issue_comments: 485497398

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https://github.com/pydata/xarray/issues/2912#issuecomment-485497398 https://api.github.com/repos/pydata/xarray/issues/2912 485497398 MDEyOklzc3VlQ29tbWVudDQ4NTQ5NzM5OA== 2443309 2019-04-22T18:06:56Z 2019-04-22T18:06:56Z MEMBER

Since the final dataset size is quite manageable, I would start by forcing computation before the write step:

python ncdat.load().to_netcdf(...)

While writing of xarray datasets backed by dask is possible, its a poorly optimized operation. Most of this comes from constraints in netCDF4/HDF5. There are ways to side step some of these challenges (save_mfdataset and the distributed dask scheduler) but they are probably overkill for this use case.

 
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