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/pull/1457#issuecomment-317758630,https://api.github.com/repos/pydata/xarray/issues/1457,317758630,MDEyOklzc3VlQ29tbWVudDMxNzc1ODYzMA==,1197350,2017-07-25T14:38:36Z,2017-07-25T14:38:36Z,MEMBER,I will merge by the end of the day if no one has any more comments.,"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,236347050
https://github.com/pydata/xarray/pull/1457#issuecomment-315401470,https://api.github.com/repos/pydata/xarray/issues/1457,315401470,MDEyOklzc3VlQ29tbWVudDMxNTQwMTQ3MA==,1197350,2017-07-14T16:17:07Z,2017-07-14T16:17:07Z,MEMBER,"I think this a great start!

I would really like to see a performance test for `open_mfdataset`, since this is my own personal bottleneck.

Regarding the dependence on hardware, I/O speeds, etc, we should be able to resolve this by running on specific instance types on a cloud platform. We could configure environments with local SSD storage, network storage, etc, in order to cover different scenarios.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,236347050