⚡ Improve performance by using iterators in graph loading

[saurabhsharma2u]

This PR addresses the "Inefficient Data Loading in Analysis" issue by optimizing loadGraphFromSnapshot in @crawlith/core.

Changes:

1. EdgeRepository.ts: Added getEdgesIteratorBySnapshot method.
2. MetricsRepository.ts: Added getMetricsIterator method.
3. graphLoader.ts: Updated loadGraphFromSnapshot to use pageRepo.getPagesIteratorBySnapshot (existing), edgeRepo.getEdgesIteratorBySnapshot, and metricsRepo.getMetricsIterator instead of get*BySnapshot methods that return arrays.

Rationale:
The previous implementation loaded all pages, edges, and metrics into arrays before processing them to build the Graph object. This caused a significant memory spike proportional to the snapshot size. By using iterators (streaming rows from SQLite), we avoid these intermediate allocations.

Verification:

• Benchmark: Created a benchmark with 20,000 pages and edges.
  • Baseline: Time: ~16.8s, Memory Increase: ~65MB
  • Optimized: Time: ~15.1s, Memory Increase: ~61MB
  • Improvement: ~10% faster, ~6% less memory overhead (peak usage reduction is likely higher but harder to measure with process.memoryUsage() alone due to GC).
• Tests: Ran pnpm -C plugins/core test and verified relevant tests pass.

Note on analyze.ts:
The task description pointed to analyze.ts, but investigation showed that analyze.ts was already using getPagesIteratorBySnapshot. The bottleneck was in loadGraphFromSnapshot which is called by analyze.ts (via loadCrawlData). This PR fixes that bottleneck.

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PR created automatically by Jules for task 6089757918901700387 started by @saurabhsharma2u

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