What happened?

When performing groupby-/resample-reduce operations (e.g., ds.resample(time="6h").mean() as shown here) the alignment of chunks is not preserved when flox is disabled:

...whereas the alignment is preserved when flox is enabled:

What did you expect to happen?

The alignment of chunks is preserved whether using flox or not.

Minimal Complete Verifiable Example

```Python import pandas as pd import numpy as np import xarray as xr

size_spatial = 1000 size_temporal = 200 time = pd.date_range("2000-01-01", periods=size_temporal, freq='h') lat = np.random.uniform(low=-90, high=90, size=size_spatial) lon = np.random.uniform(low=-180, high=180, size=size_spatial) data = np.random.rand(size_temporal, size_spatial, size_spatial)

da = xr.DataArray(data=data, dims=['time', 'x', 'y'], coords={'time': time, 'x': lon, 'y': lat}).chunk({'time': -1, 'x': 'auto', 'y': 'auto'})

Chunk alignment not preserved

with xr.set_options(use_flox=False): da_1 = da.copy(deep=True) da_1 = da_1.resample(time="6h").mean()

Chunk alignment preserved

with xr.set_options(use_flox=True): da_2 = da.copy(deep=True) da_2 = da_2.resample(time="6h").mean() ```

MVCE confirmation

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

Relevant log output

No response

Anything else we need to know?

No response

Environment

INSTALLED VERSIONS ------------------ commit: None python: 3.11.7 | packaged by conda-forge | (main, Dec 23 2023, 14:38:07) [Clang 16.0.6 ] python-bits: 64 OS: Darwin OS-release: 22.4.0 machine: arm64 processor: arm byteorder: little LC_ALL: None LANG: None LOCALE: (None, 'UTF-8') libhdf5: None libnetcdf: None xarray: 2024.1.1 pandas: 2.2.0 numpy: 1.26.3 scipy: 1.12.0 netCDF4: None pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: None nc_time_axis: None iris: None bottleneck: None dask: 2024.1.0 distributed: 2024.1.0 matplotlib: None cartopy: None seaborn: None numbagg: 0.7.1 fsspec: 2023.12.2 cupy: None pint: None sparse: None flox: 0.9.0 numpy_groupies: 0.10.2 setuptools: 69.0.3 pip: 23.3.2 conda: None pytest: None mypy: None IPython: 8.20.0 sphinx: None