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/1836#issuecomment-361532119,https://api.github.com/repos/pydata/xarray/issues/1836,361532119,MDEyOklzc3VlQ29tbWVudDM2MTUzMjExOQ==,102827,2018-01-30T09:32:26Z,2018-01-30T09:32:26Z,CONTRIBUTOR,"Thanks @jhamman for looking into this.

Currently I am fine with using `persist()` since I can break down my analysis workflow to certain time periods for which data fits into RAM on a large machine. As I have written, the distributed scheduler failed for me because of #1464. But I would like to use it in the future. From other discussions on the dask schedulers (here or on SO) using the distributed scheduler seems to be a general recommendation anyway.

In summary, I am fine with my current workaround. I do not think that solving this issue has a high priority, in particular when the distributed scheduler is further improved. The main annoyance was to track down the problem described in my first post. Hence, maybe the limitations of the schedulers could be described a bit better in the documentation. Would you want a PR on this?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,289342234
https://github.com/pydata/xarray/issues/1836#issuecomment-358445479,https://api.github.com/repos/pydata/xarray/issues/1836,358445479,MDEyOklzc3VlQ29tbWVudDM1ODQ0NTQ3OQ==,102827,2018-01-17T21:07:43Z,2018-01-17T21:07:43Z,CONTRIBUTOR,"Thanks for the quick answer. 

The problem is that my actual use case also involves writing back a `xarray.Dataset` via `to_netcdf()`. I left this out of the example above to isolate the problem. With the `distributed` scheduler and `to_netcdf()`, I ran into this issue #1464. As I can see, this might be fixed ""soon"" (#1793).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,289342234