perf(pagerank): O(V+E) 累加实现替代 O(V²) 全源遍历

旧实现每目标节点遍历全部源节点找边匹配 (943-961):
- 17628 nodes × 20 迭代 = 6.2亿次内层操作 → 单次 PageRank ~3 分钟
- 重启后多套触发器零值连锁 fire full consolidation → CPU 100% 持续 10+ 分钟

新实现先归一化每源节点总权重, 再沿出边把贡献累加到目标 (O(V+E)):
- 17628 nodes PageRank + 图谱维护: 3分钟 → <1 秒
- 重启风暴从 10+ 分钟 CPU 100% → 秒级无感

实测: 01:16:40 图谱维护开始 → 01:16:41 PageRank 更新 17628 nodes 完成

go/internal/governance/graph_sqlite.go

@@ -941,21 +941,26 @@ func (gs *SQLiteGraphStore) PageRank(damping float64, iterations int) map[string
 	}
 
 	for iter := 0; iter < iterations; iter++ {
-		newRanks := make(map[string]float64)
-		for _, node := range nodes {
-			rank := base
-			for src, edges := range outEdges {
-				totalWt := 0.0
-				for _, e := range edges {
-					totalWt += e.weight
-				}
-				for _, e := range edges {
-					if e.target == node && totalWt > 0 {
-						rank += damping * ranks[src] * e.weight / totalWt
-					}
-				}
+		// 正确 PageRank 实现 O(V+E)：先归一化每个源节点总权重，
+		// 再沿出边把贡献直接累加到目标节点（旧实现每目标遍历全源 O(V²)，
+		// 17628 节点 × 20 迭代 = 6.2 亿次 → 3 分钟；现在亚秒级）
+		contrib := make(map[string]float64, len(outEdges))
+		for src, edges := range outEdges {
+			totalWt := 0.0
+			for _, e := range edges {
+				totalWt += e.weight
 			}
-			newRanks[node] = rank
+			if totalWt <= 0 {
+				continue
+			}
+			share := damping * ranks[src] / totalWt
+			for _, e := range edges {
+				contrib[e.target] += share * e.weight
+			}
+		}
+		newRanks := make(map[string]float64, len(nodes))
+		for _, node := range nodes {
+			newRanks[node] = base + contrib[node]
 		}
 		ranks = newRanks
 	}