Performance issue while reading the data with FLAC file format via HTTP.

I tested the performance of wfdb python library for reading waveforms via HTTP.

• mimic3wdb

dtstart = datetime.datetime.now()
wfdb.rdsamp('3000003', pn_dir='mimic3wdb/1.0/30/3000003')
print(datetime.datetime.now() - dtstart)
# results 0:00:21.143365

• mitdb

dtstart = datetime.datetime.now()
wfdb.rdsamp('100', pn_dir='mitdb/1.0.0')
print(datetime.datetime.now() - dtstart)
# results 0:00:02.764091

It looks great. However, when I tried to read the mimic4wdb which has FLAC format, there was a significant performance decrease.

• mimic4wdb

dtstart = datetime.datetime.now()
wfdb.rdsamp('81739927', pn_dir='mimic4wdb/0.1.0/waves/p100/p10014354/81739927')
print(datetime.datetime.now() - dtstart)
# results 0:07:26.220685

This issue was resolved when I cached files with the buffering = -2 for openurl function in _url.py.
-> results 0:00:37.388115

After digging a bit more, I figured out that this problem is caused by repeatedly calling read function frame by frame in the _cdata_io function in soundfile.py. Whenever the read function is called, session.request in _url.py is called and HTTP communication is established. This can cause significant performance problem and also make stress to the web server.

So it seems a good idea to change buffering=-2 to default until this is fixed. Reducing the number of requests is much more efficient in both improving the performance and reducing the load of the web server.

Reproduisez les exemples de mesure du temps fournis pour wfdb.rdsamp avec mimic3wdb, mitdb et mimic4wdb. Examinez ensuite _url.py et le chemin _cdata_io dans soundfile.py, en vous concentrant sur les appels de lecture répétés et le comportement de buffering=-2. Le travail est terminé lorsque le cas FLAC-over-HTTP évite les communications HTTP inutiles et présente une amélioration du temps d’exécution sans augmenter le nombre de requêtes au serveur.