test: add regression coverage for metadata filter pagination beyond push-down cap (#16932)

### Summary

#16524 reports that a manual metadata filter matching more documents
than the ES push-down cap (`filter_doc_ids_by_meta_pushdown`'s default
`limit=10000`) drops documents once the request falls back to the
in-memory path — e.g. a `canon Not in ["0"]` filter over a
39,573-document KB where ~38,500 matching documents never come back.

I traced through the current code path for this exact scenario:
- `_filter_doc_ids_by_metadata_es` correctly detects when the match
total exceeds the push-down cap and bails to the in-memory fallback
instead of returning a truncated slice.
- `get_flatted_meta_by_kbs` (fixed by #16095) now fully paginates
through every document in the KB rather than stopping after the first
page.
- `es_conn.py`'s `search()` already switches to `search_after`-based
pagination once `offset + limit` would exceed ES's `max_result_window`
(10,000), so the outer pagination loop doesn't get cut off by that
ceiling either.
- `meta_filter()` then aggregates over the complete flattened metadata
with no additional cap.

I couldn't reproduce the drop against current `main` following that
path. This PR adds a test that simulates the exact reported scenario
(12,000 synthetic documents, `canon Not in ["0"]` matching all but 30 of
them) against a fake, paginated `docStoreConn` standing in for
Elasticsearch — both assertions pass on current `main`.

To make sure this is a meaningful regression test and not a false
positive, I temporarily reverted `get_flatted_meta_by_kbs` to stop after
the first page (the pre-#16095 behavior) and confirmed the test
correctly fails (970 of the expected 11,970 documents), then restored
the original code before committing.

Given all of that, it looks like #16524 may already be fixed by the
combination of #16095 and the existing `search_after` handling in
`es_conn.py`, but I could be missing something about the reporter's
specific deployment or a scenario I haven't considered (e.g. a
downstream cap once matched doc_ids feed into the content-chunk
retrieval query). I've left a comment on the issue with this same
analysis so a maintainer familiar with the history here can confirm or
point me at what I'm missing. Either way, this test is a useful
regression guard for the pagination behavior going forward.
This commit is contained in:
SYED ALI ABBAS RAHIL
2026-07-16 10:33:48 +09:00
committed by GitHub
parent 5c96fa51f0
commit bda703b588

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#
# Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
"""Regression test for #16524: a manual metadata filter over a knowledge base
with more documents than the ES push-down cap (``filter_doc_ids_by_meta_pushdown``'s
default ``limit=10000``) must still see every document once the request falls
back to the in-memory path, not just the first page.
Exercises ``DocMetadataService.get_flatted_meta_by_kbs`` end-to-end against a
fake, paginated ``docStoreConn`` standing in for Elasticsearch, then feeds the
result into ``meta_filter`` with the same ``not in`` condition from the
original report.
"""
from types import SimpleNamespace
import pytest
from common import settings
from common.metadata_utils import meta_filter
from api.db.services.doc_metadata_service import DocMetadataService
from api.db.db_models import DB
pytestmark = pytest.mark.p2
TOTAL_DOCS = 12000
CANON_ZERO_COUNT = 30 # a small minority tagged "0"; the rest are "1"
class _FakeDocStoreConn:
"""Stands in for the ES connection's paginated ``search``.
Mirrors the shape ``DocMetadataService._iter_search_results`` expects
(``{"hits": {"hits": [{"_id": ..., "_source": {...}}]}}``) and actually
honors ``offset``/``limit`` so a caller that stops paginating too early
provably sees a truncated result, the way the reported bug did.
"""
def __init__(self, total: int, canon_zero_count: int):
self._docs = []
for i in range(total):
canon = "0" if i < canon_zero_count else "1"
self._docs.append({"_id": f"doc-{i}", "_source": {"meta_fields": {"canon": canon}}})
def index_exist(self, index_name, kb_id):
return True
def search(self, select_fields, highlight_fields, condition, match_expressions, order_by, offset, limit, index_names, knowledgebase_ids, agg_fields=None, rank_feature=None):
page = self._docs[offset : offset + limit]
return {"hits": {"hits": page}}
def test_get_flatted_meta_by_kbs_returns_every_document_beyond_pushdown_cap(monkeypatch):
monkeypatch.setattr(DB, "connect", lambda *args, **kwargs: None)
monkeypatch.setattr(DB, "close", lambda *args, **kwargs: None)
monkeypatch.setattr(settings, "docStoreConn", _FakeDocStoreConn(TOTAL_DOCS, CANON_ZERO_COUNT))
monkeypatch.setattr(settings, "DOC_ENGINE_INFINITY", False)
fake_kb = SimpleNamespace(tenant_id="tenant-1")
monkeypatch.setattr("api.db.services.doc_metadata_service.Knowledgebase.get_by_id", lambda kb_id: fake_kb)
metas = DocMetadataService.get_flatted_meta_by_kbs(["kb-1"])
assert len(metas["canon"]["1"]) == TOTAL_DOCS - CANON_ZERO_COUNT
assert len(metas["canon"]["0"]) == CANON_ZERO_COUNT
def test_manual_not_in_filter_matches_every_document_beyond_pushdown_cap(monkeypatch):
# Same scenario as the #16524 report: a "canon Not in ['0']" manual filter
# over a KB whose match set (TOTAL_DOCS - CANON_ZERO_COUNT) exceeds the
# push-down cap, so this exercises the in-memory fallback exclusively.
monkeypatch.setattr(DB, "connect", lambda *args, **kwargs: None)
monkeypatch.setattr(DB, "close", lambda *args, **kwargs: None)
monkeypatch.setattr(settings, "docStoreConn", _FakeDocStoreConn(TOTAL_DOCS, CANON_ZERO_COUNT))
monkeypatch.setattr(settings, "DOC_ENGINE_INFINITY", False)
fake_kb = SimpleNamespace(tenant_id="tenant-1")
monkeypatch.setattr("api.db.services.doc_metadata_service.Knowledgebase.get_by_id", lambda kb_id: fake_kb)
metas = DocMetadataService.get_flatted_meta_by_kbs(["kb-1"])
doc_ids = meta_filter(metas, [{"key": "canon", "op": "not in", "value": ["0"]}])
assert len(doc_ids) == TOTAL_DOCS - CANON_ZERO_COUNT