support via a RunAll.Do(workers)
method.
I'll update my answer if I find any other tricks.