I experimented a bit with this pattern last year, using SAS Data Integration Studio (which encapsulates these techniques using its loop node), and hit a peak "parallelisation factor" of ~ 600 without trying very hard.

In the "ETL" space this is well trodden ground, but you have to take into account factors like I/O contention, how to orchestrate the results into one place without inflicting locks on yourself, and your platforms overall "bandwidth".

You can get really advanced if needs be, even getting into spinning up transient "worker servers" when you're on a Cloud platform.

But, it's really about "orchestration" in the end.

I can dig out the jobs I put together as a test harness to simulate this, and the Linux scripts I used to monitor exactly how many SAS processes I hit at peak.

(Be careful trying this on less than industrial strength kit - you can "melt" your laptop if you push things too far, and more or less DDOS it to death with SAS processes as I have a few times. I ended up hard rebooting my laptop and the whole machine basically became unresponsive when with no limits imposed.)