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  • amueller · 2 ✖

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  • How should xarray use/support sparse arrays? · 2 ✖

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  • NONE · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
615500990 https://github.com/pydata/xarray/issues/3213#issuecomment-615500990 https://api.github.com/repos/pydata/xarray/issues/3213 MDEyOklzc3VlQ29tbWVudDYxNTUwMDk5MA== amueller 449558 2020-04-17T23:07:57Z 2020-04-17T23:07:57Z NONE

@shoyer thanks! Mostly spitballing here, but it's interesting to know that 2) would be the bigger problem in your opinion, I had assumed 1) would be the main issue. That raises the question whether it's easier to wrap scipy.sparse in a duck array, or to make pydata/sparse a viable solution for sklearn.

 
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   How should xarray use/support sparse arrays? 479942077
615497160 https://github.com/pydata/xarray/issues/3213#issuecomment-615497160 https://api.github.com/repos/pydata/xarray/issues/3213 MDEyOklzc3VlQ29tbWVudDYxNTQ5NzE2MA== amueller 449558 2020-04-17T22:51:09Z 2020-04-17T22:51:09Z NONE

Small comment from #3981: sklearn has just started running benchmarks, but it looks like pydata/sparse is not feature complete enough for us to use. We might be interested in having scipy.sparse support in xarray.

There are two problems with scipy.sparse for us as far as I can see (this is very preliminary): it only has COO, which is not good for us, and ideally we'd want to avoid memory copies whenever we want to use xarray, and I think going from scipy.sparse to pydata/sparse will involve memory copies, even if pydata/sparse adds other formats.

 
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   How should xarray use/support sparse arrays? 479942077

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