Improve performance of transcode&prepare tasks
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 35/100
Research direction
Start by locating the transcode and prepare task implementations and the current one-segment-at-a-time loop. Measure the existing throughput, then investigate Go concurrency limits and how parallel work could affect broadcasters, orchestrators, and Bs. Done means transcoding is faster without reducing infrastructure reliability, but the acceptable parallelism value is not specified.
Written by the indexing model from the issue text.
Description
These tasks are unreasonably slow right now, probably because they transcode 1 segment at a time and our transcoding latency is not so much better than realtime (for a 4k video, I transcoded 10 minutes in 8 minutes).
We can improve this by parallelizing the transcoding process. This can be done easily by using go's concurrency abstractions. The only more complex part here is defining how much we're parallelizing without affecting the reliability of the transcoding infrastructure like the broadcaster, orchestrators, etc. The Bs might try to use the same O concurrently, which may not work well if we parallelize it in 5x or sth like that.
So the implementation here could be easy if it is just transcoding N segments at once or something like that, but picking the right value for N can be a complex task.
- Dominant language
- Go
- Stars
- 3
- Forks
- 1
- PR merge metrics
- No merged PRs in 30d
Getting set up
- Ships a Dockerfile or Docker Compose file
- No pull request template
- No contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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