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fix: support LargeList label list indexes (#3529)

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## Summary

This PR extends nested-field regression coverage across Rust
local/remote, Python sync/async, and Node so canonical escaped paths
stay consistent across scalar, vector, and FTS index lifecycle behavior.

It also aligns LanceDB's LabelList type gate with Lance by accepting
`LargeList<primitive>` columns while keeping `List<Struct<...>>`
unsupported until Lance defines stable membership semantics for struct
labels.

Part of #3406.
This commit is contained in:
Xuanwo
2026-06-10 23:53:56 +08:00
committed by GitHub
parent 9c12fb6437
commit 566b67a634
6 changed files with 638 additions and 20 deletions
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40
python/python/tests/test_table.py
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@@ -2399,18 +2399,32 @@ def test_create_scalar_index(mem_db: DBConnection):
def test_create_index_nested_field_paths(mem_db: DBConnection):
schema = pa.schema(
[
pa.field("rowId", pa.int32()),
pa.field("row-id", pa.int32()),
pa.field("userId", pa.int32()),
pa.field("metadata", pa.struct([pa.field("user_id", pa.int32())])),
pa.field("MetaData", pa.struct([pa.field("userId", pa.int32())])),
pa.field(
"image",
pa.struct([pa.field("embedding", pa.list_(pa.float32(), 2))]),
),
pa.field("payload", pa.struct([pa.field("text", pa.string())])),
pa.field("meta-data", pa.struct([pa.field("user-id", pa.int32())])),
pa.field("literal", pa.struct([pa.field("a.b", pa.int32())])),
]
)
data = pa.Table.from_pylist(
[
{
"rowId": i,
"row-id": i,
"userId": i,
"metadata": {"user_id": i},
"MetaData": {"userId": i},
"image": {"embedding": [float(i), float(i + 1)]},
"payload": {"text": f"document {i}"},
"meta-data": {"user-id": i},
"literal": {"a.b": i},
}
for i in range(256)
],
@@ -2418,19 +2432,37 @@ def test_create_index_nested_field_paths(mem_db: DBConnection):
)
table = mem_db.create_table("nested_index_paths", data=data)
table.create_scalar_index("rowId", name="row_id_idx")
table.create_scalar_index("`row-id`", name="row_dash_id_idx")
table.create_scalar_index("userId", name="top_user_id_idx")
table.create_scalar_index("metadata.user_id", name="metadata_user_id_idx")
table.create_scalar_index("MetaData.userId", name="mixed_case_metadata_user_id_idx")
table.create_scalar_index("`meta-data`.`user-id`", name="escaped_names_idx")
table.create_scalar_index("literal.`a.b`", name="literal_dot_idx")
table.create_index(
vector_column_name="image.embedding",
num_partitions=1,
num_sub_vectors=1,
name="image_embedding_idx",
)
table.create_fts_index("payload.text", with_position=False, name="payload_text_idx")
indices = sorted(table.list_indices(), key=lambda idx: idx.name)
assert [(idx.name, idx.index_type, idx.columns) for idx in indices] == [
("escaped_names_idx", "BTree", ["`meta-data`.`user-id`"]),
("image_embedding_idx", "IvfPq", ["image.embedding"]),
("literal_dot_idx", "BTree", ["literal.`a.b`"]),
("metadata_user_id_idx", "BTree", ["metadata.user_id"]),
("mixed_case_metadata_user_id_idx", "BTree", ["MetaData.userId"]),
("payload_text_idx", "FTS", ["payload.text"]),
("row_dash_id_idx", "BTree", ["`row-id`"]),
("row_id_idx", "BTree", ["rowId"]),
("top_user_id_idx", "BTree", ["userId"]),
]
for index in indices:
stats = table.index_stats(index.name)
assert stats is not None
assert stats.num_indexed_rows == 256
vector_results = (
table.search([0.0, 1.0], vector_column_name="image.embedding")
@@ -2448,6 +2480,14 @@ def test_create_index_nested_field_paths(mem_db: DBConnection):
assert len(filtered_results) == 1
assert filtered_results[0]["metadata"]["user_id"] == 42
escaped_results = table.search().where("`row-id` = 43").limit(1).to_list()
assert len(escaped_results) == 1
assert escaped_results[0]["row-id"] == 43
fts_results = table.search("document 44", query_type="fts").limit(1).to_list()
assert len(fts_results) == 1
assert fts_results[0]["payload"]["text"] == "document 44"
def test_empty_query(mem_db: DBConnection):
table = mem_db.create_table(