H-uru / H-uru/korman

Option to export read-optimized PRP files

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enhancement
Dominant language
Python
Stars
35
Forks
17
PR merge metrics
No merged PRs in 30d

Description

(I realize the implementation of this would probably need to happen in libHSPlasma, but it makes sense to discuss it - at least as an initial feature request concept - in the context of Korman)

In the H-uru/Plasma repo, there is a plPageOptimizer tool that sorts the object data (but not the keyring!) in the PRP file based on the expected order in which data will need to be loaded. This prevents the ResManager from needing to seek all over the file when reading and reffing objects.

It appears that content for the MOULa server is optimized by this tool as part of putting it on the file server, but that causes differences (in order but not content) between the exported files and the server-delivered files. One option would be to remember to run plPageOptimizer over all the content before committing it to git repositories, but that would be an extra manual step that people would definitely forget to do.

A better option might be for korman to always export PRP files that have already been optimized. I suspect (based on plPageOptimizer being its own tool and not built-in to the PlasmaMax plugin) that this would have to be done as an extra step at the end of the export process, but I don't think there's any reason libHSPlasma couldn't implement the same object sorting method.

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First steps

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  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reading the linked Sources/Tools/plPageOptimizer/plPageOptimizer.cpp in the H-uru/Plasma repository, then trace Korman's export entry point and the libHSPlasma boundary. Clarify where PRP output is finalized and how the keyring is handled. Done means exported PRP files use the read-optimized object ordering without requiring a separate manual step.

Written by the indexing model from the issue text.

Assessment

Tech stack
cpp, python
Domain
game-dev, tooling
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
30/100

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