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feat(query): dedup hybrid search by primary key on MemWAL tables (#4268)
Implementing a PK-based dedup to support WAL in hybrid search. Basically, the existing code just calls a vector query + FTS query and dedups locally using the row ID. Since row ID is unsupported in WAL (currently), we update the algorithm to use the tables PK (which is required in WAL, and uniquely linked to a PK on updates). To enable PK-dedup branch, we've chosen to fallback on error rather than fire an exploratory query. Specifically, we issue the regular hybrid query, using row IDs, and when that fails with "WAL does not support row IDs" we fallback to the PK-based variant, and then cache the fallback for future calls from the same client. The alternative is that we chec if WAL is enabled before issuing the query. This would require a `get_lsm_write_spec` call, slowing down all the existing non-WAL paths unnecessarily. The ultimate goal is to get row ID supported in WAL, but that is pending stable row ID GA and subsequent integration into the enterprise stack. Once that lands, we will rip out the PK-based dedup that is only for WAL-enabled tables and use the existing row ID code. This is the main reason for building this adaptively. I had spec-ed out a refactor so that rather than duplicating code between python and rust we build this in rust and have python call that through PyO3. However, that made the reverse path (ie. ) more difficult. So I think the tradeoff of maintaining duplicate code in the short term for the ease of reverting this in the medium term (hopefully 2-3 months). --------- Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
This commit is contained in:
co-authored by
Claude Opus 5
parent
604b1b583b
commit
2216586023
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# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright The LanceDB Authors
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"""WAL-PK-FUSION: delete this file with `lancedb/_wal_hybrid.py`."""
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from unittest import mock
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import lancedb
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import pyarrow as pa
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import pytest
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from lancedb._wal_hybrid import WAL_ROW_ID_UNSUPPORTED, with_pk_fallback
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from lancedb.query import LanceHybridQueryBuilder
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from lancedb.rerankers import RRFReranker
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def _wal_table(schema: pa.Schema) -> mock.Mock:
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"""A MemWAL-backed table a previous query has already been refused
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`_rowid` on, so the fusion goes straight to the primary key."""
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table = mock.Mock()
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table._hybrid_pk_fusion_learned.return_value = True
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table.schema = schema
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return table
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_PK_SCHEMA = pa.schema(
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[
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pa.field(
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"id",
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pa.string(),
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metadata={b"lance-schema:unenforced-primary-key:position": b"1"},
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),
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pa.field("text", pa.string()),
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]
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)
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def _wal_hybrid(**select):
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builder = (
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LanceHybridQueryBuilder(_wal_table(_PK_SCHEMA)).vector([0.1, 0.2]).text("puppy")
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)
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if "columns" in select:
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builder = builder.select(select["columns"])
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return builder
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def test_wal_hybrid_projects_the_key_instead_of_asking_for_row_ids():
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builder = _wal_hybrid(columns=["text"])
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builder._create_query_builders()
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assert builder._pk_fusion.pk_columns == ["id"]
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assert builder._pk_fusion.injected == ["id"]
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for leg in (builder._vector_query, builder._fts_query):
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assert leg._columns == ["text", "id"]
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# A MemWAL table rejects with_row_id before it plans.
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assert leg._with_row_id is not True
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def test_wal_hybrid_selecting_the_key_injects_nothing():
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builder = _wal_hybrid(columns=["text", "id"])
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builder._create_query_builders()
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assert builder._pk_fusion.injected == []
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def test_wal_hybrid_without_a_projection_leaves_it_alone():
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builder = _wal_hybrid()
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builder._create_query_builders()
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# Select-all already returns the key.
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assert builder._pk_fusion.injected == []
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assert builder._vector_query._columns is None
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def test_base_table_hybrid_still_joins_on_row_ids():
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table = mock.Mock()
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table._hybrid_pk_fusion_learned.return_value = False
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builder = LanceHybridQueryBuilder(table).vector([0.1, 0.2]).text("puppy")
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builder._create_query_builders()
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# `to_arrow` is what turns row ids on for this path; all that matters here
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# is that no key was resolved and no projection was touched.
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assert builder._pk_fusion is None
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assert builder._vector_query._columns is None
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def test_wal_hybrid_with_use_lsm_false_joins_on_row_ids():
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builder = _wal_hybrid().use_lsm(False)
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builder._create_query_builders()
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assert builder._pk_fusion is None
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def test_wal_hybrid_refuses_an_explicit_with_row_id():
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builder = _wal_hybrid().with_row_id(True)
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with pytest.raises(NotImplementedError, match="use_lsm"):
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builder._create_query_builders()
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def test_wal_hybrid_return_score_all_is_not_refused():
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"""`return_score="all"` turns row ids on for the reranker, not the caller."""
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builder = _wal_hybrid().rerank(RRFReranker(return_score="all"))
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builder._create_query_builders()
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assert builder._pk_fusion.pk_columns == ["id"]
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def test_wal_hybrid_fuses_on_the_key_and_drops_it_again():
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builder = _wal_hybrid(columns=["text"])
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builder._create_query_builders()
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vector_results = pa.table(
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{"text": ["a", "b"], "id": ["a", "b"], "_distance": [0.1, 0.2]}
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)
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fts_results = pa.table({"text": ["b", "c"], "id": ["b", "c"], "_score": [1.0, 2.0]})
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vector_results, fts_results = builder._pk_fusion.stamp(vector_results, fts_results)
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combined = LanceHybridQueryBuilder._combine_hybrid_results(
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fts_results=fts_results,
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vector_results=vector_results,
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norm="score",
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fts_query="puppy",
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reranker=RRFReranker(),
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limit=10,
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with_row_ids=True,
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)
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results = builder._finish_hybrid_results(combined)
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assert "_rowid" not in results.column_names, "the surrogate is internal"
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assert "id" not in results.column_names, "the caller selected only `text`"
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assert sorted(results.column("text").to_pylist()) == ["a", "b", "c"]
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@pytest.mark.parametrize(
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"row_id_first", [True, False], ids=["row_id_first", "rerank_first"]
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)
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def test_wal_hybrid_refuses_row_id_even_with_return_score_all(row_id_first: bool):
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"""`return_score="all"` sets the same flag the caller's request does, so
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asking for both must still be refused — in either call order."""
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builder = _wal_hybrid()
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reranker = RRFReranker(return_score="all")
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if row_id_first:
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builder = builder.with_row_id(True).rerank(reranker)
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else:
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builder = builder.rerank(reranker).with_row_id(True)
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with pytest.raises(NotImplementedError, match="use_lsm"):
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builder._create_query_builders()
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def test_wal_hybrid_refuses_a_blob_projection_with_return_score_all():
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"""A projected blob needs a real row id to fetch through, which the
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reranker turning `_with_row_id` on does not provide."""
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schema = pa.schema(
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[
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pa.field(
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"id",
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pa.string(),
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metadata={b"lance-schema:unenforced-primary-key:position": b"1"},
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),
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pa.field("text", pa.string()),
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lancedb.blob("blob"),
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]
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)
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builder = (
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LanceHybridQueryBuilder(_wal_table(schema))
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.vector([0.1, 0.2])
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.text("puppy")
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.select(["blob"])
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.rerank(RRFReranker(return_score="all"))
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)
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with pytest.raises(NotImplementedError, match="blob"):
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builder._create_query_builders()
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_REFUSAL = RuntimeError(
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"Bad request: the MemWAL LSM scanner does not support with_row_id"
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)
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def test_fallback_retries_on_the_key_and_remembers_it():
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table = mock.Mock()
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attempts = []
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def run():
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attempts.append(len(attempts))
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if len(attempts) == 1:
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raise _REFUSAL
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return "fused"
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result = with_pk_fallback(
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run, table, fused=lambda: False, caller_requested_row_id=False
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)
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assert result == "fused"
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assert len(attempts) == 2
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table._note_hybrid_pk_fusion.assert_called_once()
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def test_fallback_explains_the_refusal_to_a_caller_who_asked_for_row_ids():
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def run():
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raise _REFUSAL
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with pytest.raises(NotImplementedError, match="use_lsm") as info:
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with_pk_fallback(
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run, mock.Mock(), fused=lambda: False, caller_requested_row_id=True
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)
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assert str(info.value) == WAL_ROW_ID_UNSUPPORTED
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@pytest.mark.parametrize(
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"error, fused",
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[(ValueError("unrelated"), False), (_REFUSAL, True)],
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ids=["other_error", "already_fused"],
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)
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def test_fallback_reraises_what_it_cannot_retry(error, fused):
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def run():
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raise error
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table = mock.Mock()
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with pytest.raises(type(error)):
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with_pk_fallback(run, table, fused=lambda: fused, caller_requested_row_id=False)
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table._note_hybrid_pk_fusion.assert_not_called()
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