주제: search

• ripgrep의 기본 필터링은 grep -r보다 에이전트의 코드 검색을 짧게 만든다

  가설: ripgrep의 기본 무시 규칙(git에서 무시된 파일, 숨김 파일, 바이너리 파일을 건너뜀)으로 저장소를 검색하는 코딩 에이전트는, 제외 설정 없이 grep -r을 쓰는 에이전트보다 작업당 검색 호출 수가 적고 무관한 출력을 덜 읽습니다. 빌드 산출물과 의존성 안에서의 히트가 애초에 나타나지 않기 때문입니다. 실측 결과는 보고되어 있지 않습니다.

  hypothesis · ko · reviewed · 지식 기준일 2026-09-16

• PostgreSQL에서 tsvector로 전문 검색(full-text search) 구현하기

  PostgreSQL은 언어 설정(configuration)을 이용해 텍스트를 정규화된 렉심(lexeme)의 tsvector로 변환하고, 이를 tsquery와 매칭하며, ts_rank로 순위를 매기고, GIN으로 색인합니다. 어간 추출(stemming)과 불용어 처리는 기본으로 지원하지만, 오타나 동의어는 기본 기능만으로는 처리하지 못합니다.

  article · ko · reviewed · 지식 기준일 2026-09-15

• grep and ripgrep for code search: recursion, filters and exit codes

  GNU grep searches recursively with -r, narrows with --include and --exclude-dir and exits 0, 1 or 2 for match, no match or error; ripgrep does the same by default while skipping git-ignored, hidden and binary files. Know what each tool skips before trusting an empty result.

  article · en · reviewed · 지식 기준일 2026-09-16

• Document search over a corpus walk-through: indexing pipeline, permissions and reindexing

  A design walk-through for search over documents held in a system of record: a derived, rebuildable index fed by change events, ACL keys indexed as fields so filtering happens before ranking, versioned indexes switched by alias, a reconciler that finds drift, and a list of what to defer.

  methodology · en · reviewed · 지식 기준일 2026-09-17

• Tries for prefix lookups: autocomplete and longest-prefix matching

  A trie stores strings with one node per common prefix, so lookup costs the key length regardless of how many keys exist, all keys with a prefix form one subtree, and the longest stored prefix of a query is found in one walk; use it for autocomplete and routing, and compare against a sorted array first.

  article · en · reviewed · 지식 기준일 2026-09-16

• Embeddings as a data type: fixed-length vectors, a distance function and what a column of them needs

  An embedding is a fixed-length float vector produced by a specific model, meaningful only under the distance that model was trained for and only next to vectors from the same model version; storing it requires the dimension, the model identifier and the distance to be recorded, and querying it means nearest-neighbour search, exact or approximate.

  article · en · reviewed · 지식 기준일 2026-09-17

• Retrieval basics for LLM applications: chunking, passage identifiers and citing what was retrieved

  Retrieval-augmented generation feeds retrieved passages to the model; the decisions that matter are how documents are split, what context each chunk carries, and how the answer points back to a specific passage so that a reader can check it.

  article · en · reviewed · 지식 기준일 2026-09-15

기계 판독 가능: JSON