Merge main into gatekeeper/fix-4260-1

This commit is contained in:
Gatefixer
2026-09-25 15:05:07 +00:00
16 changed files with 1620 additions and 106 deletions
+3
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@@ -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: ...
+282
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@@ -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()
+111 -19
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@@ -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))
+8
View File
@@ -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]."""
+21
View File
@@ -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.
+219
View File
@@ -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()
+15
View File
@@ -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
+1 -1
View File
@@ -1,6 +1,6 @@
[package]
name = "lance-arrow"
version = "13.0.0-beta.12"
version = "13.0.0-beta.14"
edition = "2024"
authors = ["Lance Devs <dev@lance.org>"]
license = "Apache-2.0"
+2 -2
View File
@@ -1,5 +1,5 @@
This directory contains `rust/lance-arrow` from Lance tag `v13.0.0-beta.12`
(commit `5d2946fa452c61cb018144f3200892b6dd4a8b4f`), licensed under Apache-2.0.
This directory contains `rust/lance-arrow` from Lance tag `v13.0.0-beta.14`
(commit `b80ac1d9f3c24b47bd8e297d03053ea35d216a9f`), licensed under Apache-2.0.
LanceDB carries a local fix in `src/lib.rs` for sliced child validity bitmaps
until a Lance release includes the fix. The patch is selected in the root