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  • djhoese · 1 ✖

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  • Threading Lock issue with to_netcdf and Dask arrays · 1 ✖

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  • CONTRIBUTOR · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
785432974 https://github.com/pydata/xarray/issues/4406#issuecomment-785432974 https://api.github.com/repos/pydata/xarray/issues/4406 MDEyOklzc3VlQ29tbWVudDc4NTQzMjk3NA== djhoese 1828519 2021-02-24T22:42:15Z 2021-02-24T22:42:15Z CONTRIBUTOR

I'm having a similar issue to what is described here, but I'm seeing it even when I'm not rewriting an output file (although it is an option in my code). I have a delayed function that is calling to_netcdf and seem to run into some race condition where I get the same deadlock as the original poster. It seems highly dependent on the number of dask tasks and the number of workers. I think I've gotten around it for now by having my delayed function return the Dataset it is working on and then calling to_dataset later. My problem is I have cases where I might not want to write the file so my delayed function returns None. To handle this I need to pre-compute my delayed functions before calling to_dataset since I don't think there is a way to pass something to to_dataset so it doesn't create a file.

With the original code it happened quite a bit but was part of a much larger application so I can't really get a MWE together. Just wanted to mention it here as another data point (to_netcdf inside a Delayed function may not work 100% of the time).

 
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   Threading Lock issue with to_netcdf and Dask arrays 694112301

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