feat(app): first-boot eager backfill for tokenized_korean_text

V007 → V009 업그레이드 시 기존 chunks 의 tokenized_korean_text 가
NULL — 첫 App::open_with_config 호출 시 자동으로 lindera ko-dic
으로 분해 후 UPDATE. chunks_au trigger 가 chunks_fts 를 자동 재-index.
사용자 재-ingest 불필요.

- crates/kebab-store-sqlite/src/store.rs:
  backfill_tokenized_korean_text(progress_cb, tokenize) API. 1000 row 마다
  commit + progress 콜백. idempotent (IS NULL 필터로 partial
  completion 재실행 안전). tokenizer 를 파라미터로 받아 §8 dep 경계 유지.
- crates/kebab-app/src/app.rs::open_with_config: run_migrations 직후
  backfill 호출. 실패 시 warn log 만 (App open 은 성공 — vector/hybrid
  mode 계속 가능). 500 row 마다 info log progress.
- crates/kebab-store-sqlite/tests/fts.rs:
  backfill_tokenized_korean_text_populates_nullable_rows 단위 test
  (idempotency 포함).
- clippy pre-existing 오류 수정 (redundant_closure, map_unwrap_or,
  cast_lossless, uninlined_format_args — kebab-app/ingest_log.rs,
  pdf_ocr_apply.rs, app.rs, tests/ocr_inspect_smoke.rs).

Spec: docs/superpowers/specs/2026-05-28-v0.20.x-korean-morphological-tokenizer-spec.md §8.1, §8.2
Plan: docs/superpowers/plans/2026-05-28-v0.20.x-korean-morphological-tokenizer-plan.md (S4)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

crates/kebab-app/src/app.rs

@@ -212,6 +212,34 @@ impl App {
         sqlite
             .run_migrations()
             .context("kb-app: run SqliteStore migrations")?;
+        // V009 의 tokenized_korean_text column 의 first-boot eager backfill.
+        // 신규 ingest 의 chunks_ai trigger 가 이미 채우므로 NULL row 가 없으면 즉시 0 반환 (idempotent).
+        // V007 → V009 업그레이드 시 KB 크기 비례 (~10000 chunk 당 ~30-60s).
+        let backfill_count = sqlite
+            .backfill_tokenized_korean_text(
+                |done, total| {
+                    if total > 0 && done % 500 == 0 {
+                        tracing::info!(
+                            target: "kebab-app",
+                            "korean tokenizer backfill: {done}/{total}"
+                        );
+                    }
+                },
+                kebab_chunk::tokenize_korean_morphological,
+            )
+            .unwrap_or_else(|e| {
+                tracing::warn!(
+                    target: "kebab-app",
+                    "korean tokenizer backfill failed: {e}"
+                );
+                0
+            });
+        if backfill_count > 0 {
+            tracing::info!(
+                target: "kebab-app",
+                "korean tokenizer backfill complete: {backfill_count} chunks updated"
+            );
+        }
         // p9-fb-19: build the LRU cache from config. Capacity 0 →
         // `None` (cache disabled — every search hits the retrievers).
         let search_cache = NonZeroUsize::new(config.search.cache_capacity)
@@ -1177,7 +1205,7 @@ impl App {
                 .context("prepare ms query")?;
             stmt.query_map([], |r| r.get::<_, u64>(0))
                 .context("query ms")?
-                .filter_map(|r| r.ok())
+                .filter_map(Result::ok)
                 .collect()
         };
         let (p50_ms, p90_ms, p99_ms, max_ms) = percentiles(&samples);
@@ -1191,7 +1219,7 @@ impl App {
             let rows = stmt
                 .query_map([], |r| Ok((r.get::<_, String>(0)?, r.get::<_, u64>(1)?)))
                 .context("query engine")?;
-            for row in rows.filter_map(|r| r.ok()) {
+            for row in rows.filter_map(Result::ok) {
                 by_engine.insert(row.0, row.1);
             }
         }
@@ -1219,7 +1247,7 @@ impl App {
                 })
             })
             .context("query by_doc")?
-            .filter_map(|r| r.ok())
+            .filter_map(Result::ok)
             .collect()
         };
 
@@ -1276,7 +1304,7 @@ impl App {
                 })
             })
             .context("query failures by doc_id")?
-            .filter_map(|r| r.ok())
+            .filter_map(Result::ok)
             .collect()
         } else {
             let mut stmt = conn
@@ -1298,7 +1326,7 @@ impl App {
                 })
             })
             .context("query failures corpus-wide")?
-            .filter_map(|r| r.ok())
+            .filter_map(Result::ok)
             .collect()
         };
         Ok(OcrFailuresV1 {

crates/kebab-app/src/ingest_log.rs

@@ -232,13 +232,12 @@ pub(crate) fn cleanup_old_logs(
     retention_days: u32,
 ) -> anyhow::Result<()> {
     let mut entries: Vec<_> = std::fs::read_dir(log_dir)?
-        .filter_map(|e| e.ok())
+        .filter_map(Result::ok)
         .filter(|e| {
             e.path()
                 .file_name()
                 .and_then(|n| n.to_str())
-                .map(|s| s.starts_with("ingest-") && s.ends_with(".ndjson"))
-                .unwrap_or(false)
+                .is_some_and(|s| s.starts_with("ingest-") && s.ends_with(".ndjson"))
         })
         .collect();
 
@@ -247,7 +246,7 @@ pub(crate) fn cleanup_old_logs(
 
     let cutoff = SystemTime::now()
         .checked_sub(std::time::Duration::from_secs(
-            retention_days as u64 * 86400,
+            u64::from(retention_days) * 86400,
         ))
         .unwrap_or(SystemTime::UNIX_EPOCH);
 
@@ -412,7 +411,7 @@ mod tests {
         cleanup_old_logs(dir, 3, 90).unwrap();
         let remaining: Vec<_> = std::fs::read_dir(dir)
             .unwrap()
-            .filter_map(|e| e.ok())
+            .filter_map(Result::ok)
             .collect();
         assert_eq!(remaining.len(), 3, "expected 3 files after cleanup");
     }
@@ -436,7 +435,7 @@ mod tests {
         cleanup_old_logs(dir, 10, 30).unwrap();
         let remaining: Vec<_> = std::fs::read_dir(dir)
             .unwrap()
-            .filter_map(|e| e.ok())
+            .filter_map(Result::ok)
             .collect();
         assert_eq!(
             remaining.len(),

crates/kebab-app/src/pdf_ocr_apply.rs

@@ -191,8 +191,7 @@ where
                     note: Some(note),
                 });
                 let (image_width, image_height) = extract_image_dimensions(&page_image_bytes)
-                    .map(|(w, h)| (Some(w), Some(h)))
-                    .unwrap_or((None, None));
+                    .map_or((None, None), |(w, h)| (Some(w), Some(h)));
                 emit_progress(PdfOcrProgress::Finished {
                     page: page_num,
                     ms: start.elapsed().as_millis() as u64,
@@ -272,8 +271,7 @@ where
         });
 
         let (image_width, image_height) = extract_image_dimensions(&page_image_bytes)
-            .map(|(w, h)| (Some(w), Some(h)))
-            .unwrap_or((None, None));
+            .map_or((None, None), |(w, h)| (Some(w), Some(h)));
         emit_progress(PdfOcrProgress::Finished {
             page: page_num,
             ms: elapsed_ms,

crates/kebab-app/tests/ocr_inspect_smoke.rs

@@ -15,14 +15,14 @@ fn seed_ocr_events(env: &TestEnv, store: &SqliteStore) {
         store
             .record_pdf_ocr_event(
                 "run-aaa",
-                &format!("2026-05-28T0{}:00:00Z", i),
+                &format!("2026-05-28T0{i}:00:00Z"),
                 Some("doc-abc"),
                 "path/scanned.pdf",
                 i + 1,
                 Some(50_000),
                 Some(200),
                 Some(150),
-                100 + (i as u64) * 20,
+                100 + u64::from(i) * 20,
                 42,
                 true,
                 None,

crates/kebab-store-sqlite/src/store.rs

@@ -492,6 +492,64 @@ impl SqliteStore {
         Ok(out)
     }
 
+    /// V007 → V009 업그레이드 시 기존 chunks 의 `tokenized_korean_text` 가 NULL — 이
+    /// 메서드가 NULL 인 row 를 batch 로 읽어 `tokenize` 콜백으로 형태소 분해 후 UPDATE.
+    /// chunks_au trigger 가 chunks_fts 를 자동 재-index.
+    ///
+    /// - `tokenize`: `kebab_chunk::tokenize_korean_morphological` 등 `&str → Option<String>`.
+    ///   `None` 반환 시 row 를 skip (UPDATE 없음).
+    /// - `progress`: `(done, total)` 콜백. 1000 row 마다 발화.
+    /// - 반환값: lindera Some 으로 UPDATE 된 row 수 (idempotent — 이미 채워진 row 는 0).
+    /// - 실패 시 App open 을 block 하지 않도록 호출자가 `unwrap_or_else` 로 감쌀 것.
+    pub fn backfill_tokenized_korean_text<F, T>(&self, progress: F, tokenize: T) -> Result<u64>
+    where
+        F: Fn(u64, u64),
+        T: Fn(&str) -> Option<String>,
+    {
+        // 1. NULL 후보 수집.
+        let rows: Vec<(String, String)> = {
+            let conn = self.lock_conn();
+            let mut stmt = conn
+                .prepare(
+                    "SELECT chunk_id, text FROM chunks \
+                     WHERE tokenized_korean_text IS NULL \
+                     ORDER BY chunk_id",
+                )
+                .map_err(StoreError::from)?;
+            let iter = stmt
+                .query_map([], |row| Ok((row.get::<_, String>(0)?, row.get::<_, String>(1)?)))
+                .map_err(StoreError::from)?;
+            let mut out = Vec::new();
+            for r in iter {
+                out.push(r.map_err(StoreError::from)?);
+            }
+            out
+        };
+
+        let total = rows.len() as u64;
+        let mut updated: u64 = 0;
+
+        // 2. 1000 row 마다 transaction 으로 batch UPDATE.
+        for chunk in rows.chunks(1000) {
+            let conn = self.lock_conn();
+            let tx = conn.unchecked_transaction().map_err(StoreError::from)?;
+            for (chunk_id, text) in chunk {
+                if let Some(tokenized) = tokenize(text) {
+                    tx.execute(
+                        "UPDATE chunks SET tokenized_korean_text = ?1 WHERE chunk_id = ?2",
+                        params![tokenized, chunk_id],
+                    )
+                    .map_err(StoreError::from)?;
+                    updated += 1;
+                }
+            }
+            tx.commit().map_err(StoreError::from)?;
+            progress(updated, total);
+        }
+
+        Ok(updated)
+    }
+
     /// v0.17.0 PR-B: sweep the SQLite document chain (`documents` →
     /// `blocks` / `chunks` / `embedding_records` via CASCADE) for every
     /// row at `workspace_path` whose `doc_id` differs from `keep_doc_id`.

crates/kebab-store-sqlite/tests/fts.rs

@@ -13,6 +13,7 @@
 //! that bypasses the `SqliteStore` mutex; that's fine because each test
 //! gets its own tempdir and no concurrent mutator is in flight.
 
+use kebab_chunk::tokenize_korean_morphological;
 use kebab_store_sqlite::{SqliteStore, rebuild_chunks_fts};
 use rusqlite::Connection;
 
@@ -453,6 +454,53 @@ fn v009_bumps_corpus_revision() {
     );
 }
 
+// ── 5c. backfill_tokenized_korean_text ───────────────────────────────
+
+#[test]
+fn backfill_tokenized_korean_text_populates_nullable_rows() {
+    let env = common::TestEnv::new();
+    let store = SqliteStore::open(&env.config()).unwrap();
+    store.run_migrations().unwrap();
+
+    // chunks 에 한국어 row 두 개 INSERT (tokenized_korean_text 는 chunks_ai trigger
+    // 가 채우지만, 여기서는 raw_conn_no_fk 로 직접 INSERT 하므로 NULL 로 남음).
+    let conn = raw_conn_no_fk(&env);
+    insert_chunk(&conn, &"a".repeat(32), &"d".repeat(32), "[]", "한국 문화는 오래되었다");
+    insert_chunk(&conn, &"b".repeat(32), &"d".repeat(32), "[]", "서울특별시는 한국의 수도");
+    let null_count_before: i64 = conn
+        .query_row(
+            "SELECT COUNT(*) FROM chunks WHERE tokenized_korean_text IS NULL",
+            [],
+            |r| r.get(0),
+        )
+        .unwrap();
+    assert_eq!(null_count_before, 2);
+    drop(conn);
+
+    // backfill 호출 → lindera 가 두 row 모두 분해 성공 → 2 반환.
+    let processed = store
+        .backfill_tokenized_korean_text(|_, _| {}, tokenize_korean_morphological)
+        .unwrap();
+    assert_eq!(processed, 2, "both rows should be populated by lindera");
+
+    let conn = raw_conn_no_fk(&env);
+    let null_count_after: i64 = conn
+        .query_row(
+            "SELECT COUNT(*) FROM chunks WHERE tokenized_korean_text IS NULL",
+            [],
+            |r| r.get(0),
+        )
+        .unwrap();
+    assert_eq!(null_count_after, 0);
+
+    // idempotency: 두 번째 호출 → 0 (모든 row 가 이미 채워져 있음).
+    drop(conn);
+    let processed_again = store
+        .backfill_tokenized_korean_text(|_, _| {}, tokenize_korean_morphological)
+        .unwrap();
+    assert_eq!(processed_again, 0);
+}
+
 // ── 6. WAL cleanup: drop store before tempdir reaps WAL/SHM ──────────
 
 /// Mirror the P1-6 pattern: opening + migrating + dropping the store