issues: 807089005

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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
807089005 MDU6SXNzdWU4MDcwODkwMDU= 4898 Sum and prod with min_count forces evaluation 367900 closed 0     5 2021-02-12T09:42:06Z 2021-02-19T08:12:02Z 2021-02-19T08:12:01Z CONTRIBUTOR      

If I use the sum method on a lazy array with min_count != None then evaluation is forced. If there is some limitation of the implementation which means it cannot be added to the computation graph for lazy evaluation then this should be mentioned in the docs.

Minimal Complete Verifiable Example:

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

def worker(da): if da.shape == (0, 0): return da

raise RuntimeError("I was evaluated")

da = xr.DataArray( np.random.normal(size=(20, 500)), dims=("x", "y"), coords=(np.arange(20), np.arange(500)), )

da = da.chunk(dict(x=5)) lazy = da.map_blocks(worker) result1 = lazy.sum("x", skipna=True) result2 = lazy.sum("x", skipna=True, min_count=5)

```

What happened: RuntimeError: I was evaluated

What you expected to happen: No output or exceptions, as the result1 and result2 arrays are not printed or saved.

Environment:

Output of <tt>xr.show_versions()</tt> INSTALLED VERSIONS ------------------ commit: None python: 3.9.1 (default, Feb 6 2021, 06:49:13) [GCC 10.2.0] python-bits: 64 OS: Linux OS-release: 5.10.15-arch1-1 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: en_NZ.UTF-8 LOCALE: en_NZ.UTF-8 libhdf5: 1.12.0 libnetcdf: 4.7.4 xarray: 0.16.2 pandas: 1.2.1 numpy: 1.20.0 scipy: 1.6.0 netCDF4: 1.5.5.1 pydap: None h5netcdf: 0.9.0 h5py: 3.1.0 Nio: None zarr: None cftime: 1.4.1 nc_time_axis: None PseudoNetCDF: None rasterio: 1.2.0 cfgrib: None iris: None bottleneck: 1.3.2 dask: 2020.12.0 distributed: 2020.12.0 matplotlib: 3.3.4 cartopy: 0.18.0 seaborn: None numbagg: None pint: None setuptools: 53.0.0 pip: 20.3.1 conda: None pytest: 6.2.1 IPython: 7.19.0 sphinx: 3.4.3 
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   completed 13221727 issue

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