html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/4241#issuecomment-662517426,https://api.github.com/repos/pydata/xarray/issues/4241,662517426,MDEyOklzc3VlQ29tbWVudDY2MjUxNzQyNg==,1197350,2020-07-22T15:22:51Z,2020-07-22T15:22:51Z,MEMBER,"> The reason is that my function here must be applied along the time dimension (e.g., a rolling median in time), but my data is chunked across the time dimension

This is a fundamental problem that is rather hard to solve without creating a copy of the data.

We just released the [rechunker](https://rechunker.readthedocs.io/en/latest/) package, which makes it easy to create a copy of your data with a different chunking scheme (e.g contiguous in time, chunked in space). If you have enough disk space to store a copy, this might be a good solution.","{""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,662982199
https://github.com/pydata/xarray/issues/4241#issuecomment-662512964,https://api.github.com/repos/pydata/xarray/issues/4241,662512964,MDEyOklzc3VlQ29tbWVudDY2MjUxMjk2NA==,2448579,2020-07-22T15:14:53Z,2020-07-22T15:14:53Z,MEMBER,"You could try dask's `map_overlap` to share ""halo"" or Ghost points between chunks. Also see https://image.dask.org/en/latest/dask_image.ndfilters.html#dask_image.ndfilters.median_filter","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,662982199
https://github.com/pydata/xarray/issues/4241#issuecomment-661847133,https://api.github.com/repos/pydata/xarray/issues/4241,661847133,MDEyOklzc3VlQ29tbWVudDY2MTg0NzEzMw==,14808389,2020-07-21T13:02:20Z,2020-07-21T13:03:52Z,MEMBER,"> cannot be done by just using numpy-like functions

did you look at [apply_ufunc](https://xarray.pydata.org/en/stable/generated/xarray.apply_ufunc.html#xarray.apply_ufunc) ([examples](https://xarray.pydata.org/en/stable/examples/apply_ufunc_vectorize_1d.html)) and [map_blocks](https://xarray.pydata.org/en/stable/generated/xarray.map_blocks.html#xarray.map_blocks)? Functions applied with `apply_ufunc` will receive whatever was wrapped by `dask` while `map_blocks` allows you to work with xarray objects. See also the [docs](https://xarray.pydata.org/en/stable/dask.html#automatic-parallelization-with-apply-ufunc-and-map-blocks).
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,662982199