feat: add mem_wal flag to merge insert for MemWAL write path

Add support for enabling MemWAL (Memory Write-Ahead Log) mode on merge insert
operations. This allows streaming writes to route through memory nodes for
high-performance buffered writes.

Changes:
- Add `mem_wal` field to MergeInsertBuilder with validation
- Add `x-lancedb-mem-wal-enabled` header for remote requests
- Add Python `mem_wal()` method to LanceMergeInsertBuilder
- Add validation to ensure only upsert pattern is supported:
  - when_matched_update_all() without filter
  - when_not_matched_insert_all()
- Throw NotSupported error for native tables
- Add mem_wal_enabled to ClientConfig for Python/Node bindings

Generated with [Claude Code](https://claude.ai/code)
via [Happy](https://happy.engineering)

Co-Authored-By: Claude <noreply@anthropic.com>
Co-Authored-By: Happy <yesreply@happy.engineering>

.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.27.0-beta.2"
+current_version = "0.27.0-beta.3"
 parse = """(?x)
     (?P<major>0|[1-9]\\d*)\\.
     (?P<minor>0|[1-9]\\d*)\\.

.github/workflows/build_linux_wheel/action.yml

@@ -29,6 +29,7 @@ runs:
       if: ${{ inputs.arm-build == 'false' }}
       uses: PyO3/maturin-action@v1
       with:
+        maturin-version: "1.12.4"
         command: build
         working-directory: python
         docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/'"
@@ -44,6 +45,7 @@ runs:
       if: ${{ inputs.arm-build == 'true' }}
       uses: PyO3/maturin-action@v1
       with:
+        maturin-version: "1.12.4"
         command: build
         working-directory: python
         docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/'"

.github/workflows/build_mac_wheel/action.yml

@@ -20,6 +20,7 @@ runs:
       uses: PyO3/maturin-action@v1
       with:
         command: build
+        maturin-version: "1.12.4"
         # TODO: pass through interpreter
         args: ${{ inputs.args }}
         docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/'"

.github/workflows/build_windows_wheel/action.yml

@@ -25,6 +25,7 @@ runs:
       uses: PyO3/maturin-action@v1
       with:
         command: build
+        maturin-version: "1.12.4"
         args: ${{ inputs.args }}
         docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/'"
         working-directory: python

.github/workflows/npm-publish.yml

@@ -356,7 +356,8 @@ jobs:
           if [[ $DRY_RUN == "true" ]]; then
             ARGS="$ARGS --dry-run"
           fi
-          if [[ $GITHUB_REF =~ refs/tags/v(.*)-beta.* ]]; then
+          VERSION=$(node -p "require('./package.json').version")
+          if [[ $VERSION == *-* ]]; then
             ARGS="$ARGS --tag preview"
           fi
           npm publish $ARGS

.github/workflows/python.yml

@@ -10,6 +10,10 @@ on:
       - python/**
       - rust/**
       - .github/workflows/python.yml
+      - .github/workflows/build_linux_wheel/**
+      - .github/workflows/build_mac_wheel/**
+      - .github/workflows/build_windows_wheel/**
+      - .github/workflows/run_tests/**
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}

Cargo.toml

@@ -5,7 +5,7 @@ exclude = ["python"]
 resolver = "2"
 
 [workspace.package]
-edition = "2021"
+edition = "2024"
 authors = ["LanceDB Devs <dev@lancedb.com>"]
 license = "Apache-2.0"
 repository = "https://github.com/lancedb/lancedb"
@@ -15,20 +15,20 @@ categories = ["database-implementations"]
 rust-version = "1.91.0"
 
 [workspace.dependencies]
-lance = { "version" = "=3.1.0-beta.2", default-features = false, "tag" = "v3.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-core = { "version" = "=3.1.0-beta.2", "tag" = "v3.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-datagen = { "version" = "=3.1.0-beta.2", "tag" = "v3.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-file = { "version" = "=3.1.0-beta.2", "tag" = "v3.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-io = { "version" = "=3.1.0-beta.2", default-features = false, "tag" = "v3.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-index = { "version" = "=3.1.0-beta.2", "tag" = "v3.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-linalg = { "version" = "=3.1.0-beta.2", "tag" = "v3.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace = { "version" = "=3.1.0-beta.2", "tag" = "v3.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace-impls = { "version" = "=3.1.0-beta.2", default-features = false, "tag" = "v3.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-table = { "version" = "=3.1.0-beta.2", "tag" = "v3.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-testing = { "version" = "=3.1.0-beta.2", "tag" = "v3.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-datafusion = { "version" = "=3.1.0-beta.2", "tag" = "v3.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-encoding = { "version" = "=3.1.0-beta.2", "tag" = "v3.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-arrow = { "version" = "=3.1.0-beta.2", "tag" = "v3.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance = { "version" = "=3.0.0-rc.3", default-features = false, "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-core = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-datagen = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-file = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-io = { "version" = "=3.0.0-rc.3", default-features = false, "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-index = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-linalg = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace-impls = { "version" = "=3.0.0-rc.3", default-features = false, "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-table = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-testing = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-datafusion = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-encoding = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-arrow = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
 ahash = "0.8"
 # Note that this one does not include pyarrow
 arrow = { version = "57.2", optional = false }
@@ -40,13 +40,15 @@ arrow-schema = "57.2"
 arrow-select = "57.2"
 arrow-cast = "57.2"
 async-trait = "0"
-datafusion = { version = "51.0", default-features = false }
-datafusion-catalog = "51.0"
-datafusion-common = { version = "51.0", default-features = false }
-datafusion-execution = "51.0"
-datafusion-expr = "51.0"
-datafusion-physical-plan = "51.0"
-datafusion-physical-expr = "51.0"
+datafusion = { version = "52.1", default-features = false }
+datafusion-catalog = "52.1"
+datafusion-common = { version = "52.1", default-features = false }
+datafusion-execution = "52.1"
+datafusion-expr = "52.1"
+datafusion-functions = "52.1"
+datafusion-physical-plan = "52.1"
+datafusion-physical-expr = "52.1"
+datafusion-sql = "52.1"
 env_logger = "0.11"
 half = { "version" = "2.7.1", default-features = false, features = [
     "num-traits",

docs/src/java/java.md

@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
 <dependency>
     <groupId>com.lancedb</groupId>
     <artifactId>lancedb-core</artifactId>
-    <version>0.27.0-beta.2</version>
+    <version>0.27.0-beta.3</version>
 </dependency>
 ```
 

docs/src/js/interfaces/DeleteResult.md

@@ -8,6 +8,14 @@
 
 ## Properties
 
+### numDeletedRows
+
+```ts
+numDeletedRows: number;
+```
+
+***
+
 ### version
 
 ```ts

java/lancedb-core/pom.xml

@@ -8,7 +8,7 @@
     <parent>
       <groupId>com.lancedb</groupId>
       <artifactId>lancedb-parent</artifactId>
-      <version>0.27.0-beta.2</version>
+      <version>0.27.0-beta.3</version>
       <relativePath>../pom.xml</relativePath>
     </parent>
 

java/pom.xml

@@ -6,7 +6,7 @@
 
     <groupId>com.lancedb</groupId>
     <artifactId>lancedb-parent</artifactId>
-    <version>0.27.0-beta.2</version>
+    <version>0.27.0-beta.3</version>
     <packaging>pom</packaging>
     <name>${project.artifactId}</name>
     <description>LanceDB Java SDK Parent POM</description>

nodejs/Cargo.toml

@@ -1,7 +1,7 @@
 [package]
 name = "lancedb-nodejs"
 edition.workspace = true
-version = "0.27.0-beta.2"
+version = "0.27.0-beta.3"
 license.workspace = true
 description.workspace = true
 repository.workspace = true

nodejs/__test__/table.test.ts

@@ -1697,6 +1697,65 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
       expect(results2[0].text).toBe(data[1].text);
     });
 
+    test("full text search fast search", async () => {
+      const db = await connect(tmpDir.name);
+      const data = [{ text: "hello world", vector: [0.1, 0.2, 0.3], id: 1 }];
+      const table = await db.createTable("test", data);
+      await table.createIndex("text", {
+        config: Index.fts(),
+      });
+
+      // Insert unindexed data after creating the index.
+      await table.add([{ text: "xyz", vector: [0.4, 0.5, 0.6], id: 2 }]);
+
+      const withFlatSearch = await table
+        .search("xyz", "fts")
+        .limit(10)
+        .toArray();
+      expect(withFlatSearch.length).toBeGreaterThan(0);
+
+      const fastSearchResults = await table
+        .search("xyz", "fts")
+        .fastSearch()
+        .limit(10)
+        .toArray();
+      expect(fastSearchResults.length).toBe(0);
+
+      const nearestToTextFastSearch = await table
+        .query()
+        .nearestToText("xyz")
+        .fastSearch()
+        .limit(10)
+        .toArray();
+      expect(nearestToTextFastSearch.length).toBe(0);
+
+      // fastSearch should be chainable with other methods.
+      const chainedFastSearch = await table
+        .search("xyz", "fts")
+        .fastSearch()
+        .select(["text"])
+        .limit(5)
+        .toArray();
+      expect(chainedFastSearch.length).toBe(0);
+
+      await table.optimize();
+
+      const indexedFastSearch = await table
+        .search("xyz", "fts")
+        .fastSearch()
+        .limit(10)
+        .toArray();
+      expect(indexedFastSearch.length).toBeGreaterThan(0);
+
+      const indexedNearestToTextFastSearch = await table
+        .query()
+        .nearestToText("xyz")
+        .fastSearch()
+        .limit(10)
+        .toArray();
+      expect(indexedNearestToTextFastSearch.length).toBeGreaterThan(0);
+    });
+
     test("prewarm full text search index", async () => {
       const db = await connect(tmpDir.name);
       const data = [

nodejs/npm/darwin-arm64/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.27.0-beta.2",
+	"version": "0.27.0-beta.3",
 	"os": ["darwin"],
 	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",

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

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-	"version": "0.27.0-beta.2",
+	"version": "0.27.0-beta.3",
 	"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": "0.27.0-beta.2",
+	"version": "0.27.0-beta.3",
 	"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": "0.27.0-beta.2",
+	"version": "0.27.0-beta.3",
 	"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": "0.27.0-beta.2",
+	"version": "0.27.0-beta.3",
 	"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": "0.27.0-beta.2",
+  "version": "0.27.0-beta.3",
   "os": [
     "win32"
   ],

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

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.27.0-beta.2",
+	"version": "0.27.0-beta.3",
 	"os": ["win32"],
 	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",

nodejs/package-lock.json

@@ -1,12 +1,12 @@
 {
   "name": "@lancedb/lancedb",
-  "version": "0.27.0-beta.2",
+  "version": "0.27.0-beta.3",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "@lancedb/lancedb",
-      "version": "0.27.0-beta.2",
+      "version": "0.27.0-beta.3",
       "cpu": [
         "x64",
         "arm64"

nodejs/package.json

@@ -11,7 +11,7 @@
     "ann"
   ],
   "private": false,
-  "version": "0.27.0-beta.2",
+  "version": "0.27.0-beta.3",
   "main": "dist/index.js",
   "exports": {
     ".": "./dist/index.js",

nodejs/src/connection.rs

@@ -8,10 +8,10 @@ use lancedb::database::{CreateTableMode, Database};
 use napi::bindgen_prelude::*;
 use napi_derive::*;
 
+use crate::ConnectionOptions;
 use crate::error::NapiErrorExt;
 use crate::header::JsHeaderProvider;
 use crate::table::Table;
-use crate::ConnectionOptions;
 use lancedb::connection::{ConnectBuilder, Connection as LanceDBConnection};
 
 use lancedb::ipc::{ipc_file_to_batches, ipc_file_to_schema};

nodejs/src/index.rs

@@ -3,12 +3,12 @@
 
 use std::sync::Mutex;
 
+use lancedb::index::Index as LanceDbIndex;
 use lancedb::index::scalar::{BTreeIndexBuilder, FtsIndexBuilder};
 use lancedb::index::vector::{
     IvfFlatIndexBuilder, IvfHnswPqIndexBuilder, IvfHnswSqIndexBuilder, IvfPqIndexBuilder,
     IvfRqIndexBuilder,
 };
-use lancedb::index::Index as LanceDbIndex;
 use napi_derive::napi;
 
 use crate::util::parse_distance_type;

nodejs/src/query.rs

@@ -17,8 +17,8 @@ use lancedb::query::VectorQuery as LanceDbVectorQuery;
 use napi::bindgen_prelude::*;
 use napi_derive::napi;
 
-use crate::error::convert_error;
 use crate::error::NapiErrorExt;
+use crate::error::convert_error;
 use crate::iterator::RecordBatchIterator;
 use crate::rerankers::RerankHybridCallbackArgs;
 use crate::rerankers::Reranker;
@@ -551,15 +551,12 @@ fn parse_fts_query(query: Object) -> napi::Result<FullTextSearchQuery> {
             }
         };
         let mut query = FullTextSearchQuery::new_query(query);
-        if let Some(cols) = columns {
-            if !cols.is_empty() {
-                query = query.with_columns(&cols).map_err(|e| {
-                    napi::Error::from_reason(format!(
-                        "Failed to set full text search columns: {}",
-                        e
-                    ))
-                })?;
-            }
+        if let Some(cols) = columns
+            && !cols.is_empty()
+        {
+            query = query.with_columns(&cols).map_err(|e| {
+                napi::Error::from_reason(format!("Failed to set full text search columns: {}", e))
+            })?;
         }
         Ok(query)
     } else {

nodejs/src/remote.rs

@@ -145,6 +145,7 @@ impl From<ClientConfig> for lancedb::remote::ClientConfig {
             id_delimiter: config.id_delimiter,
             tls_config: config.tls_config.map(Into::into),
             header_provider: None, // the header provider is set separately later
+            mem_wal_enabled: None, // mem_wal is set per-operation in merge_insert
         }
     }
 }

nodejs/src/session.rs

@@ -95,7 +95,7 @@ impl napi::bindgen_prelude::FromNapiValue for Session {
         napi_val: napi::sys::napi_value,
     ) -> napi::Result<Self> {
         let object: napi::bindgen_prelude::ClassInstance<Self> =
-            napi::bindgen_prelude::ClassInstance::from_napi_value(env, napi_val)?;
+            unsafe { napi::bindgen_prelude::ClassInstance::from_napi_value(env, napi_val)? };
         Ok((*object).clone())
     }
 }

nodejs/src/table.rs

@@ -753,12 +753,14 @@ impl From<lancedb::table::AddResult> for AddResult {
 
 #[napi(object)]
 pub struct DeleteResult {
+    pub num_deleted_rows: i64,
     pub version: i64,
 }
 
 impl From<lancedb::table::DeleteResult> for DeleteResult {
     fn from(value: lancedb::table::DeleteResult) -> Self {
         Self {
+            num_deleted_rows: value.num_deleted_rows as i64,
             version: value.version as i64,
         }
     }

python/.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.30.0-beta.2"
+current_version = "0.30.0-beta.3"
 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 = "0.30.0-beta.2"
+version = "0.30.0-beta.3"
 edition.workspace = true
 description = "Python bindings for LanceDB"
 license.workspace = true

python/python/lancedb/merge.py

@@ -34,6 +34,7 @@ class LanceMergeInsertBuilder(object):
         self._when_not_matched_by_source_condition = None
         self._timeout = None
         self._use_index = True
+        self._mem_wal = False
 
     def when_matched_update_all(
         self, *, where: Optional[str] = None
@@ -96,6 +97,47 @@ class LanceMergeInsertBuilder(object):
         self._use_index = use_index
         return self
 
+    def mem_wal(self, enabled: bool = True) -> LanceMergeInsertBuilder:
+        """
+        Enable MemWAL (Memory Write-Ahead Log) mode for this merge insert operation.
+
+        When enabled, the merge insert will route data through a memory node service
+        that buffers writes before flushing to storage. This is only supported for
+        remote (LanceDB Cloud) tables.
+
+        **Important:** MemWAL only supports the upsert pattern. You must use:
+        - `when_matched_update_all()` (without a filter condition)
+        - `when_not_matched_insert_all()`
+
+        MemWAL does NOT support:
+        - `when_matched_update_all(where=...)` with a filter condition
+        - `when_not_matched_by_source_delete()`
+
+        Parameters
+        ----------
+        enabled: bool
+            Whether to enable MemWAL mode. Defaults to `True`.
+
+        Raises
+        ------
+        NotImplementedError
+            If used on a native (local) table, as MemWAL is only supported for
+            remote tables.
+        ValueError
+            If the merge insert pattern is not supported by MemWAL.
+
+        Examples
+        --------
+        >>> # Correct usage with MemWAL
+        >>> table.merge_insert(["id"]) \\
+        ...     .when_matched_update_all() \\
+        ...     .when_not_matched_insert_all() \\
+        ...     .mem_wal() \\
+        ...     .execute(new_data)
+        """
+        self._mem_wal = enabled
+        return self
+
     def execute(
         self,
         new_data: DATA,

python/python/lancedb/query.py

@@ -606,6 +606,7 @@ class LanceQueryBuilder(ABC):
                 query,
                 ordering_field_name=ordering_field_name,
                 fts_columns=fts_columns,
+                fast_search=fast_search,
             )
 
         if isinstance(query, list):
@@ -1456,12 +1457,14 @@ class LanceFtsQueryBuilder(LanceQueryBuilder):
         query: str | FullTextQuery,
         ordering_field_name: Optional[str] = None,
         fts_columns: Optional[Union[str, List[str]]] = None,
+        fast_search: bool = None,
     ):
         super().__init__(table)
         self._query = query
         self._phrase_query = False
         self.ordering_field_name = ordering_field_name
         self._reranker = None
+        self._fast_search = fast_search
         if isinstance(fts_columns, str):
             fts_columns = [fts_columns]
         self._fts_columns = fts_columns
@@ -1483,6 +1486,19 @@ class LanceFtsQueryBuilder(LanceQueryBuilder):
         self._phrase_query = phrase_query
         return self
 
+    def fast_search(self) -> LanceFtsQueryBuilder:
+        """
+        Skip a flat search of unindexed data. This will improve
+        search performance but search results will not include unindexed data.
+
+        Returns
+        -------
+        LanceFtsQueryBuilder
+            The LanceFtsQueryBuilder object.
+        """
+        self._fast_search = True
+        return self
+
     def to_query_object(self) -> Query:
         return Query(
             columns=self._columns,
@@ -1494,6 +1510,7 @@ class LanceFtsQueryBuilder(LanceQueryBuilder):
                 query=self._query, columns=self._fts_columns
             ),
             offset=self._offset,
+            fast_search=self._fast_search,
         )
 
     def output_schema(self) -> pa.Schema:

python/python/lancedb/remote/table.py

@@ -218,8 +218,6 @@ class RemoteTable(Table):
         train: bool = True,
     ):
         """Create an index on the table.
-        Currently, the only parameters that matter are
-        the metric and the vector column name.
 
         Parameters
         ----------
@@ -250,11 +248,6 @@ class RemoteTable(Table):
         >>> table.create_index("l2", "vector") # doctest: +SKIP
         """
 
-        if num_sub_vectors is not None:
-            logging.warning(
-                "num_sub_vectors is not supported on LanceDB cloud."
-                "This parameter will be tuned automatically."
-            )
         if accelerator is not None:
             logging.warning(
                 "GPU accelerator is not yet supported on LanceDB cloud."

python/python/lancedb/table.py

@@ -1331,7 +1331,7 @@ class Table(ABC):
         1  2  [3.0, 4.0]
         2  3  [5.0, 6.0]
         >>> table.delete("x = 2")
-        DeleteResult(version=2)
+        DeleteResult(num_deleted_rows=1, version=2)
         >>> table.to_pandas()
            x      vector
         0  1  [1.0, 2.0]
@@ -1345,7 +1345,7 @@ class Table(ABC):
         >>> to_remove
         '1, 5'
         >>> table.delete(f"x IN ({to_remove})")
-        DeleteResult(version=3)
+        DeleteResult(num_deleted_rows=1, version=3)
         >>> table.to_pandas()
            x      vector
         0  3  [5.0, 6.0]
@@ -4181,6 +4181,7 @@ class AsyncTable:
                 when_not_matched_by_source_condition=merge._when_not_matched_by_source_condition,
                 timeout=merge._timeout,
                 use_index=merge._use_index,
+                mem_wal=merge._mem_wal,
             ),
         )
 
@@ -4215,7 +4216,7 @@ class AsyncTable:
         1  2  [3.0, 4.0]
         2  3  [5.0, 6.0]
         >>> table.delete("x = 2")
-        DeleteResult(version=2)
+        DeleteResult(num_deleted_rows=1, version=2)
         >>> table.to_pandas()
            x      vector
         0  1  [1.0, 2.0]
@@ -4229,7 +4230,7 @@ class AsyncTable:
         >>> to_remove
         '1, 5'
         >>> table.delete(f"x IN ({to_remove})")
-        DeleteResult(version=3)
+        DeleteResult(num_deleted_rows=1, version=3)
         >>> table.to_pandas()
            x      vector
         0  3  [5.0, 6.0]

python/python/lancedb/util.py

@@ -324,6 +324,16 @@ def _(value: list):
     return "[" + ", ".join(map(value_to_sql, value)) + "]"
 
 
+@value_to_sql.register(dict)
+def _(value: dict):
+    # https://datafusion.apache.org/user-guide/sql/scalar_functions.html#named-struct
+    return (
+        "named_struct("
+        + ", ".join(f"'{k}', {value_to_sql(v)}" for k, v in value.items())
+        + ")"
+    )
+
+
 @value_to_sql.register(np.ndarray)
 def _(value: np.ndarray):
     return value_to_sql(value.tolist())

python/python/tests/test_fts.py

@@ -27,6 +27,7 @@ from lancedb.query import (
     PhraseQuery,
     BooleanQuery,
     Occur,
+    LanceFtsQueryBuilder,
 )
 import numpy as np
 import pyarrow as pa
@@ -882,3 +883,109 @@ def test_fts_query_to_json():
         '"must_not":[]}}'
     )
     assert json_str == expected
+
+
+def test_fts_fast_search(table):
+    table.create_fts_index("text", use_tantivy=False)
+
+    # Insert some unindexed data
+    table.add(
+        [
+            {
+                "text": "xyz",
+                "vector": [0 for _ in range(128)],
+                "id": 101,
+                "text2": "xyz",
+                "nested": {"text": "xyz"},
+                "count": 10,
+            }
+        ]
+    )
+
+    # Without fast_search, the query object should not have fast_search set
+    builder = table.search("xyz", query_type="fts").limit(10)
+    query = builder.to_query_object()
+    assert query.fast_search is None
+
+    # With fast_search, the query object should have fast_search=True
+    builder = table.search("xyz", query_type="fts").fast_search().limit(10)
+    query = builder.to_query_object()
+    assert query.fast_search is True
+
+    # fast_search should be chainable with other methods
+    builder = (
+        table.search("xyz", query_type="fts").fast_search().select(["text"]).limit(5)
+    )
+    query = builder.to_query_object()
+    assert query.fast_search is True
+    assert query.limit == 5
+    assert query.columns == ["text"]
+
+    # fast_search should be enabled by keyword argument too
+    query = LanceFtsQueryBuilder(table, "xyz", fast_search=True).to_query_object()
+    assert query.fast_search is True
+
+    # Verify it executes without error and skips unindexed data
+    results = table.search("xyz", query_type="fts").fast_search().limit(5).to_list()
+    assert len(results) == 0
+
+    # Update index and verify it returns results
+    table.optimize()
+    results = table.search("xyz", query_type="fts").fast_search().limit(5).to_list()
+    assert len(results) > 0
+
+
+@pytest.mark.asyncio
+async def test_fts_fast_search_async(async_table):
+    await async_table.create_index("text", config=FTS())
+
+    # Insert some unindexed data
+    await async_table.add(
+        [
+            {
+                "text": "xyz",
+                "vector": [0 for _ in range(128)],
+                "id": 101,
+                "text2": "xyz",
+                "nested": {"text": "xyz"},
+                "count": 10,
+            }
+        ]
+    )
+
+    # Without fast_search, should return results
+    results = await async_table.query().nearest_to_text("xyz").limit(5).to_list()
+    assert len(results) > 0
+
+    # With fast_search, should return no results data unindexed
+    fast_results = (
+        await async_table.query()
+        .nearest_to_text("xyz")
+        .fast_search()
+        .limit(5)
+        .to_list()
+    )
+    assert len(fast_results) == 0
+
+    # Update index and verify it returns results
+    await async_table.optimize()
+
+    fast_results = (
+        await async_table.query()
+        .nearest_to_text("xyz")
+        .fast_search()
+        .limit(5)
+        .to_list()
+    )
+    assert len(fast_results) > 0
+
+    # fast_search should be chainable with other methods
+    results = (
+        await async_table.query()
+        .nearest_to_text("xyz")
+        .fast_search()
+        .select(["text"])
+        .limit(5)
+        .to_list()
+    )
+    assert len(results) > 0

python/python/tests/test_util.py

@@ -121,6 +121,32 @@ def test_value_to_sql_string(tmp_path):
         assert table.to_pandas().query("search == @value")["replace"].item() == value
 
 
+def test_value_to_sql_dict():
+    # Simple flat struct
+    assert value_to_sql({"a": 1, "b": "hello"}) == "named_struct('a', 1, 'b', 'hello')"
+
+    # Nested struct
+    assert (
+        value_to_sql({"outer": {"inner": 1}})
+        == "named_struct('outer', named_struct('inner', 1))"
+    )
+
+    # List inside struct
+    assert value_to_sql({"a": [1, 2]}) == "named_struct('a', [1, 2])"
+
+    # Mixed types
+    assert (
+        value_to_sql({"name": "test", "count": 42, "rate": 3.14, "active": True})
+        == "named_struct('name', 'test', 'count', 42, 'rate', 3.14, 'active', TRUE)"
+    )
+
+    # Null value inside struct
+    assert value_to_sql({"a": None}) == "named_struct('a', NULL)"
+
+    # Empty dict
+    assert value_to_sql({}) == "named_struct()"
+
+
 def test_append_vector_columns():
     registry = EmbeddingFunctionRegistry.get_instance()
     registry.register("test")(MockTextEmbeddingFunction)

python/src/arrow.rs

@@ -10,7 +10,7 @@ use arrow::{
 use futures::stream::StreamExt;
 use lancedb::arrow::SendableRecordBatchStream;
 use pyo3::{
-    exceptions::PyStopAsyncIteration, pyclass, pymethods, Bound, Py, PyAny, PyRef, PyResult, Python,
+    Bound, Py, PyAny, PyRef, PyResult, Python, exceptions::PyStopAsyncIteration, pyclass, pymethods,
 };
 use pyo3_async_runtimes::tokio::future_into_py;
 

python/src/connection.rs

@@ -9,10 +9,10 @@ use lancedb::{
     database::{CreateTableMode, Database, ReadConsistency},
 };
 use pyo3::{
+    Bound, FromPyObject, Py, PyAny, PyRef, PyResult, Python,
     exceptions::{PyRuntimeError, PyValueError},
     pyclass, pyfunction, pymethods,
     types::{PyDict, PyDictMethods},
-    Bound, FromPyObject, Py, PyAny, PyRef, PyResult, Python,
 };
 use pyo3_async_runtimes::tokio::future_into_py;
 
@@ -506,6 +506,7 @@ pub struct PyClientConfig {
     id_delimiter: Option<String>,
     tls_config: Option<PyClientTlsConfig>,
     header_provider: Option<Py<PyAny>>,
+    mem_wal_enabled: Option<bool>,
 }
 
 #[derive(FromPyObject)]
@@ -590,6 +591,7 @@ impl From<PyClientConfig> for lancedb::remote::ClientConfig {
             id_delimiter: value.id_delimiter,
             tls_config: value.tls_config.map(Into::into),
             header_provider,
+            mem_wal_enabled: value.mem_wal_enabled,
         }
     }
 }

python/src/error.rs

@@ -2,10 +2,10 @@
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
 use pyo3::{
+    PyErr, PyResult, Python,
     exceptions::{PyIOError, PyNotImplementedError, PyOSError, PyRuntimeError, PyValueError},
     intern,
     types::{PyAnyMethods, PyNone},
-    PyErr, PyResult, Python,
 };
 
 use lancedb::error::Error as LanceError;

python/src/index.rs

@@ -3,17 +3,17 @@
 
 use lancedb::index::vector::{IvfFlatIndexBuilder, IvfRqIndexBuilder, IvfSqIndexBuilder};
 use lancedb::index::{
+    Index as LanceDbIndex,
     scalar::{BTreeIndexBuilder, FtsIndexBuilder},
     vector::{IvfHnswPqIndexBuilder, IvfHnswSqIndexBuilder, IvfPqIndexBuilder},
-    Index as LanceDbIndex,
 };
-use pyo3::types::PyStringMethods;
 use pyo3::IntoPyObject;
+use pyo3::types::PyStringMethods;
 use pyo3::{
+    Bound, FromPyObject, PyAny, PyResult, Python,
     exceptions::{PyKeyError, PyValueError},
     intern, pyclass, pymethods,
     types::PyAnyMethods,
-    Bound, FromPyObject, PyAny, PyResult, Python,
 };
 
 use crate::util::parse_distance_type;
@@ -41,7 +41,12 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                 let inner_opts = FtsIndexBuilder::default()
                     .base_tokenizer(params.base_tokenizer)
                     .language(&params.language)
-                    .map_err(|_| PyValueError::new_err(format!("LanceDB does not support the requested language: '{}'", params.language)))?
+                    .map_err(|_| {
+                        PyValueError::new_err(format!(
+                            "LanceDB does not support the requested language: '{}'",
+                            params.language
+                        ))
+                    })?
                     .with_position(params.with_position)
                     .lower_case(params.lower_case)
                     .max_token_length(params.max_token_length)
@@ -52,7 +57,7 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                     .ngram_max_length(params.ngram_max_length)
                     .ngram_prefix_only(params.prefix_only);
                 Ok(LanceDbIndex::FTS(inner_opts))
-            },
+            }
             "IvfFlat" => {
                 let params = source.extract::<IvfFlatParams>()?;
                 let distance_type = parse_distance_type(params.distance_type)?;
@@ -64,10 +69,11 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                     ivf_flat_builder = ivf_flat_builder.num_partitions(num_partitions);
                 }
                 if let Some(target_partition_size) = params.target_partition_size {
-                    ivf_flat_builder = ivf_flat_builder.target_partition_size(target_partition_size);
+                    ivf_flat_builder =
+                        ivf_flat_builder.target_partition_size(target_partition_size);
                 }
                 Ok(LanceDbIndex::IvfFlat(ivf_flat_builder))
-            },
+            }
             "IvfPq" => {
                 let params = source.extract::<IvfPqParams>()?;
                 let distance_type = parse_distance_type(params.distance_type)?;
@@ -86,7 +92,7 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                     ivf_pq_builder = ivf_pq_builder.num_sub_vectors(num_sub_vectors);
                 }
                 Ok(LanceDbIndex::IvfPq(ivf_pq_builder))
-            },
+            }
             "IvfSq" => {
                 let params = source.extract::<IvfSqParams>()?;
                 let distance_type = parse_distance_type(params.distance_type)?;
@@ -101,7 +107,7 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                     ivf_sq_builder = ivf_sq_builder.target_partition_size(target_partition_size);
                 }
                 Ok(LanceDbIndex::IvfSq(ivf_sq_builder))
-            },
+            }
             "IvfRq" => {
                 let params = source.extract::<IvfRqParams>()?;
                 let distance_type = parse_distance_type(params.distance_type)?;
@@ -117,7 +123,7 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                     ivf_rq_builder = ivf_rq_builder.target_partition_size(target_partition_size);
                 }
                 Ok(LanceDbIndex::IvfRq(ivf_rq_builder))
-            },
+            }
             "HnswPq" => {
                 let params = source.extract::<IvfHnswPqParams>()?;
                 let distance_type = parse_distance_type(params.distance_type)?;
@@ -138,7 +144,7 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                     hnsw_pq_builder = hnsw_pq_builder.num_sub_vectors(num_sub_vectors);
                 }
                 Ok(LanceDbIndex::IvfHnswPq(hnsw_pq_builder))
-            },
+            }
             "HnswSq" => {
                 let params = source.extract::<IvfHnswSqParams>()?;
                 let distance_type = parse_distance_type(params.distance_type)?;
@@ -155,7 +161,7 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                     hnsw_sq_builder = hnsw_sq_builder.target_partition_size(target_partition_size);
                 }
                 Ok(LanceDbIndex::IvfHnswSq(hnsw_sq_builder))
-            },
+            }
             not_supported => Err(PyValueError::new_err(format!(
                 "Invalid index type '{}'.  Must be one of BTree, Bitmap, LabelList, FTS, IvfPq, IvfSq, IvfHnswPq, or IvfHnswSq",
                 not_supported

python/src/lib.rs

@@ -2,14 +2,14 @@
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
 use arrow::RecordBatchStream;
-use connection::{connect, Connection};
+use connection::{Connection, connect};
 use env_logger::Env;
 use index::IndexConfig;
 use permutation::{PyAsyncPermutationBuilder, PyPermutationReader};
 use pyo3::{
-    pymodule,
+    Bound, PyResult, Python, pymodule,
     types::{PyModule, PyModuleMethods},
-    wrap_pyfunction, Bound, PyResult, Python,
+    wrap_pyfunction,
 };
 use query::{FTSQuery, HybridQuery, Query, VectorQuery};
 use session::Session;

python/src/permutation.rs

@@ -16,10 +16,10 @@ use lancedb::{
     query::Select,
 };
 use pyo3::{
+    Bound, PyAny, PyRef, PyRefMut, PyResult, Python,
     exceptions::PyRuntimeError,
     pyclass, pymethods,
     types::{PyAnyMethods, PyDict, PyDictMethods, PyType},
-    Bound, PyAny, PyRef, PyRefMut, PyResult, Python,
 };
 use pyo3_async_runtimes::tokio::future_into_py;
 

python/src/query.rs

@@ -4,9 +4,9 @@
 use std::sync::Arc;
 use std::time::Duration;
 
-use arrow::array::make_array;
 use arrow::array::Array;
 use arrow::array::ArrayData;
+use arrow::array::make_array;
 use arrow::pyarrow::FromPyArrow;
 use arrow::pyarrow::IntoPyArrow;
 use arrow::pyarrow::ToPyArrow;
@@ -22,23 +22,23 @@ use lancedb::query::{
     VectorQuery as LanceDbVectorQuery,
 };
 use lancedb::table::AnyQuery;
-use pyo3::prelude::{PyAnyMethods, PyDictMethods};
-use pyo3::pyfunction;
-use pyo3::pymethods;
-use pyo3::types::PyList;
-use pyo3::types::{PyDict, PyString};
 use pyo3::Bound;
 use pyo3::IntoPyObject;
 use pyo3::PyAny;
 use pyo3::PyRef;
 use pyo3::PyResult;
 use pyo3::Python;
-use pyo3::{exceptions::PyRuntimeError, FromPyObject};
+use pyo3::prelude::{PyAnyMethods, PyDictMethods};
+use pyo3::pyfunction;
+use pyo3::pymethods;
+use pyo3::types::PyList;
+use pyo3::types::{PyDict, PyString};
+use pyo3::{FromPyObject, exceptions::PyRuntimeError};
+use pyo3::{PyErr, pyclass};
 use pyo3::{
     exceptions::{PyNotImplementedError, PyValueError},
     intern,
 };
-use pyo3::{pyclass, PyErr};
 use pyo3_async_runtimes::tokio::future_into_py;
 
 use crate::util::parse_distance_type;

python/src/session.rs

@@ -4,7 +4,7 @@
 use std::sync::Arc;
 
 use lancedb::{ObjectStoreRegistry, Session as LanceSession};
-use pyo3::{pyclass, pymethods, PyResult};
+use pyo3::{PyResult, pyclass, pymethods};
 
 /// A session for managing caches and object stores across LanceDB operations.
 ///

python/src/storage_options.rs

@@ -66,13 +66,10 @@ impl StorageOptionsProvider for PyStorageOptionsProviderWrapper {
                     .inner
                     .bind(py)
                     .call_method0("fetch_storage_options")
-                    .map_err(|e| lance_core::Error::IO {
-                        source: Box::new(std::io::Error::other(format!(
-                            "Failed to call fetch_storage_options: {}",
-                            e
-                        ))),
-                        location: snafu::location!(),
-                    })?;
+                    .map_err(|e| lance_core::Error::io_source(Box::new(std::io::Error::other(format!(
+                        "Failed to call fetch_storage_options: {}",
+                        e
+                    )))))?;
 
                 // If result is None, return None
                 if result.is_none() {
@@ -81,26 +78,19 @@ impl StorageOptionsProvider for PyStorageOptionsProviderWrapper {
 
                 // Extract the result dict - should be a flat Map<String, String>
                 let result_dict = result.downcast::<PyDict>().map_err(|_| {
-                    lance_core::Error::InvalidInput {
-                        source: "fetch_storage_options() must return None or a dict of string key-value pairs".into(),
-                        location: snafu::location!(),
-                    }
+                    lance_core::Error::invalid_input(
+                        "fetch_storage_options() must return a dict of string key-value pairs or None",
+                    )
                 })?;
 
                 // Convert all entries to HashMap<String, String>
                 let mut storage_options = HashMap::new();
                 for (key, value) in result_dict.iter() {
                     let key_str: String = key.extract().map_err(|e| {
-                        lance_core::Error::InvalidInput {
-                            source: format!("Storage option key must be a string: {}", e).into(),
-                            location: snafu::location!(),
-                        }
+                        lance_core::Error::invalid_input(format!("Storage option key must be a string: {}", e))
                     })?;
                     let value_str: String = value.extract().map_err(|e| {
-                        lance_core::Error::InvalidInput {
-                            source: format!("Storage option value must be a string: {}", e).into(),
-                            location: snafu::location!(),
-                        }
+                        lance_core::Error::invalid_input(format!("Storage option value must be a string: {}", e))
                     })?;
                     storage_options.insert(key_str, value_str);
                 }
@@ -109,13 +99,10 @@ impl StorageOptionsProvider for PyStorageOptionsProviderWrapper {
             })
         })
         .await
-        .map_err(|e| lance_core::Error::IO {
-            source: Box::new(std::io::Error::other(format!(
-                "Task join error: {}",
-                e
-            ))),
-            location: snafu::location!(),
-        })?
+        .map_err(|e| lance_core::Error::io_source(Box::new(std::io::Error::other(format!(
+            "Task join error: {}",
+            e
+        )))))?
     }
 
     fn provider_id(&self) -> String {

python/src/table.rs

@@ -5,7 +5,7 @@ use std::{collections::HashMap, sync::Arc};
 use crate::{
     connection::Connection,
     error::PythonErrorExt,
-    index::{extract_index_params, IndexConfig},
+    index::{IndexConfig, extract_index_params},
     query::{Query, TakeQuery},
     table::scannable::PyScannable,
 };
@@ -19,10 +19,10 @@ use lancedb::table::{
     Table as LanceDbTable,
 };
 use pyo3::{
+    Bound, FromPyObject, PyAny, PyRef, PyResult, Python,
     exceptions::{PyKeyError, PyRuntimeError, PyValueError},
     pyclass, pymethods,
     types::{IntoPyDict, PyAnyMethods, PyDict, PyDictMethods},
-    Bound, FromPyObject, PyAny, PyRef, PyResult, Python,
 };
 use pyo3_async_runtimes::tokio::future_into_py;
 
@@ -112,19 +112,24 @@ impl From<lancedb::table::AddResult> for AddResult {
 #[pyclass(get_all)]
 #[derive(Clone, Debug)]
 pub struct DeleteResult {
+    pub num_deleted_rows: u64,
     pub version: u64,
 }
 
 #[pymethods]
 impl DeleteResult {
     pub fn __repr__(&self) -> String {
-        format!("DeleteResult(version={})", self.version)
+        format!(
+            "DeleteResult(num_deleted_rows={}, version={})",
+            self.num_deleted_rows, self.version
+        )
     }
 }
 
 impl From<lancedb::table::DeleteResult> for DeleteResult {
     fn from(result: lancedb::table::DeleteResult) -> Self {
         Self {
+            num_deleted_rows: result.num_deleted_rows,
             version: result.version,
         }
     }
@@ -537,7 +542,7 @@ impl Table {
         let inner = self_.inner_ref()?.clone();
         future_into_py(self_.py(), async move {
             let versions = inner.list_versions().await.infer_error()?;
-            let versions_as_dict = Python::attach(|py| {
+            Python::attach(|py| {
                 versions
                     .iter()
                     .map(|v| {
@@ -554,9 +559,7 @@ impl Table {
                         Ok(dict.unbind())
                     })
                     .collect::<PyResult<Vec<_>>>()
-            });
-
-            versions_as_dict
+            })
         })
     }
 
@@ -707,6 +710,9 @@ impl Table {
         if let Some(use_index) = parameters.use_index {
             builder.use_index(use_index);
         }
+        if let Some(mem_wal) = parameters.mem_wal {
+            builder.mem_wal(mem_wal);
+        }
 
         future_into_py(self_.py(), async move {
             let res = builder.execute(Box::new(batches)).await.infer_error()?;
@@ -867,6 +873,7 @@ pub struct MergeInsertParams {
     when_not_matched_by_source_condition: Option<String>,
     timeout: Option<std::time::Duration>,
     use_index: Option<bool>,
+    mem_wal: Option<bool>,
 }
 
 #[pyclass]

python/src/table/scannable.rs

@@ -10,11 +10,11 @@ use arrow::{
 };
 use futures::StreamExt;
 use lancedb::{
+    Error,
     arrow::{SendableRecordBatchStream, SimpleRecordBatchStream},
     data::scannable::Scannable,
-    Error,
 };
-use pyo3::{types::PyAnyMethods, FromPyObject, Py, PyAny, Python};
+use pyo3::{FromPyObject, Py, PyAny, Python, types::PyAnyMethods};
 
 /// Adapter that implements Scannable for a Python reader factory callable.
 ///
@@ -99,15 +99,15 @@ impl Scannable for PyScannable {
                         // Channel closed. Check if the task panicked — a panic
                         // drops the sender without sending an error, so without
                         // this check we'd silently return a truncated stream.
-                        if let Some(handle) = join_handle {
-                            if let Err(join_err) = handle.await {
-                                return Some((
-                                    Err(Error::Runtime {
-                                        message: format!("Reader task panicked: {}", join_err),
-                                    }),
-                                    (rx, None),
-                                ));
-                            }
+                        if let Some(handle) = join_handle
+                            && let Err(join_err) = handle.await
+                        {
+                            return Some((
+                                Err(Error::Runtime {
+                                    message: format!("Reader task panicked: {}", join_err),
+                                }),
+                                (rx, None),
+                            ));
                         }
                         None
                     }

python/src/util.rs

@@ -5,8 +5,9 @@ use std::sync::Mutex;
 
 use lancedb::DistanceType;
 use pyo3::{
+    PyResult,
     exceptions::{PyRuntimeError, PyValueError},
-    pyfunction, PyResult,
+    pyfunction,
 };
 
 /// A wrapper around a rust builder

rust/lancedb/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.27.0-beta.2"
+version = "0.27.0-beta.3"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true
@@ -25,9 +25,9 @@ datafusion-catalog.workspace = true
 datafusion-common.workspace = true
 datafusion-execution.workspace = true
 datafusion-expr.workspace = true
-datafusion-functions = "51.0"
+datafusion-functions.workspace = true
 datafusion-physical-expr.workspace = true
-datafusion-sql = "51.0"
+datafusion-sql.workspace = true
 datafusion-physical-plan.workspace = true
 datafusion.workspace = true
 object_store = { workspace = true }

rust/lancedb/examples/bedrock.rs

@@ -9,10 +9,9 @@ use aws_config::Region;
 use aws_sdk_bedrockruntime::Client;
 use futures::StreamExt;
 use lancedb::{
-    connect,
-    embeddings::{bedrock::BedrockEmbeddingFunction, EmbeddingDefinition, EmbeddingFunction},
+    Result, connect,
+    embeddings::{EmbeddingDefinition, EmbeddingFunction, bedrock::BedrockEmbeddingFunction},
     query::{ExecutableQuery, QueryBase},
-    Result,
 };
 
 #[tokio::main]

rust/lancedb/examples/full_text_search.rs

@@ -10,10 +10,10 @@ use futures::TryStreamExt;
 use lance_index::scalar::FullTextSearchQuery;
 use lancedb::connection::Connection;
 
-use lancedb::index::scalar::FtsIndexBuilder;
 use lancedb::index::Index;
+use lancedb::index::scalar::FtsIndexBuilder;
 use lancedb::query::{ExecutableQuery, QueryBase};
-use lancedb::{connect, Result, Table};
+use lancedb::{Result, Table, connect};
 use rand::random;
 
 #[tokio::main]
@@ -46,19 +46,21 @@ fn create_some_records() -> Result<Box<dyn arrow_array::RecordBatchReader + Send
         .collect::<Vec<_>>();
     let n_terms = 3;
     let batches = RecordBatchIterator::new(
-        vec![RecordBatch::try_new(
-            schema.clone(),
-            vec![
-                Arc::new(Int32Array::from_iter_values(0..TOTAL as i32)),
-                Arc::new(StringArray::from_iter_values((0..TOTAL).map(|_| {
-                    (0..n_terms)
-                        .map(|_| words[random::<u32>() as usize % words.len()])
-                        .collect::<Vec<_>>()
-                        .join(" ")
-                }))),
-            ],
-        )
-        .unwrap()]
+        vec![
+            RecordBatch::try_new(
+                schema.clone(),
+                vec![
+                    Arc::new(Int32Array::from_iter_values(0..TOTAL as i32)),
+                    Arc::new(StringArray::from_iter_values((0..TOTAL).map(|_| {
+                        (0..n_terms)
+                            .map(|_| words[random::<u32>() as usize % words.len()])
+                            .collect::<Vec<_>>()
+                            .join(" ")
+                    }))),
+                ],
+            )
+            .unwrap(),
+        ]
         .into_iter()
         .map(Ok),
         schema.clone(),

rust/lancedb/examples/hybrid_search.rs

@@ -5,16 +5,15 @@ use arrow_array::{RecordBatch, StringArray};
 use arrow_schema::{DataType, Field, Schema};
 use futures::TryStreamExt;
 use lance_index::scalar::FullTextSearchQuery;
-use lancedb::index::scalar::FtsIndexBuilder;
 use lancedb::index::Index;
+use lancedb::index::scalar::FtsIndexBuilder;
 use lancedb::{
-    connect,
+    Result, Table, connect,
     embeddings::{
-        sentence_transformers::SentenceTransformersEmbeddings, EmbeddingDefinition,
-        EmbeddingFunction,
+        EmbeddingDefinition, EmbeddingFunction,
+        sentence_transformers::SentenceTransformersEmbeddings,
     },
     query::{QueryBase, QueryExecutionOptions},
-    Result, Table,
 };
 use std::{iter::once, sync::Arc};
 

rust/lancedb/examples/ivf_pq.rs

@@ -14,10 +14,10 @@ use arrow_schema::{DataType, Field, Schema};
 use futures::TryStreamExt;
 use lancedb::connection::Connection;
 
-use lancedb::index::vector::IvfPqIndexBuilder;
 use lancedb::index::Index;
+use lancedb::index::vector::IvfPqIndexBuilder;
 use lancedb::query::{ExecutableQuery, QueryBase};
-use lancedb::{connect, DistanceType, Result, Table};
+use lancedb::{DistanceType, Result, Table, connect};
 
 #[tokio::main]
 async fn main() -> Result<()> {
@@ -51,19 +51,21 @@ fn create_some_records() -> Result<Box<dyn arrow_array::RecordBatchReader + Send
 
     // Create a RecordBatch stream.
     let batches = RecordBatchIterator::new(
-        vec![RecordBatch::try_new(
-            schema.clone(),
-            vec![
-                Arc::new(Int32Array::from_iter_values(0..TOTAL as i32)),
-                Arc::new(
-                    FixedSizeListArray::from_iter_primitive::<Float32Type, _, _>(
-                        (0..TOTAL).map(|_| Some(vec![Some(1.0); DIM])),
-                        DIM as i32,
+        vec![
+            RecordBatch::try_new(
+                schema.clone(),
+                vec![
+                    Arc::new(Int32Array::from_iter_values(0..TOTAL as i32)),
+                    Arc::new(
+                        FixedSizeListArray::from_iter_primitive::<Float32Type, _, _>(
+                            (0..TOTAL).map(|_| Some(vec![Some(1.0); DIM])),
+                            DIM as i32,
+                        ),
                     ),
-                ),
-            ],
-        )
-        .unwrap()]
+                ],
+            )
+            .unwrap(),
+        ]
         .into_iter()
         .map(Ok),
         schema.clone(),

rust/lancedb/examples/openai.rs

@@ -8,10 +8,9 @@ use std::{iter::once, sync::Arc};
 use arrow_array::{RecordBatch, StringArray};
 use futures::StreamExt;
 use lancedb::{
-    connect,
-    embeddings::{openai::OpenAIEmbeddingFunction, EmbeddingDefinition, EmbeddingFunction},
+    Result, connect,
+    embeddings::{EmbeddingDefinition, EmbeddingFunction, openai::OpenAIEmbeddingFunction},
     query::{ExecutableQuery, QueryBase},
-    Result,
 };
 
 // --8<-- [end:imports]

rust/lancedb/examples/sentence_transformers.rs

@@ -7,13 +7,12 @@ use arrow_array::{RecordBatch, StringArray};
 use arrow_schema::{DataType, Field, Schema};
 use futures::StreamExt;
 use lancedb::{
-    connect,
+    Result, connect,
     embeddings::{
-        sentence_transformers::SentenceTransformersEmbeddings, EmbeddingDefinition,
-        EmbeddingFunction,
+        EmbeddingDefinition, EmbeddingFunction,
+        sentence_transformers::SentenceTransformersEmbeddings,
     },
     query::{ExecutableQuery, QueryBase},
-    Result,
 };
 
 #[tokio::main]

rust/lancedb/examples/simple.rs

@@ -14,7 +14,7 @@ use futures::TryStreamExt;
 use lancedb::connection::Connection;
 use lancedb::index::Index;
 use lancedb::query::{ExecutableQuery, QueryBase};
-use lancedb::{connect, Result, Table as LanceDbTable};
+use lancedb::{Result, Table as LanceDbTable, connect};
 
 #[tokio::main]
 async fn main() -> Result<()> {

rust/lancedb/src/arrow.rs

@@ -12,7 +12,7 @@ use lance_datagen::{BatchCount, BatchGeneratorBuilder, RowCount};
 #[cfg(feature = "polars")]
 use {crate::polars_arrow_convertors, polars::frame::ArrowChunk, polars::prelude::DataFrame};
 
-use crate::{error::Result, Error};
+use crate::{Error, error::Result};
 
 /// An iterator of batches that also has a schema
 pub trait RecordBatchReader: Iterator<Item = Result<arrow_array::RecordBatch>> {

rust/lancedb/src/connection.rs

@@ -17,6 +17,7 @@ use lance_namespace::models::{
 #[cfg(feature = "aws")]
 use object_store::aws::AwsCredential;
 
+use crate::Table;
 use crate::connection::create_table::CreateTableBuilder;
 use crate::data::scannable::Scannable;
 use crate::database::listing::ListingDatabase;
@@ -31,7 +32,6 @@ use crate::remote::{
     client::ClientConfig,
     db::{OPT_REMOTE_API_KEY, OPT_REMOTE_HOST_OVERRIDE, OPT_REMOTE_REGION},
 };
-use crate::Table;
 use lance::io::ObjectStoreParams;
 pub use lance_encoding::version::LanceFileVersion;
 #[cfg(feature = "remote")]
@@ -566,8 +566,11 @@ pub struct ConnectBuilder {
 }
 
 #[cfg(feature = "remote")]
-const ENV_VARS_TO_STORAGE_OPTS: [(&str, &str); 1] =
-    [("AZURE_STORAGE_ACCOUNT_NAME", "azure_storage_account_name")];
+const ENV_VARS_TO_STORAGE_OPTS: [(&str, &str); 3] = [
+    ("AZURE_STORAGE_ACCOUNT_NAME", "azure_storage_account_name"),
+    ("AZURE_CLIENT_ID", "azure_client_id"),
+    ("AZURE_TENANT_ID", "azure_tenant_id"),
+];
 
 impl ConnectBuilder {
     /// Create a new [`ConnectOptions`] with the given database URI.
@@ -758,10 +761,10 @@ impl ConnectBuilder {
         options: &mut HashMap<String, String>,
     ) {
         for (env_key, opt_key) in env_var_to_remote_storage_option {
-            if let Ok(env_value) = std::env::var(env_key) {
-                if !options.contains_key(*opt_key) {
-                    options.insert((*opt_key).to_string(), env_value);
-                }
+            if let Ok(env_value) = std::env::var(env_key)
+                && !options.contains_key(*opt_key)
+            {
+                options.insert((*opt_key).to_string(), env_value);
             }
         }
     }
@@ -781,13 +784,19 @@ impl ConnectBuilder {
             message: "An api_key is required when connecting to LanceDb Cloud".to_string(),
         })?;
 
+        // Propagate mem_wal_enabled from options to client_config
+        let mut client_config = self.request.client_config;
+        if options.mem_wal_enabled.is_some() {
+            client_config.mem_wal_enabled = options.mem_wal_enabled;
+        }
+
         let storage_options = StorageOptions(options.storage_options.clone());
         let internal = Arc::new(crate::remote::db::RemoteDatabase::try_new(
             &self.request.uri,
             &api_key,
             &region,
             options.host_override,
-            self.request.client_config,
+            client_config,
             storage_options.into(),
         )?);
         Ok(Connection {
@@ -1011,14 +1020,13 @@ mod tests {
     #[cfg(feature = "remote")]
     #[test]
     fn test_apply_env_defaults() {
-        let env_key = "TEST_APPLY_ENV_DEFAULTS_ENVIRONMENT_VARIABLE_ENV_KEY";
-        let env_val = "TEST_APPLY_ENV_DEFAULTS_ENVIRONMENT_VARIABLE_ENV_VAL";
+        let env_key = "PATH";
+        let env_val = std::env::var(env_key).expect("PATH should be set in test environment");
         let opts_key = "test_apply_env_defaults_environment_variable_opts_key";
-        std::env::set_var(env_key, env_val);
 
         let mut options = HashMap::new();
         ConnectBuilder::apply_env_defaults(&[(env_key, opts_key)], &mut options);
-        assert_eq!(Some(&env_val.to_string()), options.get(opts_key));
+        assert_eq!(Some(&env_val), options.get(opts_key));
 
         options.insert(opts_key.to_string(), "EXPLICIT-VALUE".to_string());
         ConnectBuilder::apply_env_defaults(&[(env_key, opts_key)], &mut options);

rust/lancedb/src/connection/create_table.rs

@@ -6,12 +6,12 @@ use std::sync::Arc;
 use lance_io::object_store::StorageOptionsProvider;
 
 use crate::{
+    Error, Result, Table,
     connection::{merge_storage_options, set_storage_options_provider},
     data::scannable::{Scannable, WithEmbeddingsScannable},
     database::{CreateTableMode, CreateTableRequest, Database},
     embeddings::{EmbeddingDefinition, EmbeddingFunction, EmbeddingRegistry},
     table::WriteOptions,
-    Error, Result, Table,
 };
 
 pub struct CreateTableBuilder {
@@ -167,7 +167,7 @@ impl CreateTableBuilder {
 #[cfg(test)]
 mod tests {
     use arrow_array::{
-        record_batch, Array, FixedSizeListArray, Float32Array, RecordBatch, RecordBatchIterator,
+        Array, FixedSizeListArray, Float32Array, RecordBatch, RecordBatchIterator, record_batch,
     };
     use arrow_schema::{ArrowError, DataType, Field, Schema};
     use futures::TryStreamExt;
@@ -380,11 +380,12 @@ mod tests {
             .await
             .unwrap();
         let other_schema = Arc::new(Schema::new(vec![Field::new("y", DataType::Int32, false)]));
-        assert!(db
-            .create_empty_table("test", other_schema.clone())
-            .execute()
-            .await
-            .is_err()); // TODO: assert what this error is
+        assert!(
+            db.create_empty_table("test", other_schema.clone())
+                .execute()
+                .await
+                .is_err()
+        ); // TODO: assert what this error is
         let overwritten = db
             .create_empty_table("test", other_schema.clone())
             .mode(CreateTableMode::Overwrite)

rust/lancedb/src/data/inspect.rs

@@ -5,9 +5,9 @@ use std::collections::HashMap;
 
 use arrow::compute::kernels::{aggregate::bool_and, length::length};
 use arrow_array::{
+    Array, GenericListArray, OffsetSizeTrait, PrimitiveArray, RecordBatchReader,
     cast::AsArray,
     types::{ArrowPrimitiveType, Int32Type, Int64Type},
-    Array, GenericListArray, OffsetSizeTrait, PrimitiveArray, RecordBatchReader,
 };
 use arrow_ord::cmp::eq;
 use arrow_schema::DataType;
@@ -78,7 +78,7 @@ pub fn infer_vector_columns(
                 _ => {
                     return Err(Error::Schema {
                         message: format!("Column {} is not a list", col_name),
-                    })
+                    });
                 }
             } {
                 if let Some(Some(prev_dim)) = columns_to_infer.get(&col_name) {
@@ -102,8 +102,8 @@ mod tests {
     use super::*;
 
     use arrow_array::{
-        types::{Float32Type, Float64Type},
         FixedSizeListArray, Float32Array, ListArray, RecordBatch, RecordBatchIterator, StringArray,
+        types::{Float32Type, Float64Type},
     };
     use arrow_schema::{DataType, Field, Schema};
     use std::{sync::Arc, vec};

rust/lancedb/src/data/sanitize.rs

@@ -4,10 +4,10 @@
 use std::{iter::repeat_with, sync::Arc};
 
 use arrow_array::{
-    cast::AsArray,
-    types::{Float16Type, Float32Type, Float64Type, Int32Type, Int64Type},
     Array, ArrowNumericType, FixedSizeListArray, PrimitiveArray, RecordBatch, RecordBatchIterator,
     RecordBatchReader,
+    cast::AsArray,
+    types::{Float16Type, Float32Type, Float64Type, Int32Type, Int64Type},
 };
 use arrow_cast::{can_cast_types, cast};
 use arrow_schema::{ArrowError, DataType, Field, Schema};
@@ -184,7 +184,7 @@ mod tests {
     use std::sync::Arc;
 
     use arrow_array::{
-        FixedSizeListArray, Float16Array, Float32Array, Float64Array, Int32Array, Int8Array,
+        FixedSizeListArray, Float16Array, Float32Array, Float64Array, Int8Array, Int32Array,
         RecordBatch, RecordBatchIterator, StringArray,
     };
     use arrow_schema::Field;

rust/lancedb/src/data/scannable.rs

@@ -13,16 +13,16 @@ use crate::arrow::{
     SendableRecordBatchStream, SendableRecordBatchStreamExt, SimpleRecordBatchStream,
 };
 use crate::embeddings::{
-    compute_embeddings_for_batch, compute_output_schema, EmbeddingDefinition, EmbeddingFunction,
-    EmbeddingRegistry,
+    EmbeddingDefinition, EmbeddingFunction, EmbeddingRegistry, compute_embeddings_for_batch,
+    compute_output_schema,
 };
 use crate::table::{ColumnDefinition, ColumnKind, TableDefinition};
 use crate::{Error, Result};
 use arrow_array::{ArrayRef, RecordBatch, RecordBatchIterator, RecordBatchReader};
 use arrow_schema::{ArrowError, SchemaRef};
 use async_trait::async_trait;
-use futures::stream::once;
 use futures::StreamExt;
+use futures::stream::once;
 use lance_datafusion::utils::StreamingWriteSource;
 
 pub trait Scannable: Send {

rust/lancedb/src/database.rs

@@ -19,12 +19,12 @@ use std::sync::Arc;
 use std::time::Duration;
 
 use lance::dataset::ReadParams;
+use lance_namespace::LanceNamespace;
 use lance_namespace::models::{
     CreateNamespaceRequest, CreateNamespaceResponse, DescribeNamespaceRequest,
     DescribeNamespaceResponse, DropNamespaceRequest, DropNamespaceResponse, ListNamespacesRequest,
     ListNamespacesResponse, ListTablesRequest, ListTablesResponse,
 };
-use lance_namespace::LanceNamespace;
 
 use crate::data::scannable::Scannable;
 use crate::error::Result;

rust/lancedb/src/database/listing.rs

@@ -8,7 +8,7 @@ use std::path::Path;
 use std::{collections::HashMap, sync::Arc};
 
 use lance::dataset::refs::Ref;
-use lance::dataset::{builder::DatasetBuilder, ReadParams, WriteMode};
+use lance::dataset::{ReadParams, WriteMode, builder::DatasetBuilder};
 use lance::io::{ObjectStore, ObjectStoreParams, WrappingObjectStore};
 use lance_datafusion::utils::StreamingWriteSource;
 use lance_encoding::version::LanceFileVersion;
@@ -1097,11 +1097,11 @@ impl Database for ListingDatabase {
 #[cfg(test)]
 mod tests {
     use super::*;
+    use crate::Table;
     use crate::connection::ConnectRequest;
     use crate::data::scannable::Scannable;
     use crate::database::{CreateTableMode, CreateTableRequest};
     use crate::table::WriteOptions;
-    use crate::Table;
     use arrow_array::{Int32Array, RecordBatch, StringArray};
     use arrow_schema::{DataType, Field, Schema};
     use std::path::PathBuf;

rust/lancedb/src/database/namespace.rs

@@ -9,16 +9,15 @@ use std::sync::Arc;
 use async_trait::async_trait;
 use lance_io::object_store::{ObjectStoreParams, StorageOptionsAccessor};
 use lance_namespace::{
-    models::{
-        CreateEmptyTableRequest, CreateNamespaceRequest, CreateNamespaceResponse,
-        DeclareTableRequest, DescribeNamespaceRequest, DescribeNamespaceResponse,
-        DescribeTableRequest, DropNamespaceRequest, DropNamespaceResponse, DropTableRequest,
-        ListNamespacesRequest, ListNamespacesResponse, ListTablesRequest, ListTablesResponse,
-    },
     LanceNamespace,
+    models::{
+        CreateNamespaceRequest, CreateNamespaceResponse, DeclareTableRequest,
+        DescribeNamespaceRequest, DescribeNamespaceResponse, DescribeTableRequest,
+        DropNamespaceRequest, DropNamespaceResponse, DropTableRequest, ListNamespacesRequest,
+        ListNamespacesResponse, ListTablesRequest, ListTablesResponse,
+    },
 };
 use lance_namespace_impls::ConnectBuilder;
-use log::warn;
 
 use crate::database::ReadConsistency;
 use crate::error::{Error, Result};
@@ -213,63 +212,18 @@ impl Database for LanceNamespaceDatabase {
             ..Default::default()
         };
 
-        let (location, initial_storage_options) =
-            match self.namespace.declare_table(declare_request).await {
-                Ok(response) => {
-                    let loc = response.location.ok_or_else(|| Error::Runtime {
-                        message: "Table location is missing from declare_table response"
-                            .to_string(),
-                    })?;
-                    // Use storage options from response, fall back to self.storage_options
-                    let opts = response
-                        .storage_options
-                        .or_else(|| Some(self.storage_options.clone()))
-                        .filter(|o| !o.is_empty());
-                    (loc, opts)
-                }
-                Err(e) => {
-                    // Check if the error is "not supported" and try create_empty_table as fallback
-                    let err_str = e.to_string().to_lowercase();
-                    if err_str.contains("not supported") || err_str.contains("not implemented") {
-                        warn!(
-                            "declare_table is not supported by the namespace client, \
-                        falling back to deprecated create_empty_table. \
-                        create_empty_table is deprecated and will be removed in Lance 3.0.0. \
-                        Please upgrade your namespace client to support declare_table."
-                        );
-                        #[allow(deprecated)]
-                        let create_empty_request = CreateEmptyTableRequest {
-                            id: Some(table_id.clone()),
-                            ..Default::default()
-                        };
-
-                        #[allow(deprecated)]
-                        let create_response = self
-                            .namespace
-                            .create_empty_table(create_empty_request)
-                            .await
-                            .map_err(|e| Error::Runtime {
-                                message: format!("Failed to create empty table: {}", e),
-                            })?;
-
-                        let loc = create_response.location.ok_or_else(|| Error::Runtime {
-                            message: "Table location is missing from create_empty_table response"
-                                .to_string(),
-                        })?;
-                        // For deprecated path, use self.storage_options
-                        let opts = if self.storage_options.is_empty() {
-                            None
-                        } else {
-                            Some(self.storage_options.clone())
-                        };
-                        (loc, opts)
-                    } else {
-                        return Err(Error::Runtime {
-                            message: format!("Failed to declare table: {}", e),
-                        });
-                    }
-                }
-            };
+        let (location, initial_storage_options) = {
+            let response = self.namespace.declare_table(declare_request).await?;
+            let loc = response.location.ok_or_else(|| Error::Runtime {
+                message: "Table location is missing from declare_table response".to_string(),
+            })?;
+            // Use storage options from response, fall back to self.storage_options
+            let opts = response
+                .storage_options
+                .or_else(|| Some(self.storage_options.clone()))
+                .filter(|o| !o.is_empty());
+            (loc, opts)
+        };
 
         let write_params = if let Some(storage_opts) = initial_storage_options {
             let mut params = request.write_options.lance_write_params.unwrap_or_default();

rust/lancedb/src/dataloader/permutation/builder.rs

@@ -11,16 +11,16 @@ use lance_core::ROW_ID;
 use lance_datafusion::exec::SessionContextExt;
 
 use crate::{
+    Error, Result, Table,
     arrow::{SendableRecordBatchStream, SendableRecordBatchStreamExt, SimpleRecordBatchStream},
     connect,
     database::{CreateTableRequest, Database},
     dataloader::permutation::{
         shuffle::{Shuffler, ShufflerConfig},
-        split::{SplitStrategy, Splitter, SPLIT_ID_COLUMN},
-        util::{rename_column, TemporaryDirectory},
+        split::{SPLIT_ID_COLUMN, SplitStrategy, Splitter},
+        util::{TemporaryDirectory, rename_column},
     },
     query::{ExecutableQuery, QueryBase, Select},
-    Error, Result, Table,
 };
 
 pub const SRC_ROW_ID_COL: &str = "row_id";

rust/lancedb/src/dataloader/permutation/reader.rs

@@ -25,8 +25,8 @@ use futures::{StreamExt, TryStreamExt};
 use lance::dataset::scanner::DatasetRecordBatchStream;
 use lance::io::RecordBatchStream;
 use lance_arrow::RecordBatchExt;
-use lance_core::error::LanceOptionExt;
 use lance_core::ROW_ID;
+use lance_core::error::LanceOptionExt;
 use std::collections::HashMap;
 use std::sync::Arc;
 
@@ -500,10 +500,10 @@ mod tests {
     use rand::seq::SliceRandom;
 
     use crate::{
+        Table,
         arrow::SendableRecordBatchStream,
         query::{ExecutableQuery, QueryBase},
-        test_utils::datagen::{virtual_table, LanceDbDatagenExt},
-        Table,
+        test_utils::datagen::{LanceDbDatagenExt, virtual_table},
     };
 
     use super::*;

rust/lancedb/src/dataloader/permutation/shuffle.rs

@@ -18,12 +18,12 @@ use lance_io::{
     scheduler::{ScanScheduler, SchedulerConfig},
     utils::CachedFileSize,
 };
-use rand::{seq::SliceRandom, Rng, RngCore};
+use rand::{Rng, RngCore, seq::SliceRandom};
 
 use crate::{
-    arrow::{SendableRecordBatchStream, SimpleRecordBatchStream},
-    dataloader::permutation::util::{non_crypto_rng, TemporaryDirectory},
     Error, Result,
+    arrow::{SendableRecordBatchStream, SimpleRecordBatchStream},
+    dataloader::permutation::util::{TemporaryDirectory, non_crypto_rng},
 };
 
 #[derive(Debug, Clone)]
@@ -281,7 +281,7 @@ mod tests {
     use datafusion_expr::col;
     use futures::TryStreamExt;
     use lance_datagen::{BatchCount, BatchGeneratorBuilder, ByteCount, RowCount, Seed};
-    use rand::{rngs::SmallRng, SeedableRng};
+    use rand::{SeedableRng, rngs::SmallRng};
 
     fn test_gen() -> BatchGeneratorBuilder {
         lance_datagen::gen_batch()

rust/lancedb/src/dataloader/permutation/split.rs

@@ -2,8 +2,8 @@
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
 use std::sync::{
-    atomic::{AtomicBool, AtomicU64, AtomicUsize, Ordering},
     Arc,
+    atomic::{AtomicBool, AtomicU64, AtomicUsize, Ordering},
 };
 
 use arrow_array::{Array, BooleanArray, RecordBatch, UInt64Array};
@@ -15,13 +15,13 @@ use lance_arrow::SchemaExt;
 use lance_core::ROW_ID;
 
 use crate::{
+    Error, Result,
     arrow::{SendableRecordBatchStream, SimpleRecordBatchStream},
     dataloader::{
         permutation::shuffle::{Shuffler, ShufflerConfig},
         permutation::util::TemporaryDirectory,
     },
     query::{Query, QueryBase, Select},
-    Error, Result,
 };
 
 pub const SPLIT_ID_COLUMN: &str = "split_id";

rust/lancedb/src/dataloader/permutation/util.rs

@@ -7,12 +7,12 @@ use arrow_array::RecordBatch;
 use arrow_schema::{Fields, Schema};
 use datafusion_execution::disk_manager::DiskManagerMode;
 use futures::TryStreamExt;
-use rand::{rngs::SmallRng, RngCore, SeedableRng};
+use rand::{RngCore, SeedableRng, rngs::SmallRng};
 use tempfile::TempDir;
 
 use crate::{
-    arrow::{SendableRecordBatchStream, SimpleRecordBatchStream},
     Error, Result,
+    arrow::{SendableRecordBatchStream, SimpleRecordBatchStream},
 };
 
 /// Directory to use for temporary files

rust/lancedb/src/embeddings.rs

@@ -23,9 +23,9 @@ use arrow_schema::{DataType, Field, SchemaBuilder, SchemaRef};
 use serde::{Deserialize, Serialize};
 
 use crate::{
+    Error,
     error::Result,
     table::{ColumnDefinition, ColumnKind, TableDefinition},
-    Error,
 };
 
 /// Trait for embedding functions

rust/lancedb/src/embeddings/bedrock.rs

@@ -8,7 +8,7 @@ use arrow::array::{AsArray, Float32Builder};
 use arrow_array::{Array, ArrayRef, FixedSizeListArray, Float32Array};
 use arrow_data::ArrayData;
 use arrow_schema::DataType;
-use serde_json::{json, Value};
+use serde_json::{Value, json};
 
 use super::EmbeddingFunction;
 use crate::{Error, Result};

rust/lancedb/src/embeddings/openai.rs

@@ -8,9 +8,9 @@ use arrow_array::{Array, ArrayRef, FixedSizeListArray, Float32Array};
 use arrow_data::ArrayData;
 use arrow_schema::DataType;
 use async_openai::{
+    Client,
     config::OpenAIConfig,
     types::{CreateEmbeddingRequest, Embedding, EmbeddingInput, EncodingFormat},
-    Client,
 };
 use tokio::{runtime::Handle, task};
 

rust/lancedb/src/embeddings/sentence_transformers.rs

@@ -7,7 +7,7 @@ use super::EmbeddingFunction;
 use arrow::{
     array::{AsArray, PrimitiveBuilder},
     datatypes::{
-        ArrowPrimitiveType, Float16Type, Float32Type, Float64Type, Int64Type, UInt32Type, UInt8Type,
+        ArrowPrimitiveType, Float16Type, Float32Type, Float64Type, Int64Type, UInt8Type, UInt32Type,
     },
 };
 use arrow_array::{Array, FixedSizeListArray, PrimitiveArray};
@@ -16,8 +16,8 @@ use arrow_schema::DataType;
 use candle_core::{CpuStorage, Device, Layout, Storage, Tensor};
 use candle_nn::VarBuilder;
 use candle_transformers::models::bert::{BertModel, DTYPE};
-use hf_hub::{api::sync::Api, Repo, RepoType};
-use tokenizers::{tokenizer::Tokenizer, PaddingParams};
+use hf_hub::{Repo, RepoType, api::sync::Api};
+use tokenizers::{PaddingParams, tokenizer::Tokenizer};
 
 /// Compute embeddings using huggingface sentence-transformers.
 pub struct SentenceTransformersEmbeddingsBuilder {
@@ -230,7 +230,7 @@ impl SentenceTransformersEmbeddings {
             Storage::Cpu(CpuStorage::BF16(_)) => {
                 return Err(crate::Error::Runtime {
                     message: "unsupported data type".to_string(),
-                })
+                });
             }
             _ => unreachable!("we already moved the tensor to the CPU device"),
         };
@@ -298,12 +298,12 @@ impl SentenceTransformersEmbeddings {
             DataType::Utf8View => {
                 return Err(crate::Error::Runtime {
                     message: "Utf8View not yet implemented".to_string(),
-                })
+                });
             }
             _ => {
                 return Err(crate::Error::Runtime {
                     message: "invalid type".to_string(),
-                })
+                });
             }
         };
 

rust/lancedb/src/expr.rs

@@ -24,7 +24,7 @@ pub use sql::expr_to_sql_string;
 use std::sync::Arc;
 
 use arrow_schema::DataType;
-use datafusion_expr::{expr_fn::cast, Expr, ScalarUDF};
+use datafusion_expr::{Expr, ScalarUDF, expr_fn::cast};
 use datafusion_functions::string::expr_fn as string_expr_fn;
 
 pub use datafusion_expr::{col, lit};

rust/lancedb/src/index.rs

@@ -9,7 +9,7 @@ use std::time::Duration;
 use vector::IvfFlatIndexBuilder;
 
 use crate::index::vector::IvfRqIndexBuilder;
-use crate::{table::BaseTable, DistanceType, Error, Result};
+use crate::{DistanceType, Error, Result, table::BaseTable};
 
 use self::{
     scalar::{BTreeIndexBuilder, BitmapIndexBuilder, LabelListIndexBuilder},

rust/lancedb/src/index/scalar.rs

@@ -27,7 +27,7 @@
 ///
 /// The btree index does not currently have any parameters though parameters such as the
 /// block size may be added in the future.
-#[derive(Default, Debug, Clone)]
+#[derive(Default, Debug, Clone, serde::Serialize)]
 pub struct BTreeIndexBuilder {}
 
 impl BTreeIndexBuilder {}
@@ -39,7 +39,7 @@ impl BTreeIndexBuilder {}
 /// This index works best for low-cardinality (i.e., less than 1000 unique values) columns,
 /// where the number of unique values is small.
 /// The bitmap stores a list of row ids where the value is present.
-#[derive(Debug, Clone, Default)]
+#[derive(Debug, Clone, Default, serde::Serialize)]
 pub struct BitmapIndexBuilder {}
 
 /// Builder for LabelList index.
@@ -48,10 +48,10 @@ pub struct BitmapIndexBuilder {}
 /// support queries with `array_contains_all` and `array_contains_any`
 /// using an underlying bitmap index.
 ///
-#[derive(Debug, Clone, Default)]
+#[derive(Debug, Clone, Default, serde::Serialize)]
 pub struct LabelListIndexBuilder {}
 
-pub use lance_index::scalar::inverted::query::*;
 pub use lance_index::scalar::FullTextSearchQuery;
 pub use lance_index::scalar::InvertedIndexParams as FtsIndexBuilder;
 pub use lance_index::scalar::InvertedIndexParams;
+pub use lance_index::scalar::inverted::query::*;

rust/lancedb/src/index/vector.rs

@@ -7,6 +7,7 @@
 //! Vector indices are only supported on fixed-size-list (tensor) columns of floating point
 //! values
 use lance::table::format::{IndexMetadata, Manifest};
+use serde::Serialize;
 
 use crate::DistanceType;
 
@@ -181,14 +182,17 @@ macro_rules! impl_hnsw_params_setter {
 /// The partitioning process is called IVF and the `num_partitions` parameter controls how many groups to create.
 ///
 /// Note that training an IVF Flat index on a large dataset is a slow operation and currently is also a memory intensive operation.
-#[derive(Debug, Clone)]
+#[derive(Debug, Clone, Serialize)]
 pub struct IvfFlatIndexBuilder {
+    #[serde(rename = "metric_type")]
     pub(crate) distance_type: DistanceType,
 
     // IVF
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) num_partitions: Option<u32>,
     pub(crate) sample_rate: u32,
     pub(crate) max_iterations: u32,
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) target_partition_size: Option<u32>,
 }
 
@@ -213,14 +217,17 @@ impl IvfFlatIndexBuilder {
 ///
 /// This index compresses vectors using scalar quantization and groups them into IVF partitions.
 /// It offers a balance between search performance and storage footprint.
-#[derive(Debug, Clone)]
+#[derive(Debug, Clone, Serialize)]
 pub struct IvfSqIndexBuilder {
+    #[serde(rename = "metric_type")]
     pub(crate) distance_type: DistanceType,
 
     // IVF
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) num_partitions: Option<u32>,
     pub(crate) sample_rate: u32,
     pub(crate) max_iterations: u32,
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) target_partition_size: Option<u32>,
 }
 
@@ -261,18 +268,23 @@ impl IvfSqIndexBuilder {
 ///
 /// Note that training an IVF PQ index on a large dataset is a slow operation and
 /// currently is also a memory intensive operation.
-#[derive(Debug, Clone)]
+#[derive(Debug, Clone, Serialize)]
 pub struct IvfPqIndexBuilder {
+    #[serde(rename = "metric_type")]
     pub(crate) distance_type: DistanceType,
 
     // IVF
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) num_partitions: Option<u32>,
     pub(crate) sample_rate: u32,
     pub(crate) max_iterations: u32,
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) target_partition_size: Option<u32>,
 
     // PQ
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) num_sub_vectors: Option<u32>,
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) num_bits: Option<u32>,
 }
 
@@ -323,14 +335,18 @@ pub(crate) fn suggested_num_sub_vectors(dim: u32) -> u32 {
 ///
 /// Note that training an IVF RQ index on a large dataset is a slow operation and
 /// currently is also a memory intensive operation.
-#[derive(Debug, Clone)]
+#[derive(Debug, Clone, Serialize)]
 pub struct IvfRqIndexBuilder {
     // IVF
+    #[serde(rename = "metric_type")]
     pub(crate) distance_type: DistanceType,
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) num_partitions: Option<u32>,
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) num_bits: Option<u32>,
     pub(crate) sample_rate: u32,
     pub(crate) max_iterations: u32,
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) target_partition_size: Option<u32>,
 }
 
@@ -365,13 +381,16 @@ impl IvfRqIndexBuilder {
 /// quickly find the closest vectors to a query vector.
 ///
 /// The PQ (product quantizer) is used to compress the vectors as the same as IVF PQ.
-#[derive(Debug, Clone)]
+#[derive(Debug, Clone, Serialize)]
 pub struct IvfHnswPqIndexBuilder {
     // IVF
+    #[serde(rename = "metric_type")]
     pub(crate) distance_type: DistanceType,
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) num_partitions: Option<u32>,
     pub(crate) sample_rate: u32,
     pub(crate) max_iterations: u32,
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) target_partition_size: Option<u32>,
 
     // HNSW
@@ -379,7 +398,9 @@ pub struct IvfHnswPqIndexBuilder {
     pub(crate) ef_construction: u32,
 
     // PQ
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) num_sub_vectors: Option<u32>,
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) num_bits: Option<u32>,
 }
 
@@ -415,13 +436,16 @@ impl IvfHnswPqIndexBuilder {
 ///
 /// The SQ (scalar quantizer) is used to compress the vectors,
 /// each vector is mapped to a 8-bit integer vector, 4x compression ratio for float32 vector.
-#[derive(Debug, Clone)]
+#[derive(Debug, Clone, Serialize)]
 pub struct IvfHnswSqIndexBuilder {
     // IVF
+    #[serde(rename = "metric_type")]
     pub(crate) distance_type: DistanceType,
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) num_partitions: Option<u32>,
     pub(crate) sample_rate: u32,
     pub(crate) max_iterations: u32,
+    #[serde(skip_serializing_if = "Option::is_none")]
     pub(crate) target_partition_size: Option<u32>,
 
     // HNSW

rust/lancedb/src/index/waiter.rs

@@ -1,9 +1,9 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
+use crate::Error;
 use crate::error::Result;
 use crate::table::BaseTable;
-use crate::Error;
 use log::debug;
 use std::time::{Duration, Instant};
 use tokio::time::sleep;

rust/lancedb/src/io/object_store.rs

@@ -5,11 +5,11 @@
 
 use std::{fmt::Formatter, sync::Arc};
 
-use futures::{stream::BoxStream, TryFutureExt};
+use futures::{TryFutureExt, stream::BoxStream};
 use lance::io::WrappingObjectStore;
 use object_store::{
-    path::Path, Error, GetOptions, GetResult, ListResult, MultipartUpload, ObjectMeta, ObjectStore,
-    PutMultipartOptions, PutOptions, PutPayload, PutResult, Result, UploadPart,
+    Error, GetOptions, GetResult, ListResult, MultipartUpload, ObjectMeta, ObjectStore,
+    PutMultipartOptions, PutOptions, PutPayload, PutResult, Result, UploadPart, path::Path,
 };
 
 use async_trait::async_trait;

rust/lancedb/src/io/object_store/io_tracking.rs

@@ -10,8 +10,9 @@ use bytes::Bytes;
 use futures::stream::BoxStream;
 use lance::io::WrappingObjectStore;
 use object_store::{
-    path::Path, GetOptions, GetResult, ListResult, MultipartUpload, ObjectMeta, ObjectStore,
+    GetOptions, GetResult, ListResult, MultipartUpload, ObjectMeta, ObjectStore,
     PutMultipartOptions, PutOptions, PutPayload, PutResult, Result as OSResult, UploadPart,
+    path::Path,
 };
 
 #[derive(Debug, Default)]

rust/lancedb/src/query.rs

@@ -5,26 +5,26 @@ use std::sync::Arc;
 use std::{future::Future, time::Duration};
 
 use arrow::compute::concat_batches;
-use arrow_array::{make_array, Array, Float16Array, Float32Array, Float64Array};
+use arrow_array::{Array, Float16Array, Float32Array, Float64Array, make_array};
 use arrow_schema::{DataType, SchemaRef};
 use datafusion_expr::Expr;
 use datafusion_physical_plan::ExecutionPlan;
-use futures::{stream, try_join, FutureExt, TryFutureExt, TryStreamExt};
+use futures::{FutureExt, TryFutureExt, TryStreamExt, stream, try_join};
 use half::f16;
-use lance::dataset::{scanner::DatasetRecordBatchStream, ROW_ID};
+use lance::dataset::{ROW_ID, scanner::DatasetRecordBatchStream};
 use lance_arrow::RecordBatchExt;
 use lance_datafusion::exec::execute_plan;
-use lance_index::scalar::inverted::SCORE_COL;
 use lance_index::scalar::FullTextSearchQuery;
+use lance_index::scalar::inverted::SCORE_COL;
 use lance_index::vector::DIST_COL;
 use lance_io::stream::RecordBatchStreamAdapter;
 
+use crate::DistanceType;
 use crate::error::{Error, Result};
 use crate::rerankers::rrf::RRFReranker;
-use crate::rerankers::{check_reranker_result, NormalizeMethod, Reranker};
+use crate::rerankers::{NormalizeMethod, Reranker, check_reranker_result};
 use crate::table::BaseTable;
 use crate::utils::TimeoutStream;
-use crate::DistanceType;
 use crate::{arrow::SendableRecordBatchStream, table::AnyQuery};
 
 mod hybrid;
@@ -161,10 +161,11 @@ impl IntoQueryVector for &dyn Array {
         if data_type != self.data_type() {
             Err(Error::InvalidInput {
                 message: format!(
-                "failed to create query vector, the input data type was {:?} but the expected data type was {:?}",
-                self.data_type(),
-                data_type
-            )})
+                    "failed to create query vector, the input data type was {:?} but the expected data type was {:?}",
+                    self.data_type(),
+                    data_type
+                ),
+            })
         } else {
             let data = self.to_data();
             Ok(make_array(data))
@@ -186,7 +187,7 @@ impl IntoQueryVector for &[f16] {
             DataType::Float32 => {
                 let arr: Vec<f32> = self.iter().map(|x| f32::from(*x)).collect();
                 Ok(Arc::new(Float32Array::from(arr)))
-            },
+            }
             DataType::Float64 => {
                 let arr: Vec<f64> = self.iter().map(|x| f64::from(*x)).collect();
                 Ok(Arc::new(Float64Array::from(arr)))
@@ -194,8 +195,7 @@ impl IntoQueryVector for &[f16] {
             _ => Err(Error::InvalidInput {
                 message: format!(
                     "failed to create query vector, the input data type was &[f16] but the embedding model \"{}\" expected data type {:?}",
-                    embedding_model_label,
-                    data_type
+                    embedding_model_label, data_type
                 ),
             }),
         }
@@ -216,7 +216,7 @@ impl IntoQueryVector for &[f32] {
             DataType::Float32 => {
                 let arr: Vec<f32> = self.to_vec();
                 Ok(Arc::new(Float32Array::from(arr)))
-            },
+            }
             DataType::Float64 => {
                 let arr: Vec<f64> = self.iter().map(|x| *x as f64).collect();
                 Ok(Arc::new(Float64Array::from(arr)))
@@ -224,8 +224,7 @@ impl IntoQueryVector for &[f32] {
             _ => Err(Error::InvalidInput {
                 message: format!(
                     "failed to create query vector, the input data type was &[f32] but the embedding model \"{}\" expected data type {:?}",
-                    embedding_model_label,
-                    data_type
+                    embedding_model_label, data_type
                 ),
             }),
         }
@@ -239,26 +238,25 @@ impl IntoQueryVector for &[f64] {
         embedding_model_label: &str,
     ) -> Result<Arc<dyn Array>> {
         match data_type {
-                DataType::Float16 => {
-                    let arr: Vec<f16> = self.iter().map(|x| f16::from_f64(*x)).collect();
-                    Ok(Arc::new(Float16Array::from(arr)))
-                }
-                DataType::Float32 => {
-                    let arr: Vec<f32> = self.iter().map(|x| *x as f32).collect();
-                    Ok(Arc::new(Float32Array::from(arr)))
-                },
-                DataType::Float64 => {
-                    let arr: Vec<f64> = self.to_vec();
-                    Ok(Arc::new(Float64Array::from(arr)))
-                }
-                _ => Err(Error::InvalidInput {
-                    message: format!(
-                        "failed to create query vector, the input data type was &[f64] but the embedding model \"{}\" expected data type {:?}",
-                        embedding_model_label,
-                        data_type
-                    ),
-                }),
+            DataType::Float16 => {
+                let arr: Vec<f16> = self.iter().map(|x| f16::from_f64(*x)).collect();
+                Ok(Arc::new(Float16Array::from(arr)))
             }
+            DataType::Float32 => {
+                let arr: Vec<f32> = self.iter().map(|x| *x as f32).collect();
+                Ok(Arc::new(Float32Array::from(arr)))
+            }
+            DataType::Float64 => {
+                let arr: Vec<f64> = self.to_vec();
+                Ok(Arc::new(Float64Array::from(arr)))
+            }
+            _ => Err(Error::InvalidInput {
+                message: format!(
+                    "failed to create query vector, the input data type was &[f64] but the embedding model \"{}\" expected data type {:?}",
+                    embedding_model_label, data_type
+                ),
+            }),
+        }
     }
 }
 
@@ -1011,13 +1009,13 @@ impl VectorQuery {
                 message: "minimum_nprobes must be greater than 0".to_string(),
             });
         }
-        if let Some(maximum_nprobes) = self.request.maximum_nprobes {
-            if minimum_nprobes > maximum_nprobes {
-                return Err(Error::InvalidInput {
-                    message: "minimum_nprobes must be less than or equal to maximum_nprobes"
-                        .to_string(),
-                });
-            }
+        if let Some(maximum_nprobes) = self.request.maximum_nprobes
+            && minimum_nprobes > maximum_nprobes
+        {
+            return Err(Error::InvalidInput {
+                message: "minimum_nprobes must be less than or equal to maximum_nprobes"
+                    .to_string(),
+            });
         }
         self.request.minimum_nprobes = minimum_nprobes;
         Ok(self)
@@ -1407,8 +1405,8 @@ mod tests {
     use super::*;
     use arrow::{array::downcast_array, compute::concat_batches, datatypes::Int32Type};
     use arrow_array::{
-        cast::AsArray, types::Float32Type, FixedSizeListArray, Float32Array, Int32Array,
-        RecordBatch, StringArray,
+        FixedSizeListArray, Float32Array, Int32Array, RecordBatch, StringArray, cast::AsArray,
+        types::Float32Type,
     };
     use arrow_schema::{DataType, Field as ArrowField, Schema as ArrowSchema};
     use futures::{StreamExt, TryStreamExt};
@@ -1416,7 +1414,7 @@ mod tests {
     use rand::seq::IndexedRandom;
     use tempfile::tempdir;
 
-    use crate::{connect, database::CreateTableMode, index::Index, Table};
+    use crate::{Table, connect, database::CreateTableMode, index::Index};
 
     #[tokio::test]
     async fn test_setters_getters() {
@@ -1754,11 +1752,13 @@ mod tests {
             .limit(1)
             .execute()
             .await;
-        assert!(error_result
-            .err()
-            .unwrap()
-            .to_string()
-            .contains("No vector column found to match with the query vector dimension: 3"));
+        assert!(
+            error_result
+                .err()
+                .unwrap()
+                .to_string()
+                .contains("No vector column found to match with the query vector dimension: 3")
+        );
     }
 
     #[tokio::test]
@@ -2010,7 +2010,7 @@ mod tests {
 
         // Sample 1 - 3 tokens for each string value
         let tokens = ["a", "b", "c", "d", "e"];
-        use rand::{rng, Rng};
+        use rand::{Rng, rng};
 
         let mut rng = rng();
         let text: StringArray = (0..nrows)

rust/lancedb/src/query/hybrid.rs

@@ -5,7 +5,7 @@ use arrow::compute::{
     kernels::numeric::{div, sub},
     max, min,
 };
-use arrow_array::{cast::downcast_array, Float32Array, RecordBatch};
+use arrow_array::{Float32Array, RecordBatch, cast::downcast_array};
 use arrow_schema::{DataType, Field, Schema, SortOptions};
 use lance::dataset::ROW_ID;
 use lance_index::{scalar::inverted::SCORE_COL, vector::DIST_COL};
@@ -253,7 +253,10 @@ mod test {
         let result = rank(batch.clone(), "bad_col", None);
         match result {
             Err(Error::InvalidInput { message }) => {
-                assert_eq!("expected column bad_col not found in rank. found columns [\"name\", \"score\"]", message);
+                assert_eq!(
+                    "expected column bad_col not found in rank. found columns [\"name\", \"score\"]",
+                    message
+                );
             }
             _ => {
                 panic!("expected invalid input error, received {:?}", result)

rust/lancedb/src/remote/client.rs

@@ -4,8 +4,8 @@
 use http::HeaderName;
 use log::debug;
 use reqwest::{
-    header::{HeaderMap, HeaderValue},
     Body, Request, RequestBuilder, Response,
+    header::{HeaderMap, HeaderValue},
 };
 use std::{collections::HashMap, future::Future, str::FromStr, sync::Arc, time::Duration};
 
@@ -14,6 +14,7 @@ use crate::remote::db::RemoteOptions;
 use crate::remote::retry::{ResolvedRetryConfig, RetryCounter};
 
 const REQUEST_ID_HEADER: HeaderName = HeaderName::from_static("x-request-id");
+const MEM_WAL_ENABLED_HEADER: HeaderName = HeaderName::from_static("x-lancedb-mem-wal-enabled");
 
 /// Configuration for TLS/mTLS settings.
 #[derive(Clone, Debug, Default)]
@@ -52,6 +53,10 @@ pub struct ClientConfig {
     pub tls_config: Option<TlsConfig>,
     /// Provider for custom headers to be added to each request
     pub header_provider: Option<Arc<dyn HeaderProvider>>,
+    /// Enable MemWAL write path for streaming writes.
+    /// When true, write operations will use the MemWAL architecture
+    /// for high-performance streaming writes.
+    pub mem_wal_enabled: Option<bool>,
 }
 
 impl std::fmt::Debug for ClientConfig {
@@ -67,6 +72,7 @@ impl std::fmt::Debug for ClientConfig {
                 "header_provider",
                 &self.header_provider.as_ref().map(|_| "Some(...)"),
             )
+            .field("mem_wal_enabled", &self.mem_wal_enabled)
             .finish()
     }
 }
@@ -81,6 +87,7 @@ impl Default for ClientConfig {
             id_delimiter: None,
             tls_config: None,
             header_provider: None,
+            mem_wal_enabled: None,
         }
     }
 }
@@ -446,13 +453,23 @@ impl<S: HttpSend> RestfulLanceDbClient<S> {
                 })?,
             );
         }
-        if let Some(v) = options.0.get("azure_storage_account_name") {
-            headers.insert(
-                HeaderName::from_static("x-azure-storage-account-name"),
-                HeaderValue::from_str(v).map_err(|_| Error::InvalidInput {
-                    message: format!("non-ascii storage account name '{}' provided", db_name),
-                })?,
-            );
+        // Map azure storage options to x-azure-* headers.
+        // The option key uses underscores (e.g. "azure_client_id") while the
+        // header uses hyphens (e.g. "x-azure-client-id").
+        let azure_opts: [(&str, &str); 3] = [
+            ("azure_storage_account_name", "x-azure-storage-account-name"),
+            ("azure_client_id", "x-azure-client-id"),
+            ("azure_tenant_id", "x-azure-tenant-id"),
+        ];
+        for (opt_key, header_name) in azure_opts {
+            if let Some(v) = options.0.get(opt_key) {
+                headers.insert(
+                    HeaderName::from_static(header_name),
+                    HeaderValue::from_str(v).map_err(|_| Error::InvalidInput {
+                        message: format!("non-ascii value '{}' for option '{}'", v, opt_key),
+                    })?,
+                );
+            }
         }
 
         for (key, value) in &config.extra_headers {
@@ -467,6 +484,11 @@ impl<S: HttpSend> RestfulLanceDbClient<S> {
             );
         }
 
+        // Add MemWAL header if enabled
+        if let Some(true) = config.mem_wal_enabled {
+            headers.insert(MEM_WAL_ENABLED_HEADER, HeaderValue::from_static("true"));
+        }
+
         Ok(headers)
     }
 
@@ -650,14 +672,13 @@ impl<S: HttpSend> RestfulLanceDbClient<S> {
     pub fn extract_request_id(&self, request: &mut Request) -> String {
         // Set a request id.
         // TODO: allow the user to supply this, through middleware?
-        let request_id = if let Some(request_id) = request.headers().get(REQUEST_ID_HEADER) {
+        if let Some(request_id) = request.headers().get(REQUEST_ID_HEADER) {
             request_id.to_str().unwrap().to_string()
         } else {
             let request_id = uuid::Uuid::new_v4().to_string();
             self.set_request_id(request, &request_id);
             request_id
-        };
-        request_id
+        }
     }
 
     /// Set the request ID header
@@ -1076,4 +1097,34 @@ mod tests {
             _ => panic!("Expected Runtime error"),
         }
     }
+
+    #[test]
+    fn test_default_headers_azure_opts() {
+        let mut opts = HashMap::new();
+        opts.insert(
+            "azure_storage_account_name".to_string(),
+            "myaccount".to_string(),
+        );
+        opts.insert("azure_client_id".to_string(), "my-client-id".to_string());
+        opts.insert("azure_tenant_id".to_string(), "my-tenant-id".to_string());
+        let remote_opts = RemoteOptions::new(opts);
+
+        let headers = RestfulLanceDbClient::<Sender>::default_headers(
+            "test-key",
+            "us-east-1",
+            "testdb",
+            false,
+            &remote_opts,
+            None,
+            &ClientConfig::default(),
+        )
+        .unwrap();
+
+        assert_eq!(
+            headers.get("x-azure-storage-account-name").unwrap(),
+            "myaccount"
+        );
+        assert_eq!(headers.get("x-azure-client-id").unwrap(), "my-client-id");
+        assert_eq!(headers.get("x-azure-tenant-id").unwrap(), "my-tenant-id");
+    }
 }

rust/lancedb/src/remote/db.rs

@@ -16,6 +16,7 @@ use lance_namespace::models::{
     ListNamespacesResponse, ListTablesRequest, ListTablesResponse,
 };
 
+use crate::Error;
 use crate::database::{
     CloneTableRequest, CreateTableMode, CreateTableRequest, Database, DatabaseOptions,
     OpenTableRequest, ReadConsistency, TableNamesRequest,
@@ -23,12 +24,11 @@ use crate::database::{
 use crate::error::Result;
 use crate::remote::util::stream_as_body;
 use crate::table::BaseTable;
-use crate::Error;
 
+use super::ARROW_STREAM_CONTENT_TYPE;
 use super::client::{ClientConfig, HttpSend, RequestResultExt, RestfulLanceDbClient, Sender};
 use super::table::RemoteTable;
 use super::util::parse_server_version;
-use super::ARROW_STREAM_CONTENT_TYPE;
 
 // Request structure for the remote clone table API
 #[derive(serde::Serialize)]
@@ -78,6 +78,7 @@ pub const OPT_REMOTE_PREFIX: &str = "remote_database_";
 pub const OPT_REMOTE_API_KEY: &str = "remote_database_api_key";
 pub const OPT_REMOTE_REGION: &str = "remote_database_region";
 pub const OPT_REMOTE_HOST_OVERRIDE: &str = "remote_database_host_override";
+pub const OPT_REMOTE_MEM_WAL_ENABLED: &str = "remote_database_mem_wal_enabled";
 // TODO: add support for configuring client config via key/value options
 
 #[derive(Clone, Debug, Default)]
@@ -98,6 +99,12 @@ pub struct RemoteDatabaseOptions {
     /// These options are only used for LanceDB Enterprise and only a subset of options
     /// are supported.
     pub storage_options: HashMap<String, String>,
+    /// Enable MemWAL write path for high-performance streaming writes.
+    ///
+    /// When enabled, write operations (insert, merge_insert, etc.) will use
+    /// the MemWAL architecture which buffers writes in memory and Write-Ahead Log
+    /// before asynchronously merging to the base table.
+    pub mem_wal_enabled: Option<bool>,
 }
 
 impl RemoteDatabaseOptions {
@@ -109,6 +116,9 @@ impl RemoteDatabaseOptions {
         let api_key = map.get(OPT_REMOTE_API_KEY).cloned();
         let region = map.get(OPT_REMOTE_REGION).cloned();
         let host_override = map.get(OPT_REMOTE_HOST_OVERRIDE).cloned();
+        let mem_wal_enabled = map
+            .get(OPT_REMOTE_MEM_WAL_ENABLED)
+            .map(|v| v.to_lowercase() == "true");
         let storage_options = map
             .iter()
             .filter(|(key, _)| !key.starts_with(OPT_REMOTE_PREFIX))
@@ -119,6 +129,7 @@ impl RemoteDatabaseOptions {
             region,
             host_override,
             storage_options,
+            mem_wal_enabled,
         })
     }
 }
@@ -137,6 +148,12 @@ impl DatabaseOptions for RemoteDatabaseOptions {
         if let Some(host_override) = &self.host_override {
             map.insert(OPT_REMOTE_HOST_OVERRIDE.to_string(), host_override.clone());
         }
+        if let Some(mem_wal_enabled) = &self.mem_wal_enabled {
+            map.insert(
+                OPT_REMOTE_MEM_WAL_ENABLED.to_string(),
+                mem_wal_enabled.to_string(),
+            );
+        }
     }
 }
 
@@ -181,6 +198,20 @@ impl RemoteDatabaseOptionsBuilder {
         self.options.host_override = Some(host_override);
         self
     }
+
+    /// Enable MemWAL write path for high-performance streaming writes.
+    ///
+    /// When enabled, write operations will use the MemWAL architecture
+    /// which buffers writes in memory and Write-Ahead Log before
+    /// asynchronously merging to the base table.
+    ///
+    /// # Arguments
+    ///
+    /// * `enabled` - Whether to enable MemWAL writes
+    pub fn mem_wal_enabled(mut self, enabled: bool) -> Self {
+        self.options.mem_wal_enabled = Some(enabled);
+        self
+    }
 }
 
 #[derive(Debug)]
@@ -249,9 +280,9 @@ impl RemoteDatabase {
 #[cfg(all(test, feature = "remote"))]
 mod test_utils {
     use super::*;
+    use crate::remote::ClientConfig;
     use crate::remote::client::test_utils::MockSender;
     use crate::remote::client::test_utils::{client_with_handler, client_with_handler_and_config};
-    use crate::remote::ClientConfig;
 
     impl RemoteDatabase<MockSender> {
         pub fn new_mock<F, T>(handler: F) -> Self
@@ -777,7 +808,12 @@ impl RemoteOptions {
 
 impl From<StorageOptions> for RemoteOptions {
     fn from(options: StorageOptions) -> Self {
-        let supported_opts = vec!["account_name", "azure_storage_account_name"];
+        let supported_opts = vec![
+            "account_name",
+            "azure_storage_account_name",
+            "azure_client_id",
+            "azure_tenant_id",
+        ];
         let mut filtered = HashMap::new();
         for opt in supported_opts {
             if let Some(v) = options.0.get(opt) {
@@ -799,9 +835,9 @@ mod tests {
 
     use crate::connection::ConnectBuilder;
     use crate::{
-        database::CreateTableMode,
-        remote::{ClientConfig, HeaderProvider, ARROW_STREAM_CONTENT_TYPE, JSON_CONTENT_TYPE},
         Connection, Error,
+        database::CreateTableMode,
+        remote::{ARROW_STREAM_CONTENT_TYPE, ClientConfig, HeaderProvider, JSON_CONTENT_TYPE},
     };
 
     #[test]

rust/lancedb/src/remote/retry.rs

@@ -1,8 +1,8 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
-use crate::remote::RetryConfig;
 use crate::Error;
+use crate::remote::RetryConfig;
 use log::debug;
 use std::time::Duration;
 

rust/lancedb/src/remote/table.rs

@@ -6,15 +6,14 @@ pub mod insert;
 use self::insert::RemoteInsertExec;
 use crate::expr::expr_to_sql_string;
 
+use super::ARROW_STREAM_CONTENT_TYPE;
 use super::client::RequestResultExt;
 use super::client::{HttpSend, RestfulLanceDbClient, Sender};
 use super::db::ServerVersion;
-use super::ARROW_STREAM_CONTENT_TYPE;
-use crate::index::waiter::wait_for_index;
 use crate::index::Index;
 use crate::index::IndexStatistics;
+use crate::index::waiter::wait_for_index;
 use crate::query::{QueryFilter, QueryRequest, Select, VectorQueryRequest};
-use crate::table::query::create_multi_vector_plan;
 use crate::table::AddColumnsResult;
 use crate::table::AddResult;
 use crate::table::AlterColumnsResult;
@@ -23,19 +22,20 @@ use crate::table::DropColumnsResult;
 use crate::table::MergeResult;
 use crate::table::Tags;
 use crate::table::UpdateResult;
+use crate::table::query::create_multi_vector_plan;
 use crate::table::{AnyQuery, Filter, TableStatistics};
 use crate::utils::background_cache::BackgroundCache;
 use crate::utils::{supported_btree_data_type, supported_vector_data_type};
+use crate::{DistanceType, Error};
 use crate::{
     error::Result,
     index::{IndexBuilder, IndexConfig},
     query::QueryExecutionOptions,
     table::{
-        merge::MergeInsertBuilder, AddDataBuilder, BaseTable, OptimizeAction, OptimizeStats,
-        TableDefinition, UpdateBuilder,
+        AddDataBuilder, BaseTable, OptimizeAction, OptimizeStats, TableDefinition, UpdateBuilder,
+        merge::MergeInsertBuilder,
     },
 };
-use crate::{DistanceType, Error};
 use arrow_array::{RecordBatch, RecordBatchIterator, RecordBatchReader};
 use arrow_ipc::reader::FileReader;
 use arrow_schema::{DataType, SchemaRef};
@@ -50,7 +50,7 @@ use lance::arrow::json::{JsonDataType, JsonSchema};
 use lance::dataset::refs::TagContents;
 use lance::dataset::scanner::DatasetRecordBatchStream;
 use lance::dataset::{ColumnAlteration, NewColumnTransform, Version};
-use lance_datafusion::exec::{execute_plan, OneShotExec};
+use lance_datafusion::exec::{OneShotExec, execute_plan};
 use reqwest::{RequestBuilder, Response};
 use serde::{Deserialize, Serialize};
 use serde_json::Number;
@@ -62,6 +62,7 @@ use std::time::Duration;
 use tokio::sync::RwLock;
 
 const REQUEST_TIMEOUT_HEADER: HeaderName = HeaderName::from_static("x-request-timeout-ms");
+const MEM_WAL_ENABLED_HEADER: HeaderName = HeaderName::from_static("x-lancedb-mem-wal-enabled");
 const METRIC_TYPE_KEY: &str = "metric_type";
 const INDEX_TYPE_KEY: &str = "index_type";
 const SCHEMA_CACHE_TTL: Duration = Duration::from_secs(30);
@@ -612,8 +613,8 @@ impl<S: HttpSend> RemoteTable<S> {
                 message: format!(
                     "Cannot mutate table reference fixed at version {}. Call checkout_latest() to get a mutable table reference.",
                     version
-                )
-            })
+                ),
+            }),
         }
     }
 
@@ -697,10 +698,10 @@ impl<S: HttpSend> RemoteTable<S> {
             Error::Retry { status_code, .. } => *status_code,
             _ => None,
         };
-        if let Some(status_code) = status_code {
-            if Self::should_invalidate_cache_for_status(status_code) {
-                self.invalidate_schema_cache();
-            }
+        if let Some(status_code) = status_code
+            && Self::should_invalidate_cache_for_status(status_code)
+        {
+            self.invalidate_schema_cache();
         }
     }
 }
@@ -783,9 +784,9 @@ impl<S: HttpSend> std::fmt::Display for RemoteTable<S> {
 #[cfg(all(test, feature = "remote"))]
 mod test_utils {
     use super::*;
-    use crate::remote::client::test_utils::client_with_handler;
-    use crate::remote::client::test_utils::{client_with_handler_and_config, MockSender};
     use crate::remote::ClientConfig;
+    use crate::remote::client::test_utils::client_with_handler;
+    use crate::remote::client::test_utils::{MockSender, client_with_handler_and_config};
 
     impl RemoteTable<MockSender> {
         pub fn new_mock<F, T>(name: String, handler: F, version: Option<semver::Version>) -> Self
@@ -1227,7 +1228,10 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
         let body = response.text().await.err_to_http(request_id.clone())?;
         if body.trim().is_empty() {
             // Backward compatible with old servers
-            return Ok(DeleteResult { version: 0 });
+            return Ok(DeleteResult {
+                num_deleted_rows: 0,
+                version: 0,
+            });
         }
         let delete_response: DeleteResult =
             serde_json::from_str(&body).map_err(|e| Error::Http {
@@ -1248,13 +1252,13 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
             0 => {
                 return Err(Error::InvalidInput {
                     message: "No columns specified".into(),
-                })
+                });
             }
             1 => index.columns.pop().unwrap(),
             _ => {
                 return Err(Error::NotSupported {
                     message: "Indices over multiple columns not yet supported".into(),
-                })
+                });
             }
         };
         let mut body = serde_json::json!({
@@ -1273,73 +1277,24 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
             );
         }
 
-        match index.index {
-            // TODO: Should we pass the actual index parameters? SaaS does not
-            // yet support them.
-            Index::IvfFlat(index) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_FLAT".to_string());
-                body[METRIC_TYPE_KEY] =
-                    serde_json::Value::String(index.distance_type.to_string().to_lowercase());
-                if let Some(num_partitions) = index.num_partitions {
-                    body["num_partitions"] = serde_json::Value::Number(num_partitions.into());
-                }
-            }
-            Index::IvfPq(index) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_PQ".to_string());
-                body[METRIC_TYPE_KEY] =
-                    serde_json::Value::String(index.distance_type.to_string().to_lowercase());
-                if let Some(num_partitions) = index.num_partitions {
-                    body["num_partitions"] = serde_json::Value::Number(num_partitions.into());
-                }
-                if let Some(num_bits) = index.num_bits {
-                    body["num_bits"] = serde_json::Value::Number(num_bits.into());
-                }
-            }
-            Index::IvfSq(index) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_SQ".to_string());
-                body[METRIC_TYPE_KEY] =
-                    serde_json::Value::String(index.distance_type.to_string().to_lowercase());
-                if let Some(num_partitions) = index.num_partitions {
-                    body["num_partitions"] = serde_json::Value::Number(num_partitions.into());
-                }
-            }
-            Index::IvfHnswSq(index) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_HNSW_SQ".to_string());
-                body[METRIC_TYPE_KEY] =
-                    serde_json::Value::String(index.distance_type.to_string().to_lowercase());
-                if let Some(num_partitions) = index.num_partitions {
-                    body["num_partitions"] = serde_json::Value::Number(num_partitions.into());
-                }
-            }
-            Index::IvfRq(index) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_RQ".to_string());
-                body[METRIC_TYPE_KEY] =
-                    serde_json::Value::String(index.distance_type.to_string().to_lowercase());
-                if let Some(num_partitions) = index.num_partitions {
-                    body["num_partitions"] = serde_json::Value::Number(num_partitions.into());
-                }
-                if let Some(num_bits) = index.num_bits {
-                    body["num_bits"] = serde_json::Value::Number(num_bits.into());
-                }
-            }
-            Index::BTree(_) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("BTREE".to_string());
-            }
-            Index::Bitmap(_) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("BITMAP".to_string());
-            }
-            Index::LabelList(_) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("LABEL_LIST".to_string());
-            }
-            Index::FTS(fts) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("FTS".to_string());
-                let params = serde_json::to_value(&fts).map_err(|e| Error::InvalidInput {
-                    message: format!("failed to serialize FTS index params {:?}", e),
-                })?;
-                for (key, value) in params.as_object().unwrap() {
-                    body[key] = value.clone();
-                }
-            }
+        fn to_json(params: &impl serde::Serialize) -> crate::Result<serde_json::Value> {
+            serde_json::to_value(params).map_err(|e| Error::InvalidInput {
+                message: format!("failed to serialize index params {:?}", e),
+            })
+        }
+
+        // Map each Index variant to its wire type name and serializable params.
+        // Auto is special-cased since it needs schema inspection.
+        let (index_type_str, params) = match &index.index {
+            Index::IvfFlat(p) => ("IVF_FLAT", Some(to_json(p)?)),
+            Index::IvfPq(p) => ("IVF_PQ", Some(to_json(p)?)),
+            Index::IvfSq(p) => ("IVF_SQ", Some(to_json(p)?)),
+            Index::IvfHnswSq(p) => ("IVF_HNSW_SQ", Some(to_json(p)?)),
+            Index::IvfRq(p) => ("IVF_RQ", Some(to_json(p)?)),
+            Index::BTree(p) => ("BTREE", Some(to_json(p)?)),
+            Index::Bitmap(p) => ("BITMAP", Some(to_json(p)?)),
+            Index::LabelList(p) => ("LABEL_LIST", Some(to_json(p)?)),
+            Index::FTS(p) => ("FTS", Some(to_json(p)?)),
             Index::Auto => {
                 let schema = self.schema().await?;
                 let field = schema
@@ -1348,11 +1303,11 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
                         message: format!("Column {} not found in schema", column),
                     })?;
                 if supported_vector_data_type(field.data_type()) {
-                    body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_PQ".to_string());
                     body[METRIC_TYPE_KEY] =
                         serde_json::Value::String(DistanceType::L2.to_string().to_lowercase());
+                    ("IVF_PQ", None)
                 } else if supported_btree_data_type(field.data_type()) {
-                    body[INDEX_TYPE_KEY] = serde_json::Value::String("BTREE".to_string());
+                    ("BTREE", None)
                 } else {
                     return Err(Error::NotSupported {
                         message: format!(
@@ -1366,10 +1321,17 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
             _ => {
                 return Err(Error::NotSupported {
                     message: "Index type not supported".into(),
-                })
+                });
             }
         };
 
+        body[INDEX_TYPE_KEY] = index_type_str.into();
+        if let Some(params) = params {
+            for (key, value) in params.as_object().expect("params should be a JSON object") {
+                body[key] = value.clone();
+            }
+        }
+
         let request = request.json(&body);
 
         let (request_id, response) = self.send(request, true).await?;
@@ -1398,6 +1360,7 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
         self.check_mutable().await?;
 
         let timeout = params.timeout;
+        let mem_wal = params.mem_wal;
 
         let query = MergeInsertRequest::try_from(params)?;
         let mut request = self
@@ -1413,6 +1376,10 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
             }
         }
 
+        if mem_wal {
+            request = request.header(MEM_WAL_ENABLED_HEADER, "true");
+        }
+
         let (request_id, response) = self.send_streaming(request, new_data, true).await?;
 
         let response = self.check_table_response(&request_id, response).await?;
@@ -1810,8 +1777,8 @@ impl TryFrom<MergeInsertBuilder> for MergeInsertRequest {
 
 #[cfg(test)]
 mod tests {
-    use std::sync::atomic::{AtomicUsize, Ordering};
     use std::sync::Arc;
+    use std::sync::atomic::{AtomicUsize, Ordering};
     use std::time::Duration;
     use std::{collections::HashMap, pin::Pin};
 
@@ -1820,25 +1787,27 @@ mod tests {
     use crate::table::AddDataMode;
 
     use arrow::{array::AsArray, compute::concat_batches, datatypes::Int32Type};
-    use arrow_array::{record_batch, Int32Array, RecordBatch, RecordBatchIterator};
+    use arrow_array::{Int32Array, RecordBatch, RecordBatchIterator, record_batch};
     use arrow_schema::{DataType, Field, Schema};
     use chrono::{DateTime, Utc};
-    use futures::{future::BoxFuture, StreamExt, TryFutureExt};
+    use futures::{StreamExt, TryFutureExt, future::BoxFuture};
     use lance_index::scalar::inverted::query::MatchQuery;
     use lance_index::scalar::{FullTextSearchQuery, InvertedIndexParams};
     use reqwest::Body;
     use rstest::rstest;
     use serde_json::json;
 
-    use crate::index::vector::{IvfFlatIndexBuilder, IvfHnswSqIndexBuilder};
-    use crate::remote::db::DEFAULT_SERVER_VERSION;
+    use crate::index::vector::{
+        IvfFlatIndexBuilder, IvfHnswSqIndexBuilder, IvfRqIndexBuilder, IvfSqIndexBuilder,
+    };
     use crate::remote::JSON_CONTENT_TYPE;
+    use crate::remote::db::DEFAULT_SERVER_VERSION;
     use crate::utils::background_cache::clock;
     use crate::{
-        index::{vector::IvfPqIndexBuilder, Index, IndexStatistics, IndexType},
+        DistanceType, Error, Table,
+        index::{Index, IndexStatistics, IndexType, vector::IvfPqIndexBuilder},
         query::{ExecutableQuery, QueryBase},
         remote::ARROW_FILE_CONTENT_TYPE,
-        DistanceType, Error, Table,
     };
 
     #[tokio::test]
@@ -2067,11 +2036,13 @@ mod tests {
                     .unwrap(),
                 "/v1/table/my_table/insert/" => {
                     assert_eq!(request.method(), "POST");
-                    assert!(request
-                        .url()
-                        .query_pairs()
-                        .filter(|(k, _)| k == "mode")
-                        .all(|(_, v)| v == "append"));
+                    assert!(
+                        request
+                            .url()
+                            .query_pairs()
+                            .filter(|(k, _)| k == "mode")
+                            .all(|(_, v)| v == "append")
+                    );
                     assert_eq!(
                         request.headers().get("Content-Type").unwrap(),
                         ARROW_STREAM_CONTENT_TYPE
@@ -2992,6 +2963,8 @@ mod tests {
                 "IVF_FLAT",
                 json!({
                     "metric_type": "hamming",
+                    "sample_rate": 256,
+                    "max_iterations": 50,
                 }),
                 Index::IvfFlat(IvfFlatIndexBuilder::default().distance_type(DistanceType::Hamming)),
             ),
@@ -3000,6 +2973,8 @@ mod tests {
                 json!({
                     "metric_type": "hamming",
                     "num_partitions": 128,
+                    "sample_rate": 256,
+                    "max_iterations": 50,
                 }),
                 Index::IvfFlat(
                     IvfFlatIndexBuilder::default()
@@ -3011,6 +2986,8 @@ mod tests {
                 "IVF_PQ",
                 json!({
                     "metric_type": "l2",
+                    "sample_rate": 256,
+                    "max_iterations": 50,
                 }),
                 Index::IvfPq(Default::default()),
             ),
@@ -3020,6 +2997,8 @@ mod tests {
                     "metric_type": "cosine",
                     "num_partitions": 128,
                     "num_bits": 4,
+                    "sample_rate": 256,
+                    "max_iterations": 50,
                 }),
                 Index::IvfPq(
                     IvfPqIndexBuilder::default()
@@ -3028,10 +3007,29 @@ mod tests {
                         .num_bits(4),
                 ),
             ),
+            (
+                "IVF_PQ",
+                json!({
+                    "metric_type": "l2",
+                    "num_sub_vectors": 16,
+                    "sample_rate": 512,
+                    "max_iterations": 100,
+                }),
+                Index::IvfPq(
+                    IvfPqIndexBuilder::default()
+                        .num_sub_vectors(16)
+                        .sample_rate(512)
+                        .max_iterations(100),
+                ),
+            ),
             (
                 "IVF_HNSW_SQ",
                 json!({
                     "metric_type": "l2",
+                    "sample_rate": 256,
+                    "max_iterations": 50,
+                    "m": 20,
+                    "ef_construction": 300,
                 }),
                 Index::IvfHnswSq(Default::default()),
             ),
@@ -3040,11 +3038,65 @@ mod tests {
                 json!({
                     "metric_type": "l2",
                     "num_partitions": 128,
+                    "sample_rate": 256,
+                    "max_iterations": 50,
+                    "m": 40,
+                    "ef_construction": 500,
                 }),
                 Index::IvfHnswSq(
                     IvfHnswSqIndexBuilder::default()
                         .distance_type(DistanceType::L2)
-                        .num_partitions(128),
+                        .num_partitions(128)
+                        .num_edges(40)
+                        .ef_construction(500),
+                ),
+            ),
+            (
+                "IVF_SQ",
+                json!({
+                    "metric_type": "l2",
+                    "sample_rate": 256,
+                    "max_iterations": 50,
+                }),
+                Index::IvfSq(Default::default()),
+            ),
+            (
+                "IVF_SQ",
+                json!({
+                    "metric_type": "cosine",
+                    "num_partitions": 64,
+                    "sample_rate": 256,
+                    "max_iterations": 50,
+                }),
+                Index::IvfSq(
+                    IvfSqIndexBuilder::default()
+                        .distance_type(DistanceType::Cosine)
+                        .num_partitions(64),
+                ),
+            ),
+            (
+                "IVF_RQ",
+                json!({
+                    "metric_type": "l2",
+                    "sample_rate": 256,
+                    "max_iterations": 50,
+                }),
+                Index::IvfRq(Default::default()),
+            ),
+            (
+                "IVF_RQ",
+                json!({
+                    "metric_type": "cosine",
+                    "num_partitions": 64,
+                    "num_bits": 8,
+                    "sample_rate": 256,
+                    "max_iterations": 50,
+                }),
+                Index::IvfRq(
+                    IvfRqIndexBuilder::default()
+                        .distance_type(DistanceType::Cosine)
+                        .num_partitions(64)
+                        .num_bits(8),
                 ),
             ),
             // HNSW_PQ isn't yet supported on SaaS
@@ -3548,7 +3600,7 @@ mod tests {
     }
 
     fn _make_table_with_indices(unindexed_rows: usize) -> Table {
-        let table = Table::new_with_handler("my_table", move |request| {
+        Table::new_with_handler("my_table", move |request| {
             assert_eq!(request.method(), "POST");
 
             let response_body = match request.url().path() {
@@ -3592,8 +3644,7 @@ mod tests {
             let body = serde_json::to_string(&response_body).unwrap();
             let status = if body == "null" { 404 } else { 200 };
             http::Response::builder().status(status).body(body).unwrap()
-        });
-        table
+        })
     }
 
     #[tokio::test]
@@ -3804,8 +3855,8 @@ mod tests {
 
     #[tokio::test]
     async fn test_uri_caching() {
-        use std::sync::atomic::{AtomicUsize, Ordering};
         use std::sync::Arc;
+        use std::sync::atomic::{AtomicUsize, Ordering};
 
         let call_count = Arc::new(AtomicUsize::new(0));
         let call_count_clone = call_count.clone();

rust/lancedb/src/remote/table/insert.rs

@@ -16,12 +16,12 @@ use datafusion_physical_plan::{DisplayAs, DisplayFormatType, ExecutionPlan, Plan
 use futures::StreamExt;
 use http::header::CONTENT_TYPE;
 
+use crate::Error;
+use crate::remote::ARROW_STREAM_CONTENT_TYPE;
 use crate::remote::client::{HttpSend, RestfulLanceDbClient, Sender};
 use crate::remote::table::RemoteTable;
-use crate::remote::ARROW_STREAM_CONTENT_TYPE;
-use crate::table::datafusion::insert::COUNT_SCHEMA;
 use crate::table::AddResult;
-use crate::Error;
+use crate::table::datafusion::insert::COUNT_SCHEMA;
 
 /// ExecutionPlan for inserting data into a remote LanceDB table.
 ///
@@ -309,12 +309,12 @@ mod tests {
     use arrow_schema::{DataType, Field, Schema as ArrowSchema};
     use datafusion::prelude::SessionContext;
     use datafusion_catalog::MemTable;
-    use std::sync::atomic::{AtomicUsize, Ordering};
     use std::sync::Arc;
+    use std::sync::atomic::{AtomicUsize, Ordering};
 
+    use crate::Table;
     use crate::remote::ARROW_STREAM_CONTENT_TYPE;
     use crate::table::datafusion::BaseTableAdapter;
-    use crate::Table;
 
     fn schema_json() -> &'static str {
         r#"{"fields": [{"name": "id", "type": {"type": "int32"}, "nullable": true}]}"#

rust/lancedb/src/remote/util.rs

@@ -5,7 +5,7 @@ use arrow_ipc::CompressionType;
 use futures::{Stream, StreamExt};
 use reqwest::Response;
 
-use crate::{arrow::SendableRecordBatchStream, Result};
+use crate::{Result, arrow::SendableRecordBatchStream};
 
 use super::db::ServerVersion;
 

rust/lancedb/src/rerankers/rrf.rs

@@ -14,7 +14,7 @@ use async_trait::async_trait;
 use lance::dataset::ROW_ID;
 
 use crate::error::{Error, Result};
-use crate::rerankers::{Reranker, RELEVANCE_SCORE};
+use crate::rerankers::{RELEVANCE_SCORE, Reranker};
 
 /// Reranks the results using Reciprocal Rank Fusion(RRF) algorithm based
 /// on the scores of vector and FTS search.

rust/lancedb/src/table.rs

@@ -8,29 +8,29 @@ use arrow_schema::{DataType, Field, Schema, SchemaRef};
 use async_trait::async_trait;
 use datafusion_execution::TaskContext;
 use datafusion_expr::Expr;
-use datafusion_physical_plan::display::DisplayableExecutionPlan;
 use datafusion_physical_plan::ExecutionPlan;
-use futures::stream::FuturesUnordered;
+use datafusion_physical_plan::display::DisplayableExecutionPlan;
 use futures::StreamExt;
-use lance::dataset::builder::DatasetBuilder;
+use futures::stream::FuturesUnordered;
 pub use lance::dataset::ColumnAlteration;
 pub use lance::dataset::NewColumnTransform;
 pub use lance::dataset::ReadParams;
 pub use lance::dataset::Version;
 use lance::dataset::WriteMode;
+use lance::dataset::builder::DatasetBuilder;
 use lance::dataset::{InsertBuilder, WriteParams};
-use lance::index::vector::utils::infer_vector_dim;
 use lance::index::vector::VectorIndexParams;
+use lance::index::vector::utils::infer_vector_dim;
 use lance::io::{ObjectStoreParams, WrappingObjectStore};
 use lance_datafusion::utils::StreamingWriteSource;
+use lance_index::DatasetIndexExt;
+use lance_index::IndexType;
 use lance_index::scalar::{BuiltinIndexType, ScalarIndexParams};
 use lance_index::vector::bq::RQBuildParams;
 use lance_index::vector::hnsw::builder::HnswBuildParams;
 use lance_index::vector::ivf::IvfBuildParams;
 use lance_index::vector::pq::PQBuildParams;
 use lance_index::vector::sq::builder::SQBuildParams;
-use lance_index::DatasetIndexExt;
-use lance_index::IndexType;
 use lance_io::object_store::{LanceNamespaceStorageOptionsProvider, StorageOptionsAccessor};
 pub use query::AnyQuery;
 
@@ -43,19 +43,19 @@ use std::format;
 use std::path::Path;
 use std::sync::Arc;
 
-use crate::data::scannable::{estimate_write_partitions, PeekedScannable, Scannable};
+use crate::data::scannable::{PeekedScannable, Scannable, estimate_write_partitions};
 use crate::database::Database;
 use crate::embeddings::{EmbeddingDefinition, EmbeddingRegistry, MemoryRegistry};
 use crate::error::{Error, Result};
-use crate::index::vector::VectorIndex;
 use crate::index::IndexStatistics;
-use crate::index::{vector::suggested_num_sub_vectors, Index, IndexBuilder};
+use crate::index::vector::VectorIndex;
+use crate::index::{Index, IndexBuilder, vector::suggested_num_sub_vectors};
 use crate::index::{IndexConfig, IndexStatisticsImpl};
 use crate::query::{IntoQueryVector, Query, QueryExecutionOptions, TakeQuery, VectorQuery};
 use crate::table::datafusion::insert::InsertExec;
 use crate::utils::{
-    supported_bitmap_data_type, supported_btree_data_type, supported_fts_data_type,
-    supported_label_list_data_type, supported_vector_data_type, PatchReadParam, PatchWriteParam,
+    PatchReadParam, PatchWriteParam, supported_bitmap_data_type, supported_btree_data_type,
+    supported_fts_data_type, supported_label_list_data_type, supported_vector_data_type,
 };
 
 use self::dataset::DatasetConsistencyWrapper;
@@ -2555,22 +2555,21 @@ pub struct FragmentSummaryStats {
 #[cfg(test)]
 #[allow(deprecated)]
 mod tests {
-    use std::sync::atomic::{AtomicBool, Ordering};
     use std::sync::Arc;
+    use std::sync::atomic::{AtomicBool, Ordering};
     use std::time::Duration;
 
     use arrow_array::{
-        builder::{ListBuilder, StringBuilder},
         Array, BooleanArray, FixedSizeListArray, Int32Array, LargeStringArray, RecordBatch,
         RecordBatchIterator, RecordBatchReader, StringArray,
+        builder::{ListBuilder, StringBuilder},
     };
     use arrow_array::{BinaryArray, LargeBinaryArray};
     use arrow_data::ArrayDataBuilder;
     use arrow_schema::{DataType, Field, Schema};
     use futures::TryStreamExt;
-    use lance::io::{ObjectStoreParams, WrappingObjectStore};
     use lance::Dataset;
-    use rand::Rng;
+    use lance::io::{ObjectStoreParams, WrappingObjectStore};
     use tempfile::tempdir;
 
     use super::*;
@@ -2777,9 +2776,8 @@ mod tests {
             false,
         )]));
 
-        let mut rng = rand::thread_rng();
         let float_arr = Float32Array::from(
-            repeat_with(|| rng.gen::<f32>())
+            repeat_with(rand::random::<f32>)
                 .take(512 * dimension as usize)
                 .collect::<Vec<f32>>(),
         );
@@ -2884,8 +2882,8 @@ mod tests {
             .await
             .unwrap();
 
-        use lance::index::vector::ivf::v2::IvfPq as LanceIvfPq;
         use lance::index::DatasetIndexInternalExt;
+        use lance::index::vector::ivf::v2::IvfPq as LanceIvfPq;
         use lance_index::metrics::NoOpMetricsCollector;
         use lance_index::vector::VectorIndex as LanceVectorIndex;
 
@@ -2933,9 +2931,8 @@ mod tests {
             false,
         )]));
 
-        let mut rng = rand::thread_rng();
         let float_arr = Float32Array::from(
-            repeat_with(|| rng.gen::<f32>())
+            repeat_with(rand::random::<f32>)
                 .take(512 * dimension as usize)
                 .collect::<Vec<f32>>(),
         );
@@ -2993,9 +2990,8 @@ mod tests {
             false,
         )]));
 
-        let mut rng = rand::thread_rng();
         let float_arr = Float32Array::from(
-            repeat_with(|| rng.gen::<f32>())
+            repeat_with(rand::random::<f32>)
                 .take(512 * dimension as usize)
                 .collect::<Vec<f32>>(),
         );
@@ -3256,16 +3252,20 @@ mod tests {
             .unwrap();
 
         // Can not create btree or bitmap index on list column
-        assert!(table
-            .create_index(&["tags"], Index::BTree(Default::default()))
-            .execute()
-            .await
-            .is_err());
-        assert!(table
-            .create_index(&["tags"], Index::Bitmap(Default::default()))
-            .execute()
-            .await
-            .is_err());
+        assert!(
+            table
+                .create_index(&["tags"], Index::BTree(Default::default()))
+                .execute()
+                .await
+                .is_err()
+        );
+        assert!(
+            table
+                .create_index(&["tags"], Index::Bitmap(Default::default()))
+                .execute()
+                .await
+                .is_err()
+        );
 
         // Create bitmap index on the "category" column
         table

rust/lancedb/src/table/add_data.rs

@@ -7,8 +7,8 @@ use arrow_schema::{DataType, Fields, Schema};
 use lance::dataset::WriteMode;
 use serde::{Deserialize, Serialize};
 
-use crate::data::scannable::scannable_with_embeddings;
 use crate::data::scannable::Scannable;
+use crate::data::scannable::scannable_with_embeddings;
 use crate::embeddings::EmbeddingRegistry;
 use crate::table::datafusion::cast::cast_to_table_schema;
 use crate::table::datafusion::reject_nan::reject_nan_vectors;
@@ -204,13 +204,14 @@ mod tests {
 
     use arrow::datatypes::Float64Type;
     use arrow_array::{
-        record_batch, FixedSizeListArray, Float32Array, Int32Array, LargeStringArray, ListArray,
-        RecordBatch, RecordBatchIterator,
+        FixedSizeListArray, Float32Array, Int32Array, LargeStringArray, ListArray, RecordBatch,
+        RecordBatchIterator, record_batch,
     };
     use arrow_schema::{ArrowError, DataType, Field, Schema};
     use futures::TryStreamExt;
     use lance::dataset::{WriteMode, WriteParams};
 
+    use crate::Error;
     use crate::arrow::{SendableRecordBatchStream, SimpleRecordBatchStream};
     use crate::connect;
     use crate::data::scannable::Scannable;
@@ -220,9 +221,8 @@ mod tests {
     use crate::query::{ExecutableQuery, QueryBase, Select};
     use crate::table::add_data::NaNVectorBehavior;
     use crate::table::{ColumnDefinition, ColumnKind, Table, TableDefinition, WriteOptions};
-    use crate::test_utils::embeddings::MockEmbed;
     use crate::test_utils::TestCustomError;
-    use crate::Error;
+    use crate::test_utils::embeddings::MockEmbed;
 
     use super::AddDataMode;
 

rust/lancedb/src/table/datafusion.rs

@@ -17,17 +17,17 @@ use async_trait::async_trait;
 use datafusion_catalog::{Session, TableProvider};
 use datafusion_common::{DataFusionError, Result as DataFusionResult, Statistics};
 use datafusion_execution::{SendableRecordBatchStream, TaskContext};
-use datafusion_expr::{dml::InsertOp, Expr, TableProviderFilterPushDown, TableType};
+use datafusion_expr::{Expr, TableProviderFilterPushDown, TableType, dml::InsertOp};
 use datafusion_physical_plan::{
-    stream::RecordBatchStreamAdapter, DisplayAs, DisplayFormatType, ExecutionPlan, PlanProperties,
+    DisplayAs, DisplayFormatType, ExecutionPlan, PlanProperties, stream::RecordBatchStreamAdapter,
 };
 use futures::{TryFutureExt, TryStreamExt};
 use lance::dataset::{WriteMode, WriteParams};
 
 use super::{AnyQuery, BaseTable};
 use crate::{
-    query::{QueryExecutionOptions, QueryFilter, QueryRequest, Select},
     Result,
+    query::{QueryExecutionOptions, QueryFilter, QueryRequest, Select},
 };
 use arrow_schema::{DataType, Field};
 use lance_index::scalar::FullTextSearchQuery;
@@ -268,7 +268,7 @@ impl TableProvider for BaseTableAdapter {
             InsertOp::Replace => {
                 return Err(DataFusionError::NotImplemented(
                     "Replace mode is not supported for LanceDB tables".to_string(),
-                ))
+                ));
             }
         };
 
@@ -300,13 +300,13 @@ pub mod tests {
     use datafusion_catalog::TableProvider;
     use datafusion_common::stats::Precision;
     use datafusion_execution::SendableRecordBatchStream;
-    use datafusion_expr::{col, lit, LogicalPlan, LogicalPlanBuilder};
+    use datafusion_expr::{LogicalPlan, LogicalPlanBuilder, col, lit};
     use futures::{StreamExt, TryStreamExt};
     use tempfile::tempdir;
 
     use crate::{
         connect,
-        index::{scalar::BTreeIndexBuilder, Index},
+        index::{Index, scalar::BTreeIndexBuilder},
         table::datafusion::BaseTableAdapter,
     };
 

rust/lancedb/src/table/datafusion/cast.rs

@@ -5,10 +5,10 @@ use std::sync::Arc;
 
 use arrow_schema::{DataType, Field, FieldRef, Fields, Schema};
 use datafusion::functions::core::{get_field, named_struct};
-use datafusion_common::config::ConfigOptions;
 use datafusion_common::ScalarValue;
-use datafusion_physical_expr::expressions::{cast, Literal};
+use datafusion_common::config::ConfigOptions;
 use datafusion_physical_expr::ScalarFunctionExpr;
+use datafusion_physical_expr::expressions::{Literal, cast};
 use datafusion_physical_plan::expressions::Column;
 use datafusion_physical_plan::projection::ProjectionExec;
 use datafusion_physical_plan::{ExecutionPlan, PhysicalExpr};

rust/lancedb/src/table/datafusion/insert.rs

@@ -16,9 +16,9 @@ use datafusion_physical_plan::stream::RecordBatchStreamAdapter;
 use datafusion_physical_plan::{
     DisplayAs, DisplayFormatType, ExecutionPlan, ExecutionPlanProperties, PlanProperties,
 };
+use lance::Dataset;
 use lance::dataset::transaction::{Operation, Transaction};
 use lance::dataset::{CommitBuilder, InsertBuilder, WriteParams};
-use lance::Dataset;
 use lance_table::format::Fragment;
 
 use crate::table::dataset::DatasetConsistencyWrapper;
@@ -195,13 +195,13 @@ impl ExecutionPlan for InsertExec {
                 }
             };
 
-            if let Some(transactions) = to_commit {
-                if let Some(merged_txn) = merge_transactions(transactions) {
-                    let new_dataset = CommitBuilder::new(dataset.clone())
-                        .execute(merged_txn)
-                        .await?;
-                    ds_wrapper.update(new_dataset);
-                }
+            if let Some(transactions) = to_commit
+                && let Some(merged_txn) = merge_transactions(transactions)
+            {
+                let new_dataset = CommitBuilder::new(dataset.clone())
+                    .execute(merged_txn)
+                    .await?;
+                ds_wrapper.update(new_dataset);
             }
 
             Ok(RecordBatch::try_new(
@@ -222,7 +222,7 @@ mod tests {
     use std::vec;
 
     use super::*;
-    use arrow_array::{record_batch, RecordBatchIterator};
+    use arrow_array::{RecordBatchIterator, record_batch};
     use datafusion::prelude::SessionContext;
     use datafusion_catalog::MemTable;
     use tempfile::tempdir;

rust/lancedb/src/table/datafusion/scannable_exec.rs

@@ -4,11 +4,11 @@
 use core::fmt;
 use std::sync::{Arc, Mutex};
 
-use datafusion_common::{stats::Precision, DataFusionError, Result as DFResult, Statistics};
+use datafusion_common::{DataFusionError, Result as DFResult, Statistics, stats::Precision};
 use datafusion_execution::{SendableRecordBatchStream, TaskContext};
 use datafusion_physical_expr::{EquivalenceProperties, Partitioning};
 use datafusion_physical_plan::{
-    execution_plan::EmissionType, DisplayAs, DisplayFormatType, ExecutionPlan, PlanProperties,
+    DisplayAs, DisplayFormatType, ExecutionPlan, PlanProperties, execution_plan::EmissionType,
 };
 
 use crate::{arrow::SendableRecordBatchStreamExt, data::scannable::Scannable};

rust/lancedb/src/table/datafusion/udtf/fts.rs

@@ -9,7 +9,7 @@ use std::sync::Arc;
 
 use datafusion::catalog::TableFunctionImpl;
 use datafusion_catalog::TableProvider;
-use datafusion_common::{plan_err, DataFusionError, Result as DataFusionResult, ScalarValue};
+use datafusion_common::{DataFusionError, Result as DataFusionResult, ScalarValue, plan_err};
 use datafusion_expr::Expr;
 use lance_index::scalar::FullTextSearchQuery;
 
@@ -93,9 +93,9 @@ pub fn from_json(json: &str) -> crate::Result<lance_index::scalar::inverted::que
 mod tests {
     use super::*;
     use crate::{
-        index::{scalar::FtsIndexBuilder, Index},
-        table::datafusion::BaseTableAdapter,
         Connection, Table,
+        index::{Index, scalar::FtsIndexBuilder},
+        table::datafusion::BaseTableAdapter,
     };
     use arrow_array::{Int32Array, RecordBatch, StringArray};
     use arrow_schema::{DataType, Field, Schema as ArrowSchema};
@@ -212,10 +212,10 @@ mod tests {
         let explain_results = explain_df.collect().await.unwrap();
         for batch in &explain_results {
             for row_idx in 0..batch.num_rows() {
-                if let Some(col) = batch.column_by_name("plan") {
-                    if let Some(plan_str) = col.as_any().downcast_ref::<StringArray>() {
-                        println!("{}", plan_str.value(row_idx));
-                    }
+                if let Some(col) = batch.column_by_name("plan")
+                    && let Some(plan_str) = col.as_any().downcast_ref::<StringArray>()
+                {
+                    println!("{}", plan_str.value(row_idx));
                 }
             }
         }
@@ -229,10 +229,10 @@ mod tests {
         let explain_analyze_results = explain_analyze_df.collect().await.unwrap();
         for batch in &explain_analyze_results {
             for row_idx in 0..batch.num_rows() {
-                if let Some(col) = batch.column_by_name("plan") {
-                    if let Some(plan_str) = col.as_any().downcast_ref::<StringArray>() {
-                        println!("{}", plan_str.value(row_idx));
-                    }
+                if let Some(col) = batch.column_by_name("plan")
+                    && let Some(plan_str) = col.as_any().downcast_ref::<StringArray>()
+                {
+                    println!("{}", plan_str.value(row_idx));
                 }
             }
         }

rust/lancedb/src/table/dataset.rs

@@ -6,9 +6,9 @@ use std::{
     time::Duration,
 };
 
-use lance::{dataset::refs, Dataset};
+use lance::{Dataset, dataset::refs};
 
-use crate::{error::Result, utils::background_cache::BackgroundCache, Error};
+use crate::{Error, error::Result, utils::background_cache::BackgroundCache};
 
 /// A wrapper around a [Dataset] that provides consistency checks.
 ///