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
1171932478,I_kwDOAMm_X85F2kU-,6373,Zarr backend should avoid checking for invalid encodings,2448579,closed,0,,,3,2022-03-17T04:55:35Z,2022-03-18T10:06:01Z,2022-03-18T04:19:48Z,MEMBER,,,,"### What is your issue?

The zarr backend has a list of ""valid"" encodings that needs to be updated any time zarr adds something new (e.g. https://github.com/pydata/xarray/pull/6348)

https://github.com/pydata/xarray/blob/53172cb1e03a98759faf77ef48efaa64676ad24a/xarray/backends/zarr.py#L215-L234

Can we get rid of this? I don't know the backends code well, but won't all our encoding parameters have been removed by this stage? The `raise_on_invalid` kwarg suggests so.

@tomwhite points out that zarr will raise a warning:
``` python
>>> zarr.create((1,), blah=1)
/Users/tom/miniconda/envs/sgkit-3.8/lib/python3.8/site-packages/zarr/creation.py:221: UserWarning: ignoring keyword argument 'blah'
  warn('ignoring keyword argument %r' % k)
<zarr.core.Array (1,) float64>
```","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6373/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
1171916710,I_kwDOAMm_X85F2gem,6372,"apply_ufunc + dask=""parallelized"" + no core dimensions should raise a nicer error about core dimensions being absent",2448579,open,0,,,0,2022-03-17T04:25:37Z,2022-03-17T05:10:16Z,,MEMBER,,,,"### What happened?

From https://github.com/pydata/xarray/discussions/6370


Calling `apply_ufunc(..., dask=""parallelized"")` with no core dimensions and dask input ""works"" but raises an error on compute (`ValueError: axes don't match array` from `np.transpose`).

``` python
xr.apply_ufunc(
    lambda x: np.mean(x),
    dt,
    dask=""parallelized""
)
```

### What did you expect to happen?

With numpy data the apply_ufunc call does raise an error:

```
xr.apply_ufunc(
    lambda x: np.mean(x),
    dt.compute(),
    dask=""parallelized""
)
```

``` 
ValueError: applied function returned data with unexpected number of dimensions. Received 0 dimension(s) but expected 1 dimensions with names: ('x',)
```

### Minimal Complete Verifiable Example

``` python
import xarray as xr

dt = xr.Dataset(
    data_vars=dict(
        value=([""x""], [1,1,2,2,2,3,3,3,3,3]), 
    ),
    coords=dict(
        lon=([""x""], np.linspace(0,1,10)),
    ),
).chunk(chunks={'x': tuple([2,3,5])}) # three chunks of different size

xr.apply_ufunc(
    lambda x: np.mean(x),
    dt,
    dask=""parallelized""
)
```

### Relevant log output

_No response_

### Anything else we need to know?

_No response_

### Environment

N/A","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6372/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue