With large datasets, creating the Pool data structure from a dataframe (this is in Python so a Pandas dataframe, although the same holds in R as well) takes a very long time, often dominating the other parts of training and especially predicting.

I noticed that this process is single-threaded and was wondering if it was possible to optimise it in some way.