Improve architecture, performance, testability of Library management #2207

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OVERLORD · 2026-02-06T21:51:11+03:00

OVERLORD commented

2026-02-06 21:51:11 +03:00

Originally created by @xaviergxf on GitHub (Oct 22, 2020).

I was looking at the source code of library management and i believe lots of improvements could be done. I would like to open a discussion about improvements. Here are some suggestions:

Lots of static methods, that are hard to test, shouldn't we use di for that? Ex: SeriesResolver.IsSeriesFolder
Lots of classes without interfaces, they cannot be easily mocked. Ex: EpisodePathParser
Some classes are huge. Ex: Library Manager
Use of dependency injection instead of instantiating classes. Ex: EpisodeResolver
Use more composition and less inheritance.
Improve performance of regex using .net5, span, compiled regex, etc.
More use of async.
Do we still need IFileSystem abstraction?

Do anyone have other suggestions? I believe this is a complete redo of what exists currently.

Originally created by @xaviergxf on GitHub (Oct 22, 2020). I was looking at the source code of library management and i believe lots of improvements could be done. I would like to open a discussion about improvements. Here are some suggestions: - Lots of static methods, that are hard to test, shouldn't we use di for that? Ex: SeriesResolver.IsSeriesFolder - Lots of classes without interfaces, they cannot be easily mocked. Ex: EpisodePathParser - Some classes are huge. Ex: Library Manager - Use of dependency injection instead of instantiating classes. Ex: EpisodeResolver - Use more composition and less inheritance. - Improve performance of regex using .net5, span, compiled regex, etc. - More use of async. - Do we still need IFileSystem abstraction? Do anyone have other suggestions? I believe this is a complete redo of what exists currently.

OVERLORD closed this issue

2026-02-06 21:51:12 +03:00

OVERLORD commented

2026-02-06 21:51:14 +03:00

@Motophan commented on GitHub (Nov 10, 2020):

I have a 100TB library on zfs w/ a cache system. I can read and write to the array at 1.2GBps (bytes) after my cache device is fatigued (out of L2ARC and ARC). My library scans take ~ 12 hours and fail >50% of the time. Library scans are significantly slower with more users. Example: you can scan my 100TB library in a fresh jellyfin container w/ 1 user (after initial scan) in about 10 minutes. With 120 users this balloons into 4 hours and increases from there.

I think we should focus on what makes the library scan slow w/ lots of users and lots of watch time first as this seems to have the most dramatic performance increase.

If there is any way I can give you telemetry data about this please let me know. My jellyfin server is very active.

@Motophan commented on GitHub (Nov 10, 2020): I have a 100TB library on zfs w/ a cache system. I can read and write to the array at 1.2GBps (bytes) after my cache device is fatigued (out of L2ARC and ARC). My library scans take ~ 12 hours and fail >50% of the time. Library scans are significantly slower with more users. Example: you can scan my 100TB library in a fresh jellyfin container w/ 1 user (after initial scan) in about 10 minutes. With 120 users this balloons into 4 hours and increases from there. I think we should focus on what makes the library scan slow w/ lots of users and lots of watch time first as this seems to have the most dramatic performance increase. If there is any way I can give you telemetry data about this please let me know. My jellyfin server is very active.

OVERLORD commented

2026-02-06 21:51:15 +03:00

@cvium commented on GitHub (Nov 10, 2020):

@Motophan That's not really relevant to the OP. It's also a known problem and fixed in unstable (future 10.7): https://github.com/jellyfin/jellyfin/issues/4364

@cvium commented on GitHub (Nov 10, 2020): @Motophan That's not really relevant to the OP. It's also a known problem and fixed in unstable (future 10.7): https://github.com/jellyfin/jellyfin/issues/4364

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