issue_comments: 416389795

@TomNicholas I think your analysis is correct here.

I suspect that in most cases we could figure out how to tile datasets by looking at 1D coordinates along each dimension (e.g., indexes for each dataset), e.g., to find a "chunk id" along each concatenated dimension.

These could be used to build something like a NumPy object array of xarray.Dataset/DataArray objects, which could split up into a bunch of 1D calls to xarray.concat().

I would rather avoid using the positions argument of concat. It doesn't really add any flexibility compared to reordering the inputs with xarray.core.nputils.inverse_permutation.

Final point - this common use case also has the added complexity of having ghost or guard cells around every dataset, which should be thrown away. Clearly some user input is required here (ghost_cells_x=2, ghost_cells_y=2, ghost_cells_z=0, ...), but I'm really not sure what the best way to fit that kind of logic in is. Yet more arguments to open_mfdataset?

We could potentially just encourage using the existing preprocess argument.