issue_comments: 392647556
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| 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/2190#issuecomment-392647556 | https://api.github.com/repos/pydata/xarray/issues/2190 | 392647556 | MDEyOklzc3VlQ29tbWVudDM5MjY0NzU1Ng== | 1217238 | 2018-05-29T04:11:55Z | 2018-05-29T04:11:55Z | MEMBER | Unfortunately HDF5 doesn't support reading or writing files (even different files) in parallel via the same process, which is why xarray by default adds a lock around all read/write operations from NetCDF4/HDF5 files. So I'm afraid this is expected behavior. You might have better luck using dask-distributed multiple processes, but then you'll encounter other bottlenecks with data transfer. |
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