Merge main into gatekeeper/fix-4315-1

python/python/lancedb/_lancedb.pyi

@@ -514,6 +514,9 @@ class Table:
     async def set_lsm_write_spec(self, spec: LsmWriteSpec) -> None: ...
     async def unset_lsm_write_spec(self) -> None: ...
     async def get_lsm_write_spec(self) -> Optional[LsmWriteSpec]: ...
+    # WAL-PK-FUSION: delete both.
+    def hybrid_pk_fusion_learned(self) -> bool: ...
+    def note_hybrid_pk_fusion(self) -> None: ...
     async def checkpoint_lsm(self) -> None: ...
     async def flush_lsm(self) -> None: ...
     async def compact_lsm(self) -> None: ...

python/python/lancedb/_wal_hybrid.py

@@ -0,0 +1,282 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+"""WAL-PK-FUSION: hybrid search's primary-key fallback for MemWAL tables.
+
+Hybrid search joins its vector and full-text legs on `_rowid`, which a MemWAL
+table cannot supply: the fresh tier has no stable row id, so the server rejects
+`with_row_id` before it plans. When that happens the legs are joined on a
+surrogate `_rowid` built from the table's primary key instead.
+
+This is a stopgap until MemWAL supports `_rowid`, and everything it needs lives
+here so it can be removed in one pass:
+
+1. Delete this file and `tests/test_wal_hybrid.py`.
+2. Run `grep -rn WAL-PK-FUSION python/ rust/` and follow the note at each
+   marker; the Rust side has its own copy in
+   `rust/lancedb/src/query/wal_fusion.rs`.
+"""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Awaitable, Callable, List, Optional, Tuple, TypeVar
+
+import pyarrow as pa
+
+from ._blob import blob_v2_projection_sources
+
+if TYPE_CHECKING:
+    from .types import QueryProjection
+
+T = TypeVar("T")
+
+
+# Lance records the unenforced primary key as field metadata, which survives the
+# `describe` round trip — so a remote table can resolve the key without opening
+# the dataset. Keys are bytes on a pyarrow field.
+_PK_MARKER = b"lance-schema:unenforced-primary-key"
+_PK_POSITION_MARKER = b"lance-schema:unenforced-primary-key:position"
+_TRUTHY = {"1", "true", "on", "yes", "y"}
+
+
+def _pk_columns(schema: pa.Schema) -> List[str]:
+    """The unenforced primary key columns of `schema`, in key order.
+
+    Mirrors Lance's ordering: fields with an explicit 1-based position first, in
+    position order, then fields carrying only the legacy boolean marker, in
+    declaration order.
+    """
+    keyed = []
+    for index, field in enumerate(schema):
+        metadata = field.metadata or {}
+        position = metadata.get(_PK_POSITION_MARKER)
+        if position is not None:
+            try:
+                position = int(position)
+            except ValueError:
+                position = None
+        if position is None:
+            legacy = metadata.get(_PK_MARKER)
+            if legacy is None or legacy.decode().lower() not in _TRUTHY:
+                continue
+            position = 0
+        keyed.append((position == 0, position, index, field.name))
+    return [name for *_, name in sorted(keyed)]
+
+
+# Both layers raise this same sentence verbatim -- sophon's
+# `LSM_WITH_ROW_ID_UNSUPPORTED` says so explicitly, and the OSS LSM scanner
+# builds it from the same words -- so this substring survives either path and
+# the wrapping each adds. It is a coupling to a message rather than a code,
+# because the refusal arrives as a generic 400; if the server ever rewords it
+# the fallback stops firing and hybrid on a MemWAL table errors visibly again,
+# which is loud rather than silently wrong.
+_WAL_ROW_ID_REFUSAL = "does not support with_row_id"
+
+WAL_ROW_ID_UNSUPPORTED = (
+    "hybrid search on a MemWAL table cannot return _rowid: the fresh tier has "
+    "no stable row id, and the ids the fusion joins on are synthesized from "
+    "the primary key. Set use_lsm(False) to read the base table only (results "
+    "will exclude un-compacted MemWAL data)"
+)
+
+
+def _is_wal_row_id_refusal(error: BaseException) -> bool:
+    """Whether `error` is the server declining `_rowid` because the table is
+    MemWAL-backed, as opposed to any other failure the query might hit."""
+    return _WAL_ROW_ID_REFUSAL in str(error)
+
+
+def _with_pk_columns(columns, pk_columns: List[str]):
+    """Add the key columns a projection is missing.
+
+    Returns the projection to use and the columns added, which the caller drops
+    from the output again so an injected key never reaches a caller who did not
+    select it.
+    """
+    if not columns:
+        # Every non-system column, the key among them.
+        return columns, []
+    # `PyQueryRequest.select` reports a dynamic projection as (name, sql) pairs.
+    if isinstance(columns, (list, tuple)) and isinstance(columns[0], (list, tuple)):
+        columns = dict(columns)
+    missing = [c for c in pk_columns if c not in columns]
+    if isinstance(columns, dict):
+        return {**columns, **{c: c for c in missing}}, missing
+    return list(columns) + missing, missing
+
+
+def _stamp_surrogate_row_ids(
+    tables: List[pa.Table], pk_columns: List[str]
+) -> List[pa.Table]:
+    """Give each table a `_rowid` column derived from its primary key.
+
+    The fusion only ever compares that column for equality — to deduplicate, to
+    group by in a reranker, and to restore the original scores — so on a MemWAL
+    table, where the server has no stable row id to hand out, any injective
+    mapping of the primary key does the same job. Ids are assigned in first-seen
+    order across `tables`, so passing them in fusion order (vector, then FTS)
+    preserves "first occurrence wins" and its tie break.
+
+    Writing it under the `_rowid` name is what lets every reranker, third-party
+    implementations included, run unmodified. The column never reaches the
+    caller.
+    """
+    if not pk_columns:
+        raise ValueError(
+            "hybrid search on a MemWAL table needs an unenforced primary key to "
+            "deduplicate on, and this table declares none"
+        )
+
+    ids = {}
+    stamped = []
+    for table in tables:
+        if table.num_rows == 0:
+            # Both legs empty: the combined schema carries no key column, and no
+            # row that would need one.
+            row_ids = pa.array([], type=pa.uint64())
+        else:
+            missing = [c for c in pk_columns if c not in table.column_names]
+            if missing:
+                raise ValueError(
+                    "hybrid search could not deduplicate: primary key "
+                    f"column(s) {missing} missing from a result set with "
+                    f"{table.num_rows} rows"
+                )
+            keys = zip(*(table.column(c).to_pylist() for c in pk_columns))
+            row_ids = pa.array(
+                [ids.setdefault(key, len(ids)) for key in keys], type=pa.uint64()
+            )
+        stamped.append(table.append_column("_rowid", row_ids))
+    return stamped
+
+
+def pk_fusion_learned(table, use_lsm: Optional[bool]) -> bool:
+    """Whether a previous hybrid query on `table` was refused `_rowid`, so this
+    one should go straight to the primary key.
+
+    Learned from a refusal, never probed, so asking is free.
+    """
+    if table is None or use_lsm is False:
+        return False
+    # Only an unambiguous True forks to the key: a table type that answers the
+    # question loosely keeps the `_rowid` path.
+    return table._hybrid_pk_fusion_learned() is True
+
+
+class PkFusion:
+    """How the legs of a hybrid query on a MemWAL table are joined: on a
+    surrogate `_rowid` built from the primary key."""
+
+    def __init__(self, pk_columns: List[str]):
+        self.pk_columns = pk_columns
+        # Key columns the caller did not select, added to the projection so the
+        # surrogate can be built and dropped again before returning.
+        self.injected: List[str] = []
+
+    @classmethod
+    def for_query(
+        cls,
+        schema: pa.Schema,
+        projection: QueryProjection,
+        *,
+        caller_requested_row_id: bool,
+    ) -> PkFusion:
+        """Resolve the key for a hybrid query, refusing the shapes that need a
+        real `_rowid`."""
+        if caller_requested_row_id:
+            raise NotImplementedError(WAL_ROW_ID_UNSUPPORTED)
+        # A projected blob needs a real row id to fetch through, whatever else
+        # has turned `_with_row_id` on — including `return_score="all"`.
+        if blob_v2_projection_sources(schema, projection):
+            raise NotImplementedError(
+                "hybrid search cannot project a blob column on a MemWAL table: "
+                "fetching blobs needs a real _rowid, and the fresh tier has no "
+                "stable one. Set use_lsm(False) to read the base table only "
+                "(results will exclude un-compacted MemWAL data)"
+            )
+        return cls(_pk_columns(schema))
+
+    def inject(self, columns):
+        """`columns` with the key columns it is missing, to project in place of
+        the `_rowid` a MemWAL table would refuse."""
+        columns, self.injected = _with_pk_columns(columns, self.pk_columns)
+        return columns
+
+    def stamp(
+        self, vector_results: pa.Table, fts_results: pa.Table
+    ) -> Tuple[pa.Table, pa.Table]:
+        """Give both legs a surrogate `_rowid` built from the key."""
+        # Vector first: `merge_results` concatenates in that order and keeps
+        # the first occurrence, so first-seen ids preserve its tie break.
+        vector_results, fts_results = _stamp_surrogate_row_ids(
+            [vector_results, fts_results], self.pk_columns
+        )
+        return vector_results, fts_results
+
+    def strip(self, results: pa.Table) -> pa.Table:
+        """Drop the surrogate and any injected key columns from the reranked
+        results.
+
+        The surrogate is an internal join key, never an answer, and a caller
+        who asked for `_rowid` was refused in `for_query`.
+        """
+        drop = [c for c in ["_rowid", *self.injected] if c in results.column_names]
+        return results.drop(drop) if drop else results
+
+
+def _check_refusal(error: Exception, *, fused: bool, caller_requested_row_id: bool):
+    """Re-raise `error` unless it is a MemWAL `_rowid` refusal worth retrying on
+    the primary key."""
+    if fused or not _is_wal_row_id_refusal(error):
+        raise error
+    # `return_score="all"` turns row ids on for the reranker, not the caller, so
+    # it still falls back; only a caller who asked for them is refused, and with
+    # the reason rather than a bare 400.
+    if caller_requested_row_id:
+        raise NotImplementedError(WAL_ROW_ID_UNSUPPORTED) from error
+
+
+def with_pk_fallback(
+    run: Callable[[], T],
+    table,
+    *,
+    fused: Callable[[], bool],
+    caller_requested_row_id: bool,
+) -> T:
+    """Run a hybrid query, retrying on the primary key if the table refuses
+    `_rowid`.
+
+    `_rowid` is asked for first rather than paying a round trip up front to
+    find out: only a MemWAL table refuses, and the refusal has to be handled
+    anyway -- a write spec installed elsewhere can arrive between any two
+    queries. It costs nothing server-side: it is raised before the query is
+    planned. `fused` reports whether the attempt already used the key.
+    """
+    try:
+        return run()
+    except Exception as e:
+        _check_refusal(
+            e, fused=fused(), caller_requested_row_id=caller_requested_row_id
+        )
+        # Learned, so this retry and later queries go straight to the key.
+        table._note_hybrid_pk_fusion()
+        return run()
+
+
+async def with_pk_fallback_async(
+    run: Callable[[], Awaitable[T]],
+    table,
+    *,
+    fused: Callable[[], bool],
+    caller_requested_row_id: bool,
+) -> T:
+    """The async form of `with_pk_fallback`."""
+    try:
+        return await run()
+    except Exception as e:
+        _check_refusal(
+            e, fused=fused(), caller_requested_row_id=caller_requested_row_id
+        )
+        table._note_hybrid_pk_fusion()
+        return await run()

python/python/lancedb/query.py

@@ -41,6 +41,7 @@ from .rerankers.rrf import RRFReranker
 from .rerankers.util import check_reranker_result
 from .schema import is_blob_like_field, schema_has_blob_field
 from .util import flatten_columns
+from . import _wal_hybrid  # WAL-PK-FUSION: delete.
 from ._blob import (
     BLOB_MODE_TO_HANDLING,
     FetchBlobsAsync,
@@ -2207,6 +2208,12 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
         self._phrase_query = None
         self._lower_bound = None
         self._upper_bound = None
+        # WAL-PK-FUSION: delete both, and the `with_row_id` override below.
+        # Set by `_create_query_builders` when the legs are fused on the key.
+        self._pk_fusion: Optional[_wal_hybrid.PkFusion] = None
+        # `_with_row_id` is also turned on by `rerank(return_score="all")` for
+        # the reranker's own use, so it cannot answer "did the caller ask?".
+        self._caller_requested_row_id = False
 
     def _validate_query(self, query, vector=None, text=None):
         if query is not None and (vector is not None or text is not None):
@@ -2228,6 +2235,16 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
 
         return vector_query, text_query
 
+    def with_row_id(self, with_row_id: bool) -> Self:  # WAL-PK-FUSION: delete.
+        """Set whether to return row ids.
+
+        Recorded separately from `_with_row_id`, which `rerank(return_score=
+        "all")` also sets for its own use — on a MemWAL table only a caller who
+        asked is refused, and the reranker still falls back to the primary key.
+        """
+        self._caller_requested_row_id = with_row_id
+        return super().with_row_id(with_row_id)
+
     def phrase_query(self, phrase_query: bool = True) -> LanceHybridQueryBuilder:
         """Set whether to use phrase query.
 
@@ -2248,16 +2265,30 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
         raise NotImplementedError("to_query_object not yet supported on a hybrid query")
 
     def to_arrow(self, *, timeout: Optional[timedelta] = None) -> pa.Table:
+        # WAL-PK-FUSION: without the fallback, this body is `_run_hybrid`'s.
+        return _wal_hybrid.with_pk_fallback(
+            lambda: self._run_hybrid(timeout=timeout),
+            self._table,
+            fused=lambda: self._pk_fusion is not None,
+            caller_requested_row_id=self._caller_requested_row_id,
+        )
+
+    def _run_hybrid(self, *, timeout: Optional[timedelta] = None) -> pa.Table:
         self._create_query_builders()
+        fts_query, vector_query = self._fts_query, self._vector_query
+        # WAL-PK-FUSION: without the fallback, both legs always ask for row ids.
+        if self._pk_fusion is None:
+            fts_query = fts_query.with_row_id(True)
+            vector_query = vector_query.with_row_id(True)
         with ThreadPoolExecutor() as executor:
-            fts_future = executor.submit(
-                self._fts_query.with_row_id(True).to_arrow, timeout=timeout
-            )
-            vector_future = executor.submit(
-                self._vector_query.with_row_id(True).to_arrow, timeout=timeout
-            )
+            fts_future = executor.submit(fts_query.to_arrow, timeout=timeout)
+            vector_future = executor.submit(vector_query.to_arrow, timeout=timeout)
             fts_results = fts_future.result()
             vector_results = vector_future.result()
+        if self._pk_fusion is not None:  # WAL-PK-FUSION: delete.
+            vector_results, fts_results = self._pk_fusion.stamp(
+                vector_results, fts_results
+            )
 
         results = self._combine_hybrid_results(
             fts_results=fts_results,
@@ -2272,6 +2303,8 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
         return self._finish_hybrid_results(results)
 
     def _finish_hybrid_results(self, results: pa.Table) -> pa.Table:
+        if self._pk_fusion is not None:  # WAL-PK-FUSION: delete.
+            return self._pk_fusion.strip(results)
         if self._user_requested_row_id():
             return results
         if self._blob_auto_row_id_enabled():
@@ -2445,7 +2478,10 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
         self._norm = normalize
         self._reranker = reranker
         if reranker.score == "all":
-            self.with_row_id(True)
+            # WAL-PK-FUSION: without the fallback, `self.with_row_id(True)`.
+            # Not through `with_row_id`, which records caller intent: the
+            # reranker's need for row ids must not refuse a MemWAL table.
+            self._with_row_id = True
 
         return self
 
@@ -2719,13 +2755,24 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
             sub_query_limit = self._limit + (self._offset or 0)
             self._vector_query.limit(sub_query_limit)
             self._fts_query.limit(sub_query_limit)
-        if self._columns:
-            self._vector_query.select(self._columns)
-            self._fts_query.select(self._columns)
+        # WAL-PK-FUSION: without the fallback, select `self._columns` as is.
+        self._pk_fusion = None
+        columns = self._columns
+        if _wal_hybrid.pk_fusion_learned(self._table, self._use_lsm):
+            self._pk_fusion = _wal_hybrid.PkFusion.for_query(
+                self._table.schema,
+                self._columns,
+                caller_requested_row_id=self._caller_requested_row_id,
+            )
+            columns = self._pk_fusion.inject(columns)
+        if columns:
+            self._vector_query.select(columns)
+            self._fts_query.select(columns)
         if self._where:
             self._vector_query.where(self._where, not self._postfilter)
             self._fts_query.where(self._where, not self._postfilter)
-        if self._with_row_id:
+        # WAL-PK-FUSION: without the fallback, `if self._with_row_id:`.
+        if self._with_row_id and self._pk_fusion is None:
             self._vector_query.with_row_id(True)
             self._fts_query.with_row_id(True)
         if self._use_lsm is not None:
@@ -3866,6 +3913,9 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
         self._inner = inner
         self._norm = "score"
         self._reranker = RRFReranker()
+        # WAL-PK-FUSION: delete.
+        # Set by `_create_child_queries` when the legs are fused on the key.
+        self._pk_fusion: Optional[_wal_hybrid.PkFusion] = None
 
     def rerank(
         self, reranker: Reranker = RRFReranker(), normalize: str = "score"
@@ -3897,7 +3947,7 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
 
         return self
 
-    def _create_child_queries(
+    async def _create_child_queries(
         self,
     ) -> Tuple["AsyncFTSQuery", "AsyncVectorQuery", int, int]:
         """Build the sub-queries that make up this hybrid query.
@@ -3906,7 +3956,8 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
         the plans that are reported are the plans that actually run.
 
         Returns the two sub-queries along with the effective limit and offset of
-        the hybrid query itself.
+        the hybrid query itself. The key the legs are fused on, if any, is left
+        on `self._pk_fusion`.
         """
         fts_query = AsyncFTSQuery(self._inner.to_fts_query(), self._table)
         vec_query = AsyncVectorQuery(self._inner.to_vector_query(), self._table)
@@ -3924,8 +3975,27 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
             limit = DEFAULT_HYBRID_LIMIT
         offset = fts_req.offset or vec_req.offset or 0
 
-        fts_query.with_row_id()
-        vec_query.with_row_id()
+        # WAL-PK-FUSION: without the fallback, keep only the two `with_row_id`
+        # calls.
+        self._pk_fusion = None
+        if _wal_hybrid.pk_fusion_learned(self._table, fts_req.use_lsm):
+            self._pk_fusion = _wal_hybrid.PkFusion.for_query(
+                await self._table.schema(),
+                _query_request_projection(fts_req),
+                caller_requested_row_id=self._user_requested_row_id(),
+            )
+        if self._pk_fusion is None:
+            fts_query.with_row_id()
+            vec_query.with_row_id()
+        else:
+            # Ask for the key columns instead, and never for `_rowid`.
+            # `select` carries the whole projection; `select_source_columns`
+            # keeps only plain column references, so rebuilding from it would
+            # drop computed ones.
+            columns = self._pk_fusion.inject(fts_req.select)
+            if self._pk_fusion.injected:
+                fts_query.select(columns)
+                vec_query.select(columns)
 
         # offset() pushes the offset down into both sub-queries, which would make
         # each of them skip its own first `offset` rows. The window has to be
@@ -3944,7 +4014,23 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
         max_batch_length: Optional[int] = None,
         timeout: Optional[timedelta] = None,
     ) -> AsyncRecordBatchReader:
-        fts_query, vec_query, limit, offset = self._create_child_queries()
+        # WAL-PK-FUSION: without the fallback, this body is `_run_hybrid`'s.
+        return await _wal_hybrid.with_pk_fallback_async(
+            lambda: self._run_hybrid(
+                max_batch_length=max_batch_length, timeout=timeout
+            ),
+            self._table,
+            fused=lambda: self._pk_fusion is not None,
+            caller_requested_row_id=self._user_requested_row_id(),
+        )
+
+    async def _run_hybrid(
+        self,
+        *,
+        max_batch_length: Optional[int] = None,
+        timeout: Optional[timedelta] = None,
+    ) -> AsyncRecordBatchReader:
+        fts_query, vec_query, limit, offset = await self._create_child_queries()
 
         req = fts_query._inner.to_query_request()
         blob_auto_row_id = False
@@ -3968,6 +4054,10 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
             fts_query.to_arrow(timeout=timeout),
             vec_query.to_arrow(timeout=timeout),
         )
+        if self._pk_fusion is not None:  # WAL-PK-FUSION: delete.
+            vector_results, fts_results = self._pk_fusion.stamp(
+                vector_results, fts_results
+            )
 
         result = LanceHybridQueryBuilder._combine_hybrid_results(
             fts_results=fts_results,
@@ -3979,7 +4069,9 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
             with_row_ids=True,
             offset=offset,
         )
-        if (
+        if self._pk_fusion is not None:  # WAL-PK-FUSION: delete this branch.
+            result = self._pk_fusion.strip(result)
+        elif (
             not self._user_requested_row_id()
             and not blob_auto_row_id
             and "_rowid" in result.column_names
@@ -4028,7 +4120,7 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
         plan : str
         """  # noqa: E501
 
-        fts_query, vec_query, _, _ = self._create_child_queries()
+        fts_query, vec_query, _, _ = await self._create_child_queries()
         vector_plan = await vec_query.explain_plan(verbose)
         fts_plan = await fts_query.explain_plan(verbose)
         # Indent sub-plans under the reranker
@@ -4057,7 +4149,7 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
         -------
         plan : str
         """
-        fts_query, vec_query, _, _ = self._create_child_queries()
+        fts_query, vec_query, _, _ = await self._create_child_queries()
 
         results = ["Vector Search Query:"]
         results.append(await vec_query.analyze_plan(distributed_metrics))

python/python/lancedb/remote/table.py

@@ -1036,6 +1036,14 @@ class RemoteTable(Table):
         """Read the installed LsmWriteSpec, or ``None``."""
         return LOOP.run(self._table.get_lsm_write_spec())
 
+    # WAL-PK-FUSION: delete both hooks.
+    def _hybrid_pk_fusion_learned(self) -> bool:
+        # `self._table` is the async table, which owns the Rust handle.
+        return self._table._hybrid_pk_fusion_learned()
+
+    def _note_hybrid_pk_fusion(self) -> None:
+        self._table._note_hybrid_pk_fusion()
+
     def checkpoint_lsm(self) -> None:
         """Synchronous version of
         [`AsyncTable.checkpoint_lsm`][lancedb.AsyncTable.checkpoint_lsm]."""

python/python/lancedb/table.py

@@ -2647,6 +2647,18 @@ class Table(ABC):
         to check if the table is already using the new path style.
         """
 
+    # WAL-PK-FUSION: delete both hooks, here and on AsyncTable and RemoteTable.
+    def _hybrid_pk_fusion_learned(self) -> bool:
+        """Whether a hybrid query here has already been refused ``_rowid``.
+
+        Learned from a refusal, never probed, so asking is free. ``False`` for
+        table types that never refuse.
+        """
+        return False
+
+    def _note_hybrid_pk_fusion(self) -> None:
+        """Remember a ``_rowid`` refusal, so later hybrid queries skip it."""
+
 
 class LanceTable(Table):
     """
@@ -5294,6 +5306,15 @@ class AsyncTable:
         """
         return await self._inner.get_lsm_write_spec()
 
+    # WAL-PK-FUSION: delete both hooks.
+    def _hybrid_pk_fusion_learned(self) -> bool:
+        """See [`Table._hybrid_pk_fusion_learned`][lancedb.table.Table]."""
+        return self._inner.hybrid_pk_fusion_learned()
+
+    def _note_hybrid_pk_fusion(self) -> None:
+        """See [`Table._note_hybrid_pk_fusion`][lancedb.table.Table]."""
+        self._inner.note_hybrid_pk_fusion()
+
     async def checkpoint_lsm(self) -> None:
         """Converge this table's LSM write path into its base table.
 

python/python/tests/test_wal_hybrid.py

@@ -0,0 +1,219 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+"""WAL-PK-FUSION: delete this file with `lancedb/_wal_hybrid.py`."""
+
+from unittest import mock
+
+import lancedb
+import pyarrow as pa
+import pytest
+from lancedb._wal_hybrid import WAL_ROW_ID_UNSUPPORTED, with_pk_fallback
+from lancedb.query import LanceHybridQueryBuilder
+from lancedb.rerankers import RRFReranker
+
+
+def _wal_table(schema: pa.Schema) -> mock.Mock:
+    """A MemWAL-backed table a previous query has already been refused
+    `_rowid` on, so the fusion goes straight to the primary key."""
+    table = mock.Mock()
+    table._hybrid_pk_fusion_learned.return_value = True
+    table.schema = schema
+    return table
+
+
+_PK_SCHEMA = pa.schema(
+    [
+        pa.field(
+            "id",
+            pa.string(),
+            metadata={b"lance-schema:unenforced-primary-key:position": b"1"},
+        ),
+        pa.field("text", pa.string()),
+    ]
+)
+
+
+def _wal_hybrid(**select):
+    builder = (
+        LanceHybridQueryBuilder(_wal_table(_PK_SCHEMA)).vector([0.1, 0.2]).text("puppy")
+    )
+    if "columns" in select:
+        builder = builder.select(select["columns"])
+    return builder
+
+
+def test_wal_hybrid_projects_the_key_instead_of_asking_for_row_ids():
+    builder = _wal_hybrid(columns=["text"])
+    builder._create_query_builders()
+
+    assert builder._pk_fusion.pk_columns == ["id"]
+    assert builder._pk_fusion.injected == ["id"]
+    for leg in (builder._vector_query, builder._fts_query):
+        assert leg._columns == ["text", "id"]
+        # A MemWAL table rejects with_row_id before it plans.
+        assert leg._with_row_id is not True
+
+
+def test_wal_hybrid_selecting_the_key_injects_nothing():
+    builder = _wal_hybrid(columns=["text", "id"])
+    builder._create_query_builders()
+    assert builder._pk_fusion.injected == []
+
+
+def test_wal_hybrid_without_a_projection_leaves_it_alone():
+    builder = _wal_hybrid()
+    builder._create_query_builders()
+    # Select-all already returns the key.
+    assert builder._pk_fusion.injected == []
+    assert builder._vector_query._columns is None
+
+
+def test_base_table_hybrid_still_joins_on_row_ids():
+    table = mock.Mock()
+    table._hybrid_pk_fusion_learned.return_value = False
+    builder = LanceHybridQueryBuilder(table).vector([0.1, 0.2]).text("puppy")
+    builder._create_query_builders()
+
+    # `to_arrow` is what turns row ids on for this path; all that matters here
+    # is that no key was resolved and no projection was touched.
+    assert builder._pk_fusion is None
+    assert builder._vector_query._columns is None
+
+
+def test_wal_hybrid_with_use_lsm_false_joins_on_row_ids():
+    builder = _wal_hybrid().use_lsm(False)
+    builder._create_query_builders()
+    assert builder._pk_fusion is None
+
+
+def test_wal_hybrid_refuses_an_explicit_with_row_id():
+    builder = _wal_hybrid().with_row_id(True)
+    with pytest.raises(NotImplementedError, match="use_lsm"):
+        builder._create_query_builders()
+
+
+def test_wal_hybrid_return_score_all_is_not_refused():
+    """`return_score="all"` turns row ids on for the reranker, not the caller."""
+    builder = _wal_hybrid().rerank(RRFReranker(return_score="all"))
+    builder._create_query_builders()
+    assert builder._pk_fusion.pk_columns == ["id"]
+
+
+def test_wal_hybrid_fuses_on_the_key_and_drops_it_again():
+    builder = _wal_hybrid(columns=["text"])
+    builder._create_query_builders()
+
+    vector_results = pa.table(
+        {"text": ["a", "b"], "id": ["a", "b"], "_distance": [0.1, 0.2]}
+    )
+    fts_results = pa.table({"text": ["b", "c"], "id": ["b", "c"], "_score": [1.0, 2.0]})
+    vector_results, fts_results = builder._pk_fusion.stamp(vector_results, fts_results)
+
+    combined = LanceHybridQueryBuilder._combine_hybrid_results(
+        fts_results=fts_results,
+        vector_results=vector_results,
+        norm="score",
+        fts_query="puppy",
+        reranker=RRFReranker(),
+        limit=10,
+        with_row_ids=True,
+    )
+    results = builder._finish_hybrid_results(combined)
+
+    assert "_rowid" not in results.column_names, "the surrogate is internal"
+    assert "id" not in results.column_names, "the caller selected only `text`"
+    assert sorted(results.column("text").to_pylist()) == ["a", "b", "c"]
+
+
+@pytest.mark.parametrize(
+    "row_id_first", [True, False], ids=["row_id_first", "rerank_first"]
+)
+def test_wal_hybrid_refuses_row_id_even_with_return_score_all(row_id_first: bool):
+    """`return_score="all"` sets the same flag the caller's request does, so
+    asking for both must still be refused — in either call order."""
+    builder = _wal_hybrid()
+    reranker = RRFReranker(return_score="all")
+    if row_id_first:
+        builder = builder.with_row_id(True).rerank(reranker)
+    else:
+        builder = builder.rerank(reranker).with_row_id(True)
+
+    with pytest.raises(NotImplementedError, match="use_lsm"):
+        builder._create_query_builders()
+
+
+def test_wal_hybrid_refuses_a_blob_projection_with_return_score_all():
+    """A projected blob needs a real row id to fetch through, which the
+    reranker turning `_with_row_id` on does not provide."""
+    schema = pa.schema(
+        [
+            pa.field(
+                "id",
+                pa.string(),
+                metadata={b"lance-schema:unenforced-primary-key:position": b"1"},
+            ),
+            pa.field("text", pa.string()),
+            lancedb.blob("blob"),
+        ]
+    )
+    builder = (
+        LanceHybridQueryBuilder(_wal_table(schema))
+        .vector([0.1, 0.2])
+        .text("puppy")
+        .select(["blob"])
+        .rerank(RRFReranker(return_score="all"))
+    )
+
+    with pytest.raises(NotImplementedError, match="blob"):
+        builder._create_query_builders()
+
+
+_REFUSAL = RuntimeError(
+    "Bad request: the MemWAL LSM scanner does not support with_row_id"
+)
+
+
+def test_fallback_retries_on_the_key_and_remembers_it():
+    table = mock.Mock()
+    attempts = []
+
+    def run():
+        attempts.append(len(attempts))
+        if len(attempts) == 1:
+            raise _REFUSAL
+        return "fused"
+
+    result = with_pk_fallback(
+        run, table, fused=lambda: False, caller_requested_row_id=False
+    )
+
+    assert result == "fused"
+    assert len(attempts) == 2
+    table._note_hybrid_pk_fusion.assert_called_once()
+
+
+def test_fallback_explains_the_refusal_to_a_caller_who_asked_for_row_ids():
+    def run():
+        raise _REFUSAL
+
+    with pytest.raises(NotImplementedError, match="use_lsm") as info:
+        with_pk_fallback(
+            run, mock.Mock(), fused=lambda: False, caller_requested_row_id=True
+        )
+    assert str(info.value) == WAL_ROW_ID_UNSUPPORTED
+
+
+@pytest.mark.parametrize(
+    "error, fused",
+    [(ValueError("unrelated"), False), (_REFUSAL, True)],
+    ids=["other_error", "already_fused"],
+)
+def test_fallback_reraises_what_it_cannot_retry(error, fused):
+    def run():
+        raise error
+
+    table = mock.Mock()
+    with pytest.raises(type(error)):
+        with_pk_fallback(run, table, fused=lambda: fused, caller_requested_row_id=False)
+    table._note_hybrid_pk_fusion.assert_not_called()

python/src/table.rs

@@ -1637,6 +1637,21 @@ impl Table {
         })
     }
 
+    /// Whether a hybrid query on this table has already been refused `_rowid`.
+    /// Learned from a previous refusal, never probed, so this is free.
+    ///
+    /// WAL-PK-FUSION: delete this and `note_hybrid_pk_fusion`.
+    pub fn hybrid_pk_fusion_learned(self_: PyRef<'_, Self>) -> PyResult<bool> {
+        Ok(self_.inner_ref()?.base_table().hybrid_pk_fusion_learned())
+    }
+
+    /// Remember that this table refused `_rowid`, so later hybrid queries skip
+    /// straight to the primary-key fusion.
+    pub fn note_hybrid_pk_fusion(self_: PyRef<'_, Self>) -> PyResult<()> {
+        self_.inner_ref()?.base_table().note_hybrid_pk_fusion();
+        Ok(())
+    }
+
     /// Converge the table's LSM write path into its base table.
     ///
     /// Best-effort: with writes flowing, new rows may land after the last