I did not get the answer right.
After looking at the answer details, if I understand the answer correctly, we are only using $facet here becuase it gives us the ability to execute multiple pipeline with one aggregation but we are not actually $bucketing anything. So we are using $facets for a technical thing that it gives us (doing several pipelines) not for what we usually use it (bucketing).
Am I correct?
Facets imply that you get different statistics about the collection. At least from my view, you get a “face” of the data.
There is no way to “fork” your data otherwise.
So using $facet is the most facetting thing, and the other 2 are more simplified less powerful facets of the data, and they are extensions of $group
$facet allows you to run several independent pipelines within the stage of a pipeline, all using the same data, Basically, you can do several calculations in one collections and achieve it in one calculation.
In this particular lab we are calculating both top_metacritic and top_imdb in the same $facet stage.
I hope this clarifies your doubt.
Please feel free to reach out if you have any questions.
Kind Regards,
Sonali