issue_comments: 998357641

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https://github.com/pydata/xarray/issues/6084#issuecomment-998357641 https://api.github.com/repos/pydata/xarray/issues/6084 998357641 IC_kwDOAMm_X847gbqJ 1217238 2021-12-21T00:00:49Z 2021-12-21T00:00:49Z MEMBER

The challenge is that Xarray needs some way to represent the "schema" for the desired entire dataset. I'm very open to alternatives, but so far, the most convenient way to do this has been to load Dask arrays into an xarray.Dataset.

It's worth noting that any dask arrays with the desired chunking scheme will do -- you don't need to use the same dask arrays that you want to compute. When I do this sort of thing, I will often use xarray.zeros_like() to create low overhead versions of dask arrays, e.g., in this example from Xarray-Beam: https://github.com/google/xarray-beam/blob/0.2.0/examples/era5_climatology.py#L61-L68

 
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