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  • dcherian · 3 ✖

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  • .to_zarr() or .to_netcdf slow and uses excess memory when datetime64[ns] variable in output; a reproducible example · 3 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1302301808 https://github.com/pydata/xarray/issues/7028#issuecomment-1302301808 https://api.github.com/repos/pydata/xarray/issues/7028 IC_kwDOAMm_X85Nn4xw dcherian 2448579 2022-11-03T15:40:52Z 2022-11-03T15:40:52Z MEMBER

Ah now I see #7132 . Let's close this since the example there is a lot smaller.

 
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   .to_zarr() or .to_netcdf slow and uses excess memory when datetime64[ns] variable in output; a reproducible example 1371466778
1302298612 https://github.com/pydata/xarray/issues/7028#issuecomment-1302298612 https://api.github.com/repos/pydata/xarray/issues/7028 IC_kwDOAMm_X85Nn3_0 dcherian 2448579 2022-11-03T15:38:25Z 2022-11-03T15:40:29Z MEMBER

Sorry for the slow response here Jamie.

I suspect (but have not checked) that is a dupe of https://github.com/pydata/xarray/issues/3834 and https://github.com/pydata/xarray/issues/7132

To decide how to encode the datetime, it's loading the whole array.

 
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   .to_zarr() or .to_netcdf slow and uses excess memory when datetime64[ns] variable in output; a reproducible example 1371466778
1302299859 https://github.com/pydata/xarray/issues/7028#issuecomment-1302299859 https://api.github.com/repos/pydata/xarray/issues/7028 IC_kwDOAMm_X85Nn4TT dcherian 2448579 2022-11-03T15:39:24Z 2022-11-03T15:39:24Z MEMBER

The way to test would be:

``` from xarray.tests import raise_if_dask_computes

with raise_if_dask_computes(): ds.to_netcdf(compute=False) ```

 
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   .to_zarr() or .to_netcdf slow and uses excess memory when datetime64[ns] variable in output; a reproducible example 1371466778

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