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  • shoyer · 2 ✖

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  • Limiting threads/cores used by xarray(/dask?) · 2 ✖

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  • MEMBER · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
422461245 https://github.com/pydata/xarray/issues/2417#issuecomment-422461245 https://api.github.com/repos/pydata/xarray/issues/2417 MDEyOklzc3VlQ29tbWVudDQyMjQ2MTI0NQ== shoyer 1217238 2018-09-18T16:31:03Z 2018-09-18T16:31:03Z MEMBER

If your data using in-file HDF5 chunks/compression it's possible that HDF5 is uncompressing the data is parallel, though I haven't seen that before personally.

 
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   Limiting threads/cores used by xarray(/dask?) 361016974
422206083 https://github.com/pydata/xarray/issues/2417#issuecomment-422206083 https://api.github.com/repos/pydata/xarray/issues/2417 MDEyOklzc3VlQ29tbWVudDQyMjIwNjA4Mw== shoyer 1217238 2018-09-17T23:40:52Z 2018-09-17T23:40:52Z MEMBER

Step 1 would be making sure that you're actually using dask :). Xarray only uses dask with open_dataset() if you supply the chunks keyword argument.

That said, xarray's only built-in support for parallelism is through Dask, so I'm not sure what is using all your CPU.

 
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   Limiting threads/cores used by xarray(/dask?) 361016974

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