Regression: "TypeError: Vectorized indexing is not supported" with xarray 2024.10.0 + sparse

What happened?

Code that worked with xarray 2024.9.0 has begun to fail with xarray 2024.10.0, even though no breaking changes were advertised.

What did you expect to happen?

The below MCVE runs with xarray 2024.9.0, giving the output below.

I'd expect it runs the same way with xarray 2024.10.0.

Minimal Complete Verifiable Example

import pandas as pd
import xarray as xr
from numpy import nan

# Create a series
s = pd.Series(
    [nan, nan, 1.0, nan, nan, nan, 2, 3, 4, nan, 5, 6, 7, 8, 9],
    index=pd.MultiIndex.from_product(
        [["x0", "x1", "x2"], ["y0", "y1", "y2", "y3", "y4"]], names=list("xy")
    ),
)

# Create indexers
newdim = {"newdim": ["nd0", "nd1", "nd2"]}
x_idx = xr.DataArray(["x2", "x1", "x2"], coords=newdim)
y_idx = xr.DataArray(["y4", "y2", "y0"], coords=newdim)

for sparse in (False, True):
    # Create a DataArray
    da = xr.DataArray.from_series(s, sparse=sparse)

    # Do vectorized indexing
    print(da.sel(x=x_idx, y=y_idx))

MVCE confirmation

• Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• Complete example — the example is self-contained, including all data and the text of any traceback.
• Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• New issue — a search of GitHub Issues suggests this is not a duplicate.
• Recent environment — the issue occurs with the latest version of xarray and its dependencies.

Relevant log output

With xarray 2024.9.0:

<xarray.DataArray (newdim: 3)> Size: 24B
array([9., 3., 5.])
Coordinates:
    x        (newdim) object 24B 'x2' 'x1' 'x2'
    y        (newdim) object 24B 'y4' 'y2' 'y0'
  * newdim   (newdim) <U3 36B 'nd0' 'nd1' 'nd2'
<xarray.DataArray (newdim: 3)> Size: 48B
<COO: shape=(3,), dtype=float64, nnz=3, fill_value=nan>
Coordinates:
    x        (newdim) object 24B 'x2' 'x1' 'x2'
    y        (newdim) object 24B 'y4' 'y2' 'y0'
  * newdim   (newdim) <U3 36B 'nd0' 'nd1' 'nd2'

With xarray 2024.10.0:

<xarray.DataArray (newdim: 3)> Size: 24B
array([9., 3., 5.])
Coordinates:
    x        (newdim) object 24B 'x2' 'x1' 'x2'
    y        (newdim) object 24B 'y4' 'y2' 'y0'
  * newdim   (newdim) <U3 36B 'nd0' 'nd1' 'nd2'
Traceback (most recent call last):
  File "/home/khaeru/vc/genno/bug.py", line 23, in <module>
    print(da.sel(x=x_idx, y=y_idx))
          ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/khaeru/.venv/3.12/lib/python3.12/site-packages/xarray/core/dataarray.py", line 1675, in sel
    ds = self._to_temp_dataset().sel(
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/khaeru/.venv/3.12/lib/python3.12/site-packages/xarray/core/dataset.py", line 3237, in sel
    result = self.isel(indexers=query_results.dim_indexers, drop=drop)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/khaeru/.venv/3.12/lib/python3.12/site-packages/xarray/core/dataset.py", line 3070, in isel
    return self._isel_fancy(indexers, drop=drop, missing_dims=missing_dims)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/khaeru/.venv/3.12/lib/python3.12/site-packages/xarray/core/dataset.py", line 3126, in _isel_fancy
    new_var = var.isel(indexers=var_indexers)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/khaeru/.venv/3.12/lib/python3.12/site-packages/xarray/core/variable.py", line 1049, in isel
    return self[key]
           ~~~~^^^^^
  File "/home/khaeru/.venv/3.12/lib/python3.12/site-packages/xarray/core/variable.py", line 816, in __getitem__
    data = indexing.apply_indexer(indexable, indexer)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/khaeru/.venv/3.12/lib/python3.12/site-packages/xarray/core/indexing.py", line 1029, in apply_indexer
    return indexable.vindex[indexer]
           ~~~~~~~~~~~~~~~~^^^^^^^^^
  File "/home/khaeru/.venv/3.12/lib/python3.12/site-packages/xarray/core/indexing.py", line 369, in __getitem__
    return self.getter(key)
           ^^^^^^^^^^^^^^^^
  File "/home/khaeru/.venv/3.12/lib/python3.12/site-packages/xarray/core/indexing.py", line 1589, in _vindex_get
    raise TypeError("Vectorized indexing is not supported")
TypeError: Vectorized indexing is not supported

Anything else we need to know?

No response

Environment

Run the provided MCVE with xarray 2024.9.0 and 2024.10.0, then inspect the indexing path in xarray/core/indexing.py, variable.py, and dataset.py shown in the traceback. The fix is complete when vectorized selection of the sparse DataArray succeeds as it did in 2024.9.0, with a regression test covering the example.