Hi @Kevin.Thomas,
There is probably not anything wrong — ANCOM can take a long time to run, particularly if there are many samples and/or features.
The best way to speed things up is to remove low-abundance features (e.g., < 100 total observations? it depends on the sampling depth etc) and feature that are unique to samples (shared by < 5 samples? Depends on the total # of samples, size of groups, and goals of your analysis). These rare features will really slow things down.
That's a tiny test dataset (subsampled from a much larger one) — this subsample is used in the tutorial specifically to make commands fast and easy to run, but this does not give a good estimate of runtime for full data sets. It should give you an idea, though — if a tiny test dataset takes 5 min to run, a full-sized dataset will often take hours.
30 hr sounds like a record to me, but again it depends on the characteristics of the data. You might not be interested in those rare OTUs anyway, so I'd recommend killing the job, filtering your data, and re-running.
I hope that helps!