⚡ Bolt: Optimize search filter by avoiding array allocations and flatMap

.jules/bolt.md

@@ -60,3 +60,6 @@ Optimized metric route processing to O(N) by creating a mapping of routes direct
 ## 2026-06-25 - Avoid Map allocations in frontend ERD loops and mutate asyncpg records in-place
 **Learning:** The frontend `snapshotToGraph` iterates over thousands of columns to generate the graph, so repeated lookups and redundant collection assignments increase GC pressure. Backend snapshot column dictionaries are freshly instantiated for the payload, so `add_column_examples` can safely fill missing fields in place.
 **Action:** Reuse existing collections while aggregating relational data, create `Map`/`Set` entries only on first use, and check for missing example fields before calling expensive inference helpers.
+## 2026-06-25 - Avoid array allocation and .flatMap() in frontend string searches
+**Learning:** Using `.flatMap(...)` to collect fields across objects and then `.join(" ")` on them creates excessive array memory allocations, drastically degrading React rendering performance when iterating over many nodes during user typing or node rendering updates.
+**Action:** Always short-circuit using explicit `for` loops and test properties sequentially, using `continue` or `break` upon finding a match rather than allocating and joining strings in hot loops.

frontend/src/App.tsx

@@ -182,19 +182,23 @@ export default function App() {
     if (!normalizedNodeSearch) return new Set<string>();
     const matches = new Set<string>();
     for (const node of nodes) {
-      const haystack = [
-        node.data.title,
-        node.data.comment ?? "",
-        ...node.data.columns.flatMap((column) => [
-          column.column_name,
-          column.data_type,
-          column.column_comment ?? "",
-        ]),
-      ]
-        .join(" ")
-        .toLocaleLowerCase();
-      if (haystack.includes(normalizedNodeSearch)) {
+      if (node.data.title.toLocaleLowerCase().includes(normalizedNodeSearch)) {
         matches.add(node.id);
+        continue;
+      }
+      if (node.data.comment?.toLocaleLowerCase().includes(normalizedNodeSearch)) {
+        matches.add(node.id);
+        continue;
+      }
+      for (const column of node.data.columns) {
+        if (
+          column.column_name.toLocaleLowerCase().includes(normalizedNodeSearch) ||
+          column.data_type.toLocaleLowerCase().includes(normalizedNodeSearch) ||
+          column.column_comment?.toLocaleLowerCase().includes(normalizedNodeSearch)
+        ) {
+          matches.add(node.id);
+          break;
+        }
       }
     }
     return matches;