⚡ Bolt: [performance improvement] optimize jaccard similarity

[garridolecca]

• 💡 What: Replaced intermediate Set and Array allocations ([...a], new Set()) in jaccardSimilarity with O(1) manual iteration and mathematically derived union size.
• 🎯 Why: jaccardSimilarity is called inside the O(N^2) news clustering inner loop (clusterNewsCore). The previous implementation created hidden intermediate arrays and sets, resulting in high GC overhead when called millions of times.
• 📊 Impact: Reduces GC pauses and speeds up the inner clustering loop by avoiding O(N) memory allocations per comparison. Memory complexity of jaccardSimilarity goes from O(N) to O(1).
• 🔬 Measurement: Tested using npm run typecheck, npm run lint:md, and npm run test:data successfully to verify correctness. Profile news clustering to observe reduced GC pressure.

(Note: The request to make everything based on ArcGIS JavaScript API was rejected because making architectural changes is against Bolt's boundaries.)

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PR created automatically by Jules for task 11213147864841540284 started by @garridolecca

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