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
376162232,MDExOlB1bGxSZXF1ZXN0MjI3NDQzNTI3,2532,[WIP] Fix problem with wrong chunksizes when using rolling_window on dask.array,102827,closed,0,,,2,2018-10-31T21:12:03Z,2021-03-26T19:50:50Z,2021-03-26T19:50:50Z,CONTRIBUTOR,,0,pydata/xarray/pulls/2532," - [ ] Closes #2514
 - [ ] Closes #2531
 - [ ] Tests added (for all bug fixes or enhancements)
 - [ ] Fully documented, including `whats-new.rst` for all changes

## Short summary
The two rolling-window functions for `dask.array`
 * [dask_rolling_wrapper](https://github.com/pydata/xarray/blob/b622c5e7da928524ef949d9e389f6c7f38644494/xarray/core/dask_array_ops.py#L23)
 * [rolling_window](https://github.com/pydata/xarray/blob/b622c5e7da928524ef949d9e389f6c7f38644494/xarray/core/dask_array_ops.py#L43)

will be fixed to preserve `dask.array` chunksizes.

## Long summary

The specific initial problem with chunksizes and `interpolate_na()` in #2514 is caused by the padding done in

https://github.com/pydata/xarray/blob/5940100761478604080523ebb1291ecff90e779e/xarray/core/dask_array_ops.py#L74-L85

which adds a small array with a small chunk to the initial array.

There is another related problem where `DataArray.rolling()` changes the size and distribution of `dask.array` chunks which stems from this code

https://github.com/pydata/xarray/blob/b622c5e7da928524ef949d9e389f6c7f38644494/xarray/core/dask_array_ops.py#L23

For some (historic) reason there are these two rolling-window functions for `dask`. Both need to be fixed to preserve chunksize of a `dask.array` in all cases.
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2532/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull
229807027,MDExOlB1bGxSZXF1ZXN0MTIxMzc5NjAw,1414,Speed up `decode_cf_datetime`,102827,closed,0,,,12,2017-05-18T21:15:40Z,2017-07-26T07:40:24Z,2017-07-25T17:42:52Z,CONTRIBUTOR,,0,pydata/xarray/pulls/1414," - [x] Closes #1399
 - [x] Tests added / passed
 - [x] Passes ``git diff upstream/master | flake8 --diff``
 - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API

Instead of casting the input numeric dates to float, they are now
casted to nanoseconds as int64 which makes `pd.to_timedelta()`
work much faster (x100 speedup on my machine).

On my machine all existing tests for `conventions.py` pass. Overflows should be handled by [these two already existing lines](https://github.com/cchwala/xarray/commit/d7d7c01f3e2f14c38c44e62f648b30474469b078#diff-d94eba38daa73be812c57c756f01f0daR158) since everything in the valid range of `pd.to_datetime` should be save.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1414/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull