issue_comments: 432735579

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https://github.com/pydata/xarray/issues/2504#issuecomment-432735579 https://api.github.com/repos/pydata/xarray/issues/2504 432735579 MDEyOklzc3VlQ29tbWVudDQzMjczNTU3OQ== 1217238 2018-10-24T16:44:23Z 2018-10-24T16:44:23Z MEMBER

I think this is basically a netCDF4-Python issue. It is definitely a known issue that some complex indexing operations can be more expensive when done on netCDF4-Python arrays rather than in-memory NumPy arrays.

The easy work-around is to write something like ds.load() first to load the data into memory. Unfortunately this is hard to fix in general because there is a tradeoff in terms of memory usage.

The other option is to try another netCDF4 backend engine, e.g., install h5netcdf and set engine='h5netcdf'.

 
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