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Query ADT (Term|And|Or|Not|Phrase) and evalQuery over docid-sorted posting lists: boolean ops as linear merges, Not over the allDocs universe, Phrase via positional adjacency. Batched both test suites into one program eval each (search-batch) so they finish under heavy CPU load. 46/46. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
130 lines
6.5 KiB
Markdown
130 lines
6.5 KiB
Markdown
# search-on-sx: Full-text + structured search on Haskell
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rose-ash needs search across pages, posts, threads, federated content. Tokenize,
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index, query, rank, filter by visibility. Typed ADTs make query parsing clean,
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lazy lists make posting-list iteration efficient, and Haskell-on-SX is at 1514/1514.
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End-state: a Haskell-on-SX layer with inverted index, query AST, boolean +
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phrase + ranked queries (TF-IDF, BM25), ACL-aware post-filter, and a federation
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extension that merges per-peer indices.
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## Status (rolling)
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`bash lib/search/conformance.sh` → **18/18** (Phase 1 complete)
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## Ground rules
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- **Scope:** only touch `lib/search/**` and `plans/search-on-sx.md`. Do **not** edit
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`spec/`, `hosts/`, `shared/`, `lib/haskell/**`, or other `lib/<lang>/`. You may
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**import** from `lib/haskell/` (public API in `lib/haskell/haskell.sx`); do **not**
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modify Haskell.
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- **Shared-file issues** go under "Blockers" with a minimal repro; do not fix here.
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- **SX files:** use `sx-tree` MCP tools only.
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- **Architecture:** index = `Map Term [(DocId, [Pos])]`. Query AST = ADT. Eval =
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fold of posting lists with set ops + ranking math. Ranking is pure (no IO until
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result emission).
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- **Commits:** one feature per commit. Keep Progress log updated and tick boxes.
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## Architecture sketch
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```
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Document Query
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{:id :text :tags} "alice AND bob OR phrase \"x y\""
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│ │
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▼ ▼
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lib/search/tokenize.sx lib/search/parse.sx
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— tokenize :: Text → [Term] — parse :: Text → Query
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— normalize (lowercase, strip) — Query = Term | And | Or
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— (optionally) stem | Not | Phrase
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│ │
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▼ ▼
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lib/search/index.sx lib/search/eval.sx
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— Map Term [(DocId, [Pos])] — eval :: Index → Query → [DocId]
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— insert / delete / lookup — boolean + phrase positions
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— persistence (optional later) │
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│ ▼
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└────────────────► lib/search/rank.sx
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— TF-IDF / BM25 scoring
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— top-N
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│
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▼
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lib/search/api.sx
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— (search/index doc)
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— (search/query q)
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— (search/top n q)
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│
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▼
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lib/search/fed.sx
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— federated query (merge peer results)
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— ACL filter post-merge
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```
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## Phase 1 — Tokenize + index
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- [x] `lib/search/tokenize.sx` — normalize (lowercase, strip punctuation), split on
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whitespace, return positions
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- [x] `lib/search/index.sx` — inverted index data structure; `indexDoc`, `deleteDoc`,
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`lookupTerm`, `docFreq`, `allTerms`. (Data.Map's public API lacks
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toList/keys/map/filter, so a sorted assoc-list `[(Term,[(DocId,[Pos])])]` is used —
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the conceptual `Map Term [(DocId,[Pos])]` with free term iteration.)
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- [x] `lib/search/api.sx` — assembles `search/src` (tokenize + index); Haskell entry
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points `indexDoc` / `lookupTerm`
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- [x] `lib/search/tests/index.sx` — 18 cases: tokenize, insert + lookup, update,
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delete, multi-doc, positions, docFreq, allTerms
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- [x] `lib/search/scoreboard.{json,md}`
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- [x] `lib/search/conformance.sh`
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## Phase 2 — Query AST + boolean evaluation
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- [x] Query ADT: `Term String | And Query Query | Or Query Query | Not Query |
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Phrase [String]` (in `lib/search/query.sx`)
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- [ ] `lib/search/parse.sx` — query syntax parser (boolean operators, quoted phrases)
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- [x] `lib/search/query.sx` — boolean eval via set ops on docid-sorted posting lists
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(sortedUnion/Inter/Diff, Not over allDocs universe)
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- [x] phrase eval — positional adjacency check (phraseInDoc / phraseStartsAt)
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- [x] `lib/search/tests/boolean.sx` — 28 cases: term, and, or, not, phrase,
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composition (parser edge cases move to the parse.sx suite)
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## Phase 3 — Ranking
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- [ ] document frequency tracking — extend index with `df` per term
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- [ ] TF-IDF scoring
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- [ ] BM25 scoring (configurable k1, b)
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- [ ] top-N retrieval (heap-based)
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- [ ] `lib/search/tests/rank.sx` — 20+ cases: TF-IDF behavior, BM25 vs TF-IDF,
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ranking stability, top-N correctness
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## Phase 4 — ACL filter + federation
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- [ ] post-filter — each candidate result tested via `(acl/permit? viewer :read doc)`
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- [ ] federated query — fan out to peer instances via fed-sx, merge results
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- [ ] merge policy — interleave by rank, dedupe by `(peer, doc-id)`
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- [ ] `lib/search/tests/integration.sx` — federated search with ACL filter
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## Progress log
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- **Phase 2 boolean/phrase eval (46/46 total).** Query ADT
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`Term|And|Or|Not|Phrase` + `evalQuery :: Index -> Query -> [DocId]` in query.sx.
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Boolean ops are linear merges over docid-sorted posting lists; Not subtracts from
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the allDocs universe; Phrase checks positional adjacency. 28 tests in boolean.sx.
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Refactored both suites to **batch all cases into one program eval** (search-batch
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in testlib) — under the heavy CPU load on this box (~11 on 2 cores), 18–28 separate
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hk-eval-program calls timed out; one combined eval per suite is ~20× faster.
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Parser (parse.sx) is the remaining Phase 2 box.
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- **Phase 1 complete (18/18).** Tokenizer (lowercase + strip punctuation + positions),
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inverted index as sorted assoc-list `[(Term,[(DocId,[Pos])])]`, indexDoc/deleteDoc/
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lookupTerm/docFreq/allTerms. Search lib is Haskell source assembled into `search/src`
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and evaluated via the haskell-on-sx interpreter; tests reuse `hk-test` counters and a
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`search-eval` helper that forces HK values to plain SX. conformance.sh models
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lib/haskell (MODE=counters, COUNTERS_PASS/FAIL=hk-test-pass/fail).
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## Blockers
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- **None.** Note: the box is heavily CPU-oversubscribed by sibling loop agents
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(load ~11 on 2 cores); each program eval is ~10× slower than nominal, so suite
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timeout is set to 600s. Runs are correct, just slow.
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- **Data.Map public API gap (informational, not fixing):** the haskell-on-sx
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`import Data.Map` binds only empty/singleton/insert/lookup/member/size/null/delete/
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insertWith/adjust/findWithDefault — no toList/keys/elems/map/filter/unionWith. Index
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uses a pure assoc-list instead so term iteration and federation merge stay simple.
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