feat: connection pool for sync client

.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.14.0-beta.0"
+current_version = "0.13.1-beta.0"
 parse = """(?x)
     (?P<major>0|[1-9]\\d*)\\.
     (?P<minor>0|[1-9]\\d*)\\.

docs/src/guides/scalar_index.md

@@ -1,35 +1,23 @@
-# Building a Scalar Index
+# Building Scalar Index
 
-Scalar indices organize data by scalar attributes (e.g. numbers, categorical values), enabling fast filtering of vector data. In vector databases, scalar indices accelerate the retrieval of scalar data associated with vectors, thus enhancing the query performance when searching for vectors that meet certain scalar criteria. 
-
-Similar to many SQL databases, LanceDB supports several types of scalar indices to accelerate search
+Similar to many SQL databases, LanceDB supports several types of Scalar indices to accelerate search
 over scalar columns.
 
-- `BTREE`: The most common type is BTREE. The index stores a copy of the
-  column in sorted order. This sorted copy allows a binary search to be used to
-  satisfy queries.
-- `BITMAP`: this index stores a bitmap for each unique value in the column. It 
-  uses a series of bits to indicate whether a value is present in a row of a table
-- `LABEL_LIST`: a special index that can be used on `List<T>` columns to
-  support queries with `array_contains_all` and `array_contains_any`
-  using an underlying bitmap index.
+- `BTREE`: The most common type is BTREE. This index is inspired by the btree data structure
+  although only the first few layers of the btree are cached in memory.
+  It will perform well on columns with a large number of unique values and few rows per value.
+- `BITMAP`: this index stores a bitmap for each unique value in the column.
+  This index is useful for columns with a finite number of unique values and many rows per value.
+  For example, columns that represent "categories", "labels", or "tags"
+- `LABEL_LIST`: a special index that is used to index list columns whose values have a finite set of possibilities.
   For example, a column that contains lists of tags (e.g. `["tag1", "tag2", "tag3"]`) can be indexed with a `LABEL_LIST` index.
 
-!!! tips "How to choose the right scalar index type"
-
-    `BTREE`: This index is good for scalar columns with mostly distinct values and does best when the query is highly selective.
-    
-    `BITMAP`: This index works best for low-cardinality numeric or string columns, where the number of unique values is small (i.e., less than a few thousands).
-    
-    `LABEL_LIST`: This index should be used for columns containing list-type data.
-
 | Data Type                                                       | Filter                                    | Index Type   |
 | --------------------------------------------------------------- | ----------------------------------------- | ------------ |
 | Numeric, String, Temporal                                       | `<`, `=`, `>`, `in`, `between`, `is null` | `BTREE`      |
 | Boolean, numbers or strings with fewer than 1,000 unique values | `<`, `=`, `>`, `in`, `between`, `is null` | `BITMAP`     |
 | List of low cardinality of numbers or strings                   | `array_has_any`, `array_has_all`          | `LABEL_LIST` |
 
-### Create a scalar index
 === "Python"
 
     ```python
@@ -58,7 +46,7 @@ over scalar columns.
         await tlb.create_index("publisher", { config: lancedb.Index.bitmap() })
         ```
 
-The following scan will be faster if the column `book_id` has a scalar index:
+For example, the following scan will be faster if the column `my_col` has a scalar index:
 
 === "Python"
 
@@ -118,30 +106,3 @@ Scalar indices can also speed up scans containing a vector search or full text s
           .limit(10)
           .toArray();
         ```
-### Update a scalar index
-Updating the table data (adding, deleting, or modifying records) requires that you also update the scalar index. This can be done by calling `optimize`, which will trigger an update to the existing scalar index.
-=== "Python"
-
-    ```python
-    table.add([{"vector": [7, 8], "book_id": 4}])
-    table.optimize()
-    ```
-
-=== "TypeScript"
-
-    ```typescript
-    await tbl.add([{ vector: [7, 8], book_id: 4 }]);
-    await tbl.optimize();
-    ```
-
-=== "Rust"
-
-    ```rust
-    let more_data: Box<dyn RecordBatchReader + Send> = create_some_records()?;
-    tbl.add(more_data).execute().await?;
-    tbl.optimize(OptimizeAction::All).execute().await?;
-    ```
-
-!!! note
-
-    New data added after creating the scalar index will still appear in search results if optimize is not used, but with increased latency due to a flat search on the unindexed portion. LanceDB Cloud automates the optimize process, minimizing the impact on search speed.

docs/src/sql.md

@@ -7,10 +7,6 @@ performed on the top-k results returned by the vector search. However, pre-filte
 option that performs the filter prior to vector search. This can be useful to narrow down on
 the search space on a very large dataset to reduce query latency.
 
-Note that both pre-filtering and post-filtering can yield false positives. For pre-filtering, if the filter is too selective, it might eliminate relevant items that the vector search would have otherwise identified as a good match. In this case, increasing `nprobes` parameter will help reduce such false positives. It is recommended to set `use_index=false` if you know that the filter is highly selective.
-
-Similarly, a highly selective post-filter can lead to false positives. Increasing both `nprobes` and `refine_factor` can mitigate this issue. When deciding between pre-filtering and post-filtering, pre-filtering is generally the safer choice if you're uncertain.
-
 <!-- Setup Code
 ```python
 import lancedb
@@ -61,9 +57,6 @@ const tbl = await db.createTable('myVectors', data)
         ```ts
         --8<-- "docs/src/sql_legacy.ts:search"
         ```
-!!! note
-
-    Creating a [scalar index](guides/scalar_index.md) accelerates filtering
 
 ## SQL filters
 

java/core/pom.xml

@@ -8,7 +8,7 @@
     <parent>
         <groupId>com.lancedb</groupId>
         <artifactId>lancedb-parent</artifactId>
-        <version>0.14.0-beta.0</version>
+        <version>0.13.1-beta.0</version>
         <relativePath>../pom.xml</relativePath>
     </parent>
 

java/pom.xml

@@ -6,7 +6,7 @@
 
     <groupId>com.lancedb</groupId>
     <artifactId>lancedb-parent</artifactId>
-    <version>0.14.0-beta.0</version>
+    <version>0.13.1-beta.0</version>
     <packaging>pom</packaging>
 
     <name>LanceDB Parent</name>

node/package.json

@@ -1,6 +1,6 @@
 {
   "name": "vectordb",
-  "version": "0.14.0-beta.0",
+  "version": "0.13.1-beta.0",
   "description": " Serverless, low-latency vector database for AI applications",
   "main": "dist/index.js",
   "types": "dist/index.d.ts",
@@ -91,13 +91,13 @@
     }
   },
   "optionalDependencies": {
-    "@lancedb/vectordb-darwin-x64": "0.14.0-beta.0",
-    "@lancedb/vectordb-darwin-arm64": "0.14.0-beta.0",
-    "@lancedb/vectordb-linux-x64-gnu": "0.14.0-beta.0",
-    "@lancedb/vectordb-linux-arm64-gnu": "0.14.0-beta.0",
-    "@lancedb/vectordb-linux-x64-musl": "0.14.0-beta.0",
-    "@lancedb/vectordb-linux-arm64-musl": "0.14.0-beta.0",
-    "@lancedb/vectordb-win32-x64-msvc": "0.14.0-beta.0",
-    "@lancedb/vectordb-win32-arm64-msvc": "0.14.0-beta.0"
+    "@lancedb/vectordb-darwin-x64": "0.13.1-beta.0",
+    "@lancedb/vectordb-darwin-arm64": "0.13.1-beta.0",
+    "@lancedb/vectordb-linux-x64-gnu": "0.13.1-beta.0",
+    "@lancedb/vectordb-linux-arm64-gnu": "0.13.1-beta.0",
+    "@lancedb/vectordb-linux-x64-musl": "0.13.1-beta.0",
+    "@lancedb/vectordb-linux-arm64-musl": "0.13.1-beta.0",
+    "@lancedb/vectordb-win32-x64-msvc": "0.13.1-beta.0",
+    "@lancedb/vectordb-win32-arm64-msvc": "0.13.1-beta.0"
   }
 }

nodejs/Cargo.toml

@@ -1,7 +1,7 @@
 [package]
 name = "lancedb-nodejs"
 edition.workspace = true
-version = "0.14.0-beta.0"
+version = "0.13.1-beta.0"
 license.workspace = true
 description.workspace = true
 repository.workspace = true

nodejs/npm/darwin-arm64/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.14.0-beta.0",
+	"version": "0.13.1-beta.0",
 	"os": ["darwin"],
 	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",

nodejs/npm/darwin-x64/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-x64",
-	"version": "0.14.0-beta.0",
+	"version": "0.13.1-beta.0",
 	"os": ["darwin"],
 	"cpu": ["x64"],
 	"main": "lancedb.darwin-x64.node",

nodejs/npm/linux-arm64-gnu/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-	"version": "0.14.0-beta.0",
+	"version": "0.13.1-beta.0",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-gnu.node",

nodejs/npm/linux-arm64-musl/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-musl",
-	"version": "0.14.0-beta.0",
+	"version": "0.13.1-beta.0",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-musl.node",

nodejs/npm/linux-x64-gnu/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-gnu",
-	"version": "0.14.0-beta.0",
+	"version": "0.13.1-beta.0",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-gnu.node",

nodejs/npm/linux-x64-musl/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-musl",
-	"version": "0.14.0-beta.0",
+	"version": "0.13.1-beta.0",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-musl.node",

nodejs/npm/win32-arm64-msvc/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@lancedb/lancedb-win32-arm64-msvc",
-  "version": "0.14.0-beta.0",
+  "version": "0.13.1-beta.0",
   "os": [
     "win32"
   ],

nodejs/npm/win32-x64-msvc/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.14.0-beta.0",
+	"version": "0.13.1-beta.0",
 	"os": ["win32"],
 	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",

nodejs/package.json

@@ -10,7 +10,7 @@
     "vector database",
     "ann"
   ],
-  "version": "0.14.0-beta.0",
+  "version": "0.13.1-beta.0",
   "main": "dist/index.js",
   "exports": {
     ".": "./dist/index.js",

python/.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.17.0-beta.0"
+current_version = "0.16.1-beta.0"
 parse = """(?x)
     (?P<major>0|[1-9]\\d*)\\.
     (?P<minor>0|[1-9]\\d*)\\.

python/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-python"
-version = "0.17.0-beta.0"
+version = "0.16.1-beta.0"
 edition.workspace = true
 description = "Python bindings for LanceDB"
 license.workspace = true

python/pyproject.toml

@@ -3,6 +3,7 @@ name = "lancedb"
 # version in Cargo.toml
 dependencies = [
     "deprecation",
+    "nest-asyncio~=1.0",
     "pylance==0.20.0b2",
     "tqdm>=4.27.0",
     "pydantic>=1.10",

python/python/lancedb/remote/background_loop.py

@@ -1,25 +0,0 @@
-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright The LanceDB Authors
-
-import asyncio
-import threading
-
-
-class BackgroundEventLoop:
-    """
-    A background event loop that can run futures.
-
-    Used to bridge sync and async code, without messing with users event loops.
-    """
-
-    def __init__(self):
-        self.loop = asyncio.new_event_loop()
-        self.thread = threading.Thread(
-            target=self.loop.run_forever,
-            name="LanceDBBackgroundEventLoop",
-            daemon=True,
-        )
-        self.thread.start()
-
-    def run(self, future):
-        return asyncio.run_coroutine_threadsafe(future, self.loop).result()

python/python/lancedb/remote/db.py

@@ -11,6 +11,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 
+import asyncio
 from datetime import timedelta
 import logging
 from concurrent.futures import ThreadPoolExecutor
@@ -20,7 +21,6 @@ import warnings
 
 from lancedb import connect_async
 from lancedb.remote import ClientConfig
-from lancedb.remote.background_loop import BackgroundEventLoop
 import pyarrow as pa
 from overrides import override
 
@@ -31,8 +31,6 @@ from ..pydantic import LanceModel
 from ..table import Table
 from ..util import validate_table_name
 
-LOOP = BackgroundEventLoop()
-
 
 class RemoteDBConnection(DBConnection):
     """A connection to a remote LanceDB database."""
@@ -88,9 +86,18 @@ class RemoteDBConnection(DBConnection):
             raise ValueError(f"Invalid scheme: {parsed.scheme}, only accepts db://")
         self.db_name = parsed.netloc
 
+        import nest_asyncio
+
+        nest_asyncio.apply()
+        try:
+            self._loop = asyncio.get_running_loop()
+        except RuntimeError:
+            self._loop = asyncio.new_event_loop()
+            asyncio.set_event_loop(self._loop)
+
         self.client_config = client_config
 
-        self._conn = LOOP.run(
+        self._conn = self._loop.run_until_complete(
             connect_async(
                 db_url,
                 api_key=api_key,
@@ -120,7 +127,9 @@ class RemoteDBConnection(DBConnection):
         -------
         An iterator of table names.
         """
-        return LOOP.run(self._conn.table_names(start_after=page_token, limit=limit))
+        return self._loop.run_until_complete(
+            self._conn.table_names(start_after=page_token, limit=limit)
+        )
 
     @override
     def open_table(self, name: str, *, index_cache_size: Optional[int] = None) -> Table:
@@ -143,8 +152,8 @@ class RemoteDBConnection(DBConnection):
                 " (there is no local cache to configure)"
             )
 
-        table = LOOP.run(self._conn.open_table(name))
-        return RemoteTable(table, self.db_name)
+        table = self._loop.run_until_complete(self._conn.open_table(name))
+        return RemoteTable(table, self.db_name, self._loop)
 
     @override
     def create_table(
@@ -259,7 +268,7 @@ class RemoteDBConnection(DBConnection):
 
         from .table import RemoteTable
 
-        table = LOOP.run(
+        table = self._loop.run_until_complete(
             self._conn.create_table(
                 name,
                 data,
@@ -269,7 +278,7 @@ class RemoteDBConnection(DBConnection):
                 fill_value=fill_value,
             )
         )
-        return RemoteTable(table, self.db_name)
+        return RemoteTable(table, self.db_name, self._loop)
 
     @override
     def drop_table(self, name: str):
@@ -280,7 +289,7 @@ class RemoteDBConnection(DBConnection):
         name: str
             The name of the table.
         """
-        LOOP.run(self._conn.drop_table(name))
+        self._loop.run_until_complete(self._conn.drop_table(name))
 
     @override
     def rename_table(self, cur_name: str, new_name: str):
@@ -293,7 +302,7 @@ class RemoteDBConnection(DBConnection):
         new_name: str
             The new name of the table.
         """
-        LOOP.run(self._conn.rename_table(cur_name, new_name))
+        self._loop.run_until_complete(self._conn.rename_table(cur_name, new_name))
 
     async def close(self):
         """Close the connection to the database."""

python/python/lancedb/remote/table.py

@@ -12,12 +12,12 @@
 #  limitations under the License.
 
 from datetime import timedelta
+import asyncio
 import logging
 from functools import cached_property
 from typing import Dict, Iterable, List, Optional, Union, Literal
 
 from lancedb.index import FTS, BTree, Bitmap, HnswPq, HnswSq, IvfPq, LabelList
-from lancedb.remote.db import LOOP
 import pyarrow as pa
 
 from lancedb.common import DATA, VEC, VECTOR_COLUMN_NAME
@@ -33,7 +33,9 @@ class RemoteTable(Table):
         self,
         table: AsyncTable,
         db_name: str,
+        loop: Optional[asyncio.AbstractEventLoop] = None,
     ):
+        self._loop = loop
         self._table = table
         self.db_name = db_name
 
@@ -54,12 +56,12 @@ class RemoteTable(Table):
         of this Table
 
         """
-        return LOOP.run(self._table.schema())
+        return self._loop.run_until_complete(self._table.schema())
 
     @property
     def version(self) -> int:
         """Get the current version of the table"""
-        return LOOP.run(self._table.version())
+        return self._loop.run_until_complete(self._table.version())
 
     @cached_property
     def embedding_functions(self) -> dict:
@@ -96,11 +98,11 @@ class RemoteTable(Table):
 
     def list_indices(self):
         """List all the indices on the table"""
-        return LOOP.run(self._table.list_indices())
+        return self._loop.run_until_complete(self._table.list_indices())
 
     def index_stats(self, index_uuid: str):
         """List all the stats of a specified index"""
-        return LOOP.run(self._table.index_stats(index_uuid))
+        return self._loop.run_until_complete(self._table.index_stats(index_uuid))
 
     def create_scalar_index(
         self,
@@ -130,7 +132,9 @@ class RemoteTable(Table):
         else:
             raise ValueError(f"Unknown index type: {index_type}")
 
-        LOOP.run(self._table.create_index(column, config=config, replace=replace))
+        self._loop.run_until_complete(
+            self._table.create_index(column, config=config, replace=replace)
+        )
 
     def create_fts_index(
         self,
@@ -140,7 +144,9 @@ class RemoteTable(Table):
         with_position: bool = True,
     ):
         config = FTS(with_position=with_position)
-        LOOP.run(self._table.create_index(column, config=config, replace=replace))
+        self._loop.run_until_complete(
+            self._table.create_index(column, config=config, replace=replace)
+        )
 
     def create_index(
         self,
@@ -221,7 +227,9 @@ class RemoteTable(Table):
                 " 'IVF_PQ', 'IVF_HNSW_PQ', 'IVF_HNSW_SQ'"
             )
 
-        LOOP.run(self._table.create_index(vector_column_name, config=config))
+        self._loop.run_until_complete(
+            self._table.create_index(vector_column_name, config=config)
+        )
 
     def add(
         self,
@@ -253,7 +261,7 @@ class RemoteTable(Table):
             The value to use when filling vectors. Only used if on_bad_vectors="fill".
 
         """
-        LOOP.run(
+        self._loop.run_until_complete(
             self._table.add(
                 data, mode=mode, on_bad_vectors=on_bad_vectors, fill_value=fill_value
             )
@@ -341,7 +349,9 @@ class RemoteTable(Table):
     def _execute_query(
         self, query: Query, batch_size: Optional[int] = None
     ) -> pa.RecordBatchReader:
-        return LOOP.run(self._table._execute_query(query, batch_size=batch_size))
+        return self._loop.run_until_complete(
+            self._table._execute_query(query, batch_size=batch_size)
+        )
 
     def merge_insert(self, on: Union[str, Iterable[str]]) -> LanceMergeInsertBuilder:
         """Returns a [`LanceMergeInsertBuilder`][lancedb.merge.LanceMergeInsertBuilder]
@@ -358,7 +368,9 @@ class RemoteTable(Table):
         on_bad_vectors: str,
         fill_value: float,
     ):
-        LOOP.run(self._table._do_merge(merge, new_data, on_bad_vectors, fill_value))
+        self._loop.run_until_complete(
+            self._table._do_merge(merge, new_data, on_bad_vectors, fill_value)
+        )
 
     def delete(self, predicate: str):
         """Delete rows from the table.
@@ -407,7 +419,7 @@ class RemoteTable(Table):
            x      vector  _distance # doctest: +SKIP
         0  2  [3.0, 4.0]       85.0 # doctest: +SKIP
         """
-        LOOP.run(self._table.delete(predicate))
+        self._loop.run_until_complete(self._table.delete(predicate))
 
     def update(
         self,
@@ -457,7 +469,7 @@ class RemoteTable(Table):
         2  2  [10.0, 10.0] # doctest: +SKIP
 
         """
-        LOOP.run(
+        self._loop.run_until_complete(
             self._table.update(where=where, updates=values, updates_sql=values_sql)
         )
 
@@ -487,7 +499,7 @@ class RemoteTable(Table):
         )
 
     def count_rows(self, filter: Optional[str] = None) -> int:
-        return LOOP.run(self._table.count_rows(filter))
+        return self._loop.run_until_complete(self._table.count_rows(filter))
 
     def add_columns(self, transforms: Dict[str, str]):
         raise NotImplementedError(

python/python/lancedb/util.py

@@ -11,6 +11,8 @@ from datetime import date, datetime
 from functools import singledispatch
 from typing import Tuple, Union, Optional, Any
 from urllib.parse import urlparse
+from threading import Lock
+from contextlib import contextmanager
 
 import numpy as np
 import pyarrow as pa
@@ -314,3 +316,27 @@ def deprecated(func):
 def validate_table_name(name: str):
     """Verify the table name is valid."""
     native_validate_table_name(name)
+
+
+class ConnectionPool:
+    def __init__(self, connection_factory, *, max_size: Optional[int] = None):
+        self.max_size = max_size
+        self._connection_factory = connection_factory
+        self._pool = []
+        self._lock = Lock()
+
+    @contextmanager
+    def connection(self):
+        with self._lock:
+            if self._pool:
+                conn = self._pool.pop()
+            else:
+                conn = self._connection_factory()
+
+        # release the lock before yielding
+        try:
+            yield conn
+        finally:
+            with self._lock:
+                if self.max_size is None or len(self._pool) < self.max_size:
+                    self._pool.append(conn)

python/python/tests/test_remote_db.py

@@ -1,19 +1,21 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
-from concurrent.futures import ThreadPoolExecutor
 import contextlib
 from datetime import timedelta
 import http.server
 import json
 import threading
+from concurrent.futures import ThreadPoolExecutor
 from unittest.mock import MagicMock
 import uuid
 
 import lancedb
 from lancedb.conftest import MockTextEmbeddingFunction
 from lancedb.remote import ClientConfig
+from lancedb.util import ConnectionPool
 from lancedb.remote.errors import HttpError, RetryError
+import lancedb.util
 import pytest
 import pyarrow as pa
 
@@ -56,6 +58,34 @@ def mock_lancedb_connection(handler):
             handle.join()
 
 
+@contextlib.contextmanager
+def mock_lancedb_connection_pool(handler):
+    with http.server.HTTPServer(
+        ("localhost", 8080), make_mock_http_handler(handler)
+    ) as server:
+        handle = threading.Thread(target=server.serve_forever)
+        handle.start()
+
+        def conn_factory():
+            lancedb.connect(
+                "db://dev",
+                api_key="fake",
+                host_override="http://localhost:8080",
+                client_config={
+                    "retry_config": {"retries": 2},
+                    "timeout_config": {
+                        "connect_timeout": 1,
+                    },
+                },
+            )
+
+        try:
+            yield ConnectionPool(conn_factory)
+        finally:
+            server.shutdown()
+            handle.join()
+
+
 @contextlib.asynccontextmanager
 async def mock_lancedb_connection_async(handler):
     with http.server.HTTPServer(
@@ -188,49 +218,7 @@ async def test_retry_error():
         assert cause.status_code == 429
 
 
-def test_table_add_in_threadpool():
-    def handler(request):
-        if request.path == "/v1/table/test/insert/":
-            request.send_response(200)
-            request.end_headers()
-        elif request.path == "/v1/table/test/create/":
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(b"{}")
-        elif request.path == "/v1/table/test/describe/":
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            payload = json.dumps(
-                dict(
-                    version=1,
-                    schema=dict(
-                        fields=[
-                            dict(name="id", type={"type": "int64"}, nullable=False),
-                        ]
-                    ),
-                )
-            )
-            request.wfile.write(payload.encode())
-        else:
-            request.send_response(404)
-            request.end_headers()
-
-    with mock_lancedb_connection(handler) as db:
-        table = db.create_table("test", [{"id": 1}])
-        with ThreadPoolExecutor(3) as executor:
-            futures = []
-            for _ in range(10):
-                future = executor.submit(table.add, [{"id": 1}])
-                futures.append(future)
-
-            for future in futures:
-                future.result()
-
-
-@contextlib.contextmanager
-def query_test_table(query_handler):
+def http_handler(query_handler):
     def handler(request):
         if request.path == "/v1/table/test/describe/":
             request.send_response(200)
@@ -254,7 +242,12 @@ def query_test_table(query_handler):
             request.send_response(404)
             request.end_headers()
 
-    with mock_lancedb_connection(handler) as db:
+    return handler
+
+
+@contextlib.contextmanager
+def query_test_table(connection_ctx_mgr):
+    with connection_ctx_mgr as db:
         assert repr(db) == "RemoteConnect(name=dev)"
         table = db.open_table("test")
         assert repr(table) == "RemoteTable(dev.test)"
@@ -262,6 +255,7 @@ def query_test_table(query_handler):
 
 
 def test_query_sync_minimal():
+    @http_handler
     def handler(body):
         assert body == {
             "distance_type": "l2",
@@ -276,13 +270,53 @@ def test_query_sync_minimal():
 
         return pa.table({"id": [1, 2, 3]})
 
-    with query_test_table(handler) as table:
+    with query_test_table(mock_lancedb_connection(handler)) as table:
+        data = table.search([1, 2, 3]).to_list()
+        expected = [{"id": 1}, {"id": 2}, {"id": 3}]
+        assert data == expected
+
+    with query_test_table(mock_lancedb_connection_pool(handler).connection()) as table:
         data = table.search([1, 2, 3]).to_list()
         expected = [{"id": 1}, {"id": 2}, {"id": 3}]
         assert data == expected
 
 
+def test_query_sync_minimal_threaded():
+    num_query = 0
+
+    @http_handler
+    def handler(body):
+        assert body == {
+            "distance_type": "l2",
+            "k": 10,
+            "prefilter": False,
+            "refine_factor": None,
+            "ef": None,
+            "vector": [1.0, 2.0, 3.0],
+            "nprobes": 20,
+            "version": None,
+        }
+        nonlocal num_query
+        num_query += 1
+
+        return pa.table({"id": [1, 2, 3]})
+
+    pool = mock_lancedb_connection_pool(handler)
+
+    def _query(i):
+        with query_test_table(pool.connection()) as table:
+            data = table.search([1, 2, 3]).to_list()
+            expected = [{"id": 1}, {"id": 2}, {"id": 3}]
+            assert data == expected
+
+    with ThreadPoolExecutor as exec:
+        exec.map(_query, range(1000))
+
+    assert num_query == 1000
+
+
 def test_query_sync_empty_query():
+    @http_handler
     def handler(body):
         assert body == {
             "k": 10,
@@ -294,7 +328,12 @@ def test_query_sync_empty_query():
 
         return pa.table({"id": [1, 2, 3]})
 
-    with query_test_table(handler) as table:
+    with query_test_table(mock_lancedb_connection(handler)) as table:
+        data = table.search(None).where("true").select(["id"]).limit(10).to_list()
+        expected = [{"id": 1}, {"id": 2}, {"id": 3}]
+        assert data == expected
+
+    with query_test_table(mock_lancedb_connection_pool(handler).connection()) as table:
         data = table.search(None).where("true").select(["id"]).limit(10).to_list()
         expected = [{"id": 1}, {"id": 2}, {"id": 3}]
         assert data == expected

rust/ffi/node/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-node"
-version = "0.14.0-beta.0"
+version = "0.13.1-beta.0"
 description = "Serverless, low-latency vector database for AI applications"
 license.workspace = true
 edition.workspace = true

rust/lancedb/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.14.0-beta.0"
+version = "0.13.1-beta.0"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true