issue_comments: 295993132
This data as json
| 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/1379#issuecomment-295993132 | https://api.github.com/repos/pydata/xarray/issues/1379 | 295993132 | MDEyOklzc3VlQ29tbWVudDI5NTk5MzEzMg== | 7799184 | 2017-04-21T00:54:28Z | 2017-04-21T10:05:27Z | CONTRIBUTOR | I realised that some of the Datasets I was trying to concatenate had different coordinate values (for coordinates that I was assuming to be the same) so I guess xr.concat was trying to align these coordinates before concatenating and the resultant Dataset ended up being much larger than it should have been. When I ensure I only concatenate Datasets with consistent coordinates, I can do it. However still resource consumption is quite high compared to when I so the same thing with numpy arrays. The memory increased by 42% using xr.concat (against 6% using np.concatenate) and the whole processing took about 4 times longer. |
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