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- open_mfdataset() significantly slower on 0.9.1 vs. 0.8.2 · 2 ✖
| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 291512017 | https://github.com/pydata/xarray/issues/1301#issuecomment-291512017 | https://api.github.com/repos/pydata/xarray/issues/1301 | MDEyOklzc3VlQ29tbWVudDI5MTUxMjAxNw== | najascutellatus 1360241 | 2017-04-04T14:11:08Z | 2017-04-04T14:11:08Z | NONE | @rabernat This data is computed on demand from the OOI (http://oceanobservatories.org/cyberinfrastructure-technology/). Datasets can be massive and so they seem to be split up in ~500 MB files when data gets too big. That is why obs changes for each file. Would having obs be consistent across all files potentially make open_mfdataset faster? |
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open_mfdataset() significantly slower on 0.9.1 vs. 0.8.2 212561278 | |
| 286212647 | https://github.com/pydata/xarray/issues/1301#issuecomment-286212647 | https://api.github.com/repos/pydata/xarray/issues/1301 | MDEyOklzc3VlQ29tbWVudDI4NjIxMjY0Nw== | najascutellatus 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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open_mfdataset() significantly slower on 0.9.1 vs. 0.8.2 212561278 |
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