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
868352536,MDU6SXNzdWU4NjgzNTI1MzY=,5219,"Zarr encoding attributes persist after slicing data, raising error on `to_zarr`",4801430,open,0,,,9,2021-04-27T01:34:52Z,2022-12-06T16:16:20Z,,CONTRIBUTOR,,,,"**What happened**:
Opened a dataset using `open_zarr`, sliced the dataset, and then tried to resave to a zarr store using `to_zarr`.

**What you expected to happen**:
The file would save without needing to explicitly modify any `encoding` dictionary values

**Minimal Complete Verifiable Example**:

```python
ds = xr.Dataset({""data"": ((""dimA"", ), [10, 20, 30, 40])}, coords={""dimA"": [1, 2, 3, 4]})
ds = ds.chunk({""dimA"": 2})
ds.to_zarr(""test.zarr"", consolidated=True, mode=""w"")

ds2 = xr.open_zarr(""test.zarr"", consolidated=True).sel(dimA=[1,3]).persist()
ds2.to_zarr(""test2.zarr"", consolidated=True, mode=""w"")
```

This raises:
```python
NotImplementedError: Specified zarr chunks encoding['chunks']=(2,) for variable named 'data' would overlap multiple dask chunks ((1, 1),). This is not implemented in xarray yet. Consider either rechunking using `chunk()` or instead deleting or modifying `encoding['chunks']`.
```
**Anything else we need to know?**:

Not sure if there is a good way around this (or perhaps this is even desired behavior?), but figured I would flag it as it seemed unexpected and took us a second to diagnose. Once you've loaded the data from a zarr store, I feel like the default behavior should probably be to forget the encodings used to save that zarr, treating the in-memory dataset object just like any other in-memory dataset object that could have been loaded from any source. But maybe I'm in the minority or missing some nuance about why you'd want the encoding to hang around.

**Environment**:

```
INSTALLED VERSIONS
------------------
commit: None
python: 3.8.8 | packaged by conda-forge | (default, Feb 20 2021, 16:22:27) 
[GCC 9.3.0]
python-bits: 64
OS: Linux
OS-release: 5.4.89+
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: C.UTF-8
LANG: C.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.6
libnetcdf: 4.7.4

xarray: 0.17.0
pandas: 1.2.4
numpy: 1.20.2
scipy: 1.6.2
netCDF4: 1.5.6
pydap: installed
h5netcdf: 0.11.0
h5py: 3.2.1
Nio: None
zarr: 2.7.1
cftime: 1.2.1
nc_time_axis: 1.2.0
PseudoNetCDF: None
rasterio: 1.2.2
cfgrib: 0.9.9.0
iris: 3.0.1
bottleneck: 1.3.2
dask: 2021.04.1
distributed: 2021.04.1
matplotlib: 3.4.1
cartopy: 0.19.0
seaborn: 0.11.1
numbagg: None
pint: 0.17
setuptools: 49.6.0.post20210108
pip: 21.0.1
conda: None
pytest: 6.2.3
IPython: 7.22.0
sphinx: 3.5.4
```
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