issue_comments: 1534238962

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https://github.com/pydata/xarray/issues/3213#issuecomment-1534238962 https://api.github.com/repos/pydata/xarray/issues/3213 1534238962 IC_kwDOAMm_X85bcqDy 2190658 2023-05-04T07:47:04Z 2023-05-04T07:47:04Z MEMBER

Speaking a bit to things like cumprod, it's hard to support those natively with sparse data structures in many cases (at least as things stand in the current Numba framework).

While that doesn't apply in the case of cumprod, PyData/Sparse also has a policy that if the best algorithm available is a dense one, we simply raise an error, and the user should densify explicitly to avoid filling all available RAM or getting obscure MemoryErrors.

 
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