issues: 427410885

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
427410885 MDU6SXNzdWU0Mjc0MTA4ODU= 2857 Quadratic slowdown when saving multiple datasets to the same h5 file (h5netcdf) 2418513 closed 0     24 2019-03-31T15:47:40Z 2022-01-12T07:19:06Z 2022-01-12T07:19:06Z NONE      

I can't quite understand what's wrong with my side of the code, wondering if this kind of slowdown is expected or not?

Basically, what I'm doing is something like this:

python with h5py.File('file.h5', 'w') as f: f.flush() # reset the file for i, ds in enumerate(datasets): ds.to_netcdf('file.h5', group=str(i), engine='h5netcdf', mode='a')

And here's the log for saving 20 datasets, the listed times are for each dataset independently. Instead of the expected 10 sec (which is already kind of slow, but whatever), I get 2 minutes. The time to save each dataset seems to increase linearly, which leads to a quadratic overall slowdown:

``` saving dataset... 00:00:00.559135 saving dataset... 00:00:00.924617 saving dataset... 00:00:01.351670 saving dataset... 00:00:01.818111 saving dataset... 00:00:02.356307 saving dataset... 00:00:02.971077 saving dataset... 00:00:03.685565 saving dataset... 00:00:04.375104 saving dataset... 00:00:04.575837 saving dataset... 00:00:05.179975 saving dataset... 00:00:05.793876 saving dataset... 00:00:06.517916 saving dataset... 00:00:07.190257 saving dataset... 00:00:07.993795 saving dataset... 00:00:08.786421 saving dataset... 00:00:09.414821 saving dataset... 00:00:10.729006 saving dataset... 00:00:11.584044 saving dataset... 00:00:14.160655 saving dataset... 00:00:14.460564

CPU times: user 1min 49s, sys: 12.8 s, total: 2min 2s Wall time: 2min 4s ```

 
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