issue_comments: 286212647
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/1301#issuecomment-286212647 | https://api.github.com/repos/pydata/xarray/issues/1301 | 286212647 | MDEyOklzc3VlQ29tbWVudDI4NjIxMjY0Nw== | 1360241 | 2017-03-13T19:12:13Z | 2017-03-13T19:12:13Z | NONE | Data: Five files that are approximately 450 MB each. venv1 dask 0.13.0 py27_0 conda-forge xarray 0.8.2 py27_0 conda-forge 1.51642394066 seconds to load using open_mfdataset venv2: dask 0.13.0 py27_0 conda-forge xarray 0.9.1 py27_0 conda-forge 279.011202097 seconds to load using open_mfdataset I ran the same code in the OP on two conda envs with the same version of dask but two different versions of xarray. There was a significant difference in load time between the two conda envs. I've posted the data on my work site if anyone wants to double check: https://marine.rutgers.edu/~michaesm/netcdf/data/ |
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