html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/1464#issuecomment-341329662,https://api.github.com/repos/pydata/xarray/issues/1464,341329662,MDEyOklzc3VlQ29tbWVudDM0MTMyOTY2Mg==,1217238,2017-11-02T06:29:38Z,2017-11-02T06:29:38Z,MEMBER,"I did a little bit of digging here, using @mrocklin's `Client(processes=False)` trick.

The problem seems to be that the arrays that we add to the writer in `AbstractWritableDataStore.set_variables` are not pickleable. To be more concrete, consider these lines:
https://github.com/pydata/xarray/blob/f83361c76b6aa8cdba8923080bb6b98560cf3a96/xarray/backends/common.py#L221-L232

`target` is currently a `netCDF4.Variable` object (or whatever the appropriate backend type is). Anything added to the writer eventually ends up as an argument to `dask.array.store` and hence gets put into the dask graph. When dask-distributed tries to pickle the dask graph, it fails on the `netCDF4.Variable`.

What we need to instead is wrap these `target` arrays in appropriate array wrappers, e.g., `NetCDF4ArrayWrapper`, adding `__setitem__` methods to the array wrappers if needed. Unlike most backend array types, our array wrappers are pickleable, which is essentially for use with dask-distributed.

If anyone's curious, here's the traceback and code I used to debug this:
https://gist.github.com/shoyer/4564971a4d030cd43bba8241d3b36c73","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,238284894
https://github.com/pydata/xarray/issues/1464#issuecomment-311122109,https://api.github.com/repos/pydata/xarray/issues/1464,311122109,MDEyOklzc3VlQ29tbWVudDMxMTEyMjEwOQ==,1217238,2017-06-26T17:10:07Z,2017-06-26T17:10:07Z,MEMBER,"I'm a little surprised that this doesn't work because I thought we made all our xarray datastore object pickle-able.

The place to start is probably to write an integration test for this functionality. I notice now that our current tests only check *reading* netCDF files with dask-distributed: 
https://github.com/pydata/xarray/blob/master/xarray/tests/test_distributed.py","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,238284894
https://github.com/pydata/xarray/issues/1464#issuecomment-310817117,https://api.github.com/repos/pydata/xarray/issues/1464,310817117,MDEyOklzc3VlQ29tbWVudDMxMDgxNzExNw==,1217238,2017-06-24T06:05:09Z,2017-06-24T06:05:09Z,MEMBER,"Hmm. Can you try using scipy as an engine to write the netcdf file?

Honestly I've barely used dask distributed. Possibly @mrocklin has ideas.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,238284894