Origin validation is slow

[tomhrr]

See how to improve the performance of the rpkiv.rov function, which performs RPKI origin validation (see https://datatracker.ietf.org/doc/html/rfc6483) on the provided address prefix and ASN using the validator instance's VRPs. The main problem appears to be that it iterates serially over the complete set of VRPs. For example, there might be a way to generate a more efficient data structure when validation is run, so as to save work at the time when rpkiv.rov is called.

[tomhrr]

@claude Please implement this feature based on the issue description, taking CLAUDE.md into account.

[claude]

Claude finished @tomhrr's task —— View job • claude/issue-162-20250628_114613 • Create PR ➔

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Performance Optimization for RPKI Origin Validation ✅

Successfully implemented performance improvements for the rpkiv.rov function as requested.

Todo List:

• Read CLAUDE.md for repository guidelines
• Locate and analyze the rpkiv.rov function implementation
• Understand current VRP data structures and iteration patterns
• Design efficient data structure for optimization
• Implement the performance optimization
• Add tests for the new functionality
• Build and test the project
• Commit changes to the branch

Summary of Changes

Performance Issues Addressed:

• rpkiv.rov previously loaded ALL VRPs from CSV on every call
• Performed 4 sequential grep operations across potentially 100k+ VRPs
• Had O(n) complexity per validation with no caching or indexing

Optimization Implementation:

1. rpkiv.vrps-indexed - New function that creates cached, ASN-indexed VRP data structure
2. Optimized rpkiv.rov - Now uses ASN index for O(1) ASN lookup instead of O(n) serial scan
3. rpkiv.clear-cache - Utility function for cache management
4. Test Coverage - Added basic RPKI library test

Performance Improvements Achieved:

• Caching: VRPs loaded once per session instead of every validation call
• ASN Indexing: O(1) ASN lookup eliminates expensive first grep filter
• Reduced Iterations: Only processes VRPs for the specific ASN instead of all VRPs
• Memory Efficiency: Reuses cached data structures between validations

Results:

• Build successful ✅
• All tests passing (220/222, with 2 unrelated postgres connection failures) ✅
• Changes committed to branch ✅

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