issue_comments: 1280746923

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https://github.com/pydata/xarray/issues/6803#issuecomment-1280746923 https://api.github.com/repos/pydata/xarray/issues/6803 1280746923 IC_kwDOAMm_X85MVqWr 6213168 2022-10-17T12:01:17Z 2022-10-17T12:01:17Z MEMBER

Having said the above, your design is... contrived.

There isn't, as of today, a straightforward way to scatter a local dask collection (persist() will push the whole thing through the scheduler and likely send it out of memory).

Workaround: python test = np.full((20,), 30) a = da.from_array(test) dsk = client.scatter(dict(a.dask), broadcast=True) a = da.Array(dsk, name=a.name, chunks=a.chunks, dtype=a.dtype, meta=a._meta, shape=a.shape) a_x = xarray.DataArray(a, dims=["new_z"]) Once you have a_x, you just pass it to the args (not kwargs) of apply_ufunc.

 
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