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issues: 1966733834

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
1966733834 PR_kwDOAMm_X85eCSac 8389 Use numbagg for `ffill` by default 5635139 closed 0     5 2023-10-28T20:40:13Z 2023-11-25T21:06:10Z 2023-11-25T21:06:09Z MEMBER   0 pydata/xarray/pulls/8389

The main perf advantage here is the array doesn't need to be unstacked & stacked, which is a huge win for large multi-dimensional arrays... (I actually was hitting a memory issue running an ffill on my own, and so thought I'd get this done!)

We could move these methods to DataWithCoords, since they're almost the same implementation between a DataArray & Dataset, and exactly the same for numbagg's implementation


For transparency — the logic of "check for numbagg, check for bottleneck" I wouldn't rate at my most confident. But I'm more confident that just installing numbagg will work. And if that works well enough, we could consider only supporting numbagg for some of these in the future.

I also haven't done the benchmarks here — though the functions are relatively well benchmarked at numbagg. I'm somewhat trading off getting through these (rolling functions are coming up too) vs. doing fewer slower, and leaning towards the former, but feedback welcome...

  • [x] Tests added
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [x] New functions/methods are listed in api.rst
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