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/1058#issuecomment-277543644,https://api.github.com/repos/pydata/xarray/issues/1058,277543644,MDEyOklzc3VlQ29tbWVudDI3NzU0MzY0NA==,6213168,2017-02-05T19:44:33Z,2017-02-05T19:44:33Z,MEMBER,"Actually, I very much still am facing the problem.
The biggest issue is now when I need to invoke xarray.broadcast. In my use case, I'm broadcasting together

- a scalar array with numpy backend, shape=(), chunks=None
- a 1D array with dask backend, shape=(2\*\*19,), chunks=(2\*\*15,)

What broadcast does is transform the scalar array to a numpy array of 2\*\*19 elements. This is actually a view on the original 0D array, so it's got negligible RAM requirements. But after pickling and unpickling, it's become a real 2\*\*19 elements array. Add up a few hundreds of them, and I am facing GBs of wasted RAM.

A  solution would be to change broadcast() to convert to dask *before* broadcasting, and then broadcast directly to the proper chunk size.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,184722754
https://github.com/pydata/xarray/issues/1058#issuecomment-260773846,https://api.github.com/repos/pydata/xarray/issues/1058,260773846,MDEyOklzc3VlQ29tbWVudDI2MDc3Mzg0Ng==,6213168,2016-11-15T21:26:52Z,2016-11-15T21:26:52Z,MEMBER,"Confirmed that #1017 fixes my specific issue, thanks!
Leaving the ticket open as other people (particularly those that work on large arrays without dask) will still be affected.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,184722754
https://github.com/pydata/xarray/issues/1058#issuecomment-255952251,https://api.github.com/repos/pydata/xarray/issues/1058,255952251,MDEyOklzc3VlQ29tbWVudDI1NTk1MjI1MQ==,6213168,2016-10-25T06:54:02Z,2016-10-25T06:54:02Z,MEMBER,"@maximilianr, if you pickle 2 plain python objects A and B together, and one of the attributes of B is a reference to A, A does not get duplicated. 

In this case there must be some specific __getstate__ code to prevent this and/or something with the C implementation of the class 
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