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
535703663,MDU6SXNzdWU1MzU3MDM2NjM=,3608,Feature Request: Efficient rolling with strides,5802846,open,0,,,8,2019-12-10T12:38:59Z,2021-07-28T11:58:28Z,,CONTRIBUTOR,,,,"Xarray is facing the same issues in its current `rolling` implementation (`DataArrayRolling` and `DatasetRolling`) as described in [this pandas issue](https://github.com/pandas-dev/pandas/issues/15354). Namely, the `construct` methods stride parameter is applied after the rolling is computed. Technically, we are computing more than we would need to because we partially throwing it away due to striding.

In PR #3607 the issue is solved for the `...Rolling`'s  `__iter__` function but not for the `construct`, `reduce` and `_bottleneck_reduce` methods.
Since the way Xarray's rolling is implemented relies on numpy, we could introduce a sliding window function as described [here](https://github.com/numpy/numpy/issues/7753#).

Any opinions?
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