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  • Slicing DataArray can take longer than not slicing · 3 ✖

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  • NONE · 3 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
396317995 https://github.com/pydata/xarray/issues/2004#issuecomment-396317995 https://api.github.com/repos/pydata/xarray/issues/2004 MDEyOklzc3VlQ29tbWVudDM5NjMxNzk5NQ== jswhit 579593 2018-06-11T17:16:43Z 2018-06-11T17:16:43Z NONE

netcdf-c master now includes the same mechanism for strided access of HDF5 files as h5py. If netcdf4-python is linked against netcdf-c >= 4.6.2, performance for strided access should be greatly improved.

 
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   Slicing DataArray can take longer than not slicing 307318224
375102231 https://github.com/pydata/xarray/issues/2004#issuecomment-375102231 https://api.github.com/repos/pydata/xarray/issues/2004 MDEyOklzc3VlQ29tbWVudDM3NTEwMjIzMQ== jswhit 579593 2018-03-21T21:29:34Z 2018-03-21T21:29:34Z NONE

Confirmed that the slow performance of netcdf4-python on strided access is due to the way that netcdf-c calls HDF5. There's now an issue on the netcdf-c issue tracker to implement fast strided access for HDF5 files (https://github.com/Unidata/netcdf-c/issues/908).

 
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   Slicing DataArray can take longer than not slicing 307318224
375054212 https://github.com/pydata/xarray/issues/2004#issuecomment-375054212 https://api.github.com/repos/pydata/xarray/issues/2004 MDEyOklzc3VlQ29tbWVudDM3NTA1NDIxMg== jswhit 579593 2018-03-21T18:44:14Z 2018-03-21T18:44:14Z NONE

netcdf4-python does reopened[::1, ::10] by making a bunch of calls to the C lib routine nc_get_vara. As pointed out in Unidata/netcdf4-python#680, this is faster than a single call to nc_get_vars (which does strided access, but is very slow). Note that reopened[::1, ::1][:,::10] is very fast, but you have to have enough memory to hold the entire array. I wonder how h5netcdf is reading the data - is it pulling the entire array into memory and then selecting or subset?

 
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   Slicing DataArray can take longer than not slicing 307318224

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