⚡ Bolt: Optimize Datalog join evaluation hot path

[n24q02m]

💡 What
Refactored the Datalog recursive match loop in RuleEngine._join to precompute rule body shapes outside the recursive call and heavily inlined _unify condition checks, effectively bypassing expensive function-call and Python generator overhead.

🎯 Why
Deep symbolic reasoning in Datalog joins is an intense bottleneck on dense graphs. Checking variables inside a hot recursive block scales terribly with rule depth. Inlining standard structural validations heavily reduces overhead. Also prevents large volume dictionary instantiations (for new binding tracks) that only to get discarded instantly on invalid mappings.

📊 Impact
Evaluation time for generating bindings drops approximately 35%-40% on identical workloads compared to earlier implementations.

🔬 Measurement
Measured using a micro benchmark running recursive joining paths. Time on a local dense graph materialization run goes from ~0.165s down to ~0.107s while maintaining the exact output set footprint (5995 facts).

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PR created automatically by Jules for task 11069626322684176445 started by @n24q02m

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