issues: 478343417

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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
478343417 MDU6SXNzdWU0NzgzNDM0MTc= 3191 DataArray.chunk() from sparse array produces malformed dask array 6213168 closed 0     1 2019-08-08T09:08:56Z 2019-08-12T21:02:24Z 2019-08-12T21:02:24Z MEMBER      

3117 by @nvictus introduces support for sparse in plain xarray.

dask already supports it.

Running with: - xarray git head - dask 2.2.0 - numpy 1.16.4 - sparse 0.7.0 - NUMPY_EXPERIMENTAL_ARRAY_FUNCTION=1

```python

import numpy, sparse, xarray, dask.array s = sparse.COO(numpy.array([1, 2]))
da1 = dask.array.from_array(s) da1._meta <COO: shape=(0,), dtype=int64, nnz=0, fill_value=0> da1.compute() <COO: shape=(2,), dtype=int64, nnz=2, fill_value=0> da2 = xarray.DataArray(s).chunk().data da2._meta
array([], dtype=int64) # Wrong da2.compute() RuntimeError: Cannot convert a sparse array to dense automatically. To manually densify, use the todense method. ```

 
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