Long codegraph_explore queries are slow on a large index, so the prompt hook times out
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Ya se ha fusionado un pull request relacionado.
- #2804 de @colbymchenry — fusionado
Evaluación
- Dificultad
- 4/5
- Tiempo estimado
- 3-5 días
- Aptitud para principiantes
- 20/100
- Tipo de issue
- Error
- Claridad
- Bien especificado
- Estado de actividad
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- Stack tecnológico
- sqlite, typescript
- Área
- backend, performance
Línea de trabajo
The proposed fix is already available in commit 1d6f44d on the linked branch, and the issue says it was previously #2621. Review findRelevantContext, the searchNodes and getAllNodeNames paths, and scorePathRelevance; start by comparing that commit with main. The payload names __tests__/explore-term-search-cost.test.ts for coverage; done means the optimizations preserve output and ranking while reducing long-query latency.
Escrito por el modelo de indexación a partir del texto del issue.
Descripción
The Claude Code prompt hook times out on long prompts (a pasted log, a skill body): codegraph_explore cost grows with the number of distinct words in the query, and on a large index each word is expensive.
Setup: Linux, v1.6.2 and current main. One index over ~150 Java/Kotlin/TS repos: 19.5k files, 389k nodes, 757k edges, 1.1 GB db.
Cause. findRelevantContext runs searchNodes (FTS, then the LIKE and fuzzy fallbacks) and up to four findNodesByNameSubstring calls per extracted term, with no cap on terms. A 1.7k-char Oracle log gives 132 terms: 1712 SQL calls, 16 s of SQL (v1.6.2, per-statement timing):
| statement | calls | total | per call |
|---|---|---|---|
name LIKE '%x%' (findNodesByNameSubstring) |
294 | 7.3 s | 25 ms |
searchNodesLike (%x% on name/qualified_name) |
78 | 3.4 s | 43 ms |
SELECT DISTINCT name (searchNodesFuzzy → getAllNodeNames) |
63 | 3.2 s | 51 ms |
| getDominantFile aggregation | 1 | 1.1 s | |
| FTS | 236 | 0.6 s | 2.6 ms |
Plus JS: scorePathRelevance re-splits every query word for every scored result (~2.5 s on a 3k-char query).
Fix: commit 1d6f44d on retsamekohC:perf/explore-term-search (was #2621). Output byte-identical to main on all 6 test prompts; __tests__/explore-term-search-cost.test.ts covers the memo invalidation (sync, other connection, rolled-back transaction, rebind) and fuzzy ranking vs a full scan.
- FTS joins
nodeson the TEXTid;nodes_ftsis external-content withcontent_rowid='rowid', so a rowid join gives the same rows 2.5-3x faster. getAllNodeNamesis documented as cached but is not; memoized per change stamp, likegetDominantFile.- Fuzzy fallback only scans names whose length is within
maxDistof the query. scorePathRelevancecaches the per-word split.
codegraph prompt-hook, same index copy, ms:
| prompt | main | main + fix |
|---|---|---|
| short question | 2,540 | 2,390 |
| Oracle log, 1.7k chars | 19,700 | 14,500 |
| markdown, 3k | 46,000 | 31,300 |
| Java source, 3k | 30,300 | 20,600 |
| markdown, 10k | 120,000 | 72,000 |
| Java source, 10k | 69,000 | 42,000 |
Not in the fix, your call:
- The LIKE scans dominate what is left. An in-memory index of distinct lowercased names (one
\n-joined string,indexOfper term, ASCII-only case folding to match SQLite LIKE) answersfindNodesByNameSubstringin ~2 ms instead of 25 ms with identical rows;qualified_namecan be matched on its alphanumeric segments, since a[a-z0-9]term cannot span a separator. Needs invalidation in the long-lived server (the same change stamp would do). With this, a per-processgetDominantFilecache on disk, and the PR's changes, v1.6.2 runs the prompts above in 5.5 / 6.7 / 7.0 / 13.4 / 12.9 s. I run this as a--requirepreload for the hook; happy to turn it into a PR if you want the approach. - prompt-hook is a new process per prompt, so the
getDominantFilememo never hits there: ~1 s on every prompt on this index. codegraph_explorerejects queries over 10,000 chars, and prompt-hook passes the whole prompt, so a longer prompt silently gets nothing. Truncating in prompt-hook would keep the beginning.- Unrelated, noticed on the way: the dominant file of this index is a vendored
moment-with-locales.js, so the core-directory boost favors a third-party library.
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