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* perf(engine): route Expand node hydration through the id BTREE via structured filter
hydrate_nodes built an `id IN (...)` SQL string applied via Scanner::filter,
which DataFusion evaluates with InListEval (O(N×M)) rather than using the id
BTREE scalar index — measured at 72× the indexed cost on a 100k-node hop
(MR-376). Build the id IN-list as a structured DataFusion Expr, AND it with
the pushable destination filters, and apply via Scanner::filter_expr (the same
path execute_node_scan already uses); Lance then compiles it to
scalar-index-search -> take.
Destination-filter pushability is now decided by ir_filter_to_expr (structured)
instead of ir_filter_to_sql, so list-contains (array_has) pushes down too.
Removes the now-dead string-filter helpers build_lance_filter, ir_filter_to_sql,
and ir_expr_to_sql; literal_to_sql stays (still used by the mutation delete path).
* feat(engine): add TableStore::scan_edges_by_endpoint for indexed neighbor lookup
Static helper returning edge rows that match a set of endpoint keys on src/dst,
projected to [key_col, opposite_col], via a structured `key_col IN (keys)`
filter_expr. Lance routes it through the persisted BTREE on the endpoint column
(index-search -> take), so cost scales with the frontier size rather than |E|.
Unused until execute_expand's indexed mode lands; isolated in its own commit so
the storage-layer primitive is reviewable on its own.
* feat(engine): add BTREE-indexed Expand traversal path
Split execute_expand into a dispatcher over execute_expand_csr (the existing
in-memory CSR BFS, unchanged) and a new execute_expand_indexed that serves each
hop by batching the frontier into one scan_edges_by_endpoint call against the
persisted src/dst BTREE (index-search -> take), then fans out per source row.
Both share expand_hydrate_and_align — the destination hydration + alignment +
hconcat + in-memory non-pushable filters — which now aligns by string id (a
HashMap) instead of a dense row-id vec, so one tail serves both modes.
Mode selection is OMNIGRAPH_TRAVERSAL_MODE for now (default csr); the
frontier-size auto policy and lazy CSR build follow. AntiJoin stays on CSR.
tests/traversal_indexed.rs (its own #[serial] binary, so env writes never race a
reader) asserts the indexed path matches CSR for one-hop, multi-hop, cross-type,
and no-match cases, and that a freshly-appended unindexed edge is still found
(partial index coverage — fast_search=false unindexed-fragment scan).
* feat(engine): frontier-size Expand dispatcher + lazy CSR build
Replace the env-only mode switch with an auto policy: Expand uses the
BTREE-indexed path when the source frontier is small and the hop count bounded
(OMNIGRAPH_EXPAND_INDEXED_MAX_FRONTIER=1024, OMNIGRAPH_EXPAND_INDEXED_MAX_HOPS=6),
else the in-memory CSR. OMNIGRAPH_TRAVERSAL_MODE=indexed|csr still forces a mode.
Make the CSR index lazy: thread a GraphIndexHandle (memoizing OnceCell over a
Cached/Direct/None builder) through execute_query/execute_pipeline/
execute_rrf_query/execute_anti_join instead of a pre-built Option<&GraphIndex>.
A query served entirely by the indexed path with no AntiJoin never pays the
O(|E|) CSR build — the perf win of Tier 3. AntiJoin still realizes the index
(its negation uses CSR has_neighbors).
Net effect: selective traversals (the common case) skip the whole-graph CSR
build and resolve neighbors from the persisted, incrementally-maintained
src/dst BTREE. Existing traversal/aggregation/end_to_end/search suites now run
the indexed path by default and stay green.
Docs: constants.md (new env knobs), query-language.md (Expand dual path),
indexes.md (graph index is lazy + the indexed alternative).
* test(engine): bench indexed vs CSR selective traversal
Add a selective single-source knows{1,2} comparison to bench_expand: per growing
|E|, time the cold query in csr vs indexed mode (fresh db each, so CSR pays its
O(|E|) build) and assert both modes return identical rows — a guard against the
scalar-index physical_rows silent fallback dropping unindexed-fragment rows. The
existing dense hop1/2/3 latency bench is unchanged.
* feat(engine): surface silent scalar-index fallback in indexed traversal (C6)
Add TableStore::key_column_index_coverage — a metadata-only check (no IO) of
whether a `key_col IN (...)` scan will be served by the persisted BTREE or
silently fall back to a full filtered scan, mirroring Lance's own decision:
no BTREE on the column, or any fragment missing physical_rows (which disables
scalar indices for the whole scan, lance dataset/scanner.rs create_filter_plan).
execute_expand_indexed calls it once per traversal and tracing::warn!s on
Degraded, so the perf cliff is observable instead of hidden behind a bench oracle.
Detection-only: results are correct either way (the scan returns all rows). Closes
the "no silent failures" gap the traversal best-practice audit flagged as the top
deviation, and adds an IndexCoverage value a future cost-based planner can consume.
* perf(engine): dense-id BFS on the indexed traversal path (C3)
execute_expand_indexed ran its per-source BFS in string space
(Vec<HashSet<String>>, HashMap<String,Vec<String>>, ~4 String clones per neighbor
occurrence). Intern node ids to u32 once via a per-traversal TypeIndex (no
GraphIndex/CSR build — laziness preserved) and run visited/seen/frontier/
neighbor-map in dense u32 space, mirroring the CSR path; de-intern only for the
per-hop IN-list and the emitted dst ids handed to the hydrate+align tail.
Behavior-preserving — the traversal_indexed CSR-vs-indexed equivalence tests are
the guard (results are identical, the key type just changes String -> u32).
* refactor(engine): thread the opened edge dataset into indexed Expand
Hoist the edge-dataset open and the C6 index-coverage warning out of
execute_expand_indexed into execute_expand, threading the opened dataset in
as a parameter so it is opened exactly once. Extract the endpoint-column
mapping (endpoint_columns) and the coverage warning (warn_on_degraded_coverage)
as helpers.
Behavior-preserving: same dataset, same warning, same dispatch decision. This
only relocates the open so the upcoming cost-based chooser can consult index
coverage before dispatch without opening the dataset twice.
* feat(engine): cost-based Expand dispatch chooser (C5)
Replace the fixed frontier<=1024 && hops<=6 dispatch threshold with a pure,
IO-free cost model. choose_expand_mode compares the indexed path's
frontier-relative work (hops * frontier * fanout, or hops * |E| when BTREE
coverage is degraded) against the cost of building the whole-graph CSR
(BUILD_FACTOR * |E|), from cheap manifest row counts. Under good coverage this
reduces to a selectivity ratio independent of |E|, preserving the flat-in-|E|
indexed win for selective traversals while routing dense / deep / high-fanout
or degraded-and-expensive traversals to CSR.
execute_expand decides cardinality-first and only opens the edge dataset to
confirm coverage when it leans indexed (no open on a clearly-CSR traversal).
The two env knobs become hard ceilings layered on the model; the
OMNIGRAPH_TRAVERSAL_MODE override still forces a path; the chosen mode is
traced. Results are unchanged across modes — only the path differs.
Adds inline crossover unit tests and extends the traversal_indexed both_modes
harness with an auto pass asserting the chooser is result-preserving across
every traversal shape. Documents the new flag semantics in
docs/user/{constants,query-language}.md.
* test(engine): pin Lance scalar-index coverage + system-column/deletion-metadata surface
Add three Lance surface guards de-risking a future persisted-adjacency cache:
- a compile-only guard pinning the fragment physical_rows + index-detail
surface that key_column_index_coverage mirrors (the C6 fallback);
- a runtime probe confirming a scalar BTREE on the system column
_row_last_updated_at_version is not buildable via the normal create-index
path (the column is not in the user schema), so a version-column range delta
is not viable as drafted;
- a runtime probe confirming per-fragment deletion metadata
(deletion_file.num_deleted_rows) is available as cheap O(fragments) metadata,
the primitive a fragment-coverage delete model would rely on.
The probes turn the two largest substrate assumptions into green/red CI facts
before any cache work begins.
* test(engine): regression for cross-type id-collision in indexed traversal
A node id is unique only within a type, so a Person and a Company can share an
id string. A variable-length traversal over a cross-type edge (WorksAt) must
structurally stop after one hop. This test builds a graph where 'shared' is both
a Person and a Company id and asserts worksAt{1,2} returns only the one-hop
company. It fails today: the indexed path's single string interner de-interns
the hop-1 Company id back to the colliding Person id and runs a hop-2 scan that
matches that Person's edges, emitting a spurious second-hop company (indexed
["other","shared"] vs csr ["shared"]).
* fix(engine): structurally cap cross-type Expand at one hop
A cross-type edge cannot chain (e.g. a Company is not a WorksAt source), so a
variable-length traversal over one is structurally single-hop. Both traversal
paths now enforce this by capping max hops at 1 when from_type != to_type,
instead of relying on the hop-2 scan returning empty.
That reliance was a correctness hole on the indexed path: it interns every
endpoint string into one dense id space, so a cross-type id-string collision (a
Person and a Company sharing an id) let hop 2 de-intern a destination id back to
the colliding source-type id and match its edges, emitting rows the CSR path
never produces. With the cap the cross-type second-hop scan never runs, so the
shared interner can no longer alias across types. Turns the regression test
green (indexed == csr == ["shared"]).
* perf(engine): set-oriented filtered anti-join, remove per-row dispatch
execute_anti_join's filtered slow path sliced the outer batch to one row at a
time and re-ran the inner pipeline per row, so each 1-row inner Expand dispatched
to the indexed path — one Lance scan per outer row, while the CSR realized up
front sat unused.
Replace it with a set-oriented anti-semi-join: tag each outer row with a
synthetic index column, run the inner pipeline once over the whole frontier (the
tag survives Expand's hconcat and Filter's row-drop), then exclude outer rows
whose tag survived. The inner Expand now runs as a single set-at-a-time traversal
over the full frontier; config is read once per operator, not per row (the env
nit is mooted). A produced-but-untagged inner batch fails loudly rather than
silently keeping every row. Results are unchanged (the predicated-negation tests
exercise the path over a multi-row outer with dst-filters).
* test(engine): drop flaky wall-clock budget from the merge truth table
The 30s wall-clock assertion in merge_pair_truth_table flakes under parallel
test load: it tripped at ~31s in the full --test-threads=4 gate while passing at
~20s in isolation. A fixed time budget in a correctness test depends on machine
and parallelism, not correctness; elapsed is still logged for visibility, and a
real merge-perf regression belongs in a bench. The cell-count correctness
assertions (81 / 36 / 45) are unchanged.
* fix(engine): total deterministic ORDER via entity-key tie-break + NULL contract
apply_ordering used an unstable lexsort with no tie-break, so rows with equal
user-sort keys came out in a run-dependent order (the input order depends on
scan parallelism / upstream hashing) — making ORDER ... LIMIT non-deterministic,
a latent deny-list violation (no nondeterministic result ordering).
Append the bound entities' key columns (<var>.id, unique per row) in canonical
name-sorted order as ascending tie-breaks, giving a total, reproducible order
(and a deterministic top-N when ties straddle the LIMIT cutoff). NULL placement
(nulls_first = !descending) is unchanged and now documented as the contract.
New tests/ordering.rs locks descending, multi-key precedence, the deterministic
key tie-break (data loaded in a different order than the expected output, so it
proves the tie sorts by key not by load order), and NULL placement under ASC/DESC.
docs/user/query-language.md documents the total-order + NULL contract.
* test(engine): property-based query-correctness invariants over generated graphs
Adds a proptest harness (new dev-dep) that generates small graphs whose Person
and Company keys are drawn from a shared 5-key alphabet, so cross-type id
collisions, cycles, and self-loops arise by search rather than from one
hand-built fixture. Three invariants:
- prop_expand_indexed_eq_csr: csr == indexed == auto over knows{1,3} (same-type,
cycles) and worksAt{1,2} (cross-type, collision-prone) from every start.
- prop_results_subset_of_existing_nodes: no phantom rows (catches over-emission
even if both modes are wrong identically).
- prop_antijoin_partitions_persons: not{worksAt} and its complement are disjoint
and cover all persons.
Verified the guard bites: neutering the cross-type hop cap makes
prop_expand_indexed_eq_csr fail and proptest shrinks it to persons["c","e"] /
companies["b","c"] — the cross-type collision class the hand-built fixture
only sampled once. Tests are sync + #[serial] (per-case runtime; the mode test
writes OMNIGRAPH_TRAVERSAL_MODE).
* test(engine): cover cycle/self-loop termination + nested anti-join (C5 edge cases)
- variable_hops_terminate_and_dedup_on_cycle: a 3-cycle a->b->c->a traversed with
knows{1,5} (ceiling above the cycle length) terminates and emits each node once
(the c->a back-edge hits the seeded source); both_modes confirms indexed == csr.
Uses a bounded range deliberately — unbounded {1,} is a typecheck error, not a
runtime path.
- variable_hops_handle_self_loop: a->a self-loop does not loop forever and does
not re-emit the seeded source.
- nested_anti_join_double_negation: not { worksAt; not { name = Acme } } recurses
through execute_pipeline, yielding [Alice,Charlie,Diana] (people with no non-Acme
employer) — distinct from plain unemployed [Charlie,Diana].
* test(engine): execution goldens for typed-literal filters (C4 gap #4)
New literal_filters.rs covers filtering by F64/F32/Bool/Date/DateTime LITERALS
across both arms: standalone comparisons ($m.score > 1.5, $m.ratio <= 0.25,
$m.active = true, $m.born >= date(...), $m.seen < datetime(...)) exercise the
in-memory comparison path, and inline bindings (Metric { active: true },
Metric { score: 3.0 }) exercise Lance filter_expr pushdown. Seeds partition each
predicate so a dropped/miscast filter returns all rows. (Param-bound scalars and
list-column contains are covered elsewhere.)
* test(engine): full rank-order goldens for nearest + bm25 (gap #2)
Existing search tests stopped at top-1 (nearest) or non-empty (bm25), so a
regression corrupting ranks 2..k or reversing the sort direction passed CI
silently. Pin the FULL ordered slug list: nearest([0.1,0.2,0.3,0.4]) ->
[ml-intro, nlp-guide, rl-intro] (ml-intro exact at dist 0, rest by ascending
L2); bm25(Learning) -> [rl-intro, ml-intro, dl-basics] (descending score).
nearest/bm25 skip apply_ordering (is_search_ordered) and return Lance native
order, so result_slugs row order == rank order; values resolved by running and
confirmed stable across runs.
* test(engine): search fuzzy/match_text characterization + RRF non-default pairings
- match_text_matches_exact_set_excludes_unrelated: match_text(body,'neural') ==
[dl-basics] exactly (not just contains).
- fuzzy_does_not_match_under_default_tokenizer: characterizes that fuzzy() is
inert with the default tokenizer here (search/match_text work, fuzzy returns
nothing); turns red — to be promoted to a real golden — if fuzzy starts matching.
- rrf_fuses_two_fts_fields / rrf_fuses_two_vector_queries: RRF fuses arms other
than the default nearest+bm25 (bm25 title+body; two vector queries), proving
primary_var resolves and fusion runs. New fixtures/search.gq queries +
two_vector_params helper. Orders resolved by running, confirmed stable.
* test(engine): anti-join fast-vs-slow path equivalence harness
anti_join_fast_and_slow_paths_agree: the CSR has_neighbors fast path
(not { $p worksAt $_ }) and the set-oriented inner-pipeline replay (same
negation forced slow by an always-true $c.name != "" dst filter) must produce
the same result ([Charlie, Diana]). Closes the second real engine fork explicitly.
* test(engine): regression for nested slow-path anti-join tag collision
A nested not { ... not { ... } } where both levels hit the set-oriented slow
path collides on the fixed __antijoin_outer_row correlation column: the inner
call appends a duplicate, and column_by_name reads the OUTER tag. Fan-out (p1
works at two companies) makes inner row indices diverge from outer tags, so the
bug returns the wrong person set. Fails on current code (left ["p2","p4"] vs
right ["p3","p4"]).
* fix(engine): collision-free anti-join correlation tag for nested negation
The set-oriented anti-join tagged the outer batch with a fixed column name and
read it back by name. Under a nested slow-path anti-join the enclosing tag rides
through the inner pipeline, so the inner call produced a duplicate field; Arrow
permits duplicate names and column_by_name returns the first, so the inner
negation mis-correlated against the outer row indices.
Choose a tag name not already present in the batch (suffix-incremented), so each
nesting level reads its own correlation column. Turns the fan-out regression
green; the existing nested/fast-vs-slow/proptest anti-join invariants still pass.
* fix(engine): cap cross-type hops in the Expand cost model
gather_cost_inputs fed the requested max_hops into choose_expand_mode even though
execute_expand_indexed runs at most one hop for a cross-type edge. So a cross-type
variable-length expand (e.g. worksAt{1,5}) had its indexed cost scaled by 5 while
only one hop runs, skewing the chooser toward CSR (an unnecessary whole-graph
build) near the crossover. Results were unaffected (modes are equivalent); this
is a plan-accuracy fix.
Add cost_effective_hops(requested, same_type) — caps to 1 for cross-type — and
apply it in gather_cost_inputs so the estimate matches what executes. Unit test
covers the cap and the crossover consequence (capped 1 hop stays indexed where
the requested 5 would have flipped to CSR).
* perf(engine): realize anti-join CSR lazily + reuse a warm CSR in the chooser
Two CSR build/reuse fixes flagged on the set-oriented anti-join work (results
unchanged — plan/perf accuracy):
- execute_anti_join called graph_index.get() (the O(|E|) whole-graph CSR build)
unconditionally, but only the bulk fast path consumes it; a filtered/nested
slow-path anti-join's inner Expand picks its own access path. Gate the build on
a pure shape predicate (bulk_anti_join_applies) so a selective anti-join over a
large graph no longer pays a build it won't use.
- gather_cost_inputs hardcoded csr_cached=false, so once an earlier op realized
the CSR, later Expands still cost it as a cold build and could pick per-hop
indexed scans over reusing the warm in-memory CSR. Add GraphIndexHandle::
is_built() and thread it through so the chooser reuses a materialized CSR.
Anti-join, cross-type, proptest-equivalence, and chooser unit tests stay green.
* test(engine): RAII traversal-mode guard in proptest equivalence
prop_expand_indexed_eq_csr set/cleared OMNIGRAPH_TRAVERSAL_MODE manually; a panic
between set and clear (e.g. a query unwrap on a generated case) would leak the
forced mode into proptest's shrink/subsequent cases and mask the divergence under
test. Replace with a ModeGuard that clears on drop (including on unwind), scoping
the forced mode to a single query.
* test(engine): regression for multi-hop anti-join hop bounds
The bulk anti-join fast path answers via has_neighbors (one-hop existence), so
not { $p knows{2,2} $x } wrongly drops a node with a 1-hop neighbor but no
2-hop path. On a->b (sink) and c->d->e, only c has a 2-hop path; the query should
keep [a,b,d,e]. Fails on current code (left ["b","e"] — only the sinks).
* fix(engine): restrict anti-join bulk fast path to one-hop expands
bulk_anti_join_applies accepted any single Expand, but try_bulk_anti_join_mask
decides via the CSR has_neighbors one-hop existence check — wrong for multi-hop
negations. Require min_hops==1 && max_hops==1 in the predicate; anything else
falls to the slow path, whose inner Expand runs the real bounded traversal.
Turns the multi-hop regression green; one-hop anti-joins unchanged.
* fix(engine): IndexCoverage reports Degraded for uncovered fragments
key_column_index_coverage checked BTREE-exists + physical_rows but not that the
index actually covers the current fragments. Since edge-index creation is skipped
once a BTREE exists, fragments appended later stay unindexed while coverage still
reported Indexed — so the cost chooser priced a partly-full scan as fully indexed.
Compare the BTREE's fragment_bitmap (public on lance_table IndexMetadata) against
the dataset's current fragment ids; report Degraded when any are uncovered. A None
bitmap means Lance can't report coverage — don't over-degrade. Results are
unaffected (the scan returns unindexed-fragment rows either way); this corrects
the cost signal.
Test: a freshly-loaded edge BTREE is Indexed; after appending an edge the new
fragment is uncovered → Degraded. Surface guard pins IndexMetadata.fragment_bitmap.
* docs: clarify the Expand frontier ceiling bounds the initial dispatch frontier
The cap is applied at dispatch on the initial frontier; per-hop fan-out
(union_dense) is not hard-capped. Correct the constants.md and query-language.md
claims: the ceilings bound the initial-dispatch frontier/hops, the cost model
estimates total indexed work as ~hops*frontier*fanout (pricing dense fan-out
toward CSR), and per-hop work is not a hard bound. Drops the overstated 'hard
caps bound indexed work' / 'cost ∝ frontier' wording.
113 lines
6.6 KiB
Markdown
113 lines
6.6 KiB
Markdown
# Query Language (`.gq`)
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Pest grammar at `crates/omnigraph-compiler/src/query/query.pest`. AST in `query/ast.rs`. Type checker in `query/typecheck.rs`. Lowering in `ir/lower.rs`.
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## Query declarations
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```
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query <name>($p1: T1, $p2: T2?, …)
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@description("…") @instruction("…") {
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…
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}
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```
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Two body shapes:
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- **Read**: `match { … } return { … } [order { … }] [limit N]`
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- **Mutation**: one or more of `insert | update | delete` statements
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Param types reuse all schema scalars; trailing `?` makes a param optional. The compiler reserves `$__nanograph_now` for `now()`.
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## MATCH clauses
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- **Binding**: `$x: NodeType { prop: <literal | $param | now()>, … }`
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- **Traversal**: `$src EDGE_NAME { min, max? } $dst` — variable-length paths via hop bounds; default 1..1 if bounds omitted.
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- **Filter**: `<expr> <op> <expr>` with operators `>=`, `<=`, `!=`, `>`, `<`, `=`, and string `contains`.
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- **Negation**: `not { clause+ }` — desugars to anti-join over the inner pipeline.
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## Search clauses (multi-modal)
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Used inside MATCH or as expressions inside RETURN/ORDER:
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| Function | Purpose | Underlying Lance facility |
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|---|---|---|
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| `nearest($x.vec, $q)` | k-NN vector search (cosine) | Lance vector index (IVF / HNSW) |
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| `search(field, q)` | Generic FTS | Inverted index |
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| `fuzzy(field, q [, max_edits])` | Levenshtein-tolerant text search | Inverted index |
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| `match_text(field, q)` | Pattern match | Inverted index |
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| `bm25(field, q)` | BM25 scoring | Inverted index |
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| `rrf(rank_a, rank_b [, k])` | Reciprocal Rank Fusion of two rankings (default k=60) | OmniGraph fuses scored rankings |
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`nearest()` requires a `LIMIT`; the compiler resolves the query vector via the param map (or via the runtime embedding client when bound to a text input).
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## RETURN clause
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`return { <expr> [as <alias>], … }` with expressions:
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- Variable / property access: `$x`, `$x.prop`
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- Literals: string, int, float, bool, list
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- `now()`
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- Aggregates: `count`, `sum`, `avg`, `min`, `max`
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- All search functions above (so you can return a score column)
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- `AliasRef` — re-use a previous projection alias
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## ORDER & LIMIT
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- `order { <expr> [asc|desc], … }` — supports plain expressions and `nearest(...)`.
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- `limit <integer>` — required when there is a `nearest(...)` ordering.
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- **Total, deterministic order.** Rows with equal user-sort keys are broken by the bound entities' key columns (`<var>.id`, ascending) appended as a final tie-break, so the result is a *total* order — reproducible across runs, and `order … limit N` returns a deterministic top-N even when ties straddle the cutoff. (Aggregate results have no entity-key columns; their group rows are already distinct on the projected group keys.)
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- **NULL placement** is *nulls-first ascending, nulls-last descending* (i.e. `nulls_first = !descending`): a NULL sorts as if smaller than any value.
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## Mutation statements
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- `insert <Type> { prop: <value>, … }`
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- `update <Type> set { prop: <value>, … } where <prop> <op> <value>`
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- `delete <Type> where <prop> <op> <value>`
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`<value>` is a literal, `$param`, or `now()`. Multi-statement mutations execute atomically (added in v0.2.0).
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### D₂ — mixed insert/update + delete is rejected at parse time
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A single mutation query must be **either insert/update-only or delete-only**. Mixed → rejected before any I/O with the message:
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> `mutation '<name>' on the same query mixes inserts/updates and deletes; split into separate mutations: (1) inserts and updates, then (2) deletes. This restriction lifts when Lance exposes a two-phase delete API (tracked: MR-793 / Lance-upstream).`
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Reason: under the staged-write rewire (MR-794), inserts and updates accumulate in memory and commit at end-of-query, while deletes still inline-commit (Lance 4.0.0 has no public two-phase delete). Mixing creates ordering hazards (same-row insert→delete becomes a no-op because the staged insert isn't visible to delete; cascading deletes of just-inserted edges break referential integrity by silent design). Until Lance exposes `DeleteJob::execute_uncommitted`, the parse-time rejection keeps both paths atomic and correct. See [docs/dev/writes.md](../dev/writes.md) and [docs/dev/invariants.md](../dev/invariants.md).
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## IR (Intermediate Representation)
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`QueryIR { name, params, pipeline: Vec<IROp>, return_exprs, order_by, limit }`
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Pipeline operations:
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- `NodeScan { variable, type_name, filters }`
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- `Expand { src_var, dst_var, edge_type, direction (Out|In), dst_type, min_hops, max_hops, dst_filters }` — destination filters are pushed *into* the expand so Lance scalar pushdown can prune. Executed one of two ways, chosen per-expand by a cost model over cheap manifest counts (frontier size, |E|, source-vertex count, hops) plus index coverage: selective traversals (small frontier relative to the source set) resolve neighbors from the persisted `src`/`dst` BTREE (one indexed scan per hop); dense / deep / large-frontier traversals — or those whose BTREE coverage is degraded so a full scan would be paid per hop — use the in-memory CSR adjacency index. Both produce identical results. The `OMNIGRAPH_EXPAND_INDEXED_MAX_FRONTIER` / `OMNIGRAPH_EXPAND_INDEXED_MAX_HOPS` ceilings bound the *initial dispatch* frontier/hops (beyond them CSR is always used); the cost model estimates total indexed work as ~`hops × frontier × fanout` and prices dense fan-out toward CSR — they are not a hard per-hop bound. `OMNIGRAPH_TRAVERSAL_MODE=indexed|csr` forces a mode (see [constants](constants.md)).
|
||
- `Filter { left, op, right }`
|
||
- `AntiJoin { outer_var, inner: Vec<IROp> }` — for `not { … }`
|
||
|
||
Lowering:
|
||
|
||
1. Partition MATCH clauses (bindings, traversals, filters, negations).
|
||
2. Identify "deferred" bindings (a destination of a traversal that has filters) so the Expand can carry the filter as a pushdown.
|
||
3. Emit NodeScan for the first binding, then Expand operations, then remaining Filter operations, then AntiJoins for negations.
|
||
4. Translate RETURN / ORDER expressions; preserve LIMIT.
|
||
|
||
## Linting & validation (`query/lint.rs`)
|
||
|
||
Codes seen so far:
|
||
|
||
- **Q000** (Error): parse error
|
||
- **L201** (Warning): nullable property never set by any UPDATE — "{type}.{prop} exists in schema but no update query sets it"
|
||
- (Warning): mutation declares no params — hardcoded mutations are easy to miss
|
||
- Plus all type errors from `typecheck_query_decl()` (undefined types, mismatched operators, undefined edges, etc.)
|
||
|
||
Output:
|
||
|
||
```
|
||
QueryLintOutput { status, schema_source, query_path,
|
||
queries_processed, errors, warnings, infos,
|
||
results: [{ name, kind, status, error?, warnings[] }],
|
||
findings: [{ severity, code, message, type_name?, property?, query_names[] }] }
|
||
```
|
||
|
||
CLI exits non-zero only on `status = Error`.
|