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
1315111684,I_kwDOAMm_X85OYwME,6816,pandas.errors.InvalidIndexError is raised in some runs when using chunks and map_blocks(),691772,closed,0,,,5,2022-07-22T14:56:41Z,2022-09-13T09:39:48Z,2022-08-19T14:06:09Z,CONTRIBUTOR,,,,"### What is your issue?

I'm doing a lengthy computation, which involves hundreds of GB of data using chunks and map_blocks() so that things fit into RAM and can be done in parallel. From time to time, the following error is raised:

`pandas.errors.InvalidIndexError: Reindexing only valid with uniquely valued Index objects`

The line where this takes place looks pretty harmless:

    x = a * b.sel(c=d.c)

It's a line inside the function `func` which is passed to a `map_blocks()` call. In this case `a` and `b` are `xr.DataArray` or `xr.DataSet` objects shadowed from outer scope and `d` is the parameter `obj` for `map_blocks()`.

That means, the line below in the traceback looks like this:

    xr.map_blocks(
        lambda d: worker(d).compute().chunk({""time"": None}),
        d,
        template=template)

I guess it's some kind of race condition, since it's not 100% reproducible, but I have no idea how to further investigate the issue to create a proper bug report or fix my code.

Do you have any hint how I could continue building a minimal example or so in such a case? What does the error message want to tell me?","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6816/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
438389323,MDU6SXNzdWU0MzgzODkzMjM=,2928,"Dask outputs warning: ""The da.atop function has moved to da.blockwise""",691772,closed,0,,,4,2019-04-29T15:59:31Z,2019-07-12T15:56:29Z,2019-07-12T15:56:28Z,CONTRIBUTOR,,,,"#### Problem description
[dask 1.1.0](https://github.com/dask/dask/pull/4348) moved `atop()` to `blockwise()` and introduced a warning when `atop()` is used.

#### Related
* upstream ticket and PR of dask change: dask/dask#4348 dask/dask#4035
* the warning in the [dask documentation](https://examples.dask.org/xarray.html#Custom-workflows-and-automatic-parallelization) in an xarray example, probably not on purpose
* warnings have been already discussed in #2727, but not fixed there
* same issue in a different project: pytroll/satpy#608

#### Code Sample

```python
import numpy as np
import xarray as xr

xr.DataArray(np.ones(1000))
d = xr.DataArray(np.ones(1000))
d.to_netcdf('/tmp/ones.nc')
d = xr.open_dataarray('/tmp/ones.nc', chunks=10)
xr.apply_ufunc(lambda x: 42 * x, d, dask='parallelized', output_dtypes=[np.float64])
```

This outputs the warning:
```
...lib/python3.7/site-packages/dask/array/blockwise.py:204: UserWarning: The da.atop function has moved to da.blockwise
  warnings.warn(""The da.atop function has moved to da.blockwise"")
```

#### Expected Output

No warning. As user of a recent version of dask and xarray, there shouldn't be any warnings if everything is done right. The warning should be tackled inside xarray somehow.

#### Solution

Not sure, can xarray break compatibility with dask <1.1.0 with some future version? Otherwise I guess there needs to be some legacy code in xarray which calls the right function.

#### Output of ``xr.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.3 (default, Mar 27 2019, 22:11:17) 
[GCC 7.3.0]
python-bits: 64
OS: Linux
OS-release: 4.18.0-17-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.4
libnetcdf: 4.6.1

xarray: 0.12.1
pandas: 0.24.2
numpy: 1.16.3
scipy: 1.2.1
netCDF4: 1.4.2
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.0.3.4
nc_time_axis: None
PseudonetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: 1.2.0
distributed: 1.27.0
matplotlib: 3.0.3
cartopy: None
seaborn: 0.9.0
setuptools: 41.0.0
pip: 19.1
conda: None
pytest: 4.4.1
IPython: 7.5.0
sphinx: None
</details>
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