Merge remote-tracking branch 'origin/main' into gatekeeper/fix-1869-1

# Conflicts:
#	python/python/tests/test_table.py

nodejs/__test__/arrow.test.ts

@@ -197,6 +197,35 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
         expect(table.getChild("d")?.toJSON()).toEqual([9n, 10n, null]);
       });
 
+      it("will use a provided FixedSizeList schema with typed array values", function () {
+        const schema = new Schema([
+          new Field("text", new Utf8(), false),
+          new Field(
+            "vector",
+            new FixedSizeList(3, new Field("item", new Float32(), false)),
+            false,
+          ),
+        ]);
+
+        const table = makeArrowTable(
+          [
+            {
+              text: "foo",
+              vector: new Float32Array([1, 2, 3]),
+            },
+          ],
+          { schema },
+        );
+
+        expect(table.getChild("text")?.toJSON()).toEqual(["foo"]);
+        expect(
+          table
+            .getChild("vector")
+            ?.toJSON()
+            .map((value) => value.toJSON()),
+        ).toEqual([[1, 2, 3]]);
+      });
+
       it("will assume the column `vector` is FixedSizeList<Float32> by default", async function () {
         const schema = new Schema([
           new Field("a", new Float(Precision.DOUBLE), true),

nodejs/__test__/remote.test.ts

@@ -170,6 +170,38 @@ describe("remote connection", () => {
     );
   });
 
+  it("surfaces JSON server errors from remote table operations", async () => {
+    await withMockDatabase(
+      (req, res) => {
+        const path = req.url ?? "";
+        if (path.endsWith("/describe/")) {
+          res.writeHead(200, { "Content-Type": "application/json" }).end(
+            JSON.stringify({
+              name: "broken_table",
+              version: 1,
+              schema: { fields: [] },
+            }),
+          );
+          return;
+        }
+
+        if (path.endsWith("/count_rows/")) {
+          res
+            .writeHead(400, { "Content-Type": "application/json" })
+            .end(JSON.stringify({ error: "count rows failed" }));
+          return;
+        }
+
+        res.writeHead(404).end();
+      },
+      async (db) => {
+        const table = await db.openTable("broken_table");
+
+        await expect(table.countRows()).rejects.toThrow("count rows failed");
+      },
+    );
+  });
+
   it("should pass on requested extra headers", async () => {
     await withMockDatabase(
       (req, res) => {

nodejs/__test__/table.test.ts

@@ -86,6 +86,44 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
       await expect(table.countRows()).resolves.toBe(3);
     });
 
+    it("should support a foreign Float64 vector schema end to end", async () => {
+      const conn = await connect(tmpDir.name);
+      const schema = new arrow.Schema([
+        new arrow.Field("resource_id", new arrow.Int32(), false),
+        new arrow.Field(
+          "vector",
+          new arrow.FixedSizeList(
+            3,
+            new arrow.Field("value", new arrow.Float64(), true),
+          ),
+          false,
+        ),
+      ]);
+      const data = [
+        {
+          // biome-ignore lint/style/useNamingConvention: matches the reported schema
+          resource_id: 0,
+          vector: [0.1, 0.1, 0.1],
+        },
+      ];
+
+      const resources = await conn.createTable("resources", data, { schema });
+
+      const existing = await resources
+        .query()
+        .where("resource_id = 0")
+        .limit(1)
+        .toArray();
+      expect(existing).toHaveLength(1);
+
+      const matched = await resources
+        .search(Float64Array.from(data[0].vector))
+        .limit(1)
+        .toArray();
+      expect(matched).toHaveLength(1);
+      expect(matched[0]["resource_id"]).toBe(0);
+    });
+
     it("should support branches", async () => {
       await table.add([{ id: 1 }]);
       expect(await table.countRows()).toBe(1);

python/Cargo.toml

@@ -26,7 +26,7 @@ lance-namespace-impls.workspace = true
 lance-io.workspace = true
 env_logger.workspace = true
 log.workspace = true
-pyo3 = { version = "0.28", features = ["extension-module", "abi3-py39", "chrono"] }
+pyo3 = { version = "0.28", features = ["extension-module", "abi3-py310", "chrono"] }
 chrono = { version = "0.4", default-features = false, features = ["clock"] }
 pyo3-async-runtimes = { version = "0.28", features = [
     "attributes",
@@ -43,7 +43,7 @@ libc = "0.2"
 [build-dependencies]
 pyo3-build-config = { version = "0.28", features = [
     "extension-module",
-    "abi3-py39",
+    "abi3-py310",
 ] }
 
 [features]

python/python/lancedb/embeddings/instructor.py

@@ -101,8 +101,7 @@ class InstructorEmbeddingFunction(TextEmbeddingFunction):
 
     @weak_lru(maxsize=1)
     def ndims(self):
-        model = self.get_model()
-        return model.encode("foo").shape[0]
+        return len(self.generate_embeddings([[self.source_instruction, "foo"]])[0])
 
     def compute_query_embeddings(self, query: str, *args, **kwargs) -> List[np.array]:
         return self.generate_embeddings([[self.query_instruction, query]])

python/python/lancedb/util.py

@@ -395,6 +395,11 @@ def _(value: dict):
     )
 
 
+@value_to_sql.register(pa.Scalar)
+def _(value: pa.Scalar):
+    return value_to_sql(value.as_py())
+
+
 @value_to_sql.register(np.ndarray)
 def _(value: np.ndarray):
     return value_to_sql(value.tolist())

python/python/tests/test_db.py

@@ -2,6 +2,7 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
 
+import inspect
 import re
 import sys
 from datetime import timedelta
@@ -62,17 +63,23 @@ def test_basic(tmp_path):
     assert db.open_table("test").name == db["test"].name
 
 
-def test_sync_repr_does_not_use_background_loop(tmp_path, monkeypatch):
+def test_sync_debugger_inspection_does_not_use_background_loop(tmp_path, monkeypatch):
     from lancedb.background_loop import LOOP
 
     db = lancedb.connect(tmp_path)
     table = db.create_table("test", data=[{"id": 1}])
 
     def fail_run(*args, **kwargs):
-        raise AssertionError("repr should not use the Python background loop")
+        raise AssertionError("debugger inspection should not use the background loop")
 
     monkeypatch.setattr(LOOP, "run", fail_run)
 
+    # Debuggers enumerate and evaluate every exposed attribute when expanding a
+    # variable. This must remain safe while their breakpoint suspends LOOP's thread.
+    members = dict(inspect.getmembers(db))
+
+    assert members["uri"] == str(tmp_path)
+    assert members["read_consistency_interval"] is None
     assert repr(db) == f"LanceDBConnection(uri={str(tmp_path)!r})"
     assert repr(table) == f"LanceTable(name='test', _conn={db!r})"
 

python/python/tests/test_embeddings.py

@@ -64,6 +64,23 @@ def test_embedding_function(tmp_path):
     assert np.allclose(actual, expected)
 
 
+def test_instructor_ndims_uses_instruction():
+    instructor = get_registry().get("instructor").create()
+    model = MagicMock()
+    model.encode.return_value = np.zeros((1, 384))
+
+    with patch.object(type(instructor), "get_model", return_value=model):
+        assert instructor.ndims() == 384
+
+    model.encode.assert_called_once_with(
+        [[instructor.source_instruction, "foo"]],
+        batch_size=instructor.batch_size,
+        show_progress_bar=instructor.show_progress_bar,
+        normalize_embeddings=instructor.normalize_embeddings,
+        device=instructor.device,
+    )
+
+
 def test_embedding_function_variables():
     @register("variable-testing")
     class VariableTestingFunction(TextEmbeddingFunction):
@@ -115,34 +132,16 @@ def test_embedding_function_variables():
     assert func.safe_model_dump()["secret_key"] == "$var:secret"
 
 
-def test_parse_functions_with_variables():
-    @register("variable-parsing-test")
-    class VariableParsingFunction(TextEmbeddingFunction):
-        api_key: str
-        base_url: Optional[str] = None
-
-        @staticmethod
-        def sensitive_keys():
-            return ["api_key"]
-
-        def ndims(self):
-            return 10
-
-        def generate_embeddings(self, texts):
-            # Mock implementation that just returns random embeddings
-            # In real usage, this would use the api_key to call an API
-            return [np.random.rand(self.ndims()).tolist() for _ in texts]
-
+def test_openai_variables_survive_metadata_round_trip():
     registry = EmbeddingFunctionRegistry.get_instance()
 
     registry.set_var("test_api_key", "sk-test-key-12345")
-    registry.set_var("test_base_url", "https://api.example.com")
 
     conf = EmbeddingFunctionConfig(
         source_column="text",
         vector_column="vector",
-        function=registry.get("variable-parsing-test").create(
-            api_key="$var:test_api_key", base_url="$var:test_base_url"
+        function=registry.get("openai").create(
+            api_key="$var:test_api_key", base_url="https://api.example.com"
         ),
     )
 
@@ -150,7 +149,10 @@ def test_parse_functions_with_variables():
 
     # Create a mock arrow table with the metadata
     schema = pa.schema(
-        [pa.field("text", pa.string()), pa.field("vector", pa.list_(pa.float32(), 10))]
+        [
+            pa.field("text", pa.string()),
+            pa.field("vector", pa.list_(pa.float32(), 1536)),
+        ]
     )
     table = pa.table({"text": [], "vector": []}, schema=schema)
     table = table.replace_schema_metadata(metadata)
@@ -164,13 +166,15 @@ def test_parse_functions_with_variables():
 
     assert parsed_func.api_key == "sk-test-key-12345"
     assert parsed_func.base_url == "https://api.example.com"
-
-    embeddings = parsed_func.generate_embeddings(["test text"])
-    assert len(embeddings) == 1
-    assert len(embeddings[0]) == 10
-
     assert parsed_func.safe_model_dump()["api_key"] == "$var:test_api_key"
 
+    with patch("lancedb.embeddings.openai.attempt_import_or_raise") as import_openai:
+        parsed_func._openai_client
+
+    import_openai.return_value.OpenAI.assert_called_once_with(
+        api_key="sk-test-key-12345", base_url="https://api.example.com"
+    )
+
 
 def test_embedding_with_bad_results(tmp_path):
     @register("null-embedding")

python/python/tests/test_hybrid_query.py

@@ -12,7 +12,7 @@ import pyarrow.compute as pc
 import pytest
 import pytest_asyncio
 
-from lancedb.index import FTS
+from lancedb.index import BTree, FTS, IvfPq
 from lancedb.table import AsyncTable, Table
 
 
@@ -99,6 +99,86 @@ async def test_async_hybrid_query_filters(table: AsyncTable):
     assert result["text"].to_pylist() == ["cat", "b"]
 
 
+@pytest.mark.asyncio
+async def test_hybrid_query_with_stale_fixed_size_binary_prefilter(
+    tmpdir_factory,
+):
+    tmp_path = str(tmpdir_factory.mktemp("stale_scalar_prefilter"))
+    db = await lancedb.connect_async(tmp_path)
+
+    def fixed_size_binary(value: int) -> bytes:
+        return value.to_bytes(16, byteorder="big")
+
+    num_rows = 1000
+    data = pa.table(
+        {
+            "space_id": pa.array(
+                [fixed_size_binary(i) for i in range(num_rows)],
+                type=pa.binary(16),
+            ),
+            "text": ["book"] * num_rows,
+            "vector": pa.array(
+                [[float(i), float(i)] for i in range(num_rows)],
+                type=pa.list_(pa.float32(), 2),
+            ),
+        }
+    )
+    table = await db.create_table("test", data)
+    await table.create_index(
+        "vector", config=IvfPq(num_partitions=4, num_sub_vectors=2)
+    )
+    await table.create_index("space_id", config=BTree())
+    await table.create_index("text", config=FTS(with_position=False))
+
+    # Advance the search indices without advancing the scalar index. This is the
+    # state that previously let hybrid search use an incomplete scalar prefilter.
+    await table.add(data)
+    lance_dataset = await table.to_lance()
+    lance_dataset.optimize.optimize_indices(index_names=["vector_idx", "text_idx"])
+    await table.checkout_latest()
+
+    scalar_stats = await table.index_stats("space_id_idx")
+    assert scalar_stats is not None
+    assert scalar_stats.num_indexed_rows == num_rows
+    assert scalar_stats.num_unindexed_rows == num_rows
+
+    for index_name in ["vector_idx", "text_idx"]:
+        search_stats = await table.index_stats(index_name)
+        assert search_stats is not None
+        assert search_stats.num_indexed_rows == num_rows * 2
+        assert search_stats.num_unindexed_rows == 0
+
+    matching_ids = [5, 10, 15, 20, 25, 30]
+    literals = [
+        f"arrow_cast(0x{fixed_size_binary(i).hex()}, 'FixedSizeBinary(16)')"
+        for i in matching_ids
+    ]
+    predicate = f"space_id IN ({', '.join(literals)})"
+    expected_ids = sorted(fixed_size_binary(i) for i in matching_ids for _ in range(2))
+
+    vector_query = (
+        table.query().where(predicate).nearest_to([5.0, 5.0]).limit(num_rows * 2)
+    )
+    vector_results = await vector_query.to_arrow()
+    assert sorted(vector_results["space_id"].to_pylist()) == expected_ids
+
+    fts_query = (
+        table.query().where(predicate).nearest_to_text("book").limit(num_rows * 2)
+    )
+    fts_results = await fts_query.to_arrow()
+    assert sorted(fts_results["space_id"].to_pylist()) == expected_ids
+
+    hybrid_results = await (
+        table.query()
+        .where(predicate)
+        .nearest_to([5.0, 5.0])
+        .nearest_to_text("book")
+        .limit(num_rows * 2)
+        .to_arrow()
+    )
+    assert sorted(hybrid_results["space_id"].to_pylist()) == expected_ids
+
+
 @pytest.mark.asyncio
 async def test_async_hybrid_query_default_limit(table: AsyncTable):
     # add 10 new rows

python/python/tests/test_import.py

@@ -0,0 +1,33 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+import re
+import shutil
+import subprocess
+import sys
+
+import lancedb._lancedb as _lancedb
+import pytest
+
+
+@pytest.mark.skipif(sys.platform != "linux", reason="ldd is Linux-specific")
+def test_native_extension_does_not_link_openssl():
+    """OpenSSL-linked wheels abort when imported on RHEL hosts in FIPS mode."""
+    ldd = shutil.which("ldd")
+    if ldd is None:
+        pytest.skip("ldd is not installed")
+
+    result = subprocess.run(
+        [ldd, _lancedb.__file__],
+        check=True,
+        capture_output=True,
+        text=True,
+    )
+    openssl_libraries = re.findall(
+        r"^\s*(lib(?:crypto|ssl)\S*)\s+=>", result.stdout, flags=re.MULTILINE
+    )
+
+    assert not openssl_libraries, (
+        "the LanceDB native extension must use rustls instead of linking OpenSSL: "
+        f"{openssl_libraries}"
+    )

python/python/tests/test_index.py

@@ -372,6 +372,31 @@ async def test_create_vector_index(some_table: AsyncTable):
     assert stats.num_indices == 1
 
 
+@pytest.mark.asyncio
+async def test_create_ivf_index_reports_unsplittable_partitions(db_async):
+    dim = 8
+    num_partitions = 300  # More than 256 selects hierarchical k-means.
+    base_vectors = [[float(row == column) for column in range(dim)] for row in range(5)]
+    vectors = pa.array(base_vectors * 200, pa.list_(pa.float32(), dim))
+    table = await db_async.create_table(
+        "unsplittable_partitions",
+        pa.table({"vector": vectors}),
+    )
+
+    error_pattern = (
+        rf"Cannot create {num_partitions} IVF partitions: k-means could only form"
+    )
+    with pytest.raises(RuntimeError, match=error_pattern):
+        await table.create_index(
+            "vector",
+            config=IvfFlat(
+                distance_type="dot",
+                num_partitions=num_partitions,
+                max_iterations=10,
+            ),
+        )
+
+
 @pytest.mark.asyncio
 async def test_create_4bit_ivfpq_index(some_table: AsyncTable):
     # Can create

python/python/tests/test_package_metadata.py

@@ -0,0 +1,42 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+import importlib
+import re
+import sys
+from pathlib import Path
+
+import pytest
+
+
+def test_pyo3_abi_matches_minimum_supported_python():
+    project_dir = Path(__file__).parents[2]
+    pyproject = (project_dir / "pyproject.toml").read_text()
+    cargo_manifest = (project_dir / "Cargo.toml").read_text()
+
+    minimum_python = re.search(
+        r'^requires-python\s*=\s*">=(\d+)\.(\d+)"$', pyproject, re.MULTILINE
+    )
+    assert minimum_python is not None
+
+    major, minor = minimum_python.groups()
+    expected_abi = f"abi3-py{major}{minor}"
+    configured_abis = re.findall(r'"(abi3-py\d+)"', cargo_manifest)
+
+    assert configured_abis == [expected_abi, expected_abi], (
+        "the pyo3 runtime and build ABI features must both match requires-python"
+    )
+
+
+@pytest.mark.skipif(sys.platform != "win32", reason="Windows wheel regression test")
+def test_windows_wheel_tag_and_native_import():
+    project_dir = Path(__file__).parents[2]
+    wheels = list((project_dir.parent / "target" / "wheels").glob("lancedb-*.whl"))
+    if not wheels:
+        pytest.skip("no wheel artifact is available in this development environment")
+
+    assert len(wheels) == 1
+    assert wheels[0].name.endswith("-cp310-abi3-win_amd64.whl")
+
+    native_module = importlib.import_module("lancedb._lancedb")
+    assert Path(native_module.__file__).suffix == ".pyd"

python/python/tests/test_remote_db.py

@@ -35,6 +35,12 @@ def make_mock_http_handler(handler):
     return MockLanceDBHandler
 
 
+@pytest.mark.parametrize("db_name", ["a" * 64, "invalid..database"])
+def test_connect_rejects_invalid_cloud_dns_hostname(db_name):
+    with pytest.raises(ValueError, match="DNS labels must contain 1 to 63 bytes"):
+        lancedb.connect(f"db://{db_name}", api_key="fake")
+
+
 @contextlib.contextmanager
 def mock_lancedb_connection(handler):
     with http.server.HTTPServer(

python/python/tests/test_table.py

@@ -2,10 +2,13 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
 
+import ctypes
+import gc
 import os
 import sys
 import threading
 import warnings
+import weakref
 from concurrent.futures import ThreadPoolExecutor
 from datetime import date, datetime, timedelta
 from decimal import Decimal
@@ -100,6 +103,30 @@ def test_basic(mem_db: DBConnection):
     assert table.to_arrow() == expected_data
 
 
+def test_search_preserves_nulls_from_sliced_arrow_table(mem_db: DBConnection):
+    data = pa.table(
+        {
+            "id": [0, 1, 2, 3, 4],
+            "score_cn": [None, 22, None, 5, 8],
+            "score_mt": [None, 42, None, 5, 8],
+            "vector": [
+                [20, 19, -1, -1],
+                [41, 38, 22, 42],
+                [10, 10, -1, -1],
+                [5, 5, 5, 5],
+                [8, 8, 8, 8],
+            ],
+        }
+    ).slice(1)
+
+    table = mem_db.create_table("sliced_nullable", data=data)
+    result = table.search([41, 38, 22, 42]).limit(1).to_arrow()
+
+    assert result["id"].to_pylist() == [1]
+    assert result["score_cn"].to_pylist() == [22]
+    assert result["score_mt"].to_pylist() == [42]
+
+
 def test_table_to_pandas_default_matches_arrow(tmp_db: DBConnection):
     pd = pytest.importorskip("pandas")
     data = pa.table({"id": [1, 2], "text": ["one", "two"]})
@@ -451,6 +478,38 @@ def test_add(mem_db: DBConnection):
     _add(table, schema)
 
 
+def test_add_releases_arrow_buffers_without_gc(mem_db: DBConnection):
+    """Regression test for https://github.com/lancedb/lancedb/issues/2512."""
+    schema = pa.schema([pa.field("x", pa.int64())])
+    table = mem_db.create_table("test_add_releases_arrow_buffers", schema=schema)
+
+    class BufferOwner:
+        def __init__(self, size: int):
+            self.memory = ctypes.create_string_buffer(size)
+
+    owner_refs = []
+    gc_was_enabled = gc.isenabled()
+    gc.disable()
+    try:
+        for _ in range(3):
+            size = 8 * 1024
+            owner = BufferOwner(size)
+            arrow_buffer = pa.foreign_buffer(
+                ctypes.addressof(owner.memory), size, owner
+            )
+            array = pa.Array.from_buffers(pa.int64(), 1024, [None, arrow_buffer])
+            batch = pa.RecordBatch.from_arrays([array], schema=schema)
+            owner_refs.append(weakref.ref(owner))
+
+            table.add(batch)
+            del batch, array, arrow_buffer, owner
+
+        assert all(owner_ref() is None for owner_ref in owner_refs)
+    finally:
+        if gc_was_enabled:
+            gc.enable()
+
+
 def test_add_write_parallelism(mem_db: DBConnection):
     schema = pa.schema([pa.field("id", pa.int64())])
     table = mem_db.create_table("test", schema=schema)
@@ -1841,6 +1900,33 @@ def test_add_nullable_struct_with_none(mem_db: DBConnection):
     assert result.column("data").to_pylist() == [{"x": 1.0}, None]
 
 
+def test_read_mostly_null_list_v2_2_page_boundary(tmp_path):
+    # Regression test for #3194. This row/value count crosses a v2.2 structural
+    # encoding page boundary where Lance 3.0.0 sliced repetition/definition
+    # levels by row offset and decoded child arrays at different lengths.
+    num_rows = 64_885
+    num_values = 217
+    list_type = pa.list_(pa.float32())
+    source = pa.table(
+        {
+            "id": np.arange(num_rows, dtype=np.int64),
+            "coords": pa.array(
+                [[1.0, 2.0, 3.0, 4.0]] * num_values + [None] * (num_rows - num_values),
+                type=list_type,
+            ),
+        }
+    )
+    db = lancedb.connect(
+        tmp_path,
+        storage_options={"new_table_data_storage_version": "2.2"},
+    )
+    table = db.create_table("test_sparse_nullable_list", data=source)
+
+    result = table.search().select(["id", "coords"]).limit(num_rows).to_arrow()
+
+    assert result.equals(source)
+
+
 def test_add_with_integer_embeddings_preserves_casting(mem_db: DBConnection):
     class Schema(LanceModel):
         text: str
@@ -2281,6 +2367,20 @@ def test_update_expr_filter_preserves_typed_semantics(mem_db: DBConnection):
     assert result.rows_updated == 2
 
 
+def test_update_with_arrow_scalar(mem_db: DBConnection):
+    schema = pa.schema({"id": pa.int64(), "vector": pa.list_(pa.float32(), 4)})
+    table = mem_db.create_table("my_table", schema=schema)
+    table.add([{"id": 1, "vector": [1.0, 2.0, 3.0, 4.0]}])
+
+    value = table.search().select(["vector"]).limit(1).to_arrow()["vector"][0]
+    assert isinstance(value, pa.FixedSizeListScalar)
+
+    result = table.update(where="id == 1", values={"vector": value})
+
+    assert result.rows_updated == 1
+    assert table.to_arrow()["vector"].to_pylist() == [[1.0, 2.0, 3.0, 4.0]]
+
+
 def test_update_types(mem_db: DBConnection):
     table = mem_db.create_table(
         "my_table",
@@ -2448,6 +2548,55 @@ def test_merge_insert(mem_db: DBConnection):
         )
 
 
+def test_merge_insert_nullable_pandas_into_pydantic_schema(mem_db: DBConnection):
+    # Regression test for https://github.com/lancedb/lancedb/issues/2366
+    pd = pytest.importorskip("pandas")
+
+    class Document(LanceModel):
+        id: int
+        title: str
+        content: str
+
+    table = mem_db.create_table("documents", schema=Document)
+    table.add(
+        pd.DataFrame(
+            {
+                "title": ["Old title", "Unchanged"],
+                "id": [2, 3],
+                "content": ["Old content", "Keep this"],
+            }
+        )
+    )
+
+    # Pandas produces nullable Arrow fields, in an order that differs from the
+    # non-nullable Pydantic schema. This is valid as long as the data has no nulls.
+    new_data = pd.DataFrame(
+        {
+            "title": ["Inserted", "Updated"],
+            "id": [1, 2],
+            "content": ["New row", "New content"],
+        }
+    )
+    result = (
+        table.merge_insert("id")
+        .when_matched_update_all()
+        .when_not_matched_insert_all()
+        .execute(new_data)
+    )
+
+    assert result.num_inserted_rows == 1
+    assert result.num_updated_rows == 1
+    expected = pa.Table.from_pylist(
+        [
+            {"id": 1, "title": "Inserted", "content": "New row"},
+            {"id": 2, "title": "Updated", "content": "New content"},
+            {"id": 3, "title": "Unchanged", "content": "Keep this"},
+        ],
+        schema=Document.to_arrow_schema(),
+    )
+    assert table.to_arrow().sort_by("id") == expected
+
+
 def test_merge_insert_by_source_delete_expr(mem_db: DBConnection):
     table = mem_db.create_table(
         "my_table",
@@ -2548,6 +2697,36 @@ def test_merge_insert_subschema(mem_db: DBConnection, data_format):
     assert table.to_arrow().sort_by("id") == expected
 
 
+def test_repeated_partial_merge_insert_with_scalar_index(mem_db: DBConnection):
+    def make_batch(start: int) -> pa.Table:
+        return pa.table(
+            {
+                "id": [f"id-{i:04}" for i in range(start, start + 100)],
+                "category": ["A"] * 100,
+                "value_a": [float(i) for i in range(start, start + 100)],
+                "value_b": [float(i) / 10 for i in range(100)],
+            }
+        )
+
+    table = mem_db.create_table("my_table", data=make_batch(0))
+    table.add(make_batch(100))
+    table.add(make_batch(200))
+    table.create_index("id", config=BTree())
+
+    ids = [f"id-{i:04}" for i in range(100, 200)]
+    for value in (999.0, 888.0):
+        result = (
+            table.merge_insert("id")
+            .when_matched_update_all()
+            .execute(pa.table({"id": ids, "value_a": [value] * 100}))
+        )
+        assert result.num_updated_rows == 100
+
+    actual = table.to_arrow().sort_by("id")
+    assert actual.num_rows == 300
+    assert actual["value_a"].to_pylist()[100:200] == [888.0] * 100
+
+
 @pytest.mark.asyncio
 async def test_merge_insert_async(mem_db_async: AsyncConnection):
     data = pa.table({"a": [1, 2, 3], "b": ["a", "b", "c"]})
@@ -3574,8 +3753,8 @@ def test_create_table_empty_list_no_schema_error(mem_db: DBConnection):
         mem_db.create_table("test_empty_no_schema", data=[])
 
 
-def test_add_table_with_empty_embeddings(tmp_path):
-    """Test exact scenario from issue #1968
+def test_create_table_without_data_with_vector_schema(tmp_path):
+    """Test exact scenario from issue #1968.
 
     Regression test for issue #1968:
     https://github.com/lancedb/lancedb/issues/1968
@@ -3587,6 +3766,9 @@ def test_add_table_with_empty_embeddings(tmp_path):
         embedding: Vector(16)
 
     table = db.create_table("test", schema=MySchema)
+    assert table.count_rows() == 0
+    assert table.schema == MySchema.to_arrow_schema()
+
     table.add(
         [{"text": "bar", "embedding": [0.1] * 16}],
         on_bad_vectors="drop",

python/python/tests/test_voyageai_embeddings.py

@@ -75,6 +75,22 @@ class TestVoyageAIModelRegistration:
         with pytest.raises(ValueError, match="not supported"):
             func.ndims()
 
+    def test_voyage3_source_embeddings_use_text_api(self, mock_voyageai_client):
+        """Regression test for text table data being sent to the multimodal API."""
+        mock_voyageai_client.tokenize.return_value = [["hello", "world"]]
+        mock_voyageai_client.embed.return_value.embeddings = [[0.1] * 1024]
+
+        registry = get_registry()
+        func = registry.get("voyageai").create(name="voyage-3")
+
+        embeddings = func.compute_source_embeddings("hello world")
+
+        assert embeddings == [[0.1] * 1024]
+        mock_voyageai_client.embed.assert_called_once_with(
+            texts=["hello world"], model="voyage-3", input_type="document"
+        )
+        mock_voyageai_client.multimodal_embed.assert_not_called()
+
     @pytest.mark.parametrize(
         "model_name",
         [

rust/lancedb/Cargo.toml

@@ -75,6 +75,8 @@ reqwest = { version = "0.12.0", default-features = false, features = [
     "http2",
     "json",
     "macos-system-configuration",
+    # Avoid linking OpenSSL into Python wheels, which breaks on FIPS hosts.
+    "rustls-tls-native-roots",
     "stream",
 ], optional = true }
 http = { version = "1", optional = true } # Matching what is in reqwest

rust/lancedb/src/connection/create_table.rs

@@ -202,6 +202,17 @@ mod tests {
         assert_eq!(table.count_rows(None).await.unwrap(), 0);
     }
 
+    #[tokio::test]
+    async fn create_table_in_named_memory_database() {
+        let db = connect("memory://foo").execute().await.unwrap();
+        let batch = record_batch!(("id", Int64, [1, 2, 3])).unwrap();
+
+        let table = db.create_table("my_table", batch).execute().await.unwrap();
+
+        assert_eq!(table.uri().await.unwrap(), "memory://foo/my_table.lance");
+        assert_eq!(table.count_rows(None).await.unwrap(), 3);
+    }
+
     async fn test_create_table_with_data<T>(data: T)
     where
         T: Scannable + 'static,

rust/lancedb/src/database/listing.rs

@@ -1376,6 +1376,68 @@ mod tests {
         assert!(!tempdir.path().join("__manifest").exists());
     }
 
+    /// Regression test for https://github.com/lancedb/lancedb/issues/1600.
+    ///
+    /// Opening a table used to create a separate object-store client instead of
+    /// reusing the one that successfully connected to the database.  Repeating
+    /// credential discovery made S3 table opens intermittent, especially in AWS
+    /// Lambda, and the failed open was reported as `TableNotFound`.
+    #[tokio::test]
+    async fn test_open_table_reuses_connection_object_store() {
+        let tempdir = tempdir().unwrap();
+        let uri = tempdir.path().to_str().unwrap();
+        let registry = Arc::new(lance_io::object_store::ObjectStoreRegistry::default());
+        let session = Arc::new(lance::session::Session::new(16, 16, registry.clone()));
+
+        let request = ConnectRequest {
+            uri: uri.to_string(),
+            #[cfg(feature = "remote")]
+            client_config: Default::default(),
+            options: Default::default(),
+            namespace_client_properties: Default::default(),
+            manifest_enabled: false,
+            read_consistency_interval: None,
+            session: Some(session),
+        };
+        let db = ListingDatabase::connect_with_options(&request)
+            .await
+            .unwrap();
+
+        let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
+        db.create_table(CreateTableRequest {
+            name: "test".to_string(),
+            namespace_path: vec![],
+            data: Box::new(RecordBatch::new_empty(schema)) as Box<dyn Scannable>,
+            mode: CreateTableMode::Create,
+            write_options: Default::default(),
+            location: None,
+            namespace_client: None,
+        })
+        .await
+        .unwrap();
+
+        let before_open = registry.stats();
+        for _ in 0..3 {
+            let table = db
+                .open_table(OpenTableRequest {
+                    name: "test".to_string(),
+                    namespace_path: vec![],
+                    index_cache_size: None,
+                    lance_read_params: None,
+                    location: None,
+                    namespace_client: None,
+                    managed_versioning: None,
+                })
+                .await
+                .unwrap();
+            assert_eq!(table.count_rows(None).await.unwrap(), 0);
+        }
+
+        let after_open = registry.stats();
+        assert_eq!(after_open.misses, before_open.misses);
+        assert!(after_open.hits >= before_open.hits + 3);
+    }
+
     #[tokio::test]
     async fn test_clone_table_basic() {
         let (_tempdir, db) = setup_database().await;

rust/lancedb/src/io/object_store.rs

@@ -132,9 +132,14 @@ impl ObjectStore for MirroringObjectStore {
         if to.primary_only() {
             self.primary.copy_opts(from, to, options).await
         } else {
-            self.secondary.copy_opts(from, to, options.clone()).await?;
-            self.primary.copy_opts(from, to, options).await?;
-            Ok(())
+            // The secondary store can be process-local and less durable than the
+            // primary, so a source written by another process may not exist here
+            // or may be evicted before the copy begins.
+            match self.secondary.copy_opts(from, to, options.clone()).await {
+                Ok(()) | Err(Error::NotFound { .. }) => {}
+                Err(err) => return Err(err),
+            }
+            self.primary.copy_opts(from, to, options).await
         }
     }
 }
@@ -192,7 +197,8 @@ mod test {
     use futures::TryStreamExt;
     use lance::{dataset::WriteParams, io::ObjectStoreParams};
     use lance_testing::datagen::{BatchGenerator, IncrementingInt32, RandomVector};
-    use object_store::local::LocalFileSystem;
+    use object_store::{local::LocalFileSystem, memory::InMemory};
+    use std::time::Duration;
     use tempfile;
 
     use crate::{
@@ -201,6 +207,139 @@ mod test {
         table::WriteOptions,
     };
 
+    #[derive(Debug)]
+    struct EvictBeforeCopyStore {
+        inner: Arc<dyn ObjectStore>,
+    }
+
+    impl std::fmt::Display for EvictBeforeCopyStore {
+        fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
+            write!(f, "EvictBeforeCopyStore")
+        }
+    }
+
+    #[async_trait]
+    impl ObjectStore for EvictBeforeCopyStore {
+        async fn put_opts(
+            &self,
+            location: &Path,
+            payload: PutPayload,
+            options: PutOptions,
+        ) -> Result<PutResult> {
+            self.inner.put_opts(location, payload, options).await
+        }
+
+        async fn put_multipart_opts(
+            &self,
+            location: &Path,
+            options: PutMultipartOptions,
+        ) -> Result<Box<dyn MultipartUpload>> {
+            self.inner.put_multipart_opts(location, options).await
+        }
+
+        async fn get_opts(&self, location: &Path, options: GetOptions) -> Result<GetResult> {
+            self.inner.get_opts(location, options).await
+        }
+
+        fn delete_stream(
+            &self,
+            locations: BoxStream<'static, Result<Path>>,
+        ) -> BoxStream<'static, Result<Path>> {
+            self.inner.delete_stream(locations)
+        }
+
+        fn list(&self, prefix: Option<&Path>) -> BoxStream<'static, Result<ObjectMeta>> {
+            self.inner.list(prefix)
+        }
+
+        async fn list_with_delimiter(&self, prefix: Option<&Path>) -> Result<ListResult> {
+            self.inner.list_with_delimiter(prefix).await
+        }
+
+        async fn copy_opts(&self, from: &Path, to: &Path, options: CopyOptions) -> Result<()> {
+            self.inner.delete(from).await?;
+            self.inner.copy_opts(from, to, options).await
+        }
+    }
+
+    #[tokio::test]
+    async fn test_copy_when_source_is_missing_from_secondary() {
+        let primary_dir = tempfile::tempdir().unwrap();
+        let secondary_dir = tempfile::tempdir().unwrap();
+        let primary: Arc<dyn ObjectStore> =
+            Arc::new(LocalFileSystem::new_with_prefix(primary_dir.path()).unwrap());
+        let secondary: Arc<dyn ObjectStore> =
+            Arc::new(LocalFileSystem::new_with_prefix(secondary_dir.path()).unwrap());
+        let store = MirroringObjectStore {
+            primary: primary.clone(),
+            secondary: secondary.clone(),
+        };
+        let staging = Path::from("_versions/1.manifest-staging");
+        let finalized = Path::from("_versions/1.manifest");
+
+        primary
+            .put(&staging, "manifest contents".into())
+            .await
+            .unwrap();
+
+        tokio::time::timeout(Duration::from_secs(5), store.copy(&staging, &finalized))
+            .await
+            .expect("copy should not hang when the secondary source is missing")
+            .unwrap();
+
+        let copied = primary
+            .get(&finalized)
+            .await
+            .unwrap()
+            .bytes()
+            .await
+            .unwrap();
+        assert_eq!(copied, "manifest contents");
+        assert!(matches!(
+            secondary.head(&finalized).await,
+            Err(Error::NotFound { .. })
+        ));
+    }
+
+    #[tokio::test]
+    async fn test_copy_when_secondary_source_disappears_after_head() {
+        let primary: Arc<dyn ObjectStore> = Arc::new(InMemory::new());
+        let secondary_inner: Arc<dyn ObjectStore> = Arc::new(InMemory::new());
+        let secondary: Arc<dyn ObjectStore> = Arc::new(EvictBeforeCopyStore {
+            inner: secondary_inner.clone(),
+        });
+        let store = MirroringObjectStore {
+            primary: primary.clone(),
+            secondary,
+        };
+        let staging = Path::from("_versions/1.manifest-staging");
+        let finalized = Path::from("_versions/1.manifest");
+
+        primary
+            .put(&staging, "manifest contents".into())
+            .await
+            .unwrap();
+        secondary_inner
+            .put(&staging, "manifest contents".into())
+            .await
+            .unwrap();
+
+        store.copy(&staging, &finalized).await.unwrap();
+
+        let copied = primary
+            .get(&finalized)
+            .await
+            .unwrap()
+            .bytes()
+            .await
+            .unwrap();
+        assert_eq!(copied, "manifest contents");
+        assert!(matches!(
+            secondary_inner.head(&finalized).await,
+            Err(Error::NotFound { .. })
+        ));
+    }
+
     // This test is ignored because lance 3.0 introduced LocalWriter optimization
     // that bypasses the object store wrapper for local writes. The mirroring feature
     // still works for remote/cloud storage, but can't be tested with local storage.

rust/lancedb/src/query.rs

@@ -1661,14 +1661,8 @@ mod tests {
 
     #[tokio::test]
     async fn test_setters_getters() {
-        // TODO: Switch back to memory://foo after https://github.com/lancedb/lancedb/issues/1051
-        // is fixed
-        let tmp_dir = tempdir().unwrap();
-        let dataset_path = tmp_dir.path().join("test.lance");
-        let uri = dataset_path.to_str().unwrap();
-
         let batches = make_test_batches();
-        let conn = connect(uri).execute().await.unwrap();
+        let conn = connect("memory://foo").execute().await.unwrap();
         let table = conn
             .create_table("my_table", batches)
             .execute()
@@ -1763,14 +1757,8 @@ mod tests {
 
     #[tokio::test]
     async fn test_execute() {
-        // TODO: Switch back to memory://foo after https://github.com/lancedb/lancedb/issues/1051
-        // is fixed
-        let tmp_dir = tempdir().unwrap();
-        let dataset_path = tmp_dir.path().join("test.lance");
-        let uri = dataset_path.to_str().unwrap();
-
         let batches = make_non_empty_batches();
-        let conn = connect(uri).execute().await.unwrap();
+        let conn = connect("memory://foo").execute().await.unwrap();
         let table = conn
             .create_table("my_table", batches)
             .execute()
@@ -1889,14 +1877,8 @@ mod tests {
 
     #[tokio::test]
     async fn test_select_with_transform() {
-        // TODO: Switch back to memory://foo after https://github.com/lancedb/lancedb/issues/1051
-        // is fixed
-        let tmp_dir = tempdir().unwrap();
-        let dataset_path = tmp_dir.path().join("test.lance");
-        let uri = dataset_path.to_str().unwrap();
-
         let batches = make_non_empty_batches();
-        let conn = connect(uri).execute().await.unwrap();
+        let conn = connect("memory://foo").execute().await.unwrap();
         let table = conn
             .create_table("my_table", batches)
             .execute()
@@ -1993,15 +1975,9 @@ mod tests {
 
     #[tokio::test]
     async fn test_execute_no_vector() {
-        // TODO: Switch back to memory://foo after https://github.com/lancedb/lancedb/issues/1051
-        // is fixed
-        let tmp_dir = tempdir().unwrap();
-        let dataset_path = tmp_dir.path().join("test.lance");
-        let uri = dataset_path.to_str().unwrap();
-
         // test that it's ok to not specify a query vector (just filter / limit)
         let batches = make_non_empty_batches();
-        let conn = connect(uri).execute().await.unwrap();
+        let conn = connect("memory://foo").execute().await.unwrap();
         let table = conn
             .create_table("my_table", batches)
             .execute()

rust/lancedb/src/remote/client.rs

@@ -373,6 +373,37 @@ pub fn parse_db_url(db_url: &str) -> Result<ParsedDbUrl> {
     Ok(ParsedDbUrl { db_name, db_prefix })
 }
 
+fn validate_dns_hostname(hostname: &str) -> Result<()> {
+    let ascii_hostname = match url::Host::parse(hostname) {
+        Ok(url::Host::Domain(hostname)) => hostname,
+        Ok(_) => {
+            return Err(Error::InvalidInput {
+                message: "LanceDB Cloud database URI or region produced a non-DNS hostname"
+                    .to_string(),
+            });
+        }
+        Err(err) => {
+            return Err(Error::InvalidInput {
+                message: format!(
+                    "LanceDB Cloud database URI or region produced an invalid hostname: {err}"
+                ),
+            });
+        }
+    };
+
+    if ascii_hostname.len() > 253
+        || ascii_hostname
+            .split('.')
+            .any(|label| label.is_empty() || label.len() > 63)
+    {
+        return Err(Error::InvalidInput {
+            message: "LanceDB Cloud database URI or region produced an invalid hostname: DNS labels must contain 1 to 63 bytes and the full hostname must not exceed 253 bytes".to_string(),
+        });
+    }
+
+    Ok(())
+}
+
 impl RestfulLanceDbClient<Sender> {
     fn get_timeout(passed: Option<Duration>, env_var: &str) -> Result<Option<Duration>> {
         if let Some(passed) = passed {
@@ -480,7 +511,11 @@ impl RestfulLanceDbClient<Sender> {
 
         let host = match host_override {
             Some(host_override) => host_override,
-            None => format!("https://{}.{}.api.lancedb.com", parsed_url.db_name, region),
+            None => {
+                let hostname = format!("{}.{}.api.lancedb.com", parsed_url.db_name, region);
+                validate_dns_hostname(&hostname)?;
+                format!("https://{hostname}")
+            }
         };
         debug!("Created client for host: {}", host);
         let retry_config = client_config.retry_config.clone().try_into()?;
@@ -1157,6 +1192,29 @@ mod tests {
         assert_eq!(headers.get("x-api-key").unwrap(), "api-key");
     }
 
+    #[test]
+    fn test_rejects_invalid_cloud_dns_hostname() {
+        let invalid_database_names = ["a".repeat(64), "invalid..database".to_string()];
+
+        for db_name in invalid_database_names {
+            let parsed_url = parse_db_url(&format!("db://{db_name}")).unwrap();
+            let error = RestfulLanceDbClient::<Sender>::try_new(
+                &parsed_url,
+                "us-east-1",
+                None,
+                HeaderMap::new(),
+                ClientConfig::default(),
+                None,
+            )
+            .unwrap_err();
+
+            assert!(
+                matches!(error, Error::InvalidInput { ref message } if message.contains("DNS labels must contain 1 to 63 bytes")),
+                "unexpected error: {error}"
+            );
+        }
+    }
+
     // Test implementation of HeaderProvider
     #[derive(Debug, Clone)]
     struct TestHeaderProvider {

rust/lancedb/src/remote/table.rs

@@ -2791,9 +2791,10 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
     }
 
     async fn index_stats(&self, index_name: &str) -> Result<Option<IndexStatistics>> {
+        let encoded_name = urlencoding::encode(index_name);
         let mut request = self.post_read(&format!(
-            "/v1/table/{}/index/{}/stats/",
-            self.identifier, index_name
+            "/v1/table/{}/index/{encoded_name}/stats/",
+            self.identifier
         ));
         let version = self.current_version().await;
         let mut body = serde_json::json!({ "version": version });
@@ -2820,9 +2821,10 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
     }
 
     async fn drop_index(&self, index_name: &str) -> Result<()> {
+        let encoded_name = urlencoding::encode(index_name);
         let request = self.apply_branch_query(self.client.post(&format!(
-            "/v1/table/{}/index/{}/drop/",
-            self.identifier, index_name
+            "/v1/table/{}/index/{encoded_name}/drop/",
+            self.identifier
         )));
         let (request_id, response) = self.send(request, true).await?;
         if response.status() == StatusCode::NOT_FOUND {
@@ -2835,9 +2837,10 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
     }
 
     async fn prewarm_index(&self, index_name: &str) -> Result<()> {
+        let encoded_name = urlencoding::encode(index_name);
         let request = self.client.post(&format!(
-            "/v1/table/{}/index/{}/prewarm/",
-            self.identifier, index_name
+            "/v1/table/{}/index/{encoded_name}/prewarm/",
+            self.identifier
         ));
         let (request_id, response) = self.send(request, true).await?;
         if response.status() == StatusCode::NOT_FOUND {
@@ -6489,6 +6492,41 @@ mod tests {
         assert!(matches!(e, Error::IndexNotFound { .. }));
     }
 
+    /// Index names are unvalidated, so reserved characters must be
+    /// percent-encoded or they restructure the request path.
+    #[tokio::test]
+    async fn test_per_index_paths_encode_reserved_characters() {
+        const NAME: &str = "my/index?a#b c";
+        const PREFIX: &str = "/v1/table/my_table/index/my%2Findex%3Fa%23b%20c";
+
+        let table = Table::new_with_handler("my_table", |request| {
+            assert_eq!(request.url().path(), format!("{PREFIX}/stats/"));
+            let body = serde_json::json!({
+              "num_indexed_rows": 1,
+              "num_unindexed_rows": 0,
+              "index_type": "IVF_PQ",
+              "distance_type": "l2"
+            });
+            http::Response::builder()
+                .status(200)
+                .body(serde_json::to_string(&body).unwrap())
+                .unwrap()
+        });
+        assert!(table.index_stats(NAME).await.unwrap().is_some());
+
+        let table = Table::new_with_handler("my_table", |request| {
+            assert_eq!(request.url().path(), format!("{PREFIX}/drop/"));
+            http::Response::builder().status(200).body("{}").unwrap()
+        });
+        table.drop_index(NAME).await.unwrap();
+
+        let table = Table::new_with_handler("my_table", |request| {
+            assert_eq!(request.url().path(), format!("{PREFIX}/prewarm/"));
+            http::Response::builder().status(200).body("{}").unwrap()
+        });
+        table.prewarm_index(NAME).await.unwrap();
+    }
+
     #[tokio::test]
     async fn test_set_lsm_write_spec_unsharded() {
         let table = Table::new_with_handler("my_table", |request| {

rust/lancedb/src/table/merge.rs

@@ -315,7 +315,10 @@ pub(crate) async fn execute_merge_insert(
 
 #[cfg(test)]
 mod tests {
-    use arrow_array::{Int32Array, RecordBatch, RecordBatchIterator, RecordBatchReader};
+    use arrow_array::builder::FixedSizeBinaryBuilder;
+    use arrow_array::{
+        Int32Array, RecordBatch, RecordBatchIterator, RecordBatchReader, StringArray, UInt64Array,
+    };
     use arrow_schema::{DataType, Field, Schema};
     use std::sync::Arc;
 
@@ -337,6 +340,42 @@ mod tests {
         Box::new(RecordBatchIterator::new(vec![Ok(batch)], schema))
     }
 
+    fn fixed_size_binary_merge_batch(
+        id_range: std::ops::Range<u64>,
+        price: u64,
+    ) -> Box<dyn RecordBatchReader + Send> {
+        let ids = id_range.collect::<Vec<_>>();
+        let mut id_builder = FixedSizeBinaryBuilder::new(16);
+        for id in &ids {
+            let mut bytes = [0; 16];
+            bytes[..8].copy_from_slice(&id.to_le_bytes());
+            id_builder.append_value(bytes).unwrap();
+        }
+
+        let schema = Arc::new(Schema::new(vec![
+            Field::new("id", DataType::FixedSizeBinary(16), false),
+            Field::new("id_as_int", DataType::UInt64, false),
+            Field::new("name", DataType::Utf8, false),
+            Field::new("market", DataType::Utf8, false),
+        ]));
+        let batch = RecordBatch::try_new(
+            schema.clone(),
+            vec![
+                Arc::new(id_builder.finish()),
+                Arc::new(UInt64Array::from_iter_values(ids.iter().copied())),
+                Arc::new(StringArray::from_iter_values(
+                    ids.iter().map(|id| format!("name{id}")),
+                )),
+                Arc::new(StringArray::from_iter_values(std::iter::repeat_n(
+                    format!("market_{price}"),
+                    ids.len(),
+                ))),
+            ],
+        )
+        .unwrap();
+        Box::new(RecordBatchIterator::new(vec![Ok(batch)], schema))
+    }
+
     #[tokio::test]
     async fn test_merge_insert() {
         let conn = connect("memory://").execute().await.unwrap();
@@ -388,6 +427,36 @@ mod tests {
         );
     }
 
+    #[tokio::test]
+    async fn test_merge_insert_fixed_size_binary_non_nullable() {
+        // Regression test for #2869: an unrelated FixedSizeBinary column used to corrupt the
+        // outer join that implements when_not_matched_by_source_delete.
+        let conn = connect("memory://").execute().await.unwrap();
+        let table = conn
+            .create_table(
+                "fixed_size_binary_merge",
+                fixed_size_binary_merge_batch(0..256, 100),
+            )
+            .execute()
+            .await
+            .unwrap();
+
+        let mut merge_insert = table.merge_insert(&["id_as_int"]);
+        merge_insert
+            .when_matched_update_all(None)
+            .when_not_matched_insert_all()
+            .when_not_matched_by_source_delete(None);
+        let result = merge_insert
+            .execute(fixed_size_binary_merge_batch(100..356, 200))
+            .await
+            .unwrap();
+
+        assert_eq!(result.num_updated_rows, 156);
+        assert_eq!(result.num_inserted_rows, 100);
+        assert_eq!(result.num_deleted_rows, 100);
+        assert_eq!(table.count_rows(None).await.unwrap(), 256);
+    }
+
     #[tokio::test]
     async fn test_merge_insert_use_index() {
         let conn = connect("memory://").execute().await.unwrap();

rust/lancedb/src/table/optimize.rs

@@ -214,12 +214,17 @@ pub(crate) async fn execute_optimize(
 
 #[cfg(test)]
 mod tests {
-    use arrow_array::{Int32Array, RecordBatch, StringArray};
+    use arrow_array::{
+        Array, FixedSizeListArray, Float32Array, Int32Array, RecordBatch, StringArray,
+    };
     use arrow_schema::{DataType, Field, Schema};
+    use lance_arrow::FixedSizeListArrayExt;
     use rstest::rstest;
     use std::sync::Arc;
 
     use crate::connect;
+    use crate::database::listing::OPT_NEW_TABLE_ENABLE_STABLE_ROW_IDS;
+    use crate::index::vector::IvfRqIndexBuilder;
     use crate::index::{Index, scalar::BTreeIndexBuilder};
     use crate::query::ExecutableQuery;
     use crate::table::{CompactionOptions, OptimizeAction, OptimizeStats};
@@ -304,6 +309,96 @@ mod tests {
         assert_eq!(all_values, expected);
     }
 
+    #[tokio::test]
+    async fn test_compact_with_concurrent_add() {
+        const NUM_FRAGMENTS: usize = 5;
+        const ROWS_PER_FRAGMENT: i32 = 300;
+
+        let tmpdir = tempfile::tempdir().unwrap();
+        let conn = connect(tmpdir.path().to_str().unwrap())
+            .execute()
+            .await
+            .unwrap();
+        let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
+        let batch = RecordBatch::try_new(
+            schema,
+            vec![Arc::new(Int32Array::from_iter_values(0..ROWS_PER_FRAGMENT))],
+        )
+        .unwrap();
+
+        let table = conn
+            .create_table("test_concurrent_compact", batch.clone())
+            .execute()
+            .await
+            .unwrap();
+        table
+            .create_index(&["id"], Index::BTree(BTreeIndexBuilder::default()))
+            .execute()
+            .await
+            .unwrap();
+        for _ in 0..NUM_FRAGMENTS {
+            table.add(batch.clone()).execute().await.unwrap();
+        }
+
+        // Use separate handles so the two writes actually overlap, as they can
+        // when different Node connections operate on the same S3 table.
+        let compact_table = conn
+            .open_table("test_concurrent_compact")
+            .execute()
+            .await
+            .unwrap();
+        let append_table = conn
+            .open_table("test_concurrent_compact")
+            .execute()
+            .await
+            .unwrap();
+        let compact_task = tokio::spawn(async move {
+            compact_table
+                .optimize(OptimizeAction::Compact {
+                    options: CompactionOptions {
+                        target_rows_per_fragment: 1_000,
+                        ..Default::default()
+                    },
+                    remap_options: None,
+                })
+                .await
+        });
+        tokio::task::yield_now().await;
+        for _ in 0..NUM_FRAGMENTS {
+            append_table.add(batch.clone()).execute().await.unwrap();
+        }
+        compact_task.await.unwrap().unwrap();
+
+        let table = conn
+            .open_table("test_concurrent_compact")
+            .execute()
+            .await
+            .unwrap();
+        let dataset = table.dataset().unwrap().get().await.unwrap();
+        let fragment_ids = dataset
+            .get_fragments()
+            .iter()
+            .map(|fragment| fragment.id())
+            .collect::<Vec<_>>();
+        assert!(fragment_ids.windows(2).all(|ids| ids[0] < ids[1]));
+
+        // A second compaction exposed the original out-of-order row-id bug.
+        table
+            .optimize(OptimizeAction::Compact {
+                options: CompactionOptions {
+                    target_rows_per_fragment: 1_000,
+                    ..Default::default()
+                },
+                remap_options: None,
+            })
+            .await
+            .unwrap();
+        assert_eq!(
+            table.count_rows(None).await.unwrap(),
+            ROWS_PER_FRAGMENT as usize * (NUM_FRAGMENTS * 2 + 1)
+        );
+    }
+
     #[tokio::test]
     async fn test_optimize_prune_versions() {
         let conn = connect("memory://").execute().await.unwrap();
@@ -442,6 +537,58 @@ mod tests {
         assert_eq!(final_row_count, 200);
     }
 
+    #[tokio::test]
+    async fn test_optimize_vector_index_after_delete_with_stable_row_ids() {
+        const NUM_ROWS: i32 = 400;
+        const DIMENSION: i32 = 32;
+
+        let conn = connect("memory://").execute().await.unwrap();
+        let vectors = FixedSizeListArray::try_new_from_values(
+            Float32Array::from_iter_values((0..NUM_ROWS).flat_map(|id| {
+                (0..DIMENSION).map(move |offset| ((id as f32 * 0.1) + (offset as f32 * 0.3)).sin())
+            })),
+            DIMENSION,
+        )
+        .unwrap();
+        let schema = Arc::new(Schema::new(vec![
+            Field::new("id", DataType::Int32, false),
+            Field::new("vector", vectors.data_type().clone(), false),
+        ]));
+        let batch = RecordBatch::try_new(
+            schema,
+            vec![
+                Arc::new(Int32Array::from_iter_values(0..NUM_ROWS)),
+                Arc::new(vectors),
+            ],
+        )
+        .unwrap();
+        let table = conn
+            .create_table("test_vector_index_optimize_after_delete", batch)
+            .storage_option(OPT_NEW_TABLE_ENABLE_STABLE_ROW_IDS, "true")
+            .execute()
+            .await
+            .unwrap();
+
+        table
+            .create_index(
+                &["vector"],
+                Index::IvfRq(IvfRqIndexBuilder::default().num_partitions(4)),
+            )
+            .execute()
+            .await
+            .unwrap();
+        table.delete("id % 3 = 0").await.unwrap();
+
+        // Regression test for #3330: deleted stable row IDs used to become
+        // misaligned with row addresses while joining small IVF partitions.
+        table
+            .optimize(OptimizeAction::Index(Default::default()))
+            .await
+            .unwrap();
+
+        assert_eq!(table.count_rows(None).await.unwrap(), 266);
+    }
+
     #[tokio::test]
     async fn test_optimize_all() {
         let conn = connect("memory://").execute().await.unwrap();