Merge branch 'main' into gatekeeper/fix-2085-1

Merge origin/main into gatekeeper/fix-2085-1
test(rust): detect indexed delete compilation regressions
2026-09-01 19:18:38 +00:00 · 2026-08-26 05:09:04 +08:00 · 2026-08-08 20:10:35 +00:00 · 2026-08-08 12:35:32 +00:00 · 2026-08-08 12:12:43 +00:00 · 2026-08-05 23:26:26 +00:00
115 changed files with 12726 additions and 10558 deletions
@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.38.0"
+current_version = "0.38.0-beta.10"
 parse = """(?x)
    (?P<major>0|[1-9]\\d*)\\.
    (?P<minor>0|[1-9]\\d*)\\.
@@ -44,27 +44,3 @@ updates:
      python-deps:
        patterns:
          - "*"
-
-  # The npm ecosystem covers pnpm lockfiles. There are two separate installs:
-  # the bindings themselves and the examples, which have their own lockfile.
-  # As with cargo and pip above, only bump the lockfile — the version ranges
-  # in package.json are our consumers' constraints, not ours.
-  - package-ecosystem: npm
-    directory: /nodejs
-    schedule:
-      interval: weekly
-    versioning-strategy: lockfile-only
-    groups:
-      nodejs-deps:
-        patterns:
-          - "*"
-
-  - package-ecosystem: npm
-    directory: /nodejs/examples
-    schedule:
-      interval: weekly
-    versioning-strategy: lockfile-only
-    groups:
-      nodejs-examples-deps:
-        patterns:
-          - "*"
@@ -29,14 +29,12 @@ jobs:
    steps:
      - uses: actions/setup-node@v6
        with:
-          node-version: "24"
-      - uses: pnpm/action-setup@v6
-        with:
-          version: 11.1.1
+          node-version: "18"
      # These rules are disabled because Github will always ensure there
      # is a blank line between the title and the body and Github will
      # word wrap the description field to ensure a reasonable max line
      # length.
+      - run: npm install @commitlint/config-conventional
      - run: >
          echo 'module.exports = {
            "rules": {
@@ -45,11 +43,7 @@ jobs:
              "body-leading-blank": [0, "always"]
            }
          }' > .commitlintrc.js
-      - run: >
-          pnpm dlx
-          --package @commitlint/cli@21.2.2
-          --package @commitlint/config-conventional@21.2.2
-          commitlint --extends @commitlint/config-conventional --verbose <<< $COMMIT_MSG
+      - run: npx commitlint --extends @commitlint/config-conventional --verbose <<< $COMMIT_MSG
        env:
          COMMIT_MSG: >
            ${{ github.event.pull_request.title }}
@@ -60,7 +54,7 @@ jobs:
        with:
          script: |
            const message = `**ACTION NEEDED**
-
+              
              Lance follows the [Conventional Commits specification](https://www.conventionalcommits.org/en/v1.0.0/) for release automation.

              The PR title and description are used as the merge commit message.\
@@ -56,7 +56,7 @@ jobs:
        uses: lycheeverse/lychee-action@e7477775783ea5526144ba13e8db5eec57747ce8 # v2.9.0
        with:
          # Restricted to http(s) on purpose. Much of docs/src is generated
-          # API reference (the js/ tree comes from `pnpm run docs` in nodejs)
+          # API reference (the js/ tree comes from `npm run docs` in nodejs)
          # and the hand-written pages use mkdocstrings cross-references and
          # nav-relative paths that only resolve in the site mkdocs builds,
          # not in this checkout, so relative links would be reported as
@@ -55,7 +55,9 @@ jobs:
      - name: Set up node
        uses: actions/setup-node@v6
        with:
-          node-version: 24
+          node-version: 20
+          cache: 'npm'
+          cache-dependency-path: docs/package-lock.json
      - name: Install node dependencies
        working-directory: nodejs
        run: |
@@ -47,8 +47,9 @@ jobs:
        version: 11.1.1
    - uses: actions/setup-node@v6
      with:
-        # Build on a supported LTS; the matrix job below covers every
-        # Node version the library claims to support.
+        # pnpm 11 requires Node >= 22.13; use 24 since 22 hits EOL
+        # in October. The library itself still supports Node >= 18
+        # (see test matrix below).
        node-version: 24
        cache: 'pnpm'
        cache-dependency-path: nodejs/pnpm-lock.yaml
@@ -83,7 +84,7 @@ jobs:
    timeout-minutes: 30
    strategy:
      matrix:
-        node-version: [ "22", "24", "26" ]
+        node-version: [ "18", "20" ]
    runs-on: "ubuntu-22.04"
    defaults:
      run:
@@ -100,9 +101,9 @@ jobs:
    - uses: actions/setup-node@v6
      name: Setup Node.js 24 for build
      with:
-        # Build and install once on a fixed version so the generated docs
-        # are identical across matrix legs; the tests below then run on each
-        # supported Node version.
+        # pnpm 11 requires Node >= 22.13; use 24 since 22 hits EOL
+        # in October. Build/install runs on Node 24; tests run on the
+        # matrix version below using direct jest invocation.
        node-version: 24
        cache: 'pnpm'
        cache-dependency-path: nodejs/pnpm-lock.yaml
@@ -151,9 +152,9 @@ jobs:
        S3_TEST: "1"
        # Newer @smithy/core uses dynamic ESM imports.
        NODE_OPTIONS: "--experimental-vm-modules"
-      # Invoke the installed jest binary directly; the pnpm shim is set up
-      # against the build-phase Node, not the version selected above.
-      run: node_modules/.bin/jest --verbose
+      # Invoke jest directly because pnpm 11 itself requires Node 22+
+      # while the matrix tests on older Node versions.
+      run: npx jest --verbose
    - name: Test examples
      working-directory: ./
      env:
@@ -163,7 +164,7 @@ jobs:
      run: |
        python ci/mock_openai.py &
        cd nodejs/examples
-        node_modules/.bin/jest --testEnvironment jest-environment-node-single-context --verbose
+        npx jest --testEnvironment jest-environment-node-single-context --verbose
  macos:
    timeout-minutes: 30
    # macos-15 ships a newer linker; the older macos-14 linker fails to insert
@@ -184,7 +185,8 @@ jobs:
        version: 11.1.1
    - uses: actions/setup-node@v6
      with:
-        # pnpm 11 requires Node >= 22.13.
+        # pnpm 11 requires Node >= 22.13; use 24 since 22 hits EOL
+        # in October.
        node-version: 24
        cache: 'pnpm'
        cache-dependency-path: nodejs/pnpm-lock.yaml
@@ -40,31 +40,40 @@ jobs:
          - target: aarch64-apple-darwin
            host: macos-latest
            features: fp16kernels
-            # Fat LTO was ~111 of this job's ~113 minutes.
-            lto: thin
-            codegen_units: 16
            pre_build: |-
              brew install protobuf
+              # Fat LTO (the workspace default in .cargo/config.toml) is
+              # single-threaded and is the peak-memory step of the build. On
+              # this runner it accounted for ~111 of the job's ~113 minutes,
+              # making it the critical path of the entire publish pipeline.
+              # ThinLTO parallelizes it across the runner's cores, for a few
+              # percent of runtime performance.
+              export CARGO_PROFILE_RELEASE_LTO=thin
+              export CARGO_PROFILE_RELEASE_CODEGEN_UNITS=16
          - target: x86_64-pc-windows-msvc
            host: windows-2025
            features: ","
-            # The lower peak also keeps this on the standard 4-core runner.
-            lto: thin
-            codegen_units: 16
            pre_build: |-
              choco install --no-progress protoc ninja nasm
              tail -n 1000 /c/ProgramData/chocolatey/logs/chocolatey.log
              # There is an issue where choco doesn't add nasm to the path
              export PATH="$PATH:/c/Program Files/NASM"
              nasm -v
+              # See the ThinLTO note on aarch64-apple-darwin above. Keeping
+              # peak memory down is also what lets this run on the standard
+              # 4-core runner: the 8-core larger runner was only needed to
+              # stop fat LTO from OOMing rustc-LLVM.
+              export CARGO_PROFILE_RELEASE_LTO=thin
+              export CARGO_PROFILE_RELEASE_CODEGEN_UNITS=16
          - target: aarch64-pc-windows-msvc
            host: windows-2025
            features: ","
-            lto: thin
-            codegen_units: 16
            pre_build: |-
                choco install --no-progress protoc
                rustup target add aarch64-pc-windows-msvc
+                # See the ThinLTO note on aarch64-apple-darwin above.
+                export CARGO_PROFILE_RELEASE_LTO=thin
+                export CARGO_PROFILE_RELEASE_CODEGEN_UNITS=16
          - target: x86_64-unknown-linux-gnu
            host: ubuntu-latest
            features: fp16kernels
@@ -94,14 +103,6 @@ jobs:
            # https://github.com/napi-rs/napi-rs/blob/main/debian-aarch64.Dockerfile
            docker: ghcr.io/napi-rs/napi-rs/nodejs-rust:lts-debian-aarch64
            features: "fp16kernels"
-            # Fat LTO OOM-killed rustc every nightly; even with lld it peaked
-            # at 31391 MiB of the runner's 32 GiB.
-            lto: thin
-            codegen_units: 16
-            # arm64 Linux links through GNU `ld` where x86_64 defaults to
-            # `rust-lld`, which is why only arm64 OOM'd. lld cut the largest
-            # linker process 7.0 -> 4.0 GiB (lancedb/sophon#7313).
-            linker: /tmp/aarch64-lld-clang
            pre_build: |-
              set -e &&
              apt-get update &&
@@ -111,30 +112,9 @@ jobs:
              # AT_HWCAP2 (added in Linux 3.17). Define it for aws-lc-sys.
              export CFLAGS="$CFLAGS -DAT_HWCAP2=26" &&
              rustup target add aarch64-unknown-linux-gnu
-              # Not `&&`-chained: in dash, errexit does not fire for a
-              # non-final command in an `&&` list, so failures were ignored.
-              #
-              # A wrapper rather than `-C link-arg` because the per-target
-              # rustflags variable does not reach every unit that links, while
-              # the linker variable does. `clang` because GCC silently ignores
-              # `-fuse-ld=lld` unless built with lld support. Two echoes
-              # because printf's newline escape gets rewritten to `;` between
-              # here and the container.
-              echo '#!/bin/sh' > /tmp/aarch64-lld-clang
-              echo 'exec clang --target=aarch64-unknown-linux-gnu --sysroot=/usr/aarch64-unknown-linux-gnu/aarch64-unknown-linux-gnu/sysroot --gcc-toolchain=/usr/aarch64-unknown-linux-gnu -fuse-ld=lld "$@"' >> /tmp/aarch64-lld-clang
-              chmod 0755 /tmp/aarch64-lld-clang
-              # Fail now, not at the cdylib link ~30 minutes later. Linking at
-              # all also proves lld resolved; clang errors out when it cannot.
-              echo 'int main(void){return 0;}' > /tmp/probe.c
-              /tmp/aarch64-lld-clang /tmp/probe.c -o /tmp/probe
-              readelf -h /tmp/probe | grep AArch64
          - target: aarch64-unknown-linux-musl
            host: ubuntu-2404-8x-x64
            features: ","
-            # Fat LTO took the whole runner down. lld cannot help: it died
-            # inside rustc's LLVM, before any linker was spawned.
-            lto: thin
-            codegen_units: 16
            pre_build: |-
              set -e &&
              sudo apt-get update &&
@@ -143,19 +123,6 @@ jobs:
              export EXTRA_ARGS="-x"
    name: build - ${{ matrix.settings.target }}
    runs-on: ${{ matrix.settings.host }}
-    # On the job, not exported from `pre_build`: `Swatinem/rust-cache` hashes
-    # `CARGO_*` into its cache key before any step runs, so a step-local export
-    # leaves the key unchanged while cargo still rebuilds cold. The ThinLTO
-    # legs had been doing that every run.
-    #
-    # Not `RUSTFLAGS`: setting it, even to "", discards every config-file
-    # rustflag, silently dropping .cargo/config.toml's `target-cpu` and
-    # `target-feature` from the published binaries.
-    env:
-      CARGO_PROFILE_RELEASE_LTO: ${{ matrix.settings.lto || 'fat' }}
-      CARGO_PROFILE_RELEASE_CODEGEN_UNITS: ${{ matrix.settings.codegen_units || '1' }}
-      # Empty elsewhere: a per-target variable is only read for that triple.
-      CARGO_TARGET_AARCH64_UNKNOWN_LINUX_GNU_LINKER: ${{ matrix.settings.linker }}
    defaults:
      run:
        working-directory: nodejs
@@ -168,7 +135,8 @@ jobs:
      - name: Setup node
        uses: actions/setup-node@v6
        with:
-          # pnpm 11 requires Node >= 22.13.
+          # pnpm 11 requires Node >= 22.13; use 24 since 22 hits EOL
+          # in October.
          node-version: 24
          cache: pnpm
          cache-dependency-path: nodejs/pnpm-lock.yaml
@@ -201,15 +169,19 @@ jobs:
          # creating ref). The nightly cadence also keeps entries inside
          # GitHub's 7-day eviction window, which a tag-only trigger would not.
          save-if: ${{ github.ref == 'refs/heads/main' }}
-      # Docker builds can use rust-cache too: the workspace is bind-mounted, so
-      # `target/` lives on the host and rust-cache's prune keeps the entry
-      # small.
+      # Docker builds can use rust-cache too. `target/` already lives on the
+      # host because the whole workspace is bind-mounted into the container, and
+      # rust-cache's prune and save run host-side, so they can manage it -- which
+      # is what keeps the entry to dependency artifacts rather than a multi-GB
+      # copy of everything.
      #
      # Two differences from the native builds. The container's CARGO_HOME is
-      # bind-mounted from `.cargo-cache` rather than ~/.cargo, so that is cached
-      # explicitly. And the key uses the *host* rustc version, not the compiler
-      # that built these artifacts -- safe, since cargo fingerprints the real
-      # one; a base-image bump just costs one cold build.
+      # bind-mounted from `.cargo-cache` rather than the host's ~/.cargo, so that
+      # has to be cached explicitly. And the key is derived from the *host* rustc
+      # version, which is not the compiler that produced these artifacts; that is
+      # safe because cargo fingerprints the real compiler and rebuilds on a
+      # mismatch, it just means a base-image toolchain bump costs one cold build
+      # instead of invalidating the key.
      - name: Cache cargo (docker builds)
        uses: Swatinem/rust-cache@v2
        if: ${{ matrix.settings.docker }}
@@ -238,19 +210,14 @@ jobs:
          # cache step above saves. Previously the registry mounts pointed at
          # `.cargo/...`, a path nothing cached, so the container re-downloaded
          # the whole crate registry on every run.
-          #
-          # `docker run` inherits nothing; `-e NAME` carries the job's `env:` in.
          options: "--user 0:0 -v ${{ github.workspace }}/.cargo-cache/git/db:/usr/local/cargo/git/db \
                    -v ${{ github.workspace }}/.cargo-cache/registry/cache:/usr/local/cargo/registry/cache \
                    -v ${{ github.workspace }}/.cargo-cache/registry/index:/usr/local/cargo/registry/index \
-                    -e CARGO_PROFILE_RELEASE_LTO \
-                    -e CARGO_PROFILE_RELEASE_CODEGEN_UNITS \
-                    -e CARGO_TARGET_AARCH64_UNKNOWN_LINUX_GNU_LINKER \
                    -v ${{ github.workspace }}:/build -w /build/nodejs"
          run: |
            set -e
            ${{ matrix.settings.pre_build }}
-            node_modules/.bin/napi build --platform --release \
+            npx napi build --platform --release \
              --features ${{ matrix.settings.features }} \
              --target ${{ matrix.settings.target }} \
              --dts ../lancedb/native.d.ts \
@@ -270,7 +237,7 @@ jobs:
      - name: Build
        run: |
          ${{ matrix.settings.pre_build }}
-          node_modules/.bin/napi build --platform --release \
+          npx napi build --platform --release \
              --features ${{ matrix.settings.features }} \
              --target ${{ matrix.settings.target }} \
              --dts ../lancedb/native.d.ts \
@@ -289,18 +256,6 @@ jobs:
        if: always()
        run: df -h
        shell: bash
-      - name: Report peak memory
-        if: always() && runner.os == 'Linux'
-        shell: bash
-        run: |
-          peak=$(find /sys/fs/cgroup -name memory.peak -readable \
-                 -exec cat {} + 2>/dev/null | sort -n | tail -1)
-          if [ -n "$peak" ]; then
-            echo "peak memory: $((peak / 1024 / 1024)) MiB"
-          else
-            echo "peak memory: unavailable (no readable cgroup v2 memory.peak)"
-          fi
-          free -g || true
      - name: Upload artifact
        uses: actions/upload-artifact@v7
        with:
@@ -338,7 +293,7 @@ jobs:
          - target: aarch64-unknown-linux-gnu
            host: ubuntu-2404-8x-arm64
        node:
-          - '22'
+          - '20'
    runs-on: ${{ matrix.settings.host }}
    defaults:
      run:
@@ -384,9 +339,9 @@ jobs:
      - name: Move built files
        run: cp dist/native.d.ts dist/native.js dist/*.node lancedb/
      - name: Test bindings
-        # Invoke the installed jest binary directly; the pnpm shim is set up
-        # against the install-phase Node, not the version selected above.
-        run: node_modules/.bin/jest --verbose
+        # Invoke jest directly because pnpm 11 itself requires Node 22+
+        # while the matrix tests on older Node versions.
+        run: npx jest --verbose
  publish:
    name: Publish
    runs-on: ubuntu-latest
@@ -0,0 +1,22 @@
+name: Update package-lock.json
+
+on:
+  workflow_dispatch:
+
+permissions:
+  contents: read
+
+jobs:
+  publish:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v6
+        with:
+          ref: main
+          persist-credentials: false
+          fetch-depth: 0
+          lfs: true
+      - uses: ./.github/workflows/update_package_lock
+        with:
+          github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
@@ -0,0 +1,22 @@
+name: Update NodeJs package-lock.json
+
+on:
+  workflow_dispatch:
+
+permissions:
+  contents: read
+
+jobs:
+  publish:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v6
+        with:
+          ref: main
+          persist-credentials: false
+          fetch-depth: 0
+          lfs: true
+      - uses: ./.github/workflows/update_package_lock_nodejs
+        with:
+          github_token: ${{ secrets.LANCEDB_RELEASE_TOKEN }}
@@ -20,10 +20,7 @@ repos:
    hooks:
      - id: local-biome-check
        name: biome check
-        # Use the biome from nodejs/package.json rather than a separately
-        # pinned one: the two drifted apart and disagreed on formatting, so
-        # this hook rejected code that `pnpm lint` accepted.
-        entry: nodejs/node_modules/.bin/biome check --config-path nodejs/biome.json nodejs/
+        entry: npx @biomejs/biome@1.8.3 check --config-path nodejs/biome.json nodejs/
        language: system
        types: [text]
        files: "nodejs/.*"
@@ -38,7 +38,7 @@ Before committing changes, run formatting for every language you touched. At min
 * Rust changes: run `cargo fmt --all`.
 * Python changes: run `ruff format .` and `ruff check .` from the repository root,
  and run targeted tests through `cd python && uv run ...`.
-* TypeScript changes: run the relevant `pnpm` lint, format, build, and docs commands in `nodejs`.
+* TypeScript changes: run the relevant `npm`/`pnpm` lint, format, build, and docs commands in `nodejs`.

 Before creating a PR, the exact value passed to `gh pr create --title` must follow
 Conventional Commits, such as `fix: support nested field paths in native index creation`
@@ -101,12 +101,12 @@ Python bindings changes:
 TypeScript bindings changes:

 1. Add napi-rs method binding on `Table` in `nodejs/src/table.rs`.
-2. Run `pnpm build` to generate TypeScript definitions.
+2. Run `npm run build` to generate TypeScript definitions.
 3. Add typescript method on abstract class `Table` in `nodejs/src/table.ts`.
 4. Add concrete method on `LocalTable` class in `nodejs/src/native_table.ts`.
    * Note: despite the name, this class is also used for remote tables.
 5. Add test in `nodejs/__test__/table.test.ts`.
-6. Run `pnpm run docs` to generate TypeScript documentation.
+6. Run `npm run docs` to generate TypeScript documentation.

 ## Python API reference

@@ -535,9 +535,9 @@ dependencies = [

 [[package]]
 name = "async-trait"
-version = "0.1.92"
+version = "0.1.91"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "82f6aeea286b8eb4dd3431a1be1b59d290ace00f5bfd8e2a159bc2a05e2c1667"
+checksum = "ae36dc4177970ef04fde5178d3e2429882def40e57a451f919c098f72baa6cec"
 dependencies = [
 "proc-macro2",
 "quote",
@@ -1443,9 +1443,9 @@ checksum = "175812e0be2bccb6abe50bb8d566126198344f707e304f45c648fd8f2cc0365e"

 [[package]]
 name = "bytemuck"
-version = "1.25.2"
+version = "1.25.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "95832e849adfb21180ccb6826a99da14e5d266ae5c2e668e1602cf234f153797"
+checksum = "c8efb64bd706a16a1bdde310ae86b351e4d21550d98d056f22f8a7f7a2183fec"
 dependencies = [
 "bytemuck_derive",
 ]
@@ -1597,9 +1597,9 @@ checksum = "613afe47fcd5fac7ccf1db93babcb082c5994d996f20b8b159f2ad1658eb5724"

 [[package]]
 name = "chacha20"
-version = "0.10.2"
+version = "0.10.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "65c35e4b699c7e15ccbe7ee35c005e4fc0a278d22238a2857e6ce2dadeda1b06"
+checksum = "6f8d983286843e49675a4b7a2d174efe136dc93a18d69130dd18198a6c167601"
 dependencies = [
 "cfg-if 1.0.4",
 "cpufeatures 0.3.0",
@@ -3455,8 +3455,8 @@ checksum = "42703706b716c37f96a77aea830392ad231f44c9e9a67872fa5548707e11b11c"

 [[package]]
 name = "fsst"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow-array",
 "rand 0.9.5",
@@ -4815,8 +4815,8 @@ checksum = "e037a2e1d8d5fdbd49b16a4ea09d5d6401c1f29eca5ff29d03d3824dba16256a"

 [[package]]
 name = "lance"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arc-swap",
 "arrow",
@@ -4888,8 +4888,8 @@ dependencies = [

 [[package]]
 name = "lance-arrow"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -4911,7 +4911,7 @@ dependencies = [
 [[package]]
 name = "lance-arrow-scalar"
 version = "58.0.0"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -4925,7 +4925,7 @@ dependencies = [
 [[package]]
 name = "lance-arrow-stats"
 version = "58.0.0"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow-array",
 "arrow-schema",
@@ -4934,8 +4934,8 @@ dependencies = [

 [[package]]
 name = "lance-bitpacking"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrayref",
 "crunchy",
@@ -4945,8 +4945,8 @@ dependencies = [

 [[package]]
 name = "lance-core"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -4983,8 +4983,8 @@ dependencies = [

 [[package]]
 name = "lance-datafusion"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow",
 "arrow-array",
@@ -5013,8 +5013,8 @@ dependencies = [

 [[package]]
 name = "lance-datagen"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow",
 "arrow-array",
@@ -5031,8 +5031,8 @@ dependencies = [

 [[package]]
 name = "lance-derive"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "proc-macro2",
 "quote",
@@ -5041,8 +5041,8 @@ dependencies = [

 [[package]]
 name = "lance-encoding"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow-arith",
 "arrow-array",
@@ -5075,8 +5075,8 @@ dependencies = [

 [[package]]
 name = "lance-file"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow-arith",
 "arrow-array",
@@ -5107,8 +5107,8 @@ dependencies = [

 [[package]]
 name = "lance-index"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arc-swap",
 "arrow",
@@ -5172,8 +5172,8 @@ dependencies = [

 [[package]]
 name = "lance-index-core"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow-array",
 "arrow-schema",
@@ -5195,8 +5195,8 @@ dependencies = [

 [[package]]
 name = "lance-io"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow",
 "arrow-array",
@@ -5236,8 +5236,8 @@ dependencies = [

 [[package]]
 name = "lance-linalg"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow-array",
 "arrow-schema",
@@ -5251,8 +5251,8 @@ dependencies = [

 [[package]]
 name = "lance-namespace"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow",
 "async-trait",
@@ -5264,8 +5264,8 @@ dependencies = [

 [[package]]
 name = "lance-namespace-impls"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow",
 "arrow-ipc",
@@ -5318,8 +5318,8 @@ dependencies = [

 [[package]]
 name = "lance-select"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -5333,8 +5333,8 @@ dependencies = [

 [[package]]
 name = "lance-table"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow",
 "arrow-array",
@@ -5374,8 +5374,8 @@ dependencies = [

 [[package]]
 name = "lance-testing"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "arrow-array",
 "arrow-schema",
@@ -5388,8 +5388,8 @@ dependencies = [

 [[package]]
 name = "lance-tokenizer"
-version = "12.0.0-beta.5"
-source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.5#556637791d0048c2b4f1342dd84b67c8bbd65259"
+version = "11.0.0-beta.22"
+source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
 dependencies = [
 "frostem",
 "icu_segmenter",
@@ -5402,7 +5402,7 @@ dependencies = [

 [[package]]
 name = "lancedb"
-version = "0.38.0"
+version = "0.38.0-beta.10"
 dependencies = [
 "ahash",
 "anyhow",
@@ -5490,7 +5490,7 @@ dependencies = [

 [[package]]
 name = "lancedb-nodejs"
-version = "0.38.0"
+version = "0.38.0-beta.10"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -5515,7 +5515,7 @@ dependencies = [

 [[package]]
 name = "lancedb-python"
-version = "0.38.0"
+version = "0.38.0-beta.10"
 dependencies = [
 "arrow",
 "async-trait",
@@ -5748,9 +5748,9 @@ dependencies = [

 [[package]]
 name = "log"
-version = "0.4.34"
+version = "0.4.33"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f9f8bd3e56ce4dfc153cf470fffbfa98c7620958b312ca5c3a4b8d5181fd13c6"
+checksum = "0ceec5bc11778974d1bcb055b18002eba7f4b3518b6a0081b3af5f21666da9ad"

 [[package]]
 name = "loom"
@@ -6001,9 +6001,9 @@ dependencies = [

 [[package]]
 name = "moka"
-version = "0.12.16"
+version = "0.12.15"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4293f18e7567a1caf3c584855554377025c65e0aa445344d04171f5ad63d19b9"
+checksum = "957228ad12042ee839f93c8f257b62b4c0ab5eaae1d4fa60de53b27c9d7c5046"
 dependencies = [
 "async-lock",
 "crossbeam-channel",
@@ -6097,15 +6097,14 @@ dependencies = [

 [[package]]
 name = "napi"
-version = "3.12.2"
+version = "3.11.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "58c5f4d5375213fdb7be2655e152386e82f026f9a5ba36a75556e11359aafe09"
+checksum = "de33522036981030a75c231829566bc63414e08101a6f5ff4ac6cef19c8e0941"
 dependencies = [
 "bitflags 2.11.1",
 "chrono",
 "ctor 1.0.12",
 "futures",
- "libc",
 "napi-build",
 "napi-sys",
 "nohash-hasher",
@@ -6117,15 +6116,15 @@ dependencies = [

 [[package]]
 name = "napi-build"
-version = "2.4.1"
+version = "2.4.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "60fdf9b392c50e7c4170fa633bd909490ed7835cea4c046776d1a4dd8d2ae0ab"
+checksum = "5282704fbe8d49b0cf8b08e3f33233416a528658f205c7e5ace63b582de0b11c"

 [[package]]
 name = "napi-derive"
-version = "3.6.3"
+version = "3.6.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0fa55ea69990c90b888e9e77044410e304ce7f35de599dc6d0b5c1923d2e59af"
+checksum = "4d5c9c02556ea6dc99dffd36c1ce60141411657438501a125b675776d011ce92"
 dependencies = [
 "convert_case",
 "ctor 1.0.12",
@@ -6137,9 +6136,9 @@ dependencies = [

 [[package]]
 name = "napi-derive-backend"
-version = "6.1.2"
+version = "6.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "df4056ac7c18e4438ccf0edaed4340ca0d269278c8ec19284f7b23cb039fd0ae"
+checksum = "d60b5d773ad46c698c8cc2cd9fde0b283d39cbb7f71c04bee633c7bdba4423bd"
 dependencies = [
 "convert_case",
 "proc-macro2",
@@ -8602,9 +8601,9 @@ dependencies = [

 [[package]]
 name = "roaring"
-version = "0.11.5"
+version = "0.11.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "18bd8a37d17a58532776dcdf6041ce64929adca78e8489d5cacbafe99229d3e1"
+checksum = "1dedc5658c6ecb3bdb5ef5f3295bb9253f42dcf3fd1402c03f6b1f7659c3c4a9"
 dependencies = [
 "bytemuck",
 "byteorder",
@@ -9064,9 +9063,9 @@ dependencies = [

 [[package]]
 name = "serde_with"
-version = "3.22.0"
+version = "3.21.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ee78f1fbe43ac4a0e47aadb3dbd357b69eb0d3793e948624cd03dd2750ab1c0a"
+checksum = "76a5c54c7310e7b8b9577c286d7e399ddd876c3e12b3ed917a8aabc4b96e9e8c"
 dependencies = [
 "base64 0.22.1",
 "bs58",
@@ -9074,7 +9073,6 @@ dependencies = [
 "hex",
 "indexmap 1.9.3",
 "indexmap 2.14.0",
- "jiff",
 "schemars 0.9.0",
 "schemars 1.2.1",
 "serde_core",
@@ -9085,9 +9083,9 @@ dependencies = [

 [[package]]
 name = "serde_with_macros"
-version = "3.22.0"
+version = "3.21.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8705578779c2b6bd90d84d66eb2e206b708b1a4d7b9f17641b293545bf1c7e46"
+checksum = "84d57bc0c8b9a17920c178daa6bb924850d54a9c97ab45194bb8c17ad66bb660"
 dependencies = [
 "darling 0.23.0",
 "proc-macro2",
@@ -10454,9 +10452,9 @@ checksum = "06abde3611657adf66d383f00b093d7faecc7fa57071cce2578660c9f1010821"

 [[package]]
 name = "uuid"
-version = "1.26.0"
+version = "1.24.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b5772d71c9be8a8a6ac2117d949c5b224c1b72241bb611d9a3012edcf8af7812"
+checksum = "bf3923a6f5c4c6382e0b653c4117f48d631ea17f38ed86e2a828e6f7412f5239"
 dependencies = [
 "getrandom 0.4.2",
 "js-sys",
@@ -13,20 +13,20 @@ categories = ["database-implementations"]
 rust-version = "1.91.0"

 [workspace.dependencies]
-lance = { "version" = "=12.0.0-beta.5", default-features = false, "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-core = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-datagen = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-file = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-io = { "version" = "=12.0.0-beta.5", default-features = false, "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-index = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-linalg = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace-impls = { "version" = "=12.0.0-beta.5", default-features = false, "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-table = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-testing = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-datafusion = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-encoding = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
-lance-arrow = { "version" = "=12.0.0-beta.5", "tag" = "v12.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
+lance = { "version" = "=11.0.0-beta.22", default-features = false, "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
+lance-core = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
+lance-datagen = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
+lance-file = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
+lance-io = { "version" = "=11.0.0-beta.22", default-features = false, "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
+lance-index = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
+lance-linalg = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace-impls = { "version" = "=11.0.0-beta.22", default-features = false, "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
+lance-table = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
+lance-testing = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
+lance-datafusion = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
+lance-encoding = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
+lance-arrow = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
 lancedb = { path = "rust/lancedb", default-features = false }
 ahash = "0.8"
 # Note that this one does not include pyarrow
@@ -5,5 +5,5 @@ licenses:
 	cd python && cargo about generate ../about.hbs -o RUST_THIRD_PARTY_LICENSES.html -c ../about.toml
 	cd python && uv sync --all-extras && uv tool run pip-licenses --python .venv/bin/python --format=markdown --with-urls --output-file=PYTHON_THIRD_PARTY_LICENSES.md
 	cd nodejs && cargo about generate ../about.hbs -o RUST_THIRD_PARTY_LICENSES.html -c ../about.toml
-	cd nodejs && pnpm dlx license-checker@25 --markdown --out NODEJS_THIRD_PARTY_LICENSES.md
+	cd nodejs && npx license-checker --markdown --out NODEJS_THIRD_PARTY_LICENSES.md
 	cd java && ./mvnw license:aggregate-add-third-party -q
@@ -12,12 +12,16 @@ done
 # This updates the lockfile without building
 cargo metadata --quiet > /dev/null

+pushd nodejs || exit 1
+npm install --package-lock-only --silent
+popd
+
 if git diff --quiet --exit-code; then
  echo "No lockfile changes to commit; skipping amend."
 elif $AMEND; then
-  git add Cargo.lock
+  git add Cargo.lock nodejs/package-lock.json
  git commit --amend --no-edit
 else
-  git add Cargo.lock
+  git add Cargo.lock nodejs/package-lock.json
  git commit -m "Update lockfiles"
 fi
@@ -131,13 +131,18 @@ allow = [
    "BSD-3-Clause",
    "ISC",
    "Unicode-3.0",
+    "Unicode-DFS-2016",
    "Zlib",
    "CC0-1.0",
    "MPL-2.0",
    "BSL-1.0",
+    "OpenSSL",
    # 0BSD ("BSD Zero Clause") is effectively public domain — no attribution
    # required. Pulled in by `mock_instant`.
    "0BSD",
+    # bzip2-1.0.6 is the permissive upstream bzip2 license (BSD-like). Pulled
+    # in by `libbz2-rs-sys`, the pure-Rust bzip2 implementation.
+    "bzip2-1.0.6",
    # CDLA-Permissive-2.0 is a permissive data license used by `webpki-roots`
    # for the Mozilla CA root bundle. Data-only, distribution-compatible.
    "CDLA-Permissive-2.0",
@@ -145,7 +150,12 @@ allow = [
 confidence-threshold = 0.8
 # Per-crate license exceptions: allow a license for a specific crate only,
 # rather than globally via the `allow` list above.
-exceptions = []
+exceptions = [
+    # CDDL-1.0 (copyleft) is pulled in only as a dev/profiling dependency via
+    # `inferno` -> `pprof` -> `lance-testing`; it is a test dependency that we
+    # do not distribute, so scope the allowance to `inferno` alone.
+    { allow = ["CDDL-1.0"], crate = "inferno" },
+]
 # Crates whose license cannot be determined from Cargo metadata but whose
 # license we've manually confirmed from upstream. Keep this list minimal.
 [[licenses.clarify]]
@@ -47,24 +47,22 @@ pytest -vv python/tests/docs

 ### Checking typescript examples

-The examples depend on `@lancedb/lancedb` at `file:../dist`, so the package must be
-built before running the tests. This uses pnpm; see the
-[Typescript contributing guide](../nodejs/CONTRIBUTING.md) for the toolchain setup.
+The `@lancedb/lancedb` package must be built before running the tests:

 ```shell
 pushd nodejs
-pnpm install
-pnpm build
+npm ci
+npm run build
 popd
 ```

-Then you can run the examples by going to the `nodejs/examples` directory, which is a
-separate pnpm package with its own lockfile:
+Then you can run the examples by going to the `nodejs/examples` directory and
+running the tests like a normal npm package:

 ```shell
 pushd nodejs/examples
-pnpm install
-pnpm test
+npm ci
+npm test
 popd
 ```

@@ -86,7 +84,6 @@ The new files should be checked into the repository.

 ```shell
 pushd nodejs
-# `pnpm docs` would invoke pnpm's built-in `docs` command, not the script.
-pnpm run docs
+npm run docs
 popd
 ```
@@ -0,0 +1,135 @@
+{
+  "name": "lancedb-docs-test",
+  "version": "1.0.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "lancedb-docs-test",
+      "version": "1.0.0",
+      "license": "Apache 2",
+      "dependencies": {
+        "apache-arrow": "file:../node/node_modules/apache-arrow",
+        "vectordb": "file:../node"
+      },
+      "devDependencies": {
+        "@types/node": "^20.11.8",
+        "typescript": "^5.3.3"
+      }
+    },
+    "../node": {
+      "name": "vectordb",
+      "version": "0.21.2-beta.0",
+      "cpu": [
+        "x64",
+        "arm64"
+      ],
+      "license": "Apache-2.0",
+      "os": [
+        "darwin",
+        "linux",
+        "win32"
+      ],
+      "dependencies": {
+        "@neon-rs/load": "^0.0.74",
+        "axios": "^1.4.0"
+      },
+      "devDependencies": {
+        "@neon-rs/cli": "^0.0.160",
+        "@types/chai": "^4.3.4",
+        "@types/chai-as-promised": "^7.1.5",
+        "@types/mocha": "^10.0.1",
+        "@types/node": "^18.16.2",
+        "@types/sinon": "^10.0.15",
+        "@types/temp": "^0.9.1",
+        "@types/uuid": "^9.0.3",
+        "@typescript-eslint/eslint-plugin": "^5.59.1",
+        "apache-arrow-old": "npm:apache-arrow@13.0.0",
+        "cargo-cp-artifact": "^0.1",
+        "chai": "^4.3.7",
+        "chai-as-promised": "^7.1.1",
+        "eslint": "^8.39.0",
+        "eslint-config-standard-with-typescript": "^34.0.1",
+        "eslint-plugin-import": "^2.26.0",
+        "eslint-plugin-n": "^15.7.0",
+        "eslint-plugin-promise": "^6.1.1",
+        "mocha": "^10.2.0",
+        "openai": "^4.24.1",
+        "sinon": "^15.1.0",
+        "temp": "^0.9.4",
+        "ts-node": "^10.9.1",
+        "ts-node-dev": "^2.0.0",
+        "typedoc": "^0.24.7",
+        "typedoc-plugin-markdown": "^3.15.3",
+        "typescript": "^5.1.0",
+        "uuid": "^9.0.0"
+      },
+      "optionalDependencies": {
+        "@lancedb/vectordb-darwin-arm64": "0.21.2-beta.0",
+        "@lancedb/vectordb-darwin-x64": "0.21.2-beta.0",
+        "@lancedb/vectordb-linux-arm64-gnu": "0.21.2-beta.0",
+        "@lancedb/vectordb-linux-x64-gnu": "0.21.2-beta.0",
+        "@lancedb/vectordb-win32-x64-msvc": "0.21.2-beta.0"
+      },
+      "peerDependencies": {
+        "@apache-arrow/ts": "^14.0.2",
+        "apache-arrow": "^14.0.2"
+      }
+    },
+    "../node/node_modules/apache-arrow": {
+      "version": "14.0.2",
+      "license": "Apache-2.0",
+      "dependencies": {
+        "@types/command-line-args": "5.2.0",
+        "@types/command-line-usage": "5.0.2",
+        "@types/node": "20.3.0",
+        "@types/pad-left": "2.1.1",
+        "command-line-args": "5.2.1",
+        "command-line-usage": "7.0.1",
+        "flatbuffers": "23.5.26",
+        "json-bignum": "^0.0.3",
+        "pad-left": "^2.1.0",
+        "tslib": "^2.5.3"
+      },
+      "bin": {
+        "arrow2csv": "bin/arrow2csv.js"
+      }
+    },
+    "node_modules/@types/node": {
+      "version": "20.11.8",
+      "resolved": "https://registry.npmjs.org/@types/node/-/node-20.11.8.tgz",
+      "integrity": "sha512-i7omyekpPTNdv4Jb/Rgqg0RU8YqLcNsI12quKSDkRXNfx7Wxdm6HhK1awT3xTgEkgxPn3bvnSpiEAc7a7Lpyow==",
+      "dev": true,
+      "dependencies": {
+        "undici-types": "~5.26.4"
+      }
+    },
+    "node_modules/apache-arrow": {
+      "resolved": "../node/node_modules/apache-arrow",
+      "link": true
+    },
+    "node_modules/typescript": {
+      "version": "5.3.3",
+      "resolved": "https://registry.npmjs.org/typescript/-/typescript-5.3.3.tgz",
+      "integrity": "sha512-pXWcraxM0uxAS+tN0AG/BF2TyqmHO014Z070UsJ+pFvYuRSq8KH8DmWpnbXe0pEPDHXZV3FcAbJkijJ5oNEnWw==",
+      "dev": true,
+      "bin": {
+        "tsc": "bin/tsc",
+        "tsserver": "bin/tsserver"
+      },
+      "engines": {
+        "node": ">=14.17"
+      }
+    },
+    "node_modules/undici-types": {
+      "version": "5.26.5",
+      "resolved": "https://registry.npmjs.org/undici-types/-/undici-types-5.26.5.tgz",
+      "integrity": "sha512-JlCMO+ehdEIKqlFxk6IfVoAUVmgz7cU7zD/h9XZ0qzeosSHmUJVOzSQvvYSYWXkFXC+IfLKSIffhv0sVZup6pA==",
+      "dev": true
+    },
+    "node_modules/vectordb": {
+      "resolved": "../node",
+      "link": true
+    }
+  }
+}
@@ -0,0 +1,20 @@
+{
+  "name": "lancedb-docs-test",
+  "version": "1.0.0",
+  "description": "auto-generated tests from doc",
+  "author": "dev@lancedb.com",
+  "license": "Apache 2",
+  "dependencies": {
+    "apache-arrow": "file:../node/node_modules/apache-arrow",
+    "vectordb": "file:../node"
+  },
+  "scripts": {
+    "build": "tsc -b && cd ../node && npm run build-release",
+    "example": "npm run build && node",
+    "test": "npm run build && ls dist/*.js | xargs -n 1 node"
+  },
+  "devDependencies": {
+    "@types/node": "^20.11.8",
+    "typescript": "^5.3.3"
+  }
+}
@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
 <dependency>
    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-core</artifactId>
-    <version>0.38.0</version>
+    <version>0.38.0-beta.10</version>
 </dependency>
 ```

@@ -1292,18 +1292,6 @@ abstract updateFieldMetadata(updates): Promise<UpdateFieldMetadataResult>

 Update per-field (column) metadata.

-The following keys are treated specially, by convention, and should be
-used when appropriate:
-
- `lancedb:description`: for a human-readable description of a field.
- `lancedb:tag:<name>`: for a user-defined key-value tag, where the suffix
-  names the tag category; e.g. `lancedb:tag:model: "clip"`.
- `lancedb:logical-column`: for a column grouping; e.g. `feature_v1` and
-  `feature_v2` might be in the same logical column.
- `lancedb:status`: for status options (`production`, `candidate`,
-  `deprecated`, `archived`) to designate the current life cycle state of
-  this column.
-
 #### Parameters

 * **updates**: [`FieldMetadataUpdate`](../interfaces/FieldMetadataUpdate.md)[]
@@ -17,8 +17,7 @@ metadata: Record<string, null | string>;
 ```

 Metadata key/value pairs. Merged into the field's existing metadata by
-default; a value of `null` deletes that key. See
-[Table.updateFieldMetadata](../classes/Table.md#updatefieldmetadata) for the conventional `lancedb:*` keys.
+default; a value of `null` deletes that key.

 ***

@@ -159,8 +159,6 @@ and combined with [BooleanQuery][lancedb.query.BooleanQuery].

 ::: lancedb.query.FullTextOperator

-::: lancedb.query.DocumentGranularity
-
 ::: lancedb.query.Occur

 ## Embeddings
@@ -223,14 +221,10 @@ tokens = list(
 Blob columns store large binary values out of line so they can be read lazily
 instead of being materialized with the rest of the row.

-`lancedb.BlobType` is `lance.blob.BlobType` when pylance is installed. Without
-pylance, LanceDB uses a matching `lance.blob.v2` extension type so blob columns
-still work. Queries return descriptors. Call
-[`fetch_blob_files`][lancedb.table.Table.fetch_blob_files] for lazy reads or
-[`fetch_blobs`][lancedb.table.Table.fetch_blobs] for eager bytes.
-
 ::: lancedb.blob

+::: lancedb.BlobType
+
 ::: lancedb._blob.BlobFile
    options:
      show_root_full_path: false
@@ -0,0 +1,17 @@
+{
+  "include": [
+    "src/*.ts",
+  ],
+  "compilerOptions": {
+    "target": "es2022",
+    "module": "nodenext",
+    "declaration": true,
+    "outDir": "./dist",
+    "strict": true,
+    "allowJs": true,
+    "resolveJsonModule": true,
+  },
+  "exclude": [
+    "./dist/*",
+  ]
+}
@@ -8,7 +8,7 @@
    <parent>
      <groupId>com.lancedb</groupId>
      <artifactId>lancedb-parent</artifactId>
-      <version>0.38.0-final.0</version>
+      <version>0.38.0-beta.10</version>
      <relativePath>../pom.xml</relativePath>
    </parent>

@@ -6,7 +6,7 @@

    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-parent</artifactId>
-    <version>0.38.0-final.0</version>
+    <version>0.38.0-beta.10</version>
    <packaging>pom</packaging>
    <name>${project.artifactId}</name>
    <description>LanceDB Java SDK Parent POM</description>
@@ -28,7 +28,7 @@
    <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <arrow.version>15.0.0</arrow.version>
-        <lance-core.version>12.0.0-beta.5</lance-core.version>
+        <lance-core.version>11.0.0-beta.22</lance-core.version>
        <spotless.skip>false</spotless.skip>
        <spotless.version>2.30.0</spotless.version>
        <spotless.java.googlejavaformat.version>1.7</spotless.java.googlejavaformat.version>
@@ -1,7 +1,7 @@
 [package]
 name = "lancedb-nodejs"
 edition.workspace = true
-version = "0.38.0"
+version = "0.38.0-beta.10"
 publish = false
 license.workspace = true
 description.workspace = true
@@ -1,16 +1,11 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
-import * as fs from "node:fs";
-import * as vm from "node:vm";
 import * as arrow15 from "apache-arrow-15";
 import * as arrow16 from "apache-arrow-16";
 import * as arrow17 from "apache-arrow-17";
 import * as arrow18 from "apache-arrow-18";

 import {
-  Field as CurrentField,
-  LargeBinary as CurrentLargeBinary,
-  Schema as CurrentSchema,
  Vector as CurrentVector,
  convertToTable,
  tableFromIPC as currentTableFromIPC,
@@ -41,59 +36,6 @@ function sampleRecords(): Array<Record<string, any>> {
    },
  ];
 }
-
-it("serializes an Arrow Table created in another JavaScript realm", async () => {
-  const context = vm.createContext({
-    TextDecoder,
-    TextEncoder,
-    console,
-    setTimeout,
-    clearTimeout,
-  });
-  vm.runInContext(
-    fs.readFileSync(
-      require.resolve("apache-arrow-15/Arrow.es2015.min"),
-      "utf8",
-    ),
-    context,
-  );
-  const foreignTable: unknown = vm.runInContext(
-    "Arrow.tableFromArrays({ id: new Int32Array([1, 2, 3]), text: ['foo', 'bar', 'baz'] })",
-    context,
-  );
-
-  const foreignMetadata = (
-    foreignTable as { schema: { metadata: Map<string, string> } }
-  ).schema.metadata;
-  expect(foreignMetadata).not.toBeInstanceOf(Map);
-
-  const buf = await fromDataToBuffer(
-    foreignTable as Parameters<typeof fromDataToBuffer>[0],
-  );
-  const actual = currentTableFromIPC(buf);
-
-  expect(actual.numRows).toBe(3);
-  expect(actual.getChild("id")?.toJSON()).toEqual([1, 2, 3]);
-  expect(actual.getChild("text")?.toJSON()).toEqual(["foo", "bar", "baz"]);
-});
-
-it("preserves field metadata from a provided schema", async function () {
-  const jsonMetadata = new Map([["ARROW:extension:name", "lance.json"]]);
-  const schema = new CurrentSchema([
-    new CurrentField("meta", new CurrentLargeBinary(), true, jsonMetadata),
-  ]);
-
-  const table = makeArrowTable(
-    [{ meta: Buffer.from(JSON.stringify({ source: "test" })) }],
-    { schema },
-  );
-
-  expect(table.schema.fields[0].metadata).toEqual(jsonMetadata);
-
-  const roundTripped = currentTableFromIPC(await fromTableToBuffer(table));
-  expect(roundTripped.schema.fields[0].metadata).toEqual(jsonMetadata);
-});
-
 describe.each([arrow15, arrow16, arrow17, arrow18])(
  "Arrow",
  (
@@ -187,58 +187,6 @@ describe("embedding functions", () => {
    const vector0 = JSON.parse(JSON.stringify(arr[0].vector));
    expect(vector0).toEqual([1, 2, 3]);
  });
-  it("should append multiple Python embeddings with the same alias", async () => {
-    @register("python-mock")
-    // biome-ignore lint/correctness/noUnusedVariables: the decorator registers this class
-    class MockEmbeddingFunction extends EmbeddingFunction<string> {
-      ndims() {
-        return 3;
-      }
-      embeddingDataType(): Float {
-        return new Float32();
-      }
-      async computeQueryEmbeddings(_data: string) {
-        return [1, 2, 3];
-      }
-      async computeSourceEmbeddings(data: string[]) {
-        return data.map((value) =>
-          value === "hello world" ? [1, 2, 3] : [4, 5, 6],
-        );
-      }
-    }
-
-    const metadata = new Map([
-      [
-        "embedding_functions",
-        '[{"source_column":"text1","vector_column":"vector1","name":"python-mock","model":{}},{"source_column":"text2","vector_column":"vector2","name":"python-mock","model":{}}]',
-      ],
-    ]);
-    const schema = new Schema(
-      [
-        new Field("text1", new Utf8(), true),
-        new Field("text2", new Utf8(), true),
-        new Field(
-          "vector1",
-          new FixedSizeList(3, new Field("item", new Float32(), true)),
-          true,
-        ),
-        new Field(
-          "vector2",
-          new FixedSizeList(3, new Field("item", new Float32(), true)),
-          true,
-        ),
-      ],
-      metadata,
-    );
-
-    const db = await connect(tmpDir.name);
-    const table = await db.createEmptyTable("test", schema);
-    await table.add([{ text1: "hello world", text2: "goodbye world" }]);
-
-    const rows = await table.query().toArray();
-    expect(JSON.parse(JSON.stringify(rows[0].vector1))).toEqual([1, 2, 3]);
-    expect(JSON.parse(JSON.stringify(rows[0].vector2))).toEqual([4, 5, 6]);
-  });

  it("should append generated vectors to a non-nullable schema", async () => {
    @register("non_nullable_schema_test")
@@ -5,8 +5,8 @@ import packageJson = require("../package.json");

 describe("package metadata", () => {
  it("requires Node.js type declarations compatible with the runtime", () => {
-    expect(packageJson.engines.node).toBe(">= 22");
-    expect(packageJson.peerDependencies["@types/node"]).toBe(">=22");
+    expect(packageJson.engines.node).toBe(">= 18");
+    expect(packageJson.peerDependencies["@types/node"]).toBe(">=18");
    expect(packageJson.peerDependenciesMeta["@types/node"]).toEqual({
      optional: true,
    });
@@ -3,7 +3,6 @@

 import * as http from "http";
 import { RequestListener } from "http";
-import packageJson = require("../package.json");
 import {
  ClientConfig,
  Connection,
@@ -71,13 +70,7 @@ async function withMockDatabase(
  try {
    await callback(db);
  } finally {
-    // `close()` alone leaves the port bound until keep-alive sockets drain, so
-    // a single failing test would cascade into EADDRINUSE for every test after
-    // it. Destroy the connections and wait for the port to actually be free.
-    await new Promise<void>((resolve) => {
-      server.closeAllConnections();
-      server.close(() => resolve());
-    });
+    server.close();
  }
 }

@@ -138,7 +131,7 @@ describe("remote connection", () => {
      (req, res) => {
        expect(req.headers["x-api-key"]).toEqual("fake");
        expect(req.headers["user-agent"]).toEqual(
-          `LanceDB-Node-Client/${packageJson.version}`,
+          `LanceDB-Node-Client/${process.env.npm_package_version}`,
        );

        const body = JSON.stringify({ tables: [] });
@@ -685,56 +685,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
  },
 );

-// https://github.com/lancedb/lancedb/issues/1963
-it("should query documents with LangChain PDF metadata", async () => {
-  const tmpDir = tmp.dirSync({ unsafeCleanup: true });
-  try {
-    const db = await connect(tmpDir.name);
-    const documents = [
-      {
-        text: "first page",
-        vector: [1, 0],
-        source: "first.pdf",
-        loc: { pageNumber: 1, lines: { from: 1, to: 12 } },
-        pdf: {
-          version: "1.10.100",
-          info: {
-            format: "PDF 1.7",
-            producer: "pdf.js",
-            creator: "Writer",
-          },
-          totalPages: 2,
-        },
-      },
-      {
-        text: "second page",
-        vector: [0, 1],
-        source: "second.pdf",
-        loc: { pageNumber: 2, lines: { from: 13, to: 24 } },
-        pdf: {
-          version: "1.10.100",
-          info: {
-            format: "PDF 1.7",
-            producer: "pdf.js",
-            creator: "Writer",
-          },
-          totalPages: 2,
-        },
-      },
-    ];
-    const documentsTable = await db.createTable("documents", documents);
-
-    const results = await documentsTable.query().toArray();
-
-    expect(results).toHaveLength(2);
-    expect(results[0].source).toBe("first.pdf");
-    expect(results[0].pdf.info.producer).toBe("pdf.js");
-    expect(results[1].loc.pageNumber).toBe(2);
-  } finally {
-    tmpDir.removeCallback();
-  }
-});
-
 describe("merge insert", () => {
  let tmpDir: tmp.DirResult;
  let table: Table;
@@ -2585,24 +2535,7 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
      );
    });

-    test("full text search if only an unrelated embedding function is registered", async () => {
-      register("unused")(
-        class extends EmbeddingFunction<string> {
-          ndims() {
-            return 3;
-          }
-          embeddingDataType() {
-            return new Float32();
-          }
-          async computeQueryEmbeddings(_data: string) {
-            return [1, 2, 3];
-          }
-          async computeSourceEmbeddings(data: string[]) {
-            return data.map(() => [1, 2, 3]);
-          }
-        },
-      );
-
+    test("full text search if no embedding function provided", async () => {
      const db = await connect(tmpDir.name);
      const data = [
        { text: "hello world", vector: [0.1, 0.2, 0.3] },
@@ -2624,306 +2557,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
      expect(results2[0].text).toBe(data[1].text);
    });

-    test("auto search stays consistent with the active revision", async () => {
-      let initCalls = 0;
-      let queryCalls = 0;
-      let markStarted!: () => void;
-      const started = new Promise<void>((resolve) => {
-        markStarted = resolve;
-      });
-      let releaseEmbedding!: () => void;
-      const embeddingReleased = new Promise<void>((resolve) => {
-        releaseEmbedding = resolve;
-      });
-
-      @register("refresh-test")
-      class TestEmbedding extends EmbeddingFunction<string> {
-        async init() {
-          initCalls += 1;
-        }
-        ndims() {
-          return 1;
-        }
-        embeddingDataType() {
-          return new arrow.Float32();
-        }
-        async computeQueryEmbeddings(value: string) {
-          queryCalls += 1;
-          if (value === "blocked") {
-            markStarted();
-            await embeddingReleased;
-          }
-          return value === "greetings" ? [0.1] : [0.2];
-        }
-        async computeSourceEmbeddings(values: string[]) {
-          return values.map((value) =>
-            value === "hello world" ? [0.1] : [0.2],
-          );
-        }
-      }
-
-      const writer = await connect(tmpDir.name);
-      await writer.createTable("test", [{ text: "plain", vector: [0.0] }]);
-      const reader = await connect(tmpDir.name, {
-        readConsistencyInterval: 0,
-      });
-      const tracked = await reader.openTable("test");
-      type SnapshotCountingNative = {
-        querySnapshot: () => Promise<unknown>;
-      };
-      const native = (tracked as unknown as { inner: SnapshotCountingNative })
-        .inner;
-      const querySnapshot = native.querySnapshot.bind(native);
-      let snapshotCalls = 0;
-      native.querySnapshot = async () => {
-        snapshotCalls += 1;
-        return await querySnapshot();
-      };
-      const autoQuery = tracked.search("greetings").select(["text"]).limit(1);
-
-      const func = new TestEmbedding();
-      const schema = LanceSchema({
-        text: func.sourceField(new arrow.Utf8()),
-        vector: func.vectorField(),
-      });
-      const data = [{ text: "hello world" }, { text: "goodbye world" }];
-      await writer.createTable("test", data, { mode: "overwrite", schema });
-      const baselineInitCalls = initCalls;
-
-      expect(
-        (await tracked.schema()).metadata.get("embedding_functions"),
-      ).toBeDefined();
-      const results = await autoQuery.toArray();
-      expect(results[0].text).toBe(data[0].text);
-      expect(initCalls).toBe(baselineInitCalls + 1);
-      expect(queryCalls).toBe(1);
-      expect(snapshotCalls).toBe(1);
-
-      const repeatedResults = await autoQuery.toArray();
-      expect(repeatedResults[0].text).toBe(data[0].text);
-      expect(initCalls).toBe(baselineInitCalls + 1);
-      expect(queryCalls).toBe(1);
-      expect(snapshotCalls).toBe(2);
-
-      const pending = tracked
-        .search("blocked")
-        .select(["text"])
-        .limit(1)
-        .toArray();
-      await started;
-
-      const ftsData = [
-        { text: "greetings from full text", vector: [0.0] },
-        { text: "blocked from full text", vector: [0.0] },
-      ];
-      const ftsTable = await writer.createTable("test", ftsData, {
-        mode: "overwrite",
-      });
-      await ftsTable.createIndex("text", { config: Index.fts() });
-      releaseEmbedding();
-
-      const pendingResults = await pending;
-      expect(pendingResults[0].text).toBe(data[1].text);
-
-      expect(
-        (await tracked.schema()).metadata.get("embedding_functions"),
-      ).toBeUndefined();
-      const ftsResults = await autoQuery.toArray();
-      expect(ftsResults[0].text).toBe(ftsData[0].text);
-    });
-
-    test("auto search keeps newer preparation during a revision race", async () => {
-      let aCalls = 0;
-      let bCalls = 0;
-      let markAStarted!: () => void;
-      const aStarted = new Promise<void>((resolve) => {
-        markAStarted = resolve;
-      });
-      let releaseA!: () => void;
-      const aReleased = new Promise<void>((resolve) => {
-        releaseA = resolve;
-      });
-      let markBStarted!: () => void;
-      const bStarted = new Promise<void>((resolve) => {
-        markBStarted = resolve;
-      });
-      let releaseB!: () => void;
-      const bReleased = new Promise<void>((resolve) => {
-        releaseB = resolve;
-      });
-
-      @register("race-a")
-      class EmbeddingA extends EmbeddingFunction<string> {
-        ndims() {
-          return 1;
-        }
-        embeddingDataType() {
-          return new arrow.Float32();
-        }
-        async computeQueryEmbeddings() {
-          aCalls += 1;
-          markAStarted();
-          await aReleased;
-          return [0.1];
-        }
-        async computeSourceEmbeddings(values: string[]) {
-          return values.map(() => [0.1]);
-        }
-      }
-
-      @register("race-b")
-      class EmbeddingB extends EmbeddingFunction<string> {
-        ndims() {
-          return 1;
-        }
-        embeddingDataType() {
-          return new arrow.Float32();
-        }
-        async computeQueryEmbeddings() {
-          bCalls += 1;
-          markBStarted();
-          await bReleased;
-          return [0.2];
-        }
-        async computeSourceEmbeddings(values: string[]) {
-          return values.map(() => [0.2]);
-        }
-      }
-
-      const writer = await connect(tmpDir.name);
-      const embeddingA = new EmbeddingA();
-      const schemaA = LanceSchema({
-        text: embeddingA.sourceField(new arrow.Utf8()),
-        vector: embeddingA.vectorField(),
-      });
-      await writer.createTable("race", [{ text: "revision a" }], {
-        schema: schemaA,
-      });
-      const reader = await connect(tmpDir.name, {
-        readConsistencyInterval: 0,
-      });
-      const tracked = await reader.openTable("race");
-      const query = tracked.search("query");
-
-      const first = query.toArray();
-      await aStarted;
-
-      const embeddingB = new EmbeddingB();
-      const schemaB = LanceSchema({
-        text: embeddingB.sourceField(new arrow.Utf8()),
-        vector: embeddingB.vectorField(),
-      });
-      await writer.createTable("race", [{ text: "revision b" }], {
-        mode: "overwrite",
-        schema: schemaB,
-      });
-      const second = query.toArray();
-      await bStarted;
-
-      releaseA();
-      releaseB();
-      await Promise.all([first, second]);
-      expect(aCalls).toBe(1);
-      expect(bCalls).toBe(1);
-    });
-
-    test("stale FTS routing keeps newer vector preparation", async () => {
-      let vectorCalls = 0;
-      let markVectorStarted!: () => void;
-      const vectorStarted = new Promise<void>((resolve) => {
-        markVectorStarted = resolve;
-      });
-      let releaseVector!: () => void;
-      const vectorReleased = new Promise<void>((resolve) => {
-        releaseVector = resolve;
-      });
-
-      @register("stale-fts-race")
-      class RaceEmbedding extends EmbeddingFunction<string> {
-        ndims() {
-          return 1;
-        }
-        embeddingDataType() {
-          return new arrow.Float32();
-        }
-        async computeQueryEmbeddings() {
-          vectorCalls += 1;
-          markVectorStarted();
-          await vectorReleased;
-          return [0.1];
-        }
-        async computeSourceEmbeddings(values: string[]) {
-          return values.map(() => [0.1]);
-        }
-      }
-
-      const writer = await connect(tmpDir.name);
-      const ftsTable = await writer.createTable("stale_fts", [
-        { text: "hello", vector: [0.0] },
-      ]);
-      await ftsTable.createIndex("text", { config: Index.fts() });
-
-      const reader = await connect(tmpDir.name, {
-        readConsistencyInterval: 0,
-      });
-      const tracked = await reader.openTable("stale_fts");
-      type Snapshot = {
-        schema: () => Promise<Buffer>;
-      };
-      type NativeWithSnapshot = {
-        querySnapshot: () => Promise<Snapshot>;
-      };
-      const native = (tracked as unknown as { inner: NativeWithSnapshot })
-        .inner;
-      const querySnapshot = native.querySnapshot.bind(native);
-      let snapshotCalls = 0;
-      let markStaleSchemaStarted!: () => void;
-      const staleSchemaStarted = new Promise<void>((resolve) => {
-        markStaleSchemaStarted = resolve;
-      });
-      let releaseStaleSchema!: () => void;
-      const staleSchemaReleased = new Promise<void>((resolve) => {
-        releaseStaleSchema = resolve;
-      });
-      native.querySnapshot = async () => {
-        const snapshot = await querySnapshot();
-        snapshotCalls += 1;
-        if (snapshotCalls === 1) {
-          const schema = snapshot.schema.bind(snapshot);
-          snapshot.schema = async () => {
-            markStaleSchemaStarted();
-            await staleSchemaReleased;
-            return await schema();
-          };
-        }
-        return snapshot;
-      };
-
-      const query = tracked.search("hello");
-      const staleFtsExecution = query.toArray();
-      await staleSchemaStarted;
-
-      const embedding = new RaceEmbedding();
-      const vectorSchema = LanceSchema({
-        text: embedding.sourceField(new arrow.Utf8()),
-        vector: embedding.vectorField(),
-      });
-      await writer.createTable("stale_fts", [{ text: "hello" }], {
-        mode: "overwrite",
-        schema: vectorSchema,
-      });
-
-      const vectorExecution = query.toArray();
-      await vectorStarted;
-      releaseStaleSchema();
-      await staleFtsExecution;
-      releaseVector();
-      await vectorExecution;
-
-      await query.toArray();
-      expect(vectorCalls).toBe(1);
-    });
-
    test("tokenizes FTS queries by column or index name", async () => {
      const db = await connect(tmpDir.name);
      const data = [
@@ -3474,30 +3107,6 @@ describe("column name options", () => {
    expect(results[1].query_index).toBe(1);
  });

-  test("observes promised additional vectors while the query is pending", async () => {
-    const initialVector = new Promise<number[]>(() => undefined);
-    const query = table.query().nearestTo(initialVector);
-    const unhandled: unknown[] = [];
-    const onUnhandled = (reason: unknown) => unhandled.push(reason);
-    process.on("unhandledRejection", onUnhandled);
-
-    try {
-      query.addQueryVector(Promise.reject(new Error("extra vector failed")));
-      await new Promise<void>((resolve) => setImmediate(resolve));
-      expect(unhandled).toEqual([]);
-
-      const rejectedQuery = table
-        .query()
-        .nearestTo([0.1, 0.2])
-        .addQueryVector(Promise.reject(new Error("consumed vector failed")));
-      await expect(rejectedQuery.toArray()).rejects.toThrow(
-        "consumed vector failed",
-      );
-    } finally {
-      process.off("unhandledRejection", onUnhandled);
-    }
-  });
-
  test("index and search multivectors", async () => {
    const db = await connect(tmpDir.name);
    const data = [];
@@ -3561,27 +3170,6 @@ describe("when creating an empty table", () => {
    expect((actualSchema.fields[1].type as Float64).precision).toBe(2);
  });

-  it("can add and query JSON data", async () => {
-    const schema = new Schema([
-      new Field("id", new Int32(), true),
-      new Field(
-        "meta",
-        new Utf8(),
-        true,
-        new Map([["ARROW:extension:name", "arrow.json"]]),
-      ),
-    ]);
-    const table = await con.createEmptyTable("json", schema);
-    const meta = JSON.stringify({ x: 1 });
-
-    await table.add([{ id: 1, meta }]);
-
-    const rows = await table.query().toArray();
-    expect(rows).toHaveLength(1);
-    expect(rows[0].id).toBe(1);
-    expect(rows[0].meta).toBe(meta);
-  });
-
  it("can create an empty table from schema that specifies field types by name", async () => {
    const schemaLike = {
      fields: [
@@ -170,7 +170,7 @@ test("basic table examples", async () => {
    // --8<-- [end:create_index]

    // --8<-- [start:delete_rows]
-    await tbl.delete("item = 'fizz'");
+    await tbl.delete('item = "fizz"');
    // --8<-- [end:delete_rows]

    // --8<-- [start:drop_table]
@@ -8,8 +8,7 @@
    "//1": "--experimental-vm-modules is needed to run jest with sentence-transformers",
    "//2": "--testEnvironment is needed to run jest with sentence-transformers",
    "//3": "See: https://github.com/huggingface/transformers.js/issues/57",
-    "//4": "jest is invoked by its JS entry, not node_modules/.bin/jest: under pnpm that path is a shell shim, which `node` cannot execute",
-    "test": "node --experimental-vm-modules node_modules/jest/bin/jest.js --testEnvironment jest-environment-node-single-context --verbose",
+    "test": "node --experimental-vm-modules node_modules/.bin/jest --testEnvironment jest-environment-node-single-context --verbose",
    "lint": "biome check *.ts && biome format *.ts",
    "lint-ci": "biome ci .",
    "lint-fix": "biome check --write *.ts && pnpm format",
@@ -72,7 +72,8 @@ export type FieldLike =
    };

 export type DataLike =
-  | import("apache-arrow").Data
+  // biome-ignore lint/suspicious/noExplicitAny: <explanation>
+  | import("apache-arrow").Data<Struct<any>>
  | {
      // biome-ignore lint/suspicious/noExplicitAny: <explanation>
      type: any;
@@ -81,7 +82,6 @@ export type DataLike =
      stride: number;
      nullable: boolean;
      children: DataLike[];
-      dictionary?: { data: readonly DataLike[] };
      get nullCount(): number;
      // biome-ignore lint/suspicious/noExplicitAny: <explanation>
      values: Buffers<any>[BufferType.DATA];
@@ -100,29 +100,6 @@ export interface FullTextSearchOptions {
  columns?: string | string[];
 }

-function nearestToNative(
-  inner: NativeQuery,
-  vector: Awaited<IntoVector>,
-): NativeVectorQuery {
-  const raw = Array.isArray(vector) ? null : extractVectorBuffer(vector);
-  if (raw) {
-    return inner.nearestToRaw(raw.data, raw.dtype);
-  }
-  return inner.nearestTo(Float32Array.from(vector as number[]));
-}
-
-function addQueryVectorToNative(
-  inner: NativeVectorQuery,
-  vector: Awaited<IntoVector>,
-) {
-  const raw = Array.isArray(vector) ? null : extractVectorBuffer(vector);
-  if (raw) {
-    inner.addQueryVectorRaw(raw.data, raw.dtype);
-  } else {
-    inner.addQueryVector(Float32Array.from(vector as number[]));
-  }
-}
-
 /** Common methods supported by all query types
 *
 * @see {@link Query}
@@ -522,13 +499,6 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
    super(inner);
  }

-  /**
-   * @hidden
-   */
-  protected doVectorCall(fn: (inner: NativeVectorQuery) => void) {
-    super.doCall(fn);
-  }
-
  /**
   * Set the number of partitions to search (probe)
   *
@@ -556,7 +526,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * the minimum and maximum to the same value.
   */
  nprobes(nprobes: number): VectorQuery {
-    this.doVectorCall((inner) => inner.nprobes(nprobes));
+    super.doCall((inner) => inner.nprobes(nprobes));

    return this;
  }
@@ -570,7 +540,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * but will also increase latency.
   */
  minimumNprobes(minimumNprobes: number): VectorQuery {
-    this.doVectorCall((inner) => inner.minimumNprobes(minimumNprobes));
+    super.doCall((inner) => inner.minimumNprobes(minimumNprobes));
    return this;
  }

@@ -584,7 +554,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * potential false negatives.
   */
  maximumNprobes(maximumNprobes: number): VectorQuery {
-    this.doVectorCall((inner) => inner.maximumNprobes(maximumNprobes));
+    super.doCall((inner) => inner.maximumNprobes(maximumNprobes));
    return this;
  }

@@ -597,7 +567,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * `undefined` means no lower or upper bound.
   */
  distanceRange(lowerBound?: number, upperBound?: number): VectorQuery {
-    this.doVectorCall((inner) => inner.distanceRange(lowerBound, upperBound));
+    super.doCall((inner) => inner.distanceRange(lowerBound, upperBound));
    return this;
  }

@@ -611,7 +581,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * also increase the latency of your query. The default value is 1.5*limit.
   */
  ef(ef: number): VectorQuery {
-    this.doVectorCall((inner) => inner.ef(ef));
+    super.doCall((inner) => inner.ef(ef));
    return this;
  }

@@ -625,7 +595,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * whose data type is a fixed-size-list of floats.
   */
  column(column: string): VectorQuery {
-    this.doVectorCall((inner) => inner.column(column));
+    super.doCall((inner) => inner.column(column));
    return this;
  }

@@ -646,7 +616,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
  distanceType(
    distanceType: Required<IvfPqOptions>["distanceType"],
  ): VectorQuery {
-    this.doVectorCall((inner) => inner.distanceType(distanceType));
+    super.doCall((inner) => inner.distanceType(distanceType));
    return this;
  }

@@ -680,7 +650,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * distance between the query vector and the actual uncompressed vector.
   */
  refineFactor(refineFactor: number): VectorQuery {
-    this.doVectorCall((inner) => inner.refineFactor(refineFactor));
+    super.doCall((inner) => inner.refineFactor(refineFactor));
    return this;
  }

@@ -705,7 +675,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * factor can often help restore some of the results lost by post filtering.
   */
  postfilter(): VectorQuery {
-    this.doVectorCall((inner) => inner.postfilter());
+    super.doCall((inner) => inner.postfilter());
    return this;
  }

@@ -719,7 +689,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * calculate your recall to select an appropriate value for nprobes.
   */
  bypassVectorIndex(): VectorQuery {
-    this.doVectorCall((inner) => inner.bypassVectorIndex());
+    super.doCall((inner) => inner.bypassVectorIndex());
    return this;
  }

@@ -727,39 +697,43 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * Add a query vector to the search
   *
   * This method can be called multiple times to add multiple query vectors
-   * to the search. A column called `query_index` will be added to indicate the index
-   * of the query vector that produced the result. Flat searches share one table scan
-   * across the query vectors, avoiding the scan and memory amplification of running
-   * multiple queries concurrently. Indexed searches may still perform per-vector
-   * index work.
+   * to the search. If multiple query vectors are added, then they will be searched
+   * in parallel, and the results will be concatenated. A column called `query_index`
+   * will be added to indicate the index of the query vector that produced the result.
+   *
+   * Performance wise, this is equivalent to running multiple queries concurrently.
   */
  addQueryVector(vector: IntoVector): VectorQuery {
    if (vector instanceof Promise) {
-      // Observe the promise as soon as it is accepted. The existing native
-      // query may still be pending, and delaying observation until it resolves
-      // can otherwise surface a fast rejection as unhandled.
-      const settledVector = vector.then(
-        (value) => ({ status: "fulfilled" as const, value }),
-        (reason) => ({ status: "rejected" as const, reason }),
-      );
      const res = (async () => {
-        const inner = await this.getInner();
-        const outcome = await settledVector;
-        if (outcome.status === "rejected") {
-          throw outcome.reason;
+        try {
+          const v = await vector;
+          // biome-ignore lint/suspicious/noExplicitAny: we need to get the `inner`, but js has no package scoping
+          const value: any = this.addQueryVector(v);
+          const inner = value.inner as
+            | NativeVectorQuery
+            | Promise<NativeVectorQuery>;
+          return inner;
+        } catch (e) {
+          return Promise.reject(e);
        }
-        addQueryVectorToNative(inner, outcome.value);
-        return inner;
      })();
      return new VectorQuery(res);
    } else {
-      this.doVectorCall((inner) => addQueryVectorToNative(inner, vector));
+      super.doCall((inner) => {
+        const raw = Array.isArray(vector) ? null : extractVectorBuffer(vector);
+        if (raw) {
+          inner.addQueryVectorRaw(raw.data, raw.dtype);
+        } else {
+          inner.addQueryVector(Float32Array.from(vector as number[]));
+        }
+      });
      return this;
    }
  }

  rerank(reranker: Reranker): VectorQuery {
-    this.doVectorCall((inner) =>
+    super.doCall((inner) =>
      inner.rerank(async (args) => {
        const vecResults = await fromBufferToRecordBatch(args.vecResults);
        const ftsResults = await fromBufferToRecordBatch(args.ftsResults);
@@ -778,71 +752,6 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
  }
 }

-/**
- * Create a string query whose vector/FTS routing is resolved against the active
- * table schema when the query executes.
- *
- * @hidden
- */
-export function createAutoQuery(
-  table: NativeTable,
-  query: string,
-  columns: string[] | null,
-  getVector: (metadata: string) => Promise<Awaited<IntoVector>>,
-): AutoQuery {
-  type RouteSnapshot = {
-    table: NativeTable;
-    embeddingMetadata: string | undefined;
-  };
-  type CachedPreparation = {
-    metadata: string;
-    vector: Promise<Awaited<IntoVector>>;
-  };
-
-  let cachedPreparation: CachedPreparation | undefined;
-
-  const snapshotRoute = async (): Promise<RouteSnapshot> => {
-    const snapshot = await table.querySnapshot();
-    const schema = tableFromIPC(await snapshot.schema()).schema;
-    return {
-      table: snapshot,
-      embeddingMetadata: schema.metadata.get("embedding_functions"),
-    };
-  };
-
-  const createInner = async (): Promise<NativeQuery | NativeVectorQuery> => {
-    const route = await snapshotRoute();
-    if (route.embeddingMetadata === undefined) {
-      const inner = route.table.query();
-      inner.fullTextSearch({ query, columns });
-      return inner;
-    }
-
-    const metadata = route.embeddingMetadata;
-    if (cachedPreparation?.metadata !== metadata) {
-      cachedPreparation = {
-        metadata,
-        vector: Promise.resolve().then(() => getVector(metadata)),
-      };
-    }
-
-    const preparation = cachedPreparation;
-    let vector: Awaited<IntoVector>;
-    try {
-      vector = await preparation.vector;
-    } catch (error) {
-      if (cachedPreparation === preparation) {
-        cachedPreparation = undefined;
-      }
-      throw error;
-    }
-
-    return nearestToNative(route.table.query(), vector);
-  };
-
-  return new AutoQuery(createInner);
-}
-
 /**
 * A query that returns a subset of the rows in the table.
 *
@@ -927,6 +836,37 @@ export class Query extends StandardQueryBase<NativeQuery> {
    super(tbl.query());
  }

+  /** @hidden */
+  static autoSearch(
+    tbl: () => Promise<NativeTable>,
+    query: string,
+    vector: (tbl: NativeTable) => Promise<Awaited<IntoVector> | undefined>,
+    columns?: string[],
+  ): AutoQuery {
+    const nativeQuery = async () => {
+      const snapshot = await Promise.resolve(tbl());
+      const resolved = await vector(snapshot);
+      const inner = snapshot.query();
+      if (resolved === undefined) {
+        inner.fullTextSearch({
+          query,
+          columns: columns ?? null,
+        });
+        return inner;
+      }
+
+      const raw = Array.isArray(resolved)
+        ? null
+        : extractVectorBuffer(resolved);
+      if (raw) {
+        return inner.nearestToRaw(raw.data, raw.dtype);
+      }
+      return inner.nearestTo(Float32Array.from(resolved as number[]));
+    };
+
+    return new AutoQuery(nativeQuery);
+  }
+
  /**
   * Find the nearest vectors to the given query vector.
   *
@@ -965,19 +905,45 @@ export class Query extends StandardQueryBase<NativeQuery> {
   * a default `limit` of 10 will be used.  @see {@link Query#limit}
   */
  nearestTo(vector: IntoVector): VectorQuery {
-    const inner = this.inner;
-    if (inner instanceof Promise) {
-      const nativeQuery = inner.then(async (resolvedInner) =>
-        nearestToNative(resolvedInner, await vector),
-      );
+    const callNearestTo = (
+      inner: NativeQuery,
+      resolved: Float32Array | Float64Array | Uint8Array | number[],
+    ): NativeVectorQuery => {
+      const raw = Array.isArray(resolved)
+        ? null
+        : extractVectorBuffer(resolved);
+      if (raw) {
+        return inner.nearestToRaw(raw.data, raw.dtype);
+      }
+      return inner.nearestTo(Float32Array.from(resolved as number[]));
+    };
+
+    if (this.inner instanceof Promise) {
+      const nativeQuery = this.inner.then(async (inner) => {
+        const resolved = vector instanceof Promise ? await vector : vector;
+        return callNearestTo(inner, resolved);
+      });
      return new VectorQuery(nativeQuery);
    }
    if (vector instanceof Promise) {
-      return new VectorQuery(
-        vector.then((resolvedVector) => nearestToNative(inner, resolvedVector)),
-      );
+      const res = (async () => {
+        try {
+          const v = await vector;
+          // biome-ignore lint/suspicious/noExplicitAny: we need to get the `inner`, but js has no package scoping
+          const value: any = this.nearestTo(v);
+          const inner = value.inner as
+            | NativeVectorQuery
+            | Promise<NativeVectorQuery>;
+          return inner;
+        } catch (e) {
+          return Promise.reject(e);
+        }
+      })();
+      return new VectorQuery(res);
+    } else {
+      const vectorQuery = callNearestTo(this.inner, vector);
+      return new VectorQuery(vectorQuery);
    }
-    return new VectorQuery(nearestToNative(inner, vector));
  }

  nearestToText(query: string | FullTextQuery, columns?: string[]): Query {
@@ -94,24 +94,17 @@ export function sanitizeMetadata(
  if (metadataLike === undefined || metadataLike === null) {
    return undefined;
  }
-
-  let entries: IterableIterator<[unknown, unknown]>;
-  try {
-    entries = Map.prototype.entries.call(metadataLike);
-  } catch {
+  if (!(metadataLike instanceof Map)) {
    throw Error("Expected metadata, if present, to be a Map<string, string>");
  }
-
-  const metadata = new Map<string, string>();
-  for (const [key, value] of entries) {
-    if (typeof key !== "string" || typeof value !== "string") {
+  for (const item of metadataLike) {
+    if (typeof item[0] !== "string" || typeof item[1] !== "string") {
      throw Error(
        "Expected metadata, if present, to be a Map<string, string> but it had non-string keys or values",
      );
    }
-    metadata.set(key, value);
  }
-  return metadata;
+  return metadataLike as Map<string, string>;
 }

 export function sanitizeInt(typeLike: object) {
@@ -406,11 +406,10 @@ function matchingFields(fields: Field[], tree: FieldTree): Field[] {
          field.name,
          new Struct(matchingFields(struct.children, value)),
          field.nullable,
-          field.metadata,
        ),
      );
    } else {
-      matches.push(field);
+      matches.push(new Field(field.name, value as DataType, field.nullable));
    }
  }
  return matches;
@@ -48,7 +48,6 @@ import {
  Query,
  TakeQuery,
  VectorQuery,
-  createAutoQuery,
  instanceOfFullTextQuery,
 } from "./query";
 import { sanitizeType } from "./sanitize";
@@ -630,18 +629,6 @@ export abstract class Table {

  /**
   * Update per-field (column) metadata.
-   *
-   * The following keys are treated specially, by convention, and should be
-   * used when appropriate:
-   *
-   * - `lancedb:description`: for a human-readable description of a field.
-   * - `lancedb:tag:<name>`: for a user-defined key-value tag, where the suffix
-   *   names the tag category; e.g. `lancedb:tag:model: "clip"`.
-   * - `lancedb:logical-column`: for a column grouping; e.g. `feature_v1` and
-   *   `feature_v2` might be in the same logical column.
-   * - `lancedb:status`: for status options (`production`, `candidate`,
-   *   `deprecated`, `archived`) to designate the current life cycle state of
-   *   this column.
   * @param {FieldMetadataUpdate[]} updates One or more per-field updates. Each
   * update's metadata is merged into the field's existing metadata by default;
   * a value of `null` deletes that key, and `replace: true` swaps the whole map.
@@ -1190,29 +1177,33 @@ export class LocalTable extends Table {
      });
    }

-    if (queryType === "auto") {
-      if (instanceOfFullTextQuery(query)) {
-        return this.query().fullTextSearch(query, {
-          columns: ftsColumns,
-        });
-      }
+    if (queryType === "auto" && typeof query !== "string") {
+      return this.query().fullTextSearch(query, {
+        columns: ftsColumns,
+      });
+    }

-      const columns =
-        typeof ftsColumns === "string" ? [ftsColumns] : (ftsColumns ?? null);
-      return createAutoQuery(this.inner, query, columns, async (metadata) => {
-        const functions = await getRegistry().parseFunctions(
-          new Map([["embedding_functions", metadata]]),
-        );
+    if (queryType === "auto" && typeof query === "string") {
+      const vector = async (snapshot: _NativeTable) => {
+        const functions = await this.getEmbeddingFunctions(snapshot);
        // TODO: Support multiple embedding functions
        const embeddingFunc: EmbeddingFunctionConfig | undefined = functions
          .values()
          .next().value;
-        // The route only calls this callback when embedding metadata exists.
-        // parseFunctions either yields a provider or reports malformed metadata.
-        if (!embeddingFunc)
-          throw new Error("Invalid embedding function metadata");
+        if (embeddingFunc === undefined) {
+          return undefined;
+        }
        return await embeddingFunc.function.computeQueryEmbeddings(query);
-      });
+      };
+
+      const columns =
+        typeof ftsColumns === "string" ? [ftsColumns] : ftsColumns;
+      return Query.autoSearch(
+        () => this.inner.checkoutCurrent(),
+        query,
+        vector,
+        columns,
+      );
    }

    const queryPromise = this.getEmbeddingFunctions().then(
@@ -1567,8 +1558,7 @@ export interface FieldMetadataUpdate {
  path: string;
  /**
   * Metadata key/value pairs. Merged into the field's existing metadata by
-   * default; a value of `null` deletes that key. See
-   * {@link Table.updateFieldMetadata} for the conventional `lancedb:*` keys.
+   * default; a value of `null` deletes that key.
   */
  metadata: Record<string, string | null>;
  /** If true, replace the field's entire metadata map instead of merging. */
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.38.0",
+	"version": "0.38.0-beta.10",
 	"os": ["darwin"],
 	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-	"version": "0.38.0",
+	"version": "0.38.0-beta.10",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-gnu.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-musl",
-	"version": "0.38.0",
+	"version": "0.38.0-beta.10",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-musl.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-gnu",
-	"version": "0.38.0",
+	"version": "0.38.0-beta.10",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-gnu.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-musl",
-	"version": "0.38.0",
+	"version": "0.38.0-beta.10",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-musl.node",
@@ -1,6 +1,6 @@
 {
  "name": "@lancedb/lancedb-win32-arm64-msvc",
-  "version": "0.38.0",
+  "version": "0.38.0-beta.10",
  "os": [
    "win32"
  ],
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.38.0",
+	"version": "0.38.0-beta.10",
 	"os": ["win32"],
 	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",
@@ -11,7 +11,7 @@
    "ann"
  ],
  "private": false,
-  "version": "0.38.0",
+  "version": "0.38.0-beta.10",
  "main": "dist/index.js",
  "exports": {
    ".": "./dist/index.js",
@@ -67,7 +67,7 @@
    "timeout": "3m"
  },
  "engines": {
-    "node": ">= 22"
+    "node": ">= 18"
  },
  "packageManager": "pnpm@11.1.1",
  "cpu": ["x64", "arm64"],
@@ -101,7 +101,7 @@
    "openai": "4.29.2"
  },
  "peerDependencies": {
-    "@types/node": ">=22",
+    "@types/node": ">=18",
    "apache-arrow": ">=15.0.0 <=18.1.0"
  },
  "peerDependenciesMeta": {
@@ -664,11 +664,7 @@ impl JsFullTextQuery {
 }

 fn parse_fts_query(query: Object) -> napi::Result<FullTextSearchQuery> {
-    // `&JsFullTextQuery` recovers a native class reference through napi's borrow-tracked
-    // path, which is only usable from generated `#[napi]` argument conversion. This is a
-    // manual lookup on a nested `Object` property instead, so use `ClassInstance`, which
-    // unwraps the class without requiring a borrow scope.
-    if let Ok(Some(query)) = query.get::<ClassInstance<JsFullTextQuery>>("query") {
+    if let Ok(Some(query)) = query.get::<&JsFullTextQuery>("query") {
        Ok(FullTextSearchQuery::new_query(query.inner.clone()))
    } else if let Ok(Some(query_text)) = query.get::<String>("query") {
        let mut query_text = query_text;
@@ -278,13 +278,6 @@ impl Table {
        Ok(Query::new(self.inner_ref()?.query()))
    }

-    /// Return a read-only table handle pinned to the current query revision.
-    #[napi(catch_unwind)]
-    pub async fn query_snapshot(&self) -> napi::Result<Self> {
-        let snapshot = self.inner_ref()?.query_snapshot().await.default_error()?;
-        Ok(Self::new(snapshot))
-    }
-
    #[napi(catch_unwind)]
    pub fn take_offsets(&self, offsets: Vec<i64>) -> napi::Result<TakeQuery> {
        Ok(TakeQuery::new(
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-python"
-version = "0.38.0"
+version = "0.38.0-beta.10"
 publish = false
 edition.workspace = true
 description = "Python bindings for LanceDB"
@@ -6,7 +6,7 @@ import importlib.metadata
 import os
 from concurrent.futures import ThreadPoolExecutor
 from datetime import timedelta
-from typing import Dict, Optional, Union, Any, List, Iterable, TYPE_CHECKING
+from typing import Dict, Optional, Union, Any, List, Iterable

 __version__ = importlib.metadata.version("lancedb")

@@ -20,7 +20,7 @@ from .db import AsyncConnection, DBConnection, LanceDBConnection
 from .remote import ClientConfig
 from .remote.db import RemoteDBConnection
 from .expr import Expr, col, lit, func
-from .schema import blob, vector
+from .schema import blob, vector, BlobType
 from .job import AsyncJob, Job
 from .functions import (
    FunctionArtifactRequest as FunctionArtifactRequest,
@@ -49,19 +49,6 @@ from .namespace import (
 )


-if TYPE_CHECKING:
-    from lance.blob import BlobType as BlobType
-
-
-def __getattr__(name: str):
-    if name == "BlobType":
-        from .schema import BlobType
-
-        globals()["BlobType"] = BlobType
-        return BlobType
-    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
-
-
 def _check_s3_bucket_with_dots(
    uri: str, storage_options: Optional[Dict[str, str]]
 ) -> None:
@@ -12,7 +12,7 @@ from typing import TYPE_CHECKING, Optional, Union
 import pyarrow as pa

 from .expr import Expr
-from .schema import row_addressable_blob_v2_paths
+from .schema import blob_v2_column_paths
 from .types import BlobMode, QueryProjection, QueryProjectionSpec

 if TYPE_CHECKING:
@@ -119,7 +119,7 @@ def blob_v2_projection_sources(
    schema: pa.Schema,
    projection: QueryProjection,
 ) -> dict[str, str]:
-    blob_columns = row_addressable_blob_v2_paths(schema)
+    blob_columns = blob_v2_column_paths(schema)
    if not blob_columns:
        return {}
    columns = set(blob_columns)
@@ -140,9 +140,7 @@ def v2_projection_needs_row_id(
 ) -> bool:
    if with_row_id:
        return False
-    return projection_includes_blob_column(
-        projection, row_addressable_blob_v2_paths(schema)
-    )
+    return projection_includes_blob_column(projection, blob_v2_column_paths(schema))


 def blob_auto_row_id_for_scan(
@@ -272,8 +270,7 @@ def _iter_projection_pairs(
            if isinstance(expr, str):
                yield name, expr
            elif isinstance(expr, Expr):
-                source = expr._column_name()
-                yield name, source if source is not None else expr.to_sql()
+                yield name, expr.to_sql()
        return
    for column in projection:
        if isinstance(column, str):
@@ -283,8 +280,7 @@ def _iter_projection_pairs(
            if isinstance(expr, str):
                yield name, expr
            elif isinstance(expr, Expr):
-                source = expr._column_name()
-                yield name, source if source is not None else expr.to_sql()
+                yield name, expr.to_sql()


 def _set_blob_column(tbl: pa.Table, output_name: str, blobs: pa.Array) -> pa.Table:
@@ -87,7 +87,6 @@ class PyExpr:
    def contains(self, substr: "PyExpr") -> "PyExpr": ...
    def isin(self, values: List["PyExpr"]) -> "PyExpr": ...
    def cast(self, data_type: pa.DataType) -> "PyExpr": ...
-    def column_name(self) -> Optional[str]: ...
    def to_sql(self) -> str: ...

 def expr_col(name: str) -> PyExpr: ...
@@ -150,12 +149,9 @@ class Connection(object):
    def job(self, job_id: str) -> Job: ...
    async def create_function_async(self, request_json: str) -> Job: ...
    async def get_function(self, name: str, version: str) -> str: ...
-    async def drop_function(self, name: str, version: str) -> bool: ...
    async def list_jobs(self) -> List[JobInfo]: ...
    async def get_job(self, job_id: str) -> Optional[JobDescription]: ...
    async def cancel_job(self, job_id: str) -> bool: ...
-    async def pause_job(self, job_id: str) -> str: ...
-    async def resume_job(self, job_id: str) -> str: ...
    async def job_history(
        self, job_id: Optional[str] = None
    ) -> List[pa.RecordBatch]: ...
@@ -609,11 +605,9 @@ class FullTextQuery:
 class PyQueryRequest:
    limit: Optional[int]
    offset: Optional[int]
-    take_offsets: Optional[List[int]]
    filter: Optional[Union[str, bytes]]
    full_text_search: Optional[FullTextQuery]
    select: Optional[Union[str, List[str]]]
-    select_source_columns: Optional[Dict[str, str]]
    fast_search: Optional[bool]
    with_row_id: Optional[bool]
    use_lsm: Optional[bool]
@@ -712,16 +712,6 @@ class DBConnection(EnforceOverrides):
            "Function catalog operations are not supported for this connection type"
        )

-    def drop_function(self, name: str, *, version: str) -> bool:
-        """Drop one exact immutable Function version from the remote catalog.
-
-        Returns True when the version changed to Dropped and False for an
-        idempotent replay. Local connections raise NotImplementedError.
-        """
-        raise NotImplementedError(
-            "Function catalog operations are not supported for this connection type"
-        )
-
    def job(self, job_id: str) -> Job:
        """A [Job][lancedb.job.Job] handle for a server-side job by id.

@@ -753,26 +743,6 @@ class DBConnection(EnforceOverrides):
            "cancel_job is not supported for this connection type"
        )

-    def pause_job(self, job_id: str) -> str:
-        """Pause a server-side job by id.
-
-        The job's workers drain and it stays parked until resumed. Returns
-        "pausing", "already_paused", or "committing" -- a job finalizing its
-        results cannot be parked; retry shortly.
-        """
-        raise NotImplementedError("pause_job is not supported for this connection type")
-
-    def resume_job(self, job_id: str) -> str:
-        """Resume a paused server-side job by id.
-
-        Its workers pick their work back up from checkpoints. Returns
-        "resumed", "still_pausing" -- the pause's worker drain is not
-        confirmed yet; retry shortly -- or "not_paused".
-        """
-        raise NotImplementedError(
-            "resume_job is not supported for this connection type"
-        )
-
    def job_history(self, job_id: Optional[str] = None) -> List[pa.RecordBatch]:
        """The lifecycle event history of a server-side job, as Arrow batches.

@@ -1443,10 +1413,6 @@ class LanceDBConnection(DBConnection):
    def get_function(self, name: str, *, version: str) -> FunctionVersion:
        return LOOP.run(self._conn.get_function(name, version=version))

-    @override
-    def drop_function(self, name: str, *, version: str) -> bool:
-        return LOOP.run(self._conn.drop_function(name, version=version))
-
    @override
    def list_jobs(self) -> List[JobInfo]:
        """List server-side jobs across the database's tables."""
@@ -1470,22 +1436,6 @@ class LanceDBConnection(DBConnection):
        """
        return LOOP.run(self._conn.cancel_job(job_id))

-    @override
-    def pause_job(self, job_id: str) -> str:
-        """Pause a server-side job by id.
-
-        Returns "pausing", "already_paused", or "committing".
-        """
-        return LOOP.run(self._conn.pause_job(job_id))
-
-    @override
-    def resume_job(self, job_id: str) -> str:
-        """Resume a paused server-side job by id.
-
-        Returns "resumed", "still_pausing", or "not_paused".
-        """
-        return LOOP.run(self._conn.resume_job(job_id))
-
    @override
    def job_history(self, job_id: Optional[str] = None) -> List[pa.RecordBatch]:
        """The lifecycle event history of a server-side job, as Arrow batches.
@@ -2293,10 +2243,6 @@ class AsyncConnection(object):
        """Open one exact immutable Function version from the remote catalog."""
        return FunctionVersion.from_json(await self._inner.get_function(name, version))

-    async def drop_function(self, name: str, *, version: str) -> bool:
-        """Drop one exact immutable Function version from the remote catalog."""
-        return await self._inner.drop_function(name, version)
-
    async def list_jobs(self) -> List[JobInfo]:
        """List server-side jobs across the database's tables."""
        return await self._inner.list_jobs()
@@ -2317,23 +2263,6 @@ class AsyncConnection(object):
        """
        return await self._inner.cancel_job(job_id)

-    async def pause_job(self, job_id: str) -> str:
-        """Pause a server-side job by id.
-
-        The job's workers drain and it stays parked until resumed. Returns
-        "pausing", "already_paused", or "committing" -- a job finalizing its
-        results cannot be parked; retry shortly.
-        """
-        return await self._inner.pause_job(job_id)
-
-    async def resume_job(self, job_id: str) -> str:
-        """Resume a paused server-side job by id.
-
-        Its workers pick their work back up from checkpoints. Returns
-        "resumed", "still_pausing" -- retry shortly -- or "not_paused".
-        """
-        return await self._inner.resume_job(job_id)
-
    async def job_history(self, job_id: Optional[str] = None) -> List[pa.RecordBatch]:
        """The lifecycle event history of a server-side job, as Arrow batches.

@@ -249,10 +249,6 @@ class Expr:

    # ── utilities ────────────────────────────────────────────────────────────

-    def _column_name(self) -> str | None:
-        """Return the source name when this is a bare column expression."""
-        return self._inner.column_name()
-
    def to_sql(self) -> str:
        """Render the expression as a SQL string (useful for debugging)."""
        return self._inner.to_sql()
@@ -316,7 +312,7 @@ def func(name: str, *args: ExprLike) -> Expr:
    --------
    >>> from lancedb.expr import col, func
    >>> func("lower", col("name"))
-    Expr(lower(`name`))
+    Expr(lower(name))
    """
    inner_args = [_coerce(a)._inner for a in args]
    return Expr(expr_func(name, inner_args))
@@ -49,25 +49,11 @@ from pydantic import (
    model_validator,
 )

-from .schema import is_blob_v2_field as _is_blob_v2_field
-
 _Int32 = conint(strict=True, ge=-(2**31), le=2**31 - 1)
 _UInt32 = conint(strict=True, ge=0, le=2**32 - 1)
 _UInt64 = conint(strict=True, ge=0, le=2**64 - 1)


-def _validate_gpu_wire_marker(value: Any) -> bool:
-    if value is not True:
-        raise ValueError("runtime.gpu must be true")
-    return True
-
-
-def _normalize_gpu_marker(value: bool) -> Optional[bool]:
-    if not isinstance(value, bool):
-        raise ValueError("gpu must be a boolean")
-    return True if value else None
-
-
 class _FrozenDict(dict):
    def _immutable(self, *args, **kwargs):
        raise TypeError("remote canonical values are immutable")
@@ -236,7 +222,6 @@ class PythonEnvironmentSpec(_RemoteValue):

    kind: str
    packages: tuple[str, ...] = ()
-    channels: tuple[str, ...] = ()
    path: Optional[str] = None
    modules: tuple[str, ...] = ()
    image: Optional[str] = None
@@ -253,23 +238,6 @@ class PythonRuntimeSpec(_RemoteValue):
    python_version: Optional[str] = None
    environment: Optional[PythonEnvironmentSpec] = None
    env: Optional[Mapping[str, str]] = None
-    gpu: Optional[bool] = None
-
-    @model_validator(mode="before")
-    @classmethod
-    def _discard_unknown_runtime_payload(cls, value):
-        if isinstance(value, Mapping):
-            kind = value.get("kind")
-            if isinstance(kind, str) and kind not in {"python", "python_v2"}:
-                return {"kind": kind}
-        return value
-
-    @field_validator("gpu", mode="before")
-    @classmethod
-    def _validate_gpu_marker(cls, value):
-        if value is None:
-            return None
-        return _validate_gpu_wire_marker(value)

    @model_validator(mode="after")
    def _validate_runtime_kind(self):
@@ -278,28 +246,18 @@ class PythonRuntimeSpec(_RemoteValue):
                raise ValueError("python runtime requires python_version")
            if self.environment is None:
                raise ValueError("python runtime requires environment")
-            if self.gpu is not None:
-                raise ValueError("python runtime with gpu requires kind='python_v2'")
-        elif self.kind == "python_v2":
-            if self.python_version is None:
-                raise ValueError("python_v2 runtime requires python_version")
-            if self.environment is None:
-                raise ValueError("python_v2 runtime requires environment")
-            if self.gpu is None:
-                raise ValueError("python_v2 runtime requires gpu")
        else:
            object.__setattr__(self, "python_version", None)
            object.__setattr__(self, "environment", None)
            object.__setattr__(self, "env", None)
-            object.__setattr__(self, "gpu", None)
        return self


 class FunctionVersion(_RemoteValue):
    """An exact immutable Function version returned by Enterprise.

-    The GPU execution requirement is part of this identity. CPU and memory sizing,
-    priority, concurrency, and retry policy belong to the execution platform.
+    Scheduling resources, priority, concurrency, and retry policy belong to
+    the submitting Job and are not part of this identity.
    """

    name: str
@@ -520,7 +478,6 @@ class RefreshColumnResult(_RemoteValue):


 _FUNCTION_NAME = re.compile(r"^[A-Za-z_][A-Za-z0-9_.-]*$")
-_FUNCTION_BLOB_V2_TYPE = "blob_v2"


 _GRAMMAR_PRIMITIVES = (
@@ -537,7 +494,6 @@ _GRAMMAR_PRIMITIVES = (
    (pa.float32(), "float32"),
    (pa.float64(), "float64"),
    (pa.string(), "utf8"),
-    (pa.large_string(), "large_utf8"),
    (pa.binary(), "binary"),
    (pa.date32(), "date32"),
    (pa.date64(), "date64"),
@@ -545,177 +501,31 @@ _GRAMMAR_PRIMITIVES = (


 def _canonical_arrow_type(data_type: pa.DataType) -> str:
-    """The compact Function grammar, or canonical exact JSON for nested types."""
-    grammar = _grammar_arrow_type(data_type)
-    if grammar is not None:
-        return grammar
-    exact = _exact_arrow_type(data_type)
-    return json.dumps(exact, ensure_ascii=False, sort_keys=True, separators=(",", ":"))
-
-
-def _grammar_arrow_type(data_type: pa.DataType) -> Optional[str]:
+    """The server's V1 Function type grammar. Anything outside it is rejected
+    here rather than at registration."""
    for candidate, name in _GRAMMAR_PRIMITIVES:
        if data_type == candidate:
            return name
    if pa.types.is_list(data_type) or pa.types.is_large_list(data_type):
-        item = _grammar_list_item(data_type)
-        if item is None:
-            return None
        prefix = "list" if pa.types.is_list(data_type) else "large_list"
-        return f"{prefix}<{item}>"
+        return f"{prefix}<{_canonical_list_item(data_type)}>"
    if pa.types.is_fixed_size_list(data_type) and data_type.list_size > 0:
-        item = _grammar_list_item(data_type)
-        if item is not None:
-            return f"fixed_size_list<{item}, {data_type.list_size}>"
-    return None
+        return (
+            f"fixed_size_list<{_canonical_list_item(data_type)}, {data_type.list_size}>"
+        )
+    raise TypeError(f"unsupported Arrow type for Function signature: {data_type}")


-def _grammar_list_item(data_type: pa.DataType) -> Optional[str]:
+def _canonical_list_item(data_type: pa.DataType) -> str:
    """The grammar names only the item type; it always means a non-nullable
-    child called `item`, so other child properties require exact JSON."""
+    child called `item`, so any other child metadata cannot be represented."""
    child = data_type.value_field
    if child.name != "item" or child.nullable or child.metadata:
-        return None
-    return _grammar_arrow_type(child.type)
-
-
-def _validate_exact_arrow_field(field: pa.Field) -> None:
-    if not field.name:
        raise TypeError(
-            "unsupported Arrow type for Function signature: field names "
-            "must not be empty"
+            "unsupported Arrow type for Function signature: list items must be a "
+            f"non-nullable field named 'item', got {child}"
        )
-    if _is_blob_v2_field(field):
-        if not _has_supported_blob_v2_layout(field):
-            raise TypeError(
-                "unsupported Arrow type for Function signature: lance.blob.v2 "
-                f"requires a supported Blob storage layout, got {field}"
-            )
-    elif field.metadata:
-        raise TypeError(
-            "unsupported Arrow type for Function signature: field metadata "
-            f"is not supported, got {field}"
-        )
-
-
-def _has_supported_blob_v2_layout(field: pa.Field) -> bool:
-    data_type = field.type
-    if isinstance(data_type, pa.ExtensionType):
-        data_type = data_type.storage_type
-    if not pa.types.is_struct(data_type):
-        return False
-
-    fields = tuple(data_type)
-
-    def matches(spec, compare_nullable) -> bool:
-        return len(fields) == len(spec) and all(
-            actual.name == name
-            and actual.type == expected_type
-            and (not check_nullable or actual.nullable == nullable)
-            for actual, (name, expected_type, nullable), check_nullable in zip(
-                fields, spec, compare_nullable
-            )
-        )
-
-    logical_minimal = (
-        ("data", pa.large_binary(), True),
-        ("uri", pa.utf8(), True),
-    )
-    logical_full = logical_minimal + (
-        ("position", pa.uint64(), True),
-        ("size", pa.uint64(), True),
-    )
-    prepared = (
-        ("kind", pa.uint8(), True),
-        ("data", pa.large_binary(), True),
-        ("uri", pa.utf8(), True),
-        ("blob_id", pa.uint32(), True),
-        ("blob_size", pa.uint64(), True),
-        ("position", pa.uint64(), True),
-    )
-    descriptor = (
-        ("kind", pa.uint8(), False),
-        ("position", pa.uint64(), False),
-        ("size", pa.uint64(), False),
-        ("blob_id", pa.uint32(), False),
-        ("blob_uri", pa.utf8(), False),
-    )
-    return (
-        matches(logical_minimal, (True, True))
-        or matches(logical_full, (True, True, False, False))
-        or matches(prepared, (True,) * len(prepared))
-        or matches(descriptor, (False,) * len(descriptor))
-    )
-
-
-def _canonical_arrow_field(field: pa.Field) -> str:
-    _validate_exact_arrow_field(field)
-    if _is_blob_v2_field(field):
-        return _FUNCTION_BLOB_V2_TYPE
-    return _canonical_arrow_type(field.type)
-
-
-def _exact_arrow_field(field: pa.Field) -> dict[str, Any]:
-    _validate_exact_arrow_field(field)
-    if _is_blob_v2_field(field):
-        raise TypeError(
-            "unsupported Arrow type for Function signature: nested Blob v2 "
-            "fields are not supported; declare Blob parameters or named result "
-            "fields directly"
-        )
-    value = {
-        "name": field.name,
-        "nullable": field.nullable,
-        "type": _exact_arrow_type(field.type),
-    }
-    return value
-
-
-def _exact_arrow_type(data_type: pa.DataType) -> dict[str, Any]:
-    for candidate, name in _GRAMMAR_PRIMITIVES:
-        if data_type == candidate:
-            return {"type": name}
-    if pa.types.is_struct(data_type):
-        fields = list(data_type)
-        names = [field.name for field in fields]
-        if not fields or len(set(names)) != len(names):
-            raise TypeError(
-                "unsupported Arrow type for Function signature: structs must have "
-                "non-empty, uniquely named fields"
-            )
-        return {
-            "type": "struct",
-            "fields": [_exact_arrow_field(field) for field in fields],
-        }
-    if (
-        pa.types.is_list(data_type)
-        or pa.types.is_large_list(data_type)
-        or pa.types.is_fixed_size_list(data_type)
-    ):
-        if pa.types.is_fixed_size_list(data_type):
-            if data_type.value_field.name != "item":
-                raise TypeError(
-                    "unsupported Arrow type for Function signature: fixed-size list "
-                    "items must be named 'item'"
-                )
-            if data_type.list_size <= 0:
-                raise TypeError(
-                    f"unsupported Arrow type for Function signature: {data_type}"
-                )
-        value: dict[str, Any] = {
-            "type": (
-                "list"
-                if pa.types.is_list(data_type)
-                else "large_list"
-                if pa.types.is_large_list(data_type)
-                else "fixed_size_list"
-            ),
-            "fields": [_exact_arrow_field(data_type.value_field)],
-        }
-        if pa.types.is_fixed_size_list(data_type):
-            value["length"] = data_type.list_size
-        return value
-    raise TypeError(f"unsupported Arrow type for Function signature: {data_type}")
+    return _canonical_arrow_type(child.type)


 def _list_of(item: pa.DataType) -> pa.DataType:
@@ -789,15 +599,8 @@ def _callable_parameters(function: Callable[..., Any]) -> tuple[inspect.Paramete

 def _function_output(output: pa.DataType | pa.Field | pa.Schema) -> FunctionOutput:
    if isinstance(output, pa.Schema):
-        if output.metadata:
-            raise TypeError("Function output schema metadata is not supported")
        fields = tuple(output)
-    elif (
-        isinstance(output, pa.Field)
-        and not _is_blob_v2_field(output)
-        and pa.types.is_struct(output.type)
-    ):
-        _validate_exact_arrow_field(output)
+    elif isinstance(output, pa.Field) and pa.types.is_struct(output.type):
        if output.nullable:
            raise ValueError("Function output must be non-nullable")
        fields = tuple(output.type)
@@ -813,12 +616,11 @@ def _function_output(output: pa.DataType | pa.Field | pa.Schema) -> FunctionOutp
            raise TypeError(
                "output_schema must be a PyArrow DataType, Field, or Schema"
            )
-        _validate_exact_arrow_field(field)
        if field.nullable:
            raise ValueError("Function output must be non-nullable")
        return FunctionOutput(
            kind="scalar",
-            arrow_type=_canonical_arrow_field(field),
+            arrow_type=_canonical_arrow_type(field.type),
            nullable=False,
        )

@@ -826,8 +628,6 @@ def _function_output(output: pa.DataType | pa.Field | pa.Schema) -> FunctionOutp
        raise ValueError("named-struct Function output must contain at least one field")
    if any(field.nullable for field in fields):
        raise ValueError("Function output fields must be non-nullable")
-    for field in fields:
-        _validate_exact_arrow_field(field)
    names = [field.name for field in fields]
    if len(set(names)) != len(names):
        raise ValueError("Function output field names must be unique")
@@ -836,7 +636,7 @@ def _function_output(output: pa.DataType | pa.Field | pa.Schema) -> FunctionOutp
        fields=tuple(
            FunctionResultField(
                name=field.name,
-                arrow_type=_canonical_arrow_field(field),
+                arrow_type=_canonical_arrow_type(field.type),
                nullable=False,
            )
            for field in fields
@@ -856,10 +656,6 @@ def _infer_signature(
    if input_schema is not None:
        if not isinstance(input_schema, pa.Schema):
            raise TypeError("input_schema must be a PyArrow Schema")
-        if input_schema.metadata:
-            raise TypeError("Function input schema metadata is not supported")
-        for field in input_schema:
-            _validate_exact_arrow_field(field)
        expected = tuple(parameter.name for parameter in parameters)
        actual = tuple(input_schema.names)
        if actual != expected:
@@ -870,7 +666,7 @@ def _infer_signature(
        inputs = tuple(
            FunctionParameter(
                name=field.name,
-                arrow_type=_canonical_arrow_field(field),
+                arrow_type=_canonical_arrow_type(field.type),
                nullable=field.nullable,
            )
            for field in input_schema
@@ -893,9 +689,7 @@ def _infer_signature(
        inputs.append(
            FunctionParameter(
                name=parameter.name,
-                arrow_type=_canonical_arrow_field(
-                    pa.field(parameter.name, data_type, nullable=nullable)
-                ),
+                arrow_type=_canonical_arrow_type(data_type),
                nullable=nullable,
            )
        )
@@ -1115,26 +909,13 @@ class UdfDefinition:
        pip: tuple[str, ...],
        env: Mapping[str, str],
        python_version: Optional[str],
-        gpu: bool = False,
-        conda: tuple[str, ...] = (),
-        conda_channels: tuple[str, ...] = (),
    ):
        function_name = name or function.__name__
        if not _FUNCTION_NAME.fullmatch(function_name):
            raise ValueError(f"invalid Function name: {function_name!r}")
-        if pip and conda:
-            raise ValueError("a Function environment is pip or conda, not both")
-        if conda_channels and not conda:
-            raise ValueError("conda_channels requires conda packages")
-        packages = tuple(sorted(set(conda if conda else pip)))
+        packages = tuple(sorted(set(pip)))
        if any(not package or package != package.strip() for package in packages):
-            raise ValueError("package requirements must be non-empty and trimmed")
-        if conda:
-            environment_spec = PythonEnvironmentSpec(
-                kind="conda", packages=packages, channels=tuple(conda_channels)
-            )
-        else:
-            environment_spec = PythonEnvironmentSpec(kind="pip", packages=packages)
+            raise ValueError("pip requirements must be non-empty and trimmed")
        environment = dict(env)
        if any(
            not isinstance(key, str) or not isinstance(value, str)
@@ -1144,14 +925,12 @@ class UdfDefinition:
        signature = _infer_signature(function, input_schema, output_schema)
        source = _package_source(function)
        digest = f"sha256:{hashlib.sha256(source).hexdigest()}"
-        gpu_marker = _normalize_gpu_marker(gpu)
        runtime = PythonRuntimeSpec(
-            kind="python_v2" if gpu_marker is not None else "python",
+            kind="python",
            python_version=python_version
            or f"{sys.version_info.major}.{sys.version_info.minor}",
-            environment=environment_spec,
+            environment=PythonEnvironmentSpec(kind="pip", packages=packages),
            env=environment,
-            gpu=gpu_marker,
        )
        self._function = function
        self._request = FunctionRegistrationRequest(
@@ -1197,9 +976,6 @@ def udf(
    pip: tuple[str, ...] | list[str] = (),
    env: Optional[Mapping[str, str]] = None,
    python_version: Optional[str] = None,
-    gpu: bool = False,
-    conda: tuple[str, ...] | list[str] = (),
-    conda_channels: tuple[str, ...] | list[str] = (),
 ) -> Callable[[Callable[..., Any]], UdfDefinition]: ...


@@ -1212,9 +988,6 @@ def udf(
    pip: tuple[str, ...] | list[str] = (),
    env: Optional[Mapping[str, str]] = None,
    python_version: Optional[str] = None,
-    gpu: bool = False,
-    conda: tuple[str, ...] | list[str] = (),
-    conda_channels: tuple[str, ...] | list[str] = (),
 ):
    """Prepare a scalar Python callable for remote Function registration.

@@ -1237,18 +1010,10 @@ def udf(
        provided together with ``input_schema``.
    pip : sequence of str, optional
        Pip requirements for the remote environment.
-    conda : sequence of str, optional
-        Conda packages for the remote environment, instead of ``pip``.
-    conda_channels : sequence of str, optional
-        Conda channels in priority order; requires ``conda``.
    env : mapping of str to str, optional
        Environment variables included in the Function definition.
    python_version : str, optional
        Remote Python major/minor version. Defaults to the client version.
-    gpu : bool, default False
-        Whether every remote execution requires a GPU. The execution platform
-        selects one compatible GPU for each worker. The requirement is part of
-        the immutable Function version.

    The packaged artifact is a snapshot: the function source plus exactly
    the module-level names it references (modules as imports, importable
@@ -1273,11 +1038,6 @@ def udf(
    ...     return value * 2
    >>> score(1.5)
    3.0
-    >>> @udf(pip=["cupy-cuda12x"], gpu=True)
-    ... def gpu_score(value: int) -> int:
-    ...     return value * 2
-    >>> gpu_score.registration_request.runtime.gpu
-    True
    """

    def decorate(target: Callable[..., Any]) -> UdfDefinition:
@@ -1289,9 +1049,6 @@ def udf(
            pip=tuple(pip),
            env={} if env is None else env,
            python_version=python_version,
-            gpu=gpu,
-            conda=tuple(conda),
-            conda_channels=tuple(conda_channels),
        )

    if function is None:
@@ -7,7 +7,6 @@ from typing import List, Literal, Optional
 from ._lancedb import (
    IndexConfig,
 )
-from .query import DocumentGranularity
 from .types import BaseTokenizerType

 lang_mapping = {
@@ -122,11 +121,6 @@ class FTS:

    >>> config = FTS(block_size=256)

-    Create an index that treats each deepest-list element as one document:
-
-    >>> from lancedb.query import DocumentGranularity
-    >>> config = FTS(document_granularity=DocumentGranularity.LIST_ELEMENT)
-
    Attributes
    ----------
    with_position : bool, default False
@@ -178,11 +172,6 @@ class FTS:
        roughly half of the available CPU cores. The effective value is
        limited by the available compute capacity. This build-only setting is
        not persisted with the index and does not apply to remote tables.
-    document_granularity : DocumentGranularity, default ROW
-        ``ROW`` treats the selected text in one table row as one document.
-        ``LIST_ELEMENT`` treats each element of the deepest list on the indexed
-        field path as one document and returns its physical coordinates in
-        ``_doc_index`` for matching queries.

    Notes
    -----
@@ -207,7 +196,6 @@ class FTS:
    custom_stop_words: Optional[List[str]] = None
    memory_limit: Optional[int] = None
    num_workers: Optional[int] = None
-    document_granularity: DocumentGranularity = DocumentGranularity.ROW


@dataclass
@@ -109,7 +109,6 @@ def _query_is_plain_scan(query: Query) -> bool:
    return (
        query.vector is None
        and query.full_text_query is None
-        and query.take_offsets is None
        and not query.postfilter
        and not query.order_by
    )
@@ -168,12 +167,6 @@ def _projection_to_scanner_kwargs(columns: QueryProjection) -> Dict[str, Any]:
    return {"columns": projection}


-def _query_request_projection(req: "PyQueryRequest") -> QueryProjection:
-    if req.select_source_columns is not None:
-        return req.select_source_columns
-    return req.select
-
-
 def _scanner_kwargs_for_query(
    query: Query,
    blob_mode: BlobMode,
@@ -382,13 +375,6 @@ class FullTextOperator(str, Enum):
    OR = "OR"


-class DocumentGranularity(str, Enum):
-    """The unit treated as one full-text-search document."""
-
-    ROW = "row"
-    LIST_ELEMENT = "list_element"
-
-
 class Occur(str, Enum):
    SHOULD = "SHOULD"
    MUST = "MUST"
@@ -492,10 +478,6 @@ class MatchQuery(FullTextQuery):
    prefix_length : int, optional
        The number of beginning characters being unchanged for fuzzy matching.
        This is useful to achieve prefix matching.
-    document_granularity : DocumentGranularity, optional
-        Explicitly select row or deepest-list-element documents. If omitted,
-        the indexed granularity is inferred. When both granularities are indexed
-        for the field, this must be specified. With no index, row granularity is used.
    """

    query: str
@@ -505,9 +487,6 @@ class MatchQuery(FullTextQuery):
    max_expansions: int = pydantic.Field(50, kw_only=True)
    operator: FullTextOperator = pydantic.Field(FullTextOperator.OR, kw_only=True)
    prefix_length: int = pydantic.Field(0, kw_only=True)
-    document_granularity: Optional[DocumentGranularity] = pydantic.Field(
-        None, kw_only=True
-    )

    def query_type(self) -> FullTextQueryType:
        return FullTextQueryType.MATCH
@@ -524,20 +503,11 @@ class PhraseQuery(FullTextQuery):
        The query string to match against.
    column : str
        The name of the column to match against.
-    slop : int, default 0
-        The maximum number of intervening positions permitted in the phrase.
-    document_granularity : DocumentGranularity, optional
-        Explicitly select row or deepest-list-element documents. If omitted,
-        the indexed granularity is inferred. When both granularities are indexed
-        for the field, this must be specified. With no index, row granularity is used.
    """

    query: str
    column: str
    slop: int = pydantic.Field(0, kw_only=True)
-    document_granularity: Optional[DocumentGranularity] = pydantic.Field(
-        None, kw_only=True
-    )

    def query_type(self) -> FullTextQueryType:
        return FullTextQueryType.MATCH_PHRASE
@@ -805,10 +775,6 @@ class Query(pydantic.BaseModel):
    # offset to start fetching results from
    offset: Optional[int] = None

-    # Dataset offsets whose duplicate occurrences must be restored after lookup.
-    # This is populated when a take query is converted to this serializable form.
-    take_offsets: Optional[List[int]] = None
-
    # if true, will only search the indexed data
    fast_search: Optional[bool] = None

@@ -830,7 +796,6 @@ class Query(pydantic.BaseModel):
        query = cls()
        query.limit = req.limit
        query.offset = req.offset
-        query.take_offsets = req.take_offsets
        query.filter = req.filter
        query.full_text_query = req.full_text_search
        query.columns = req.select
@@ -2811,16 +2776,15 @@ class AsyncQueryBase(object):

        req = self._inner.to_query_request()
        schema = await self._table.schema()
-        projection = _query_request_projection(req)
        self._blob_auto_row_id = blob_auto_row_id_for_scan(
            schema,
-            projection,
+            req.select,
            with_row_id=self._with_row_id,
        )
        if not self._blob_auto_row_id:
            self._blob_paths = ()
            return
-        self._blob_paths = tuple(blob_v2_projection_sources(schema, projection).keys())
+        self._blob_paths = tuple(blob_v2_projection_sources(schema, req.select).keys())
        self._inner.with_row_id()

    def select(self, columns: Union[List[str], dict[str, str]]) -> Self:
@@ -3414,10 +3378,9 @@ class AsyncQuery(AsyncStandardQuery):
        pass in multiple vectors. When multiple vectors are passed in, if the vector
        column is with multivector type, then the vectors will be treated as a single
        query. Or the vectors will be treated as multiple queries, this can be useful
-        if you want to find the nearest vectors to multiple query vectors. Flat
-        searches share one table scan across the query vectors, avoiding the scan
-        and memory amplification of making multiple queries concurrently. If
-        multiple vectors are passed in then
+        if you want to find the nearest vectors to multiple query vectors.
+        This is not expected to be faster than making multiple queries concurrently;
+        it is just a convenience method. If multiple vectors are passed in then
        an additional column `query_index` will be added to the results. This column
        will contain the index of the query vector that the result is nearest to.
        """
@@ -3546,8 +3509,8 @@ class AsyncFTSQuery(AsyncStandardQuery):

        Typically, a single vector is passed in as the query. However, you can also
        pass in multiple vectors.  This can be useful if you want to find the nearest
-        vectors to multiple query vectors. Flat searches share one table scan across
-        the query vectors instead of issuing concurrent full scans.
+        vectors to multiple query vectors. This is not expected to be faster than
+        making multiple queries concurrently; it is just a convenience method.
        If multiple vectors are passed in then an additional column `query_index`
        will be added to the results.  This column will contain the index of the
        query vector that the result is nearest to.
@@ -3907,15 +3870,14 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
        blob_paths: tuple[str, ...] = ()
        if self._table is not None:
            schema = await self._table.schema()
-            projection = _query_request_projection(req)
            blob_auto_row_id = blob_auto_row_id_for_scan(
                schema,
-                projection,
+                req.select,
                with_row_id=self._with_row_id,
            )
            if blob_auto_row_id:
                blob_paths = tuple(
-                    blob_v2_projection_sources(schema, projection).keys()
+                    blob_v2_projection_sources(schema, req.select).keys()
                )
        self._blob_auto_row_id = blob_auto_row_id
        self._blob_paths = blob_paths
@@ -749,10 +749,6 @@ class RemoteDBConnection(DBConnection):
    def get_function(self, name: str, *, version: str) -> FunctionVersion:
        return LOOP.run(self._conn.get_function(name, version=version))

-    @override
-    def drop_function(self, name: str, *, version: str) -> bool:
-        return LOOP.run(self._conn.drop_function(name, version=version))
-
    @override
    def list_jobs(self) -> List["JobInfo"]:
        """List server-side jobs across the database's tables."""
@@ -776,22 +772,6 @@ class RemoteDBConnection(DBConnection):
        """
        return LOOP.run(self._conn.cancel_job(job_id))

-    @override
-    def pause_job(self, job_id: str) -> str:
-        """Pause a server-side job by id.
-
-        Returns "pausing", "already_paused", or "committing".
-        """
-        return LOOP.run(self._conn.pause_job(job_id))
-
-    @override
-    def resume_job(self, job_id: str) -> str:
-        """Resume a paused server-side job by id.
-
-        Returns "resumed", "still_pausing", or "not_paused".
-        """
-        return LOOP.run(self._conn.resume_job(job_id))
-
    @override
    def job_history(self, job_id: Optional[str] = None) -> List[pa.RecordBatch]:
        """The lifecycle event history of a server-side job, as Arrow batches.
@@ -36,7 +36,6 @@ from lancedb._lancedb import (
    UpdateResult,
 )
 from lancedb.embeddings.base import EmbeddingFunctionConfig
-from lancedb.expr import Expr
 from lancedb.index import (
    FTS,
    BTree,
@@ -62,20 +61,11 @@ from lancedb.table import _normalize_progress

 from ..query import (
    AnalyzePlanDistributedMetrics,
-    DocumentGranularity,
    LanceQueryBuilder,
    LanceTakeQueryBuilder,
    LanceVectorQueryBuilder,
 )
-from ..table import (
-    AsyncTable,
-    BlobMode,
-    Branches,
-    IndexStatistics,
-    Query,
-    Table,
-    Tags,
-)
+from ..table import AsyncTable, BlobMode, Branches, IndexStatistics, Query, Table, Tags
 from ..types import BaseTokenizerType


@@ -359,7 +349,6 @@ class RemoteTable(Table):
        ngram_max_length: int = 3,
        prefix_only: bool = False,
        block_size: int = 128,
-        document_granularity: DocumentGranularity = DocumentGranularity.ROW,
        name: Optional[str] = None,
    ):
        """Create a full-text search index on a column.
@@ -382,7 +371,6 @@ class RemoteTable(Table):
            ngram_max_length=ngram_max_length,
            prefix_only=prefix_only,
            block_size=block_size,
-            document_granularity=document_granularity,
        )
        LOOP.run(
            self._table.create_index(
@@ -872,7 +860,7 @@ class RemoteTable(Table):

    def update(
        self,
-        where: Optional[Union[str, Expr]] = None,
+        where: Optional[str] = None,
        values: Optional[dict] = None,
        *,
        values_sql: Optional[Dict[str, str]] = None,
@@ -883,11 +871,9 @@ class RemoteTable(Table):

        Parameters
        ----------
-        where: str or [Expr][lancedb.expr.Expr], optional
-            The filter condition. Can be a SQL string or a type-safe
-            [Expr][lancedb.expr.Expr] built with [col][lancedb.expr.col] and
-            [lit][lancedb.expr.lit]. The filter must not be empty, or it will
-            error.
+        where: str, optional
+            The SQL where clause to use when updating rows. For example, 'x = 2'
+            or 'x IN (1, 2, 3)'. The filter must not be empty, or it will error.
        values: dict, optional
            The values to update. The keys are the column names and the values
            are the values to set.
@@ -4,34 +4,30 @@

 """Schema helpers for Lance blob columns."""

-import importlib
-from typing import TYPE_CHECKING
-
 import pyarrow as pa
-import pyarrow.ipc
-
-if TYPE_CHECKING:
-    from lance.blob import BlobType as BlobType

 _BLOB_EXTENSION_NAME = "lance.blob.v2"
 _BLOB_V1_KEY = "lance-encoding:blob"
 _ARROW_EXT_NAME_KEY = "ARROW:extension:name"
-_BLOB_V2_STORAGE_TYPE = pa.struct(
-    [
-        pa.field("data", pa.large_binary(), nullable=True),
-        pa.field("uri", pa.utf8(), nullable=True),
-        pa.field("position", pa.uint64(), nullable=True),
-        pa.field("size", pa.uint64(), nullable=True),
-    ]
-)
-_resolved_blob_type = None


-class _FallbackBlobType(pa.ExtensionType):
-    """lance.blob.v2 extension type used when pylance is not installed."""
+class BlobType(pa.ExtensionType):
+    """PyArrow extension type for a Lance blob v2 column.
+
+    Queries return descriptors; call :meth:`~lancedb.table.Table.fetch_blob_files`
+    for lazy reads or :meth:`~lancedb.table.Table.fetch_blobs` for eager bytes.
+    """

    def __init__(self) -> None:
-        pa.ExtensionType.__init__(self, _BLOB_V2_STORAGE_TYPE, _BLOB_EXTENSION_NAME)
+        storage_type = pa.struct(
+            [
+                pa.field("data", pa.large_binary(), nullable=True),
+                pa.field("uri", pa.utf8(), nullable=True),
+                pa.field("position", pa.uint64(), nullable=True),
+                pa.field("size", pa.uint64(), nullable=True),
+            ]
+        )
+        super().__init__(storage_type, _BLOB_EXTENSION_NAME)

    def __arrow_ext_serialize__(self) -> bytes:
        return b""
@@ -39,16 +35,23 @@ class _FallbackBlobType(pa.ExtensionType):
    @classmethod
    def __arrow_ext_deserialize__(
        cls, storage_type: pa.DataType, serialized: bytes
-    ) -> "_FallbackBlobType":
+    ) -> "BlobType":
        return cls()

    def __reduce__(self):
+        # Ensure pickle round-trips on older pyarrow (apache/arrow#35599).
        return type(self).__arrow_ext_deserialize__, (
            self.storage_type,
            self.__arrow_ext_serialize__(),
        )


+try:
+    pa.register_extension_type(BlobType())  # type: ignore[arg-type]
+except pa.ArrowKeyError:
+    pass
+
+
 def _metadata_value(metadata: dict, key: str):
    return metadata.get(key.encode()) or metadata.get(key)

@@ -89,105 +92,43 @@ def is_blob_like_field(field: pa.Field) -> bool:
    return is_blob_v2_field(field) or _metadata_marks_legacy_blob(field.metadata or {})


-def _collect_blob_paths(schema: pa.Schema, is_blob) -> list[tuple[str, bool]]:
-    """Walk the schema and return (path, has_list_ancestor) for each blob field."""
-    paths: list[tuple[str, bool]] = []
+def _collect_blob_paths(schema: pa.Schema, is_blob) -> list[str]:
+    paths: list[str] = []

-    def walk(fields, prefix: str, has_list_ancestor: bool) -> None:
+    def walk(fields, prefix: str) -> None:
        for field in fields:
            path = f"{prefix}.{field.name}" if prefix else field.name
            if is_blob(field):
-                paths.append((path, has_list_ancestor))
+                paths.append(path)
            elif pa.types.is_struct(field.type):
-                walk(field.type, path, has_list_ancestor)
+                walk(field.type, path)
            elif (
                pa.types.is_list(field.type)
                or pa.types.is_large_list(field.type)
                or pa.types.is_fixed_size_list(field.type)
            ):
-                walk([field.type.value_field], path, True)
+                walk([field.type.value_field], path)

-    walk(schema, "", False)
+    walk(schema, "")
    return paths


 def blob_column_paths(schema: pa.Schema) -> list[str]:
    """Dotted paths of blob-like columns (v2 extension or legacy metadata)."""
-    return [path for path, _ in _collect_blob_paths(schema, is_blob_like_field)]
+    return _collect_blob_paths(schema, is_blob_like_field)


 def blob_v2_column_paths(schema: pa.Schema) -> list[str]:
-    return [path for path, _ in _collect_blob_paths(schema, is_blob_v2_field)]
-
-
-def row_addressable_blob_v2_paths(schema: pa.Schema) -> list[str]:
-    """Blob v2 paths with one blob addressable by table row id.
-
-    ``fetch_blobs`` and the descriptor row-id ride-along address one blob per
-    row, so a blob inside a list container has no row-id slot and no fetch
-    path. Those columns still store and query as raw descriptors.
-    """
-    return [
-        path
-        for path, has_list_ancestor in _collect_blob_paths(schema, is_blob_v2_field)
-        if not has_list_ancestor
-    ]
+    return _collect_blob_paths(schema, is_blob_v2_field)


 def schema_has_blob_field(schema: pa.Schema) -> bool:
    return bool(blob_column_paths(schema))


-def _deserialize_registered_type(extension_type: pa.ExtensionType) -> pa.DataType:
-    """Return the type Arrow reconstructs for this extension name."""
-    schema = pa.schema([pa.field("value", extension_type)])
-    restored = pa.ipc.read_schema(schema.serialize())
-    return restored.field("value").type
-
-
-def _resolve_blob_type():
-    """Return the BlobType class this process should use.
-
-    pylance's class when it owns the lance.blob.v2 registry entry,
-    otherwise LanceDB's fallback. A different registered class is an error.
-    """
-    global _resolved_blob_type
-    if _resolved_blob_type is not None:
-        return _resolved_blob_type
-    try:
-        blob_module = importlib.import_module("lance.blob")
-    except ModuleNotFoundError as err:
-        if err.name not in ("lance", "lance.blob"):
-            raise
-    else:
-        blob_type = getattr(blob_module, "BlobType", None)
-        if blob_type is not None:
-            registered_type = _deserialize_registered_type(blob_type())
-            if type(registered_type) is not blob_type:
-                registered_cls = type(registered_type)
-                raise ValueError(
-                    "lance.blob.v2 is already registered by "
-                    f"{registered_cls.__module__}.{registered_cls.__qualname__}"
-                )
-            _resolved_blob_type = blob_type
-            return blob_type
-    try:
-        pa.register_extension_type(_FallbackBlobType())  # type: ignore[arg-type]
-    except pa.ArrowKeyError as err:
-        raise ValueError(
-            "lance.blob.v2 is already registered by another extension class"
-        ) from err
-    _resolved_blob_type = _FallbackBlobType
-    return _resolved_blob_type
-
-
 def blob(name: str, nullable: bool = True) -> pa.Field:
-    """Create a Lance blob v2 column field.
-
-    When pylance is installed this is ``lance.blob.BlobType``.
-    """
-    blob_type = _resolve_blob_type()
-    return pa.field(name, blob_type(), nullable=nullable)
+    """Create a Lance blob v2 column field."""
+    return pa.field(name, BlobType(), nullable=nullable)


 def vector(dimension: int, value_type: pa.DataType = pa.float32()) -> pa.DataType:
@@ -214,11 +155,3 @@ def vector(dimension: int, value_type: pa.DataType = pa.float32()) -> pa.DataTyp
    ... ])
    """
    return pa.list_(value_type, dimension)
-
-
-def __getattr__(name: str):
-    if name == "BlobType":
-        blob_type = _resolve_blob_type()
-        globals()["BlobType"] = blob_type
-        return blob_type
-    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
@@ -85,7 +85,6 @@ from .query import (
    AsyncQuery,
    AsyncTakeQuery,
    AsyncVectorQuery,
-    DocumentGranularity,
    FullTextQuery,
    LanceEmptyQueryBuilder,
    LanceFtsQueryBuilder,
@@ -104,12 +103,7 @@ from .util import (
    value_to_sql,
 )
 from .index import lang_mapping
-from .schema import (
-    blob_v2_column_paths,
-    is_blob_v2_field,
-    row_addressable_blob_v2_paths,
-    schema_has_blob_field,
-)
+from .schema import blob_v2_column_paths, schema_has_blob_field


 def _should_push_down_query_table(
@@ -431,7 +425,6 @@ def _cast_to_target_schema(

    def gen():
        for batch in reader:
-            batch = _coerce_blob_write_columns(batch, reordered_schema)
            # Table but not RecordBatch has cast.
            cast_batches = (
                pa.Table.from_batches([batch]).cast(reordered_schema).to_batches()
@@ -444,166 +437,6 @@ def _cast_to_target_schema(
    return pa.RecordBatchReader.from_batches(reordered_schema, gen())


-def _coerce_blob_write_columns(
-    batch: pa.RecordBatch, target_schema: pa.Schema
-) -> pa.RecordBatch:
-    """Materialize blob storage structs before the stream leaves Python.
-
-    merge_insert requires its source reader to already match the table's
-    physical schema. Unlike add and insert, it does not pass through
-    LanceDB's Rust blob coercion, so preserving binary input here would
-    reach Lance as binary and fail the schema check.
-    """
-    columns = []
-    fields = []
-    changed = False
-    for field, column in zip(batch.schema, batch.columns):
-        target_field = target_schema.field(field.name)
-        coerced = _coerce_blob_value(column, target_field)
-        if coerced is not column:
-            column = coerced
-            field = pa.field(
-                field.name,
-                coerced.type,
-                field.nullable,
-                target_field.metadata,
-            )
-            changed = True
-        columns.append(column)
-        fields.append(field)
-    if not changed:
-        return batch
-    return pa.RecordBatch.from_arrays(
-        columns, schema=pa.schema(fields, metadata=batch.schema.metadata)
-    )
-
-
-def _coerce_blob_value(column: pa.Array, target_field: pa.Field) -> pa.Array:
-    if is_blob_v2_field(target_field) and _can_coerce_to_blob(column.type):
-        return _coerce_value_to_blob(column, target_field)
-
-    target_type = target_field.type
-    if pa.types.is_struct(target_type) and pa.types.is_struct(column.type):
-        children = []
-        fields = []
-        changed = False
-        for source_field in column.type:
-            source_column = column.field(source_field.name)
-            nested_target = next(
-                (field for field in target_type if field.name == source_field.name),
-                None,
-            )
-            if nested_target is None:
-                children.append(source_column)
-                fields.append(source_field)
-                continue
-            coerced = _coerce_blob_value(source_column, nested_target)
-            if coerced is not source_column:
-                changed = True
-            child_array, child_type = _physical_array_and_type(coerced)
-            children.append(child_array)
-            fields.append(
-                pa.field(
-                    source_field.name,
-                    child_type,
-                    source_field.nullable,
-                    nested_target.metadata,
-                )
-            )
-        if not changed:
-            return column
-        return pa.StructArray.from_arrays(
-            children,
-            fields=fields,
-            mask=column.is_null() if column.null_count else None,
-        )
-
-    if _is_list_like(target_type) and _is_list_like(column.type):
-        return _coerce_blob_list_values(column, target_type.value_field)
-
-    return column
-
-
-def _coerce_blob_list_values(
-    column: pa.Array, target_value_field: pa.Field
-) -> pa.Array:
-    """Coerce blob values inside a list column, preserving offsets and nulls.
-
-    Works on the raw child values window instead of ``pc.list_flatten`` because
-    flatten drops values spanned by null slots, which would misalign offsets.
-    """
-    mask = column.is_null() if column.null_count else None
-    if pa.types.is_fixed_size_list(column.type):
-        list_size = column.type.list_size
-        values = column.values.slice(column.offset * list_size, len(column) * list_size)
-        coerced = _coerce_blob_value(values, target_value_field)
-        if coerced is values:
-            return column
-        physical_values, _ = _physical_array_and_type(coerced)
-        return pa.FixedSizeListArray.from_arrays(physical_values, list_size, mask=mask)
-    offsets = column.offsets
-    first_offset = offsets[0].as_py()
-    values = column.values.slice(
-        first_offset,
-        offsets[-1].as_py() - first_offset,
-    )
-    coerced = _coerce_blob_value(values, target_value_field)
-    if coerced is values:
-        return column
-    physical_values, _ = _physical_array_and_type(coerced)
-    if first_offset:
-        offsets = pc.subtract(offsets, pa.scalar(first_offset, offsets.type))
-    if pa.types.is_large_list(column.type):
-        return pa.LargeListArray.from_arrays(offsets, physical_values, mask=mask)
-    return pa.ListArray.from_arrays(offsets, physical_values, mask=mask)
-
-
-def _coerce_value_to_blob(values: pa.Array, target_field: pa.Field) -> pa.Array:
-    if pa.types.is_null(values.type):
-        data = pa.nulls(len(values), type=pa.large_binary())
-    elif pa.types.is_large_binary(values.type):
-        data = values
-    else:
-        data = values.cast(pa.large_binary())
-    length = len(values)
-    storage_type = target_field.type
-    if isinstance(storage_type, pa.ExtensionType):
-        storage_type = storage_type.storage_type
-    storage_fields = list(storage_type)
-    children = []
-    for storage_field in storage_fields:
-        if storage_field.name == "data":
-            children.append(data)
-        else:
-            children.append(pa.nulls(length, type=storage_field.type))
-    storage = pa.StructArray.from_arrays(
-        children,
-        fields=storage_fields,
-        mask=values.is_null() if values.null_count else None,
-    )
-    if isinstance(target_field.type, pa.ExtensionType):
-        return pa.ExtensionArray.from_storage(target_field.type, storage)
-    return storage
-
-
-def _physical_array_and_type(array: pa.Array) -> tuple[pa.Array, pa.DataType]:
-    if isinstance(array.type, pa.ExtensionType):
-        return array.storage, array.type.storage_type
-    return array, array.type
-
-
-def _can_coerce_to_blob(data_type: pa.DataType) -> bool:
-    return _is_binary_like(data_type) or pa.types.is_null(data_type)
-
-
-def _is_binary_like(data_type: pa.DataType) -> bool:
-    return (
-        pa.types.is_binary(data_type)
-        or pa.types.is_large_binary(data_type)
-        or pa.types.is_binary_view(data_type)
-    )
-
-
 def _field_extension_name(field: pa.Field) -> Optional[str]:
    extension_name = getattr(field.type, "extension_name", None)
    if extension_name is not None:
@@ -630,73 +463,65 @@ def _align_field_types(
        target_field = next((f for f in target_fields if f.name == field.name), None)
        if target_field is None:
            raise ValueError(f"Field '{field.name}' not found in target schema")
-        new_fields.append(_align_field(field, target_field))
+        # Preserve arrow.json input until it reaches Lance. LanceDB exposes stored
+        # JSON columns as lance.json (JSONB-backed LargeBinary), but casting the
+        # input to that storage type here merely relabels the raw JSON bytes as
+        # JSONB. Lance must see arrow.json so it can perform the JSONB encoding.
+        if (
+            _field_extension_name(field) == "arrow.json"
+            and _field_extension_name(target_field) == "lance.json"
+        ):
+            new_fields.append(field)
+            continue
+        if pa.types.is_struct(target_field.type):
+            if pa.types.is_struct(field.type):
+                new_type = pa.struct(
+                    _align_field_types(
+                        field.type.fields,
+                        target_field.type.fields,
+                    )
+                )
+            else:
+                new_type = target_field.type
+        elif pa.types.is_list(target_field.type):
+            if _is_list_like(field.type):
+                new_type = pa.list_(
+                    _align_field_types(
+                        [field.type.value_field],
+                        [target_field.type.value_field],
+                    )[0]
+                )
+            else:
+                new_type = target_field.type
+        elif pa.types.is_large_list(target_field.type):
+            if _is_list_like(field.type):
+                new_type = pa.large_list(
+                    _align_field_types(
+                        [field.type.value_field],
+                        [target_field.type.value_field],
+                    )[0]
+                )
+            else:
+                new_type = target_field.type
+        elif pa.types.is_fixed_size_list(target_field.type):
+            if _is_list_like(field.type):
+                new_type = pa.list_(
+                    _align_field_types(
+                        [field.type.value_field],
+                        [target_field.type.value_field],
+                    )[0],
+                    target_field.type.list_size,
+                )
+            else:
+                new_type = target_field.type
+        else:
+            new_type = target_field.type
+        new_fields.append(
+            pa.field(field.name, new_type, field.nullable, target_field.metadata)
+        )
    return new_fields


-def _align_list_value_field(
-    value_field: pa.Field, target_value_field: pa.Field
-) -> pa.Field:
-    # A list has exactly one child, so the inferred child name ("item") aligns
-    # positionally and adopts the table's child name; pa.Table.cast renames it.
-    return _align_field(value_field, target_value_field).with_name(
-        target_value_field.name
-    )
-
-
-def _align_field(field: pa.Field, target_field: pa.Field) -> pa.Field:
-    # Preserve arrow.json input until it reaches Lance. LanceDB exposes stored
-    # JSON columns as lance.json (JSONB-backed LargeBinary), but casting the
-    # input to that storage type here merely relabels the raw JSON bytes as
-    # JSONB. Lance must see arrow.json so it can perform the JSONB encoding.
-    if (
-        _field_extension_name(field) == "arrow.json"
-        and _field_extension_name(target_field) == "lance.json"
-    ):
-        return field
-    if pa.types.is_struct(target_field.type):
-        if pa.types.is_struct(field.type):
-            new_type = pa.struct(
-                _align_field_types(
-                    field.type.fields,
-                    target_field.type.fields,
-                )
-            )
-        else:
-            new_type = target_field.type
-    elif pa.types.is_list(target_field.type):
-        if _is_list_like(field.type):
-            new_type = pa.list_(
-                _align_list_value_field(
-                    field.type.value_field, target_field.type.value_field
-                )
-            )
-        else:
-            new_type = target_field.type
-    elif pa.types.is_large_list(target_field.type):
-        if _is_list_like(field.type):
-            new_type = pa.large_list(
-                _align_list_value_field(
-                    field.type.value_field, target_field.type.value_field
-                )
-            )
-        else:
-            new_type = target_field.type
-    elif pa.types.is_fixed_size_list(target_field.type):
-        if _is_list_like(field.type):
-            new_type = pa.list_(
-                _align_list_value_field(
-                    field.type.value_field, target_field.type.value_field
-                ),
-                target_field.type.list_size,
-            )
-        else:
-            new_type = target_field.type
-    else:
-        new_type = target_field.type
-    return pa.field(field.name, new_type, field.nullable, target_field.metadata)
-
-
 def _infer_subschema(
    schema: List[pa.Field],
    reference_fields: List[pa.Field],
@@ -763,7 +588,7 @@ def sanitize_create_table(
        schema = data.schema
    else:
        if schema is not None:
-            data = pa.Table.from_batches([], schema=schema)
+            data = pa.Table.from_pylist([], schema)
    if schema is None:
        if data is None:
            raise ValueError("Either data or schema must be provided")
@@ -1343,7 +1168,6 @@ class Table(ABC):
        ngram_max_length: int = 3,
        prefix_only: bool = False,
        block_size: int = 128,
-        document_granularity: DocumentGranularity = DocumentGranularity.ROW,
        wait_timeout: Optional[timedelta] = None,
        name: Optional[str] = None,
    ):
@@ -1422,11 +1246,6 @@ class Table(ABC):
            The number of documents per compressed posting block. Must be 128
            or 256. A value of 256 uses the experimental FTS V3 format and
            may introduce breaking changes.
-        document_granularity: DocumentGranularity, default ROW
-            ``ROW`` treats the selected text in one table row as one document.
-            ``LIST_ELEMENT`` treats each element of the deepest list on the field
-            path as one document and returns its physical coordinates in
-            ``_doc_index`` for matching queries.
        wait_timeout: timedelta, optional
            The timeout to wait if indexing is asynchronous.
        name: str, optional
@@ -1678,9 +1497,9 @@ class Table(ABC):
        Offsets are mostly useful for sampling as the set of all valid offsets is easily
        known in advance to be [0, len(table)).

-        No guarantees are made regarding the order in which results are returned.
-        Repeated offsets produce repeated rows, which makes this method suitable for
-        sampling with replacement.
+        No guarantees are made regarding the order in which results are returned.  If
+        you desire an output order that matches the order of the given offsets, you will
+        need to add the row offset column to the output and align it yourself.

        Parameters
        ----------
@@ -1918,7 +1737,7 @@ class Table(ABC):
    @abstractmethod
    def update(
        self,
-        where: Optional[Union[str, Expr]] = None,
+        where: Optional[str] = None,
        values: Optional[dict] = None,
        *,
        values_sql: Optional[Dict[str, str]] = None,
@@ -1933,11 +1752,9 @@ class Table(ABC):

        Parameters
        ----------
-        where: str or [Expr][lancedb.expr.Expr], optional
-            The filter condition. Can be a SQL string or a type-safe
-            [Expr][lancedb.expr.Expr] built with [col][lancedb.expr.col] and
-            [lit][lancedb.expr.lit]. The filter must not be empty, or it will
-            error.
+        where: str, optional
+            The SQL where clause to use when updating rows. For example, 'x = 2'
+            or 'x IN (1, 2, 3)'. The filter must not be empty, or it will error.
        values: dict, optional
            The values to update. The keys are the column names and the values
            are the values to set.
@@ -1955,7 +1772,6 @@ class Table(ABC):
        Examples
        --------
        >>> import lancedb
-        >>> from lancedb.expr import col
        >>> import pandas as pd
        >>> data = pd.DataFrame({"x": [1, 2, 3], "vector": [[1.0, 2], [3, 4], [5, 6]]})
        >>> db = lancedb.connect("./.lancedb")
@@ -1965,7 +1781,7 @@ class Table(ABC):
        0  1  [1.0, 2.0]
        1  2  [3.0, 4.0]
        2  3  [5.0, 6.0]
-        >>> table.update(where=col("x") == 2, values={"vector": [10.0, 10]})
+        >>> table.update(where="x = 2", values={"vector": [10.0, 10]})
        UpdateResult(rows_updated=1, version=2)
        >>> table.to_pandas()
           x        vector
@@ -2165,11 +1981,9 @@ class Table(ABC):
            Function columns are supported only on LanceDB Cloud and
            Enterprise.
        computed: Dict[str, str], optional
-            A mapping from output column names to SQL expressions derives each
-            output field from its expression. A direct projection of a Blob v2
-            field inherits Blob v2 semantics; other expressions derive their
-            ordinary Arrow type. Mapping order is declaration and dependency
-            order.
+            A map of column name to a SQL expression defining the column. The
+            column's type and inputs are derived from the expression, so no
+            data type is supplied.

            Unlike ``transforms``, the expression is stored rather than
            evaluated now: the column is committed with no values, and rows get
@@ -2306,25 +2120,12 @@ class Table(ABC):
        ----------
        updates : dict
            One or more dicts, each with:
-
            - "path": str — dot-path to the field (e.g. "embedding" or "a.b.c").
            - "metadata": dict[str, str | None] — keys to set; a value of ``None``
              deletes that key.
            - "replace": bool, optional — replace the field's whole metadata map
              instead of merging (default False).

-            The following keys are treated specially, by convention, and should
-            be used when appropriate:
-
-            - "lancedb:description": for a human-readable description of a field.
-            - ``"lancedb:tag:<name>"`` for a user-defined key-value tag, where the
-                suffix names the tag category; e.g. "lancedb:tag:model": "clip".
-            - "lancedb:logical-column" for a column grouping; e.g. "feature_v1"
-                and "feature_v2" might be in the same logical column.
-            - "lancedb:status" for status options ("production", "candidate",
-                "deprecated", "archived") to designate the current life cycle
-                state of this column.
-
        Returns
        -------
        UpdateFieldMetadataResult
@@ -2874,7 +2675,7 @@ class LanceTable(Table):
            arrow_tbl = self.to_arrow()
            if blob_mode == "descriptions":
                arrow_tbl = strip_auto_row_ids(
-                    arrow_tbl, row_addressable_blob_v2_paths(self.schema)
+                    arrow_tbl, blob_v2_column_paths(self.schema)
                )
            return arrow_tbl.to_pandas(**kwargs)

@@ -3472,7 +3273,6 @@ class LanceTable(Table):
        ngram_max_length: int = 3,
        prefix_only: bool = False,
        block_size: int = 128,
-        document_granularity: DocumentGranularity = DocumentGranularity.ROW,
        name: Optional[str] = None,
    ):
        """Create a full-text search index on a column.
@@ -3524,11 +3324,7 @@ class LanceTable(Table):
            tokenizer_configs = self.infer_tokenizer_configs(tokenizer_name)
            tokenizer_configs["custom_stop_words"] = custom_stop_words

-        config = FTS(
-            block_size=block_size,
-            document_granularity=document_granularity,
-            **tokenizer_configs,
-        )
+        config = FTS(block_size=block_size, **tokenizer_configs)

        try:
            LOOP.run(
@@ -4020,7 +3816,7 @@ class LanceTable(Table):

    def update(
        self,
-        where: Optional[Union[str, Expr]] = None,
+        where: Optional[str] = None,
        values: Optional[dict] = None,
        *,
        values_sql: Optional[Dict[str, str]] = None,
@@ -4031,11 +3827,9 @@ class LanceTable(Table):

        Parameters
        ----------
-        where: str or [Expr][lancedb.expr.Expr], optional
-            The filter condition. Can be a SQL string or a type-safe
-            [Expr][lancedb.expr.Expr] built with [col][lancedb.expr.col] and
-            [lit][lancedb.expr.lit]. The filter must not be empty, or it will
-            error.
+        where: str, optional
+            The SQL where clause to use when updating rows. For example, 'x = 2'
+            or 'x IN (1, 2, 3)'. The filter must not be empty, or it will error.
        values: dict, optional
            The values to update. The keys are the column names and the values
            are the values to set.
@@ -4053,7 +3847,6 @@ class LanceTable(Table):
        Examples
        --------
        >>> import lancedb
-        >>> from lancedb.expr import col
        >>> import pandas as pd
        >>> data = pd.DataFrame({"x": [1, 2, 3], "vector": [[1.0, 2], [3, 4], [5, 6]]})
        >>> db = lancedb.connect("./.lancedb")
@@ -4063,7 +3856,7 @@ class LanceTable(Table):
        0  1  [1.0, 2.0]
        1  2  [3.0, 4.0]
        2  3  [5.0, 6.0]
-        >>> table.update(where=col("x") == 2, values={"vector": [10.0, 10]})
+        >>> table.update(where="x = 2", values={"vector": [10.0, 10]})
        UpdateResult(rows_updated=1, version=2)
        >>> table.to_pandas()
           x        vector
@@ -4090,7 +3883,6 @@ class LanceTable(Table):
            )
            and not self._route_pushdown_to_rust
            and self.current_branch() is None
-            and query.take_offsets is None
        ):
            from lancedb.namespace import _execute_server_side_query

@@ -5279,9 +5071,7 @@ class AsyncTable:
        if blob_mode == "descriptions" or not schema_has_blob_field(schema):
            arrow_tbl = await self.to_arrow()
            if blob_mode == "descriptions":
-                arrow_tbl = strip_auto_row_ids(
-                    arrow_tbl, row_addressable_blob_v2_paths(schema)
-                )
+                arrow_tbl = strip_auto_row_ids(arrow_tbl, blob_v2_column_paths(schema))
            return arrow_tbl.to_pandas(**kwargs)

        if blob_mode == "lazy" and get_uri_scheme(await self.uri()) == "memory":
@@ -5984,23 +5774,7 @@ class AsyncTable:

    def _sync_query_to_async(
        self, query: Query
-    ) -> (
-        AsyncHybridQuery
-        | AsyncFTSQuery
-        | AsyncVectorQuery
-        | AsyncQuery
-        | AsyncTakeQuery
-    ):
-        if query.take_offsets is not None:
-            take_query = self.take_offsets(query.take_offsets)
-            if query.columns:
-                take_query = take_query.select(query.columns)
-            if query.use_lsm is not None:
-                take_query = take_query.use_lsm(query.use_lsm)
-            if query.with_row_id:
-                take_query = take_query.with_row_id()
-            return take_query
-
+    ) -> AsyncHybridQuery | AsyncFTSQuery | AsyncVectorQuery | AsyncQuery:
        async_query = self.query()
        if query.limit is not None:
            async_query = async_query.limit(query.limit)
@@ -6065,7 +5839,6 @@ class AsyncTable:
                self._namespace_client, self._pushdown_operations
            )
            and not self._route_pushdown_to_rust
-            and query.take_offsets is None
        ):
            from lancedb.namespace import _execute_server_side_query

@@ -6197,7 +5970,7 @@ class AsyncTable:
        self,
        updates: Optional[Dict[str, Any]] = None,
        *,
-        where: Optional[Union[str, Expr]] = None,
+        where: Optional[str] = None,
        updates_sql: Optional[Dict[str, str]] = None,
    ) -> UpdateResult:
        """
@@ -6212,11 +5985,9 @@ class AsyncTable:
            The updates to apply.  The keys should be the name of the column to
            update.  The values should be the new values to assign.  This is
            required unless updates_sql is supplied.
-        where: str or [Expr][lancedb.expr.Expr], optional
-            The filter condition. Can be a SQL string or a type-safe
-            [Expr][lancedb.expr.Expr] built with [col][lancedb.expr.col] and
-            [lit][lancedb.expr.lit]. Only rows that satisfy this filter will
-            be updated.
+        where: str, optional
+            An SQL filter that controls which rows are updated. For example, 'x = 2'
+            or 'x IN (1, 2, 3)'.  Only rows that satisfy this filter will be udpated.
        updates_sql: dict, optional
            The updates to apply, expressed as SQL expression strings.  The keys should
            be column names. The values should be SQL expressions.  These can be SQL
@@ -6234,14 +6005,13 @@ class AsyncTable:
        --------
        >>> import asyncio
        >>> import lancedb
-        >>> from lancedb.expr import col
        >>> import pandas as pd
        >>> async def demo_update():
        ...     data = pd.DataFrame({"x": [1, 2], "vector": [[1, 2], [3, 4]]})
        ...     db = await lancedb.connect_async("./.lancedb")
        ...     table = await db.create_table("my_table", data)
        ...     # x is [1, 2], vector is [[1, 2], [3, 4]]
-        ...     await table.update({"vector": [10, 10]}, where=col("x") == 2)
+        ...     await table.update({"vector": [10, 10]}, where="x = 2")
        ...     # x is [1, 2], vector is [[1, 2], [10, 10]]
        ...     await table.update(updates_sql={"x": "x + 1"})
        ...     # x is [2, 3], vector is [[1, 2], [10, 10]]
@@ -6255,8 +6025,7 @@ class AsyncTable:
        if updates is not None:
            updates_sql = {k: value_to_sql(v) for k, v in updates.items()}

-        predicate = where.to_sql() if isinstance(where, Expr) else where
-        return await self._inner.update(updates_sql, predicate)
+        return await self._inner.update(updates_sql, where)

    async def add_columns(
        self,
@@ -6288,11 +6057,8 @@ class AsyncTable:
            Function columns are supported only on LanceDB Cloud and
            Enterprise.
        computed: Dict[str, str], optional
-            A mapping from output column names to SQL expressions derives each
-            output field from its expression. A direct projection of a Blob v2
-            field inherits Blob v2 semantics; other expressions derive their
-            ordinary Arrow type. Mapping order is declaration and dependency
-            order.
+            A map of column name to a SQL expression defining the column. The
+            column's type and inputs are derived from the expression.

            Unlike ``transforms``, the expression is stored rather than
            evaluated now: the column is committed with no values, and rows get
@@ -6563,9 +6329,6 @@ class AsyncTable:
        Offsets are mostly useful for sampling as the set of all valid offsets is easily
        known in advance to be [0, len(table)).

-        No guarantees are made regarding the order in which results are returned.
-        Repeated offsets produce repeated rows.
-
        Parameters
        ----------
        offsets: list[int]
@@ -105,7 +105,7 @@ def test_quickstart(tmp_path):
    tbl.create_index(num_sub_vectors=1)
    # --8<-- [end:create_index]
    # --8<-- [start:delete_rows]
-    tbl.delete("item = 'fizz'")
+    tbl.delete('item = "fizz"')
    # --8<-- [end:delete_rows]
    # --8<-- [start:drop_table]
    db.drop_table("my_table")
@@ -201,7 +201,7 @@ async def test_quickstart_async(tmp_path):
    await tbl.create_index("vector")
    # --8<-- [end:create_index_async]
    # --8<-- [start:delete_rows_async]
-    await tbl.delete("item = 'fizz'")
+    await tbl.delete('item = "fizz"')
    # --8<-- [end:delete_rows_async]
    # --8<-- [start:drop_table_async]
    await db.drop_table("my_table_async")
@@ -266,7 +266,7 @@ def test_table():
    tbl.add(pydantic_model_items)
    # --8<-- [end:add_table_from_pydantic]
    # --8<-- [start:delete_row]
-    tbl.delete("item = 'fizz'")
+    tbl.delete('item = "fizz"')
    # --8<-- [end:delete_row]
    # --8<-- [start:delete_specific_row]
    data = [
@@ -538,7 +538,7 @@ async def test_table_async():
    await async_tbl.add(pydantic_model_items)
    # --8<-- [end:add_table_async_from_pydantic]
    # --8<-- [start:delete_row_async]
-    await async_tbl.delete("item = 'fizz'")
+    await async_tbl.delete('item = "fizz"')
    # --8<-- [end:delete_row_async]
    # --8<-- [start:delete_specific_row_async]
    data = [
@@ -2,41 +2,17 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors

 import io
-import subprocess
-import sys
-import textwrap

-import lance
 import pyarrow as pa
 import pyarrow.compute as pc
 import pytest
-from lance.blob import BlobType as LanceBlobType

 import lancedb
-from lancedb._blob import (
-    blob_v2_projection_sources,
-    read_row_ids_from_hits,
-    stash_auto_row_ids,
-)
-from lancedb.expr import col
+from lancedb._blob import read_row_ids_from_hits, stash_auto_row_ids
 from lancedb.index import FTS
 from lancedb.schema import blob_column_paths, blob_v2_column_paths


-_HIDE_LANCE_BLOB = """\
-import importlib.abc
-import sys
-
-class _MissingLanceBlob(importlib.abc.MetaPathFinder):
-    def find_spec(self, fullname, path, target=None):
-        if fullname == "lance.blob" or fullname.startswith("lance.blob."):
-            raise ModuleNotFoundError(fullname, name="lance.blob")
-
-sys.modules.pop("lance.blob", None)
-sys.meta_path.insert(0, _MissingLanceBlob())
-"""
-
-
 def _blob_table(name, rows):
    db = lancedb.connect("memory:///")
    schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("image")])
@@ -70,181 +46,6 @@ def test_blob_factory_declares_v2_field():
    field = lancedb.blob("image")
    assert isinstance(field.type, pa.ExtensionType)
    assert field.type.extension_name == "lance.blob.v2"
-    assert lancedb.BlobType is LanceBlobType
-    assert type(field.type) is LanceBlobType
-
-
-def test_blob_type_works_without_pylance():
-    script = _HIDE_LANCE_BLOB + textwrap.dedent(
-        """\
-        import lancedb
-        import pyarrow as pa
-
-        field = lancedb.blob("image")
-        if not isinstance(field.type, pa.ExtensionType):
-            raise SystemExit("expected an extension type")
-        if field.type.extension_name != "lance.blob.v2":
-            raise SystemExit(field.type.extension_name)
-        if lancedb.BlobType is not type(field.type):
-            raise SystemExit("BlobType is not the field type class")
-        if lancedb.BlobType.__module__ != "lancedb.schema":
-            raise SystemExit(lancedb.BlobType.__module__)
-
-        db = lancedb.connect("memory:///")
-        table = db.create_table(
-            "images",
-            schema=pa.schema([pa.field("id", pa.int64()), field]),
-        )
-        table.add([{"id": 1, "image": b"hello"}])
-        result = (
-            table.merge_insert("id")
-            .when_matched_update_all()
-            .when_not_matched_insert_all()
-            .execute([{"id": 1, "image": b"updated"}, {"id": 2, "image": b"inserted"}])
-        )
-        if result.num_updated_rows != 1 or result.num_inserted_rows != 1:
-            raise SystemExit(
-                f"merge_insert rows updated={result.num_updated_rows} "
-                f"inserted={result.num_inserted_rows}"
-            )
-        """
-    )
-    result = subprocess.run(
-        [sys.executable, "-c", script],
-        capture_output=True,
-        text=True,
-        check=False,
-    )
-    assert result.returncode == 0, result.stderr
-
-
-def test_blob_resolves_pylance_type_without_eager_import():
-    script = textwrap.dedent(
-        """\
-        import sys
-        import lancedb
-
-        if "lance.blob" in sys.modules:
-            raise SystemExit("import lancedb imported lance.blob")
-        field = lancedb.blob("image")
-        from lance.blob import BlobType
-
-        if type(field.type) is not BlobType:
-            raise SystemExit(f"{type(field.type)} is not {BlobType}")
-        import lance
-
-        image = lance.blob_array([b"x"])
-        if type(image.type) is not BlobType:
-            raise SystemExit("blob_array used a different class")
-        if type(image.type) is not type(field.type):
-            raise SystemExit("field and array classes differ")
-        """
-    )
-    result = subprocess.run(
-        [sys.executable, "-c", script],
-        capture_output=True,
-        text=True,
-        check=False,
-    )
-    assert result.returncode == 0, result.stderr
-
-
-def test_blob_fallback_fails_if_name_already_registered():
-    script = _HIDE_LANCE_BLOB + textwrap.dedent(
-        """\
-        import pyarrow as pa
-
-        class OtherBlobType(pa.ExtensionType):
-            def __init__(self):
-                super().__init__(
-                    pa.struct([pa.field("data", pa.large_binary())]),
-                    "lance.blob.v2",
-                )
-
-            def __arrow_ext_serialize__(self):
-                return b""
-
-            @classmethod
-            def __arrow_ext_deserialize__(cls, storage_type, serialized):
-                return cls()
-
-        pa.register_extension_type(OtherBlobType())
-        import lancedb
-
-        try:
-            lancedb.blob("image")
-        except ValueError as err:
-            if "already registered" not in str(err):
-                raise SystemExit(err)
-        else:
-            raise SystemExit("expected ValueError")
-        """
-    )
-    result = subprocess.run(
-        [sys.executable, "-c", script],
-        capture_output=True,
-        text=True,
-        check=False,
-    )
-    assert result.returncode == 0, result.stderr
-
-
-def test_blob_type_rejects_competing_registration_with_pylance():
-    script = textwrap.dedent(
-        """\
-        import pyarrow as pa
-        import pyarrow.ipc
-
-        class OtherBlobType(pa.ExtensionType):
-            def __init__(self):
-                super().__init__(
-                    pa.struct(
-                        [
-                            pa.field("data", pa.large_binary()),
-                            pa.field("uri", pa.utf8()),
-                            pa.field("position", pa.uint64()),
-                            pa.field("size", pa.uint64()),
-                        ]
-                    ),
-                    "lance.blob.v2",
-                )
-
-            def __arrow_ext_serialize__(self):
-                return b""
-
-            @classmethod
-            def __arrow_ext_deserialize__(cls, storage_type, serialized):
-                return cls()
-
-        pa.register_extension_type(OtherBlobType())
-
-        from lance.blob import BlobType
-
-        if BlobType is OtherBlobType:
-            raise SystemExit("pylance BlobType was replaced")
-        schema = pa.schema([pa.field("value", BlobType())])
-        restored = pa.ipc.read_schema(schema.serialize())
-        if type(restored.field("value").type) is not OtherBlobType:
-            raise SystemExit(type(restored.field("value").type))
-
-        import lancedb
-
-        try:
-            lancedb.blob("image")
-        except ValueError as err:
-            if "__main__.OtherBlobType" not in str(err):
-                raise SystemExit(err)
-        else:
-            raise SystemExit("expected ValueError")
-        """
-    )
-    result = subprocess.run(
-        [sys.executable, "-c", script],
-        capture_output=True,
-        text=True,
-        check=False,
-    )
-    assert result.returncode == 0, result.stderr


 def test_blob_v2_column_paths_include_list_children():
@@ -269,14 +70,6 @@ def test_blob_v2_column_paths_include_list_children():
    ]


-def test_blob_v2_projection_sources_use_typed_column_name():
-    schema = pa.schema([lancedb.blob("blob")])
-
-    assert blob_v2_projection_sources(schema, {"blob_alias": col("blob")}) == {
-        "blob_alias": "blob"
-    }
-
-
 def _legacy_v1_table(name):
    db = lancedb.connect("memory:///")
    schema = pa.schema(
@@ -373,20 +166,6 @@ async def test_async_table_to_pandas_descriptions_mode_omits_row_id():
    assert set(descriptor.keys()) == {"kind", "position", "size", "blob_id", "blob_uri"}


-@pytest.mark.asyncio
-async def test_async_typed_blob_projection_preserves_source_column():
-    db = await lancedb.connect_async("memory:///typed_blob_projection")
-    schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("blob")])
-    table = await db.create_table("typed_blob_projection", schema=schema)
-    await table.add([{"id": 1, "blob": b"alpha"}])
-
-    hits = await table.query().select({"blob_alias": col("blob")}).to_arrow()
-
-    assert "_lance_row_id" in hits.schema.field("blob_alias").type.names
-    blobs = await table.fetch_blobs("blob", hits)
-    assert blobs.to_pylist() == [b"alpha"]
-
-
 def test_fetch_blobs_round_trip():
    table = _blob_table(
        "round_trip",
@@ -397,292 +176,6 @@ def test_fetch_blobs_round_trip():
    assert [blobs[0].as_py(), blobs[1].as_py()] == [b"alpha", b"beta"]


-def test_merge_insert_writes_python_bytes():
-    table = _blob_table("merge_bytes", [{"id": 1, "image": b"before"}])
-    result = (
-        table.merge_insert("id")
-        .when_matched_update_all()
-        .when_not_matched_insert_all()
-        .execute([{"id": 1, "image": b"updated"}, {"id": 2, "image": b"inserted"}])
-    )
-    assert result.num_updated_rows == 1
-    assert result.num_inserted_rows == 1
-    by_id = _row_ids_by_id(table)
-    blobs = table.fetch_blobs("image", [by_id[1], by_id[2]])
-    assert blobs.to_pylist() == [b"updated", b"inserted"]
-
-
-def test_merge_insert_bytes_after_reopen_without_touching_blob_type(tmp_path):
-    db = lancedb.connect(tmp_path)
-    schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("image")])
-    table = db.create_table("images", schema=schema)
-    table.add([{"id": 1, "image": b"hello"}])
-
-    script = textwrap.dedent(
-        f"""\
-        import lancedb
-
-        db = lancedb.connect({str(tmp_path)!r})
-        table = db.open_table("images")
-        image_type = table.schema.field("image").type
-        if type(image_type).__name__ != "StructType":
-            raise SystemExit(f"expected StructType, got {{type(image_type)}}")
-        result = (
-            table.merge_insert("id")
-            .when_matched_update_all()
-            .when_not_matched_insert_all()
-            .execute(
-                [{{"id": 1, "image": b"updated"}}, {{"id": 2, "image": b"inserted"}}]
-            )
-        )
-        if result.num_updated_rows != 1 or result.num_inserted_rows != 1:
-            raise SystemExit(
-                f"rows updated={{result.num_updated_rows}} "
-                f"inserted={{result.num_inserted_rows}}"
-            )
-        hits = table.search().with_row_id(True).limit(10).to_arrow()
-        by_id = dict(zip(hits["id"].to_pylist(), hits["_rowid"].to_pylist()))
-        blobs = table.fetch_blobs("image", [by_id[1], by_id[2]])
-        if blobs.to_pylist() != [b"updated", b"inserted"]:
-            raise SystemExit(blobs.to_pylist())
-        """
-    )
-    result = subprocess.run(
-        [sys.executable, "-c", script],
-        capture_output=True,
-        text=True,
-        check=False,
-    )
-    assert result.returncode == 0, result.stderr
-
-
-def test_merge_insert_bytes_after_reopen_without_pylance(tmp_path):
-    db = lancedb.connect(tmp_path)
-    schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("image")])
-    table = db.create_table("images", schema=schema)
-    table.add([{"id": 1, "image": b"hello"}])
-
-    script = _HIDE_LANCE_BLOB + textwrap.dedent(
-        f"""\
-        import lancedb
-
-        db = lancedb.connect({str(tmp_path)!r})
-        table = db.open_table("images")
-        image_type = table.schema.field("image").type
-        if type(image_type).__name__ != "StructType":
-            raise SystemExit(f"expected StructType, got {{type(image_type)}}")
-        result = (
-            table.merge_insert("id")
-            .when_matched_update_all()
-            .when_not_matched_insert_all()
-            .execute(
-                [{{"id": 1, "image": b"updated"}}, {{"id": 2, "image": b"inserted"}}]
-            )
-        )
-        if result.num_updated_rows != 1 or result.num_inserted_rows != 1:
-            raise SystemExit(
-                f"rows updated={{result.num_updated_rows}} "
-                f"inserted={{result.num_inserted_rows}}"
-            )
-        hits = table.search().with_row_id(True).limit(10).to_arrow()
-        by_id = dict(zip(hits["id"].to_pylist(), hits["_rowid"].to_pylist()))
-        blobs = table.fetch_blobs("image", [by_id[1], by_id[2]])
-        if blobs.to_pylist() != [b"updated", b"inserted"]:
-            raise SystemExit(blobs.to_pylist())
-        """
-    )
-    result = subprocess.run(
-        [sys.executable, "-c", script],
-        capture_output=True,
-        text=True,
-        check=False,
-    )
-    assert result.returncode == 0, result.stderr
-
-
-def test_merge_insert_blob_array_into_reopened_unregistered_table(tmp_path):
-    db = lancedb.connect(tmp_path)
-    schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("image")])
-    table = db.create_table("images", schema=schema)
-    table.add([{"id": 1, "image": b"before"}])
-
-    script = textwrap.dedent(
-        f"""\
-        import pyarrow as pa
-        import lancedb
-
-        db = lancedb.connect({str(tmp_path)!r})
-        table = db.open_table("images")
-        image_type = table.schema.field("image").type
-        if type(image_type).__name__ != "StructType":
-            raise SystemExit(
-                f"expected StructType before lance import, got {{type(image_type)}}"
-            )
-
-        import lance
-
-        updates = pa.Table.from_arrays(
-            [
-                pa.array([1, 2], type=pa.int64()),
-                lance.blob_array([b"updated", b"inserted"]),
-            ],
-            names=["id", "image"],
-        )
-        result = (
-            table.merge_insert("id")
-            .when_matched_update_all()
-            .when_not_matched_insert_all()
-            .execute(updates)
-        )
-        if result.num_updated_rows != 1 or result.num_inserted_rows != 1:
-            raise SystemExit(
-                f"rows updated={{result.num_updated_rows}} "
-                f"inserted={{result.num_inserted_rows}}"
-            )
-        hits = table.search().with_row_id(True).limit(10).to_arrow()
-        by_id = dict(zip(hits["id"].to_pylist(), hits["_rowid"].to_pylist()))
-        blobs = table.fetch_blobs("image", [by_id[1], by_id[2]])
-        if blobs.to_pylist() != [b"updated", b"inserted"]:
-            raise SystemExit(blobs.to_pylist())
-        """
-    )
-    result = subprocess.run(
-        [sys.executable, "-c", script],
-        capture_output=True,
-        text=True,
-        check=False,
-    )
-    assert result.returncode == 0, result.stderr
-
-
-def test_add_all_null_blob_column():
-    db = lancedb.connect("memory:///")
-    schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("image")])
-    table = db.create_table("all_null", schema=schema)
-    table.add([{"id": 1, "image": None}, {"id": 2, "image": None}])
-    by_id = _row_ids_by_id(table)
-    blobs = table.fetch_blobs("image", [by_id[1], by_id[2]])
-    assert blobs.to_pylist() == [None, None]
-
-
-def test_create_table_nested_blob_schema_without_rows():
-    db = lancedb.connect("memory:///")
-    schema = pa.schema(
-        [
-            pa.field("id", pa.int64()),
-            pa.field("info", pa.struct([lancedb.blob("blob")])),
-            pa.field("images", pa.list_(lancedb.blob("image"))),
-        ]
-    )
-    table = db.create_table("nested_empty", schema=schema)
-    assert table.count_rows() == 0
-
-
-def test_merge_insert_nested_blob_dicts():
-    db = lancedb.connect("memory:///")
-    info = pa.StructArray.from_arrays(
-        [
-            pa.array(["first"], type=pa.string()),
-            _blob_array("blob", [b"before"]),
-        ],
-        names=["name", "blob"],
-    )
-    data = pa.Table.from_arrays(
-        [pa.array([1], type=pa.int64()), info],
-        names=["id", "info"],
-    )
-    table = db.create_table("nested_merge", data=data)
-    result = (
-        table.merge_insert("id")
-        .when_matched_update_all()
-        .execute([{"id": 1, "info": {"name": "first", "blob": b"after"}}])
-    )
-    assert result.num_updated_rows == 1
-    by_id = _row_ids_by_id(table)
-    blobs = table.fetch_blobs("info.blob", [by_id[1]])
-    assert blobs.to_pylist() == [b"after"]
-
-
-def _list_blob_table(name):
-    db = lancedb.connect("memory:///")
-    blob_field = lancedb.blob("image")
-    images = pa.ListArray.from_arrays(
-        pa.array([0, 1], type=pa.int32()), _blob_array("image", [b"before"])
-    )
-    data = pa.Table.from_arrays(
-        [pa.array([1], type=pa.int64()), images],
-        schema=pa.schema(
-            [pa.field("id", pa.int64()), pa.field("images", pa.list_(blob_field))]
-        ),
-    )
-    return db.create_table(name, data=data)
-
-
-def test_merge_insert_list_blob_dicts():
-    table = _list_blob_table("list_merge")
-    result = (
-        table.merge_insert("id")
-        .when_matched_update_all()
-        .when_not_matched_insert_all()
-        .execute([{"id": 1, "images": [b"one", b"two"]}, {"id": 2, "images": None}])
-    )
-    assert result.num_updated_rows == 1
-    assert result.num_inserted_rows == 1
-    hits = table.search().limit(10).to_arrow()
-    sizes = {
-        row["id"]: None if row["images"] is None else [d["size"] for d in row["images"]]
-        for row in hits.to_pylist()
-    }
-    assert sizes == {1: [3, 3], 2: None}
-
-
-def test_list_blob_column_queries_as_raw_descriptors():
-    table = _list_blob_table("list_query")
-    hits = table.search().limit(10).to_arrow()
-    element = hits.schema.field("images").type.value_type
-    assert pa.types.is_struct(element)
-    assert "_lance_row_id" not in element.names
-    with pytest.raises(ValueError, match="expected struct before segment"):
-        table.fetch_blobs("images.image", [0])
-
-
-def test_row_addressable_paths_exclude_list_children():
-    from lancedb.schema import row_addressable_blob_v2_paths
-
-    schema = pa.schema(
-        [
-            pa.field("id", pa.int64()),
-            pa.field("info", pa.struct([lancedb.blob("blob")])),
-            pa.field("images", pa.list_(lancedb.blob("image"))),
-        ]
-    )
-    assert blob_v2_column_paths(schema) == ["info.blob", "images.image"]
-    assert row_addressable_blob_v2_paths(schema) == ["info.blob"]
-
-
-def test_merge_insert_writes_pylance_blob_array():
-    table = _blob_table("merge_pylance", [{"id": 1, "image": b"before"}])
-    image = lance.blob_array([b"updated", b"inserted"])
-    assert type(image.type) is LanceBlobType
-    assert type(image.type) is type(lancedb.BlobType())
-    updates = pa.Table.from_arrays(
-        [pa.array([1, 2], type=pa.int64()), image], names=["id", "image"]
-    )
-
-    result = (
-        table.merge_insert("id")
-        .when_matched_update_all()
-        .when_not_matched_insert_all()
-        .execute(updates)
-    )
-
-    assert result.num_updated_rows == 1
-    assert result.num_inserted_rows == 1
-    by_id = _row_ids_by_id(table)
-    blobs = table.fetch_blobs("image", [by_id[1], by_id[2]])
-    assert blobs.to_pylist() == [b"updated", b"inserted"]
-
-
 def test_fetch_blobs_accepts_query_result():
    table = _blob_table("from_result", [{"id": 1, "image": b"gamma"}])
    hits = table.search().limit(10).to_arrow()
@@ -910,50 +403,6 @@ async def test_blob_v2_hybrid_fetch_blobs_async():
    assert {blobs[i].as_py() for i in range(len(blobs))} == {b"alpha", b"beta"}


-@pytest.mark.asyncio
-async def test_async_hybrid_typed_blob_projection_preserves_source_column():
-    db = await lancedb.connect_async("memory:///hybrid_typed_blob")
-    schema = pa.schema(
-        [
-            pa.field("id", pa.int64()),
-            pa.field("text", pa.utf8()),
-            pa.field("vector", pa.list_(pa.float32(), list_size=2)),
-            lancedb.blob("blob"),
-        ]
-    )
-    table = await db.create_table("hybrid_typed_blob", schema=schema)
-    await table.add(
-        [
-            {
-                "id": 1,
-                "text": "hello alpha",
-                "vector": [1.0, 0.0],
-                "blob": b"alpha",
-            },
-            {
-                "id": 2,
-                "text": "hello beta",
-                "vector": [0.9, 0.1],
-                "blob": b"beta",
-            },
-        ]
-    )
-    await table.create_index("text", config=FTS(with_position=False))
-
-    hits = await (
-        table.query()
-        .nearest_to([1.0, 0.0])
-        .nearest_to_text("hello")
-        .select({"blob_alias": col("blob")})
-        .limit(2)
-        .to_arrow()
-    )
-
-    assert "_lance_row_id" in hits.schema.field("blob_alias").type.names
-    blobs = await table.fetch_blobs("blob", hits)
-    assert {blobs[i].as_py() for i in range(len(blobs))} == {b"alpha", b"beta"}
-
-
 def test_blob_file_seek_read_and_read_range():
    payload = _identifiable_payload(1024)
    table = _blob_table("seek_read", [{"id": 1, "image": payload}])
@@ -52,7 +52,7 @@ class TestExprConstruction:
    def test_func(self):
        e = func("lower", col("name"))
        assert isinstance(e, Expr)
-        assert e.to_sql() == "lower(`name`)"
+        assert e.to_sql() == "lower(name)"

    def test_func_unknown_raises(self):
        with pytest.raises(Exception):
@@ -115,7 +115,7 @@ class TestExprOperators:
    def test_and_operator(self):
        e = (col("age") > lit(18)) & (col("status") == lit("active"))
        assert isinstance(e, Expr)
-        assert e.to_sql() == "((age > 18) AND (`status` = 'active'))"
+        assert e.to_sql() == "((age > 18) AND (status = 'active'))"

    def test_or_operator(self):
        e = (col("a") == lit(1)) | (col("b") == lit(2))
@@ -166,7 +166,7 @@ class TestExprOperators:
    def test_coerce_plain_str(self):
        e = col("name") == "alice"
        assert isinstance(e, Expr)
-        assert e.to_sql() == "(`name` = 'alice')"
+        assert e.to_sql() == "(name = 'alice')"

    def test_reflexive_comparisons(self):
        # 10 < col("age") swaps to col("age") > 10
@@ -198,85 +198,85 @@ class TestExprBytesLiteral:

    def test_bytes_equality_expr_sql(self):
        e = col("data") == lit(b"\xca\xfe")
-        assert e.to_sql() == "(`data` = X'CAFE')"
+        assert e.to_sql() == "(data = X'CAFE')"

    def test_bytes_ne_expr_sql(self):
        e = col("data") != lit(b"\xff")
-        assert e.to_sql() == "(`data` <> X'FF')"
+        assert e.to_sql() == "(data <> X'FF')"

    def test_bytes_compound_expr_sql(self):
        e = (col("data") == lit(b"\x01")) & (col("id") > lit(5))
-        assert e.to_sql() == "((`data` = X'01') AND (id > 5))"
+        assert e.to_sql() == "((data = X'01') AND (id > 5))"

    def test_bytes_in_function_call(self):
        # Regression test: binary literals inside scalar function calls
        # used to fail because DataFusion's unparser does not support Binary
        # scalars.  Now handled via a placeholder-substitution rewrite.
        e = func("contains", col("data"), lit(b"\xff"))
-        assert e.to_sql() == "contains(`data`, X'FF')"
+        assert e.to_sql() == "contains(data, X'FF')"

    def test_bytes_in_not(self):
        e = ~(col("data") == lit(b"\xff"))
-        assert e.to_sql() == "NOT (`data` = X'FF')"
+        assert e.to_sql() == "NOT (data = X'FF')"


 class TestExprStringMethods:
    def test_lower(self):
        e = col("name").lower()
        assert isinstance(e, Expr)
-        assert e.to_sql() == "lower(`name`)"
+        assert e.to_sql() == "lower(name)"

    def test_upper(self):
        e = col("name").upper()
        assert isinstance(e, Expr)
-        assert e.to_sql() == "upper(`name`)"
+        assert e.to_sql() == "upper(name)"

    def test_contains(self):
        e = col("text").contains(lit("hello"))
        assert isinstance(e, Expr)
-        assert e.to_sql() == "contains(`text`, 'hello')"
+        assert e.to_sql() == "contains(text, 'hello')"

    def test_contains_with_str_coerce(self):
        e = col("text").contains("hello")
        assert isinstance(e, Expr)
-        assert e.to_sql() == "contains(`text`, 'hello')"
+        assert e.to_sql() == "contains(text, 'hello')"

    def test_chained_lower_eq(self):
        e = col("name").lower() == lit("alice")
        assert isinstance(e, Expr)
-        assert e.to_sql() == "(lower(`name`) = 'alice')"
+        assert e.to_sql() == "(lower(name) = 'alice')"


 class TestExprCast:
    def test_cast_string(self):
        e = col("id").cast("string")
        assert isinstance(e, Expr)
-        assert e.to_sql() == "arrow_cast(id, 'Utf8')"
+        assert e.to_sql() == "CAST(id AS VARCHAR)"

    def test_cast_int32(self):
        e = col("score").cast("int32")
        assert isinstance(e, Expr)
-        assert e.to_sql() == "arrow_cast(score, 'Int32')"
+        assert e.to_sql() == "CAST(score AS INTEGER)"

    def test_cast_float64(self):
        e = col("val").cast("float64")
        assert isinstance(e, Expr)
-        assert e.to_sql() == "arrow_cast(val, 'Float64')"
+        assert e.to_sql() == "CAST(val AS DOUBLE)"

    def test_cast_pyarrow_type(self):
        e = col("score").cast(pa.int32())
        assert isinstance(e, Expr)
-        assert e.to_sql() == "arrow_cast(score, 'Int32')"
+        assert e.to_sql() == "CAST(score AS INTEGER)"

    def test_cast_pyarrow_float64(self):
        e = col("val").cast(pa.float64())
        assert isinstance(e, Expr)
-        assert e.to_sql() == "arrow_cast(val, 'Float64')"
+        assert e.to_sql() == "CAST(val AS DOUBLE)"

    def test_cast_pyarrow_string(self):
        e = col("id").cast(pa.string())
        assert isinstance(e, Expr)
-        assert e.to_sql() == "arrow_cast(id, 'Utf8')"
+        assert e.to_sql() == "CAST(id AS VARCHAR)"

    def test_cast_pyarrow_and_string_equivalent(self):
        # pa.int32() and "int32" should produce equivalent SQL
@@ -597,14 +597,14 @@ class TestExprIsin:
    def test_isin_strs(self):
        assert (
            col("status").isin(["active", "pending"]).to_sql()
-            == "`status` IN ('active', 'pending')"
+            == "status IN ('active', 'pending')"
        )

    def test_isin_coerces_and_mixes(self):
        assert col("id").isin([lit(1), 2]).to_sql() == "id IN (1, 2)"

    def test_isin_empty(self):
-        assert col("id").isin([]).to_sql() == "false"
+        assert col("id").isin([]).to_sql() == "id IN ()"

    def test_isin_filter(self, simple_table):
        result = simple_table.search().where(col("id").isin([1, 3, 5])).to_arrow()
@@ -12,8 +12,6 @@ from datetime import date
 import http.server
 import json
 from pathlib import Path
-import subprocess
-import sys
 import threading
 from typing import Optional

@@ -21,13 +19,7 @@ import pyarrow as pa
 import pytest

 import lancedb
-from lancedb.functions import (
-    PythonRuntimeSpec,
-    UdfDefinition,
-    _canonical_arrow_type,
-    _GRAMMAR_PRIMITIVES,
-    udf,
-)
+from lancedb.functions import UdfDefinition, udf

 THRESHOLD = 20
 _CACHE = None
@@ -69,80 +61,6 @@ def test_scalar_udf_matches_shared_registration_golden_and_remains_callable():
    }


-def _main_udf_source(
-    *, threshold: int = 20, input_annotation: str = "int", comparison: str = ">="
-) -> str:
-    return (
-        "from __future__ import annotations\n"
-        "from lancedb.functions import udf\n"
-        f"THRESHOLD = {threshold}\n"
-        "\n"
-        "@udf\n"
-        f"def label(value: {input_annotation}) -> str:\n"
-        f"    return 'big' if value {comparison} THRESHOLD else 'small'\n"
-        "\n"
-        "assert label.__module__ == '__main__'\n"
-        "print(label.registration_request.to_canonical_json())\n"
-    )
-
-
-def _run_main_udf(path: Path, source: str) -> dict:
-    path.parent.mkdir(parents=True, exist_ok=True)
-    path.write_text(source)
-    result = subprocess.run(
-        [sys.executable, str(path)],
-        check=True,
-        capture_output=True,
-        text=True,
-    )
-    return json.loads(result.stdout)
-
-
-def test_main_udf_registration_identity_is_stable_across_processes_and_paths(
-    tmp_path,
-):
-    source = _main_udf_source()
-    original_path = tmp_path / "original" / "job.py"
-    moved_path = tmp_path / "moved" / "renamed_job.py"
-
-    original_runs = [_run_main_udf(original_path, source) for _ in range(2)]
-    moved_run = _run_main_udf(moved_path, source)
-
-    assert len({run["artifact"]["digest"] for run in [*original_runs, moved_run]}) == 1
-    assert all(
-        run["signature"] == original_runs[0]["signature"]
-        for run in [original_runs[1], moved_run]
-    )
-    assert original_runs[0] == original_runs[1] == moved_run
-
-    body_change = _run_main_udf(
-        tmp_path / "changes" / "body.py", _main_udf_source(comparison=">")
-    )
-    global_change = _run_main_udf(
-        tmp_path / "changes" / "global.py", _main_udf_source(threshold=21)
-    )
-    annotation_change = _run_main_udf(
-        tmp_path / "changes" / "annotation.py",
-        _main_udf_source(input_annotation="float"),
-    )
-
-    baseline = original_runs[0]
-    assert baseline["signature"] == body_change["signature"]
-    assert baseline["signature"] == global_change["signature"]
-    assert baseline["signature"] != annotation_change["signature"]
-    assert (
-        len(
-            {
-                baseline["artifact"]["digest"],
-                body_change["artifact"]["digest"],
-                global_change["artifact"]["digest"],
-                annotation_change["artifact"]["digest"],
-            }
-        )
-        == 4
-    )
-
-
 def _run_packaged(definition, *args):
    """Execute the shipped artifact in a fresh namespace, as a worker would."""
    source = base64.b64decode(definition.registration_request.artifact.content.data)
@@ -151,78 +69,6 @@ def _run_packaged(definition, *args):
    return namespace[definition.registration_request.artifact.entrypoint](*args)


-def test_udf_conda_environment():
-    @udf(conda=["scipy", "numpy"], conda_channels=["conda-forge", "defaults"])
-    def halve(value: float) -> float:
-        return value / 2
-
-    request = json.loads(halve.registration_request.to_canonical_json())
-    assert request["runtime"]["environment"] == {
-        "kind": "conda",
-        "packages": ["numpy", "scipy"],
-        "channels": ["conda-forge", "defaults"],
-    }
-    pip_request = json.loads(normalize_score.registration_request.to_canonical_json())
-    assert "channels" not in pip_request["runtime"]["environment"]
-
-    with pytest.raises(ValueError, match="not both"):
-        udf(name="both", pip=["numpy"], conda=["numpy"])(lambda value: value)
-    with pytest.raises(ValueError, match="requires conda"):
-        udf(name="channels", conda_channels=["conda-forge"])(lambda value: value)
-
-
-def test_udf_gpu_marker_uses_gpu_runtime():
-    @udf(pip=["cupy-cuda12x"], gpu=True)
-    def double_on_gpu(value: int) -> int:
-        return value * 2
-
-    request = json.loads(double_on_gpu.registration_request.to_canonical_json())
-    assert request["runtime"]["kind"] == "python_v2"
-    assert request["runtime"]["gpu"] is True
-
-    @udf(pip=["pyarrow"])
-    def cpu_function(value: int) -> int:
-        return value
-
-    cpu_runtime = json.loads(cpu_function.registration_request.to_canonical_json())[
-        "runtime"
-    ]
-    assert cpu_runtime["kind"] == "python"
-    assert "gpu" not in cpu_runtime
-
-    def identity(value: int) -> int:
-        return value
-
-    for invalid in [None, 0, 1, -1, 1.5, "", "true", "1", "H100"]:
-        with pytest.raises(ValueError, match="gpu must be a boolean"):
-            udf(name="invalid_gpu", gpu=invalid)(identity)
-
-    base_runtime = {
-        "kind": "python_v2",
-        "python_version": "3.12",
-        "environment": {"kind": "pip"},
-    }
-    runtime = PythonRuntimeSpec.model_validate({**base_runtime, "gpu": True})
-    assert runtime.gpu is True
-    for invalid in [False, 1, 0, "", "true", "1", "H100"]:
-        with pytest.raises(ValueError, match="runtime.gpu must be true"):
-            PythonRuntimeSpec.model_validate({**base_runtime, "gpu": invalid})
-
-
-def test_unknown_runtime_discards_payload_before_known_field_validation():
-    for payload in [
-        {"kind": "python_v3", "gpu": {"model": "H100"}},
-        {"kind": "python_v3", "resources": []},
-        {
-            "kind": "python_v3",
-            "environment": {"kind": []},
-            "python_version": 3.15,
-        },
-    ]:
-        runtime = PythonRuntimeSpec.model_validate(payload)
-        assert runtime.to_canonical_json() == '{"kind":"python_v3"}'
-
-
 def test_udf_packages_attribute_access_and_body_imports():
    @udf
    def word_norm(body: str) -> float:
@@ -302,7 +148,9 @@ def test_udf_resolves_module_globals_before_builtins(tmp_path):
        udf(module.uses_callable_shadow)


-def test_canonical_arrow_type_prefers_the_compact_grammar():
+def test_canonical_arrow_type_is_exactly_the_grammar():
+    from lancedb.functions import _GRAMMAR_PRIMITIVES, _canonical_arrow_type
+
    golden = json.loads(
        (
            Path(__file__).parents[3]
@@ -313,19 +161,14 @@ def test_canonical_arrow_type_prefers_the_compact_grammar():
        case["arrow_type"] for case in golden["valid"] if "<" not in case["arrow_type"]
    ]
    assert [name for _, name in _GRAMMAR_PRIMITIVES] == primitives
-    assert _canonical_arrow_type(pa.list_(pa.field("item", pa.float32(), False))) == (
-        "list<float32>"
-    )
-    assert (
-        _canonical_arrow_type(pa.large_list(pa.field("item", pa.float32(), False)))
-        == "large_list<float32>"
-    )
    for outside in [
        pa.timestamp("us"),
        pa.decimal128(10, 2),
+        pa.large_string(),
        pa.large_binary(),
        pa.binary(4),
        pa.duration("s"),
+        pa.struct([pa.field("a", pa.int32())]),
        pa.list_(pa.float32(), 0),
        pa.list_(pa.timestamp("us")),
    ]:
@@ -515,27 +358,14 @@ def test_udf_recursion_versus_a_rebound_module_name(tmp_path):
        udf(raw_fact)


-def test_canonical_arrow_type_uses_exact_json_for_list_child_properties():
-    nullable = pa.list_(pa.float32())
-    assert json.loads(_canonical_arrow_type(nullable)) == {
-        "type": "list",
-        "fields": [
-            {
-                "name": "item",
-                "nullable": True,
-                "type": {"type": "float32"},
-            }
-        ],
-    }
-    named = pa.list_(pa.field("custom", pa.float32(), nullable=False))
-    assert json.loads(_canonical_arrow_type(named))["fields"][0]["name"] == "custom"
+def test_canonical_arrow_type_rejects_unrepresentable_list_children():
+    from lancedb.functions import _canonical_arrow_type
+
    for outside in [
+        pa.list_(pa.float32()),  # pyarrow default: nullable child
+        pa.list_(pa.field("custom", pa.float32(), nullable=False)),
        pa.list_(pa.field("item", pa.float32(), nullable=False, metadata={"k": "v"})),
        pa.list_(pa.field("item", pa.float32(), nullable=False), 0),
-        pa.list_(
-            pa.field("item", pa.float32(), nullable=False, metadata={"k": "v"}), 3
-        ),
-        pa.list_(pa.field("custom", pa.float32(), nullable=False), 3),
    ]:
        with pytest.raises(TypeError, match="unsupported Arrow type"):
            _canonical_arrow_type(outside)
@@ -545,29 +375,6 @@ def test_canonical_arrow_type_uses_exact_json_for_list_child_properties():
        )
        == "fixed_size_list<float32, 3>"
    )
-    fixed = json.loads(_canonical_arrow_type(pa.list_(pa.float32(), 3)))
-    assert fixed == {
-        "type": "fixed_size_list",
-        "fields": [
-            {
-                "name": "item",
-                "nullable": True,
-                "type": {"type": "float32"},
-            }
-        ],
-        "length": 3,
-    }
-    large = json.loads(_canonical_arrow_type(pa.large_list(pa.float32())))
-    assert large["type"] == "large_list"
-    assert large["fields"][0]["nullable"] is True
-
-    for invalid_struct in [
-        pa.struct([]),
-        pa.struct([pa.field("a", pa.int32()), pa.field("a", pa.int64())]),
-        pa.struct([pa.field("", pa.int32())]),
-    ]:
-        with pytest.raises(TypeError, match="unsupported Arrow type"):
-            _canonical_arrow_type(invalid_struct)


 def _calls_missing(value: int) -> int:
@@ -605,7 +412,6 @@ def _arrow_type_from_golden(spec: dict) -> pa.DataType:
        "null": pa.null(),
        "bool": pa.bool_(),
        "utf8": pa.string(),
-        "large_utf8": pa.large_string(),
        "binary": pa.binary(),
        "float16": pa.float16(),
        "float32": pa.float32(),
@@ -622,6 +428,8 @@ def test_arrow_type_grammar_matches_the_shared_golden():
            / "rust/lancedb/tests/fixtures/first_class_functions/v1/arrow_types.json"
        ).read_text()
    )
+    from lancedb.functions import _canonical_arrow_type
+
    emitted = {
        case["arrow_type"]: _canonical_arrow_type(_arrow_type_from_golden(case["json"]))
        for case in golden["valid"]
@@ -654,250 +462,6 @@ def test_explicit_arrow_schema_is_deterministic():
    assert signature.output.nullable is False


-def test_blob_fields_use_the_scalar_function_semantic_type():
-    @udf(
-        input_schema=pa.schema([lancedb.blob("image", nullable=False)]),
-        output_schema=lancedb.blob("result", nullable=False),
-    )
-    def copy_blob(image):
-        return image
-
-    signature = copy_blob.registration_request.signature
-    assert signature.inputs[0].arrow_type == "blob_v2"
-    assert signature.output.kind == "scalar"
-    assert signature.output.arrow_type == "blob_v2"
-
-
-def test_named_struct_function_can_include_a_blob_result_field():
-    @udf(
-        input_schema=pa.schema([lancedb.blob("image", nullable=False)]),
-        output_schema=pa.schema(
-            [
-                lancedb.blob("thumbnail", nullable=False),
-                pa.field("width", pa.int32(), nullable=False),
-            ]
-        ),
-    )
-    def inspect_blob(image):
-        return {"thumbnail": image, "width": 1}
-
-    output = inspect_blob.registration_request.signature.output
-    assert output.kind == "named_struct"
-    assert [(field.name, field.arrow_type) for field in output.fields] == [
-        ("thumbnail", "blob_v2"),
-        ("width", "int32"),
-    ]
-
-
-def test_metadata_marked_blob_field_uses_the_semantic_type():
-    extension = lancedb.blob("image", nullable=False).type
-    storage = (
-        extension.storage_type if isinstance(extension, pa.ExtensionType) else extension
-    )
-    metadata_blob = pa.field(
-        "image",
-        storage,
-        nullable=False,
-        metadata={"ARROW:extension:name": "lance.blob.v2"},
-    )
-
-    @udf(
-        input_schema=pa.schema([metadata_blob]),
-        output_schema=pa.field("size", pa.int64(), nullable=False),
-    )
-    def blob_size(image):
-        return len(image)
-
-    assert blob_size.registration_request.signature.inputs[0].arrow_type == "blob_v2"
-
-
-def test_blob_marker_rejects_invalid_storage_layout():
-    malformed = pa.field(
-        "image",
-        pa.int64(),
-        nullable=False,
-        metadata={"ARROW:extension:name": "lance.blob.v2"},
-    )
-
-    with pytest.raises(TypeError, match="requires a supported Blob storage layout"):
-
-        @udf(
-            input_schema=pa.schema([malformed]),
-            output_schema=pa.field("size", pa.int64(), nullable=False),
-        )
-        def blob_size(image):
-            return len(image)
-
-
-def test_nested_blob_signature_field_has_a_clear_error():
-    nested = pa.field(
-        "value",
-        pa.struct([lancedb.blob("image", nullable=False)]),
-        nullable=False,
-    )
-    with pytest.raises(TypeError, match="nested Blob v2 fields are not supported"):
-
-        @udf(
-            input_schema=pa.schema([nested]),
-            output_schema=pa.field("size", pa.int64(), nullable=False),
-        )
-        def blob_size(value):
-            return len(value["image"])
-
-
-def test_nested_non_blob_extension_is_not_silently_unwrapped():
-    class TestExtension(pa.ExtensionType):
-        def __init__(self):
-            super().__init__(pa.int64(), "test.function.extension")
-
-        def __arrow_ext_serialize__(self):
-            return b""
-
-        @classmethod
-        def __arrow_ext_deserialize__(cls, storage_type, serialized):
-            return cls()
-
-    nested = pa.field(
-        "value",
-        pa.struct([pa.field("extended", TestExtension(), nullable=False)]),
-        nullable=False,
-    )
-    with pytest.raises(TypeError, match="unsupported Arrow type"):
-
-        @udf(
-            input_schema=pa.schema([nested]),
-            output_schema=pa.field("result", pa.int64(), nullable=False),
-        )
-        def extension_value(value):
-            return value["extended"]
-
-
-def test_explicit_large_utf8_schemas_use_the_canonical_function_name():
-    input_schema = pa.schema([pa.field("text", pa.large_string(), nullable=True)])
-    output_schema = pa.field("result", pa.large_string(), nullable=False)
-
-    @udf(input_schema=input_schema, output_schema=output_schema)
-    def preserve(text):
-        return text
-
-    signature = preserve.registration_request.signature
-    assert signature.inputs[0].arrow_type == "large_utf8"
-    assert signature.inputs[0].nullable is True
-    assert signature.output.arrow_type == "large_utf8"
-    assert signature.output.nullable is False
-
-    nested = pa.struct([pa.field("text", pa.large_string(), nullable=True)])
-    assert json.loads(_canonical_arrow_type(nested)) == {
-        "type": "struct",
-        "fields": [
-            {
-                "name": "text",
-                "nullable": True,
-                "type": {"type": "large_utf8"},
-            }
-        ],
-    }
-
-
-def test_nested_struct_output_uses_canonical_exact_json():
-    token = pa.struct(
-        [
-            pa.field("position", pa.int32(), nullable=False),
-            pa.field("value", pa.string(), nullable=False),
-            pa.field("length", pa.int32(), nullable=False),
-        ]
-    )
-    analysis = pa.struct(
-        [
-            pa.field("normalized_text", pa.string(), nullable=False),
-            pa.field("has_content", pa.bool_(), nullable=False),
-            pa.field(
-                "metrics",
-                pa.struct(
-                    [
-                        pa.field("character_count", pa.int64(), nullable=False),
-                        pa.field("word_count", pa.int32(), nullable=False),
-                        pa.field("average_word_length", pa.float64(), nullable=False),
-                    ]
-                ),
-                nullable=False,
-            ),
-            pa.field(
-                "diagnostics",
-                pa.struct(
-                    [
-                        pa.field("status", pa.string(), nullable=False),
-                        pa.field(
-                            "normalization",
-                            pa.struct(
-                                [
-                                    pa.field("changed", pa.bool_(), nullable=False),
-                                    pa.field(
-                                        "original_length", pa.int64(), nullable=False
-                                    ),
-                                ]
-                            ),
-                            nullable=False,
-                        ),
-                    ]
-                ),
-                nullable=False,
-            ),
-            pa.field(
-                "token_preview",
-                pa.list_(pa.field("item", token, nullable=False)),
-                nullable=False,
-            ),
-        ]
-    )
-
-    @udf(
-        input_schema=pa.schema([pa.field("text", pa.string(), nullable=False)]),
-        output_schema=pa.field("analysis", analysis, nullable=False),
-    )
-    def analyze(text):
-        return {"normalized_text": text}
-
-    output = analyze.registration_request.signature.output
-    assert output.kind == "named_struct"
-    assert [field.name for field in output.fields] == [
-        "normalized_text",
-        "has_content",
-        "metrics",
-        "diagnostics",
-        "token_preview",
-    ]
-    metrics = json.loads(output.fields[2].arrow_type)
-    assert metrics == {
-        "type": "struct",
-        "fields": [
-            {
-                "name": "character_count",
-                "nullable": False,
-                "type": {"type": "int64"},
-            },
-            {
-                "name": "word_count",
-                "nullable": False,
-                "type": {"type": "int32"},
-            },
-            {
-                "name": "average_word_length",
-                "nullable": False,
-                "type": {"type": "float64"},
-            },
-        ],
-    }
-    preview = json.loads(output.fields[4].arrow_type)
-    assert preview["type"] == "list"
-    assert preview["fields"][0]["type"]["type"] == "struct"
-    assert [field["name"] for field in preview["fields"][0]["type"]["fields"]] == [
-        "position",
-        "value",
-        "length",
-    ]
-
-
 def test_annotation_and_explicit_schema_validation_fail_closed():
    with pytest.raises(TypeError, match="missing Function annotations"):

@@ -941,72 +505,6 @@ def test_annotation_and_explicit_schema_validation_fail_closed():
        def nullable_explicit(value):
            return value

-    for invalid_field in [
-        pa.field("", pa.int32(), nullable=False),
-        pa.field("result", pa.int32(), nullable=False, metadata={"k": "v"}),
-    ]:
-        with pytest.raises(TypeError, match="unsupported Arrow type"):
-
-            @udf(
-                input_schema=pa.schema([pa.field("value", pa.int64())]),
-                output_schema=pa.schema([invalid_field]),
-            )
-            def invalid_explicit_field(value):
-                return value
-
-    with pytest.raises(TypeError, match="unsupported Arrow type"):
-
-        @udf(
-            input_schema=pa.schema(
-                [pa.field("value", pa.int64(), metadata={"k": "v"})]
-            ),
-            output_schema=pa.int64(),
-        )
-        def input_field_metadata(value):
-            return value
-
-    with pytest.raises(TypeError, match="unsupported Arrow type"):
-
-        @udf(
-            input_schema=pa.schema([pa.field("value", pa.int64())]),
-            output_schema=pa.field(
-                "result", pa.int64(), nullable=False, metadata={"k": "v"}
-            ),
-        )
-        def scalar_output_field_metadata(value):
-            return value
-
-    struct_type = pa.struct([pa.field("value", pa.int64(), nullable=False)])
-    with pytest.raises(TypeError, match="unsupported Arrow type"):
-
-        @udf(
-            input_schema=pa.schema([pa.field("value", pa.int64())]),
-            output_schema=pa.field(
-                "result", struct_type, nullable=False, metadata={"k": "v"}
-            ),
-        )
-        def struct_output_field_metadata(value):
-            return {"value": value}
-
-    for input_schema, output_schema in [
-        (
-            pa.schema([pa.field("value", pa.int64())], metadata={"k": "v"}),
-            pa.int64(),
-        ),
-        (
-            pa.schema([pa.field("value", pa.int64())]),
-            pa.schema(
-                [pa.field("result", pa.int64(), nullable=False)],
-                metadata={"k": "v"},
-            ),
-        ),
-    ]:
-        with pytest.raises(TypeError, match="schema metadata"):
-
-            @udf(input_schema=input_schema, output_schema=output_schema)
-            def schema_metadata(value):
-                return value
-

 def test_local_function_catalog_operations_are_not_supported(tmp_path):
    db = lancedb.connect(tmp_path)
@@ -1017,8 +515,6 @@ def test_local_function_catalog_operations_are_not_supported(tmp_path):
        db.create_function_async(normalize_score)
    with pytest.raises(NotImplementedError, match=message):
        db.get_function("normalize_score", version="fv_exact")
-    with pytest.raises(NotImplementedError, match=message):
-        db.drop_function("normalize_score", version="fv_exact")


@contextlib.contextmanager
@@ -1064,12 +560,6 @@ def _mock_remote_function_catalog():
                    "version": "fv_exact",
                }
                response = state["version"]
-            elif self.path == "/v1/functions/drop":
-                assert body == {
-                    "name": "normalize_score",
-                    "version": "fv_exact",
-                }
-                response = {"dropped": True}
            else:
                status = 404
                response = {"error": "not found"}
@@ -1128,40 +618,3 @@ def test_blocking_remote_registration_returns_function_version():
        "/v1/functions/create",
        "/v1/jobs/describe",
    ]
-
-
-def test_remote_drop_function_sends_exact_version():
-    with _mock_remote_function_catalog() as (host, state):
-        db = lancedb.connect(
-            "db://dev",
-            api_key="fake",
-            host_override=host,
-            client_config={"retry_config": {"retries": 0}},
-        )
-        assert db.drop_function("normalize_score", version="fv_exact") is True
-
-    assert state["requests"] == [
-        (
-            "/v1/functions/drop",
-            {"name": "normalize_score", "version": "fv_exact"},
-        )
-    ]
-
-
-@pytest.mark.asyncio
-async def test_async_remote_drop_function_sends_exact_version():
-    with _mock_remote_function_catalog() as (host, state):
-        db = await lancedb.connect_async(
-            "db://dev",
-            api_key="fake",
-            host_override=host,
-            client_config={"retry_config": {"retries": 0}},
-        )
-        assert await db.drop_function("normalize_score", version="fv_exact") is True
-
-    assert state["requests"] == [
-        (
-            "/v1/functions/drop",
-            {"name": "normalize_score", "version": "fv_exact"},
-        )
-    ]
@@ -25,7 +25,6 @@ from lancedb.db import DBConnection
 from lancedb.index import FTS
 from lancedb.query import (
    BoostQuery,
-    DocumentGranularity,
    MatchQuery,
    MultiMatchQuery,
    PhraseQuery,
@@ -246,55 +245,6 @@ def test_create_inverted_index_rejects_invalid_block_size(table):
        table.create_index("text", config=FTS(block_size=129))


-def test_list_element_document_granularity(tmp_path):
-    docs_type = pa.list_(pa.struct([pa.field("content", pa.string())]))
-    docs = pa.array(
-        [
-            [
-                {"content": "alpha beta"},
-                None,
-                {"content": ""},
-                {"content": "the and"},
-                {"content": "alpha beta"},
-            ]
-        ],
-        type=docs_type,
-    )
-    table = ldb.connect(tmp_path).create_table(
-        "list_element_docs", pa.table({"id": [0], "docs": docs})
-    )
-    row_table = ldb.connect(tmp_path).create_table(
-        "row_docs", pa.table({"id": [0], "docs": docs})
-    )
-    row_table.create_index("docs.content", config=FTS())
-    row_result = row_table.search(MatchQuery("alpha", "docs.content")).to_arrow()
-    assert row_result.num_rows == 1
-    assert "_doc_index" not in row_result.column_names
-
-    granularity = DocumentGranularity.LIST_ELEMENT
-    table.create_index(
-        "docs.content",
-        config=FTS(with_position=True, document_granularity=granularity),
-    )
-    assert table.list_indices()[0].columns == ["docs.content"]
-
-    def coordinates(query):
-        result = table.search(query).limit(10).to_arrow()
-        doc_index_type = result.schema.field("_doc_index").type
-        assert pa.types.is_list(doc_index_type)
-        assert doc_index_type.value_type == pa.uint32()
-        return sorted(result["_doc_index"].to_pylist())
-
-    assert coordinates(
-        MatchQuery("alpha", "docs.content", document_granularity=granularity)
-    ) == [[0], [4]]
-    assert coordinates(
-        PhraseQuery("alpha beta", "docs.content", document_granularity=granularity)
-    ) == [[0], [4]]
-    assert coordinates(MatchQuery("alpha", "docs.content")) == [[0], [4]]
-    assert FTS().document_granularity is DocumentGranularity.ROW
-
-
 def test_create_inverted_index_respects_build_memory_limit(table):
    with pytest.raises(ValueError, match="exceeds worker memory limit"):
        table.create_index(
@@ -1139,20 +1089,6 @@ def test_fts_query_to_json():
    )
    assert json_str == expected

-    # Test MatchQuery with list-element document granularity
-    match_query = MatchQuery(
-        "hello world",
-        "text",
-        document_granularity=DocumentGranularity.LIST_ELEMENT,
-    )
-    json_str = match_query.to_json()
-    expected = (
-        '{"match":{"column":"text","terms":"hello world","boost":1.0,'
-        '"fuzziness":0,"max_expansions":50,"operator":"Or","prefix_length":0,'
-        '"document_granularity":"list_element"}}'
-    )
-    assert json_str == expected
-
    # Test MatchQuery with options
    match_query = MatchQuery("puppy", "text", fuzziness=2, boost=1.5, prefix_length=3)
    json_str = match_query.to_json()
@@ -1162,19 +1098,6 @@ def test_fts_query_to_json():
    )
    assert json_str == expected

-    # Test PhraseQuery with list-element document granularity
-    phrase_query = PhraseQuery(
-        "quick brown fox",
-        "title",
-        document_granularity=DocumentGranularity.LIST_ELEMENT,
-    )
-    json_str = phrase_query.to_json()
-    expected = (
-        '{"phrase":{"column":"title","terms":"quick brown fox","slop":0,'
-        '"document_granularity":"list_element"}}'
-    )
-    assert json_str == expected
-
    # Test PhraseQuery
    phrase_query = PhraseQuery("quick brown fox", "title")
    json_str = phrase_query.to_json()
@@ -675,21 +675,6 @@ def test_distance_range(table: lancedb.table.Table):
    assert res["_distance"].to_pylist() == [min_dist, max_dist]


-@pytest.mark.parametrize("expression", ["1 - _distance", "1.0 - _distance"])
-def test_select_arithmetic_with_distance(table, expression):
-    result = (
-        table.search([10, 10])
-        .select({"similarity": expression, "_distance": "_distance"})
-        .distance_type("cosine")
-        .to_arrow()
-    )
-
-    assert result.schema.field("similarity").type == pa.float32()
-    assert result["similarity"].to_pylist() == pytest.approx(
-        [1 - distance for distance in result["_distance"].to_pylist()]
-    )
-
-
@pytest.mark.asyncio
 async def test_distance_range_async(table_async: AsyncTable):
    q = [0, 0]
@@ -912,23 +897,6 @@ def test_query_builder_batches(table):
    assert rs_list["id"][1] == 2


-def test_batch_vector_query_shares_filtered_flat_scan(table):
-    query = (
-        table.search([[1.0, 2.0], [3.0, 4.0]])
-        .where("id > 0", prefilter=True)
-        .limit(1)
-        .select(["id"])
-    )
-
-    plan = query.explain_plan(verbose=True)
-    assert "KNNVectorDistance: queries=2" in plan
-    assert "UnionExec" not in plan
-
-    results = query.to_arrow()
-    assert len(results) == 2
-    assert results["query_index"].to_pylist() == [0, 1]
-
-
 def test_dynamic_projection(table):
    rs = (
        LanceVectorQueryBuilder(table, [0, 0], "vector")
@@ -1923,21 +1891,6 @@ def test_take_queries(tmp_path):
        17,
    ]

-    # Duplicate offsets are occurrences, not set members. Ordering is unspecified.
-    assert sorted(table.take_offsets([5, 2, 5, 17]).to_pandas()["idx"].to_list()) == [
-        2,
-        5,
-        5,
-        17,
-    ]
-
-    # Converting a take builder to its serializable query representation must
-    # retain occurrence metadata and execute with the same multiplicity.
-    query = table.take_offsets([5, 2, 5, 17]).select(["idx"]).to_query_object()
-    assert query.take_offsets == [5, 2, 5, 17]
-    converted = table._execute_query(query).read_all()
-    assert sorted(converted["idx"].to_pylist()) == [2, 5, 5, 17]
-
    # Take by row id
    assert list(
        sorted(table.take_row_ids([5, 2, 17]).to_pandas()["idx"].to_list())
@@ -479,49 +479,24 @@ def test_remote_permutation_is_picklable():
                match = re.search(
                    r"_rowoffset\s+in\s+\((.*?)\)", body["filter"], re.IGNORECASE
                )
-                offsets = list(
-                    dict.fromkeys(int(o.strip()) for o in match.group(1).split(","))
-                )
+                offsets = [int(o.strip()) for o in match.group(1).split(",")]
            else:
                offsets = list(range(len(rows)))
-            columns = body.get("columns") or ["a"]
-            table = pa.table(
-                {
-                    column: (
-                        [rows[offset] for offset in offsets]
-                        if column == "a"
-                        else offsets
-                    )
-                    for column in columns
-                }
-            )
+            table = pa.table({"a": [rows[offset] for offset in offsets]})

            request.send_response(200)
            request.send_header("Content-Type", "application/vnd.apache.arrow.file")
            request.end_headers()
            with pa.ipc.new_file(request.wfile, schema=table.schema) as writer:
-                writer.write_table(table, max_chunksize=2)
+                writer.write_table(table)
        else:
            request.send_response(404)
            request.end_headers()

    with mock_lancedb_connection(handler) as db:
-        table = db.open_table("test")
-        assert table.take_offsets([0, 2, 0, 4]).to_list() == [
-            {"a": 0},
-            {"a": 0},
-            {"a": 2},
-            {"a": 4},
-        ]
-
-        permutation = Permutation.identity(table)
+        permutation = Permutation.identity(db.open_table("test"))
        restored = pickle.loads(pickle.dumps(permutation))
-        assert restored.__getitems__([0, 2, 0, 4]) == [
-            {"a": 0},
-            {"a": 2},
-            {"a": 0},
-            {"a": 4},
-        ]
+        assert restored.__getitems__([0, 2, 4]) == [{"a": 0}, {"a": 2}, {"a": 4}]


 def test_create_table_exist_ok():
@@ -1643,49 +1618,6 @@ def test_query_sync_fts():
        )


-def test_query_sync_fts_document_granularity():
-    from lancedb.query import DocumentGranularity, MatchQuery
-
-    def handler(body):
-        assert body == {
-            "full_text_query": {
-                "query": {
-                    "match": {
-                        "column": "docs.content",
-                        "terms": "alpha",
-                        "boost": 1.0,
-                        "fuzziness": 0,
-                        "max_expansions": 50,
-                        "operator": "Or",
-                        "prefix_length": 0,
-                        "document_granularity": "list_element",
-                    }
-                }
-            },
-            "k": 10,
-            "prefilter": True,
-            "vector": [],
-            "version": None,
-        }
-        return pa.table(
-            {
-                "id": [1, 1],
-                "_doc_index": pa.array([[0], [4]], type=pa.list_(pa.uint32())),
-            }
-        )
-
-    with query_test_table(handler, server_version=Version("0.6.0")) as table:
-        result = table.search(
-            MatchQuery(
-                "alpha",
-                "docs.content",
-                document_granularity=DocumentGranularity.LIST_ELEMENT,
-            )
-        ).to_arrow()
-
-    assert result["_doc_index"].to_pylist() == [[0], [4]]
-
-
 def test_query_sync_hybrid():
    def handler(body):
        if "full_text_query" in body:
@@ -2534,26 +2466,6 @@ def test_remote_connection_jobs_surface():
            request.send_header("Content-Type", "application/json")
            request.end_headers()
            request.wfile.write(b'{"job_id": "job-1"}')
-        elif request.path == "/v1/jobs/pause":
-            if payload["job_id"] != "job-1":
-                request.send_response(404)
-                request.end_headers()
-                return
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(b'{"job_id": "job-1", "paused": true}')
-        elif request.path == "/v1/jobs/resume":
-            if payload["job_id"] != "job-1":
-                request.send_response(404)
-                request.end_headers()
-                return
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(
-                b'{"job_id": "job-1", "resumed": false, "still_pausing": true}'
-            )
        elif request.path == "/v1/jobs/query_events":
            assert payload["job_id"] == "job-1"
            request.send_response(200)
@@ -2582,9 +2494,6 @@ def test_remote_connection_jobs_surface():
        assert db.cancel_job("job-1") is True
        assert db.cancel_job("missing") is False

-        assert db.pause_job("job-1") == "pausing"
-        assert db.resume_job("job-1") == "still_pausing"
-
        batches = db.job_history("job-1")
        assert len(batches) == 1
        assert batches[0].num_rows == 2
@@ -4,7 +4,6 @@

 import asyncio
 import copy
-from concurrent.futures import ThreadPoolExecutor
 from datetime import timedelta
 import threading

@@ -87,25 +86,6 @@ def test_s3_lifecycle(s3_bucket: str):
    asyncio.run(test())


-@pytest.mark.s3_test
-def test_concurrent_open_table(s3_bucket: str):
-    uri = f"s3://{s3_bucket}/test_concurrent_open_table"
-    db = lancedb.connect(uri, storage_options=copy.copy(CONFIG))
-    db.create_table("test", pa.table({"x": [1, 2, 3]}))
-
-    num_workers = 32
-    barrier = threading.Barrier(num_workers)
-
-    def open_and_count(_):
-        barrier.wait()
-        return db.open_table("test").count_rows()
-
-    with ThreadPoolExecutor(max_workers=num_workers) as pool:
-        row_counts = list(pool.map(open_and_count, range(num_workers)))
-
-    assert row_counts == [3] * num_workers
-
-
@pytest.fixture()
 def kms_key():
    kms = get_boto3_client("kms", endpoint_url=CONFIG["aws_endpoint"])
@@ -11,7 +11,6 @@ import warnings
 import weakref
 from concurrent.futures import ThreadPoolExecutor
 from datetime import date, datetime, timedelta
-from decimal import Decimal
 from time import sleep
 from typing import List
 from unittest.mock import patch
@@ -337,21 +336,6 @@ async def test_update_async(mem_db_async: AsyncConnection):
    assert await table.count_rows("id == 10") == 1


-@pytest.mark.asyncio
-async def test_update_expr_filter_literals_async(mem_db_async: AsyncConnection):
-    values = ["5", "4.66e-84", "it's"]
-    table = await mem_db_async.create_table(
-        "update_expr_literals",
-        data=[{"field": value, "result": "original"} for value in values],
-    )
-
-    for value in values:
-        update_res = await table.update({"result": value}, where=col("field") == value)
-        assert update_res.rows_updated == 1
-
-    assert (await table.to_arrow())["result"].to_pylist() == values
-
-
 def test_create_table(mem_db: DBConnection):
    schema = pa.schema(
        {
@@ -2359,148 +2343,6 @@ def test_update(mem_db: DBConnection):
    assert np.allclose(v, np.array([[1.2, 1.9], [1.1, 1.1]]))


-def test_update_expr_filter_literals(mem_db: DBConnection):
-    values = ["5", "4.66e-84", "it's"]
-    table = mem_db.create_table(
-        "update_expr_literals",
-        data=[{"field": value, "result": "original"} for value in values],
-    )
-
-    for value in values:
-        update_res = table.update(where=col("field") == value, values={"result": value})
-        assert update_res.rows_updated == 1
-
-    assert table.to_arrow()["result"].to_pylist() == values
-
-
-def test_update_expr_filter_preserves_typed_semantics(mem_db: DBConnection):
-    low = Decimal("1.234567890123456789")
-    high = Decimal("1.234567890123456790")
-    decimal_schema = pa.schema(
-        [("val", pa.decimal128(19, 18)), ("result", pa.string())]
-    )
-    decimal_table = mem_db.create_table(
-        "update_expr_decimal",
-        pa.table(
-            {"val": [low, high], "result": ["old", "old"]},
-            schema=decimal_schema,
-        ),
-    )
-    predicate = col("val") < lit(high)
-    assert decimal_table.search().where(predicate).to_arrow().num_rows == 1
-    result = decimal_table.update(where=predicate, values={"result": "new"})
-    assert result.rows_updated == 1
-
-    keyword_table = mem_db.create_table(
-        "update_expr_keyword", [{"null": 1, "result": "old"}]
-    )
-    predicate = col("null") == 1
-    assert keyword_table.search().where(predicate).to_arrow().num_rows == 1
-    result = keyword_table.update(where=predicate, values={"result": "new"})
-    assert result.rows_updated == 1
-
-    empty_in_table = mem_db.create_table(
-        "update_expr_empty_in", [{"id": 1, "result": "old"}]
-    )
-    predicate = col("id").isin([])
-    assert empty_in_table.search().where(predicate).to_arrow().num_rows == 0
-    result = empty_in_table.update(where=predicate, values={"result": "new"})
-    assert result.rows_updated == 0
-
-    marker = "__lancedb_binary_placeholder_0__"
-    binary_schema = pa.schema(
-        [("payload", pa.binary()), ("text", pa.string()), ("result", pa.string())]
-    )
-    binary_table = mem_db.create_table(
-        "update_expr_binary",
-        pa.table(
-            {
-                "payload": [b"\x01", b"\x02"],
-                "text": ["other", marker],
-                "result": ["old", "old"],
-            },
-            schema=binary_schema,
-        ),
-    )
-    predicate = (col("payload") == lit(b"\x01")) | (col("text") == marker)
-    assert binary_table.search().where(predicate).to_arrow().num_rows == 2
-    result = binary_table.update(where=predicate, values={"result": "new"})
-    assert result.rows_updated == 2
-
-    nonfinite_table = mem_db.create_table(
-        "update_expr_nonfinite",
-        [{"x": 1.0, "result": "old"}, {"x": 2.0, "result": "old"}],
-    )
-    predicate = col("x") < float("inf")
-    assert nonfinite_table.search().where(predicate).to_arrow().num_rows == 2
-    result = nonfinite_table.update(where=predicate, values={"result": "new"})
-    assert result.rows_updated == 2
-
-    float16_table = mem_db.create_table(
-        "update_expr_float16",
-        [{"x": 1.0, "result": "old"}, {"x": 3.0, "result": "old"}],
-    )
-    predicate = col("x").cast(pa.float16()) < 2.0
-    assert float16_table.search().where(predicate).to_arrow().num_rows == 1
-    result = float16_table.update(where=predicate, values={"result": "new"})
-    assert result.rows_updated == 1
-
-    string_cast_table = mem_db.create_table(
-        "update_expr_string_cast",
-        [{"x": 1, "result": "old"}, {"x": 2, "result": "old"}],
-    )
-    predicate = col("x").cast("string") == "1"
-    assert string_cast_table.search().where(predicate).to_arrow().num_rows == 1
-    result = string_cast_table.update(where=predicate, values={"result": "new"})
-    assert result.rows_updated == 1
-
-    quoted_identifier_schema = pa.schema(
-        [("payload", pa.binary()), ("odd'name", pa.int64()), ("result", pa.string())]
-    )
-    quoted_identifier_table = mem_db.create_table(
-        "update_expr_quoted_identifier",
-        pa.table(
-            {"payload": [b"\x01"], "odd'name": [1], "result": ["old"]},
-            schema=quoted_identifier_schema,
-        ),
-    )
-    predicate = (col("payload") == lit(b"\x01")) & (col("odd'name") == 1)
-    assert quoted_identifier_table.search().where(predicate).to_arrow().num_rows == 1
-    result = quoted_identifier_table.update(where=predicate, values={"result": "new"})
-    assert result.rows_updated == 1
-
-    decimal256_schema = pa.schema(
-        [("val", pa.decimal256(40, 2)), ("result", pa.string())]
-    )
-    decimal256_table = mem_db.create_table(
-        "update_expr_decimal256",
-        pa.table(
-            {
-                "val": [Decimal("1.00"), Decimal("3.00")],
-                "result": ["old", "old"],
-            },
-            schema=decimal256_schema,
-        ),
-    )
-    predicate = col("val") < lit(Decimal("2.00")).cast(pa.decimal256(40, 2))
-    assert decimal256_table.search().where(predicate).to_arrow().num_rows == 1
-    result = decimal256_table.update(where=predicate, values={"result": "new"})
-    assert result.rows_updated == 1
-
-    binary_empty_table = mem_db.create_table(
-        "update_expr_binary_empty",
-        pa.table(
-            {"payload": [b"\x01", b"\x02"], "result": ["old", "old"]},
-            schema=pa.schema([("payload", pa.binary()), ("result", pa.string())]),
-        ),
-    )
-    predicate = (col("payload") == lit(b"\x01")).isin([])
-    assert binary_empty_table.search().where(predicate).to_arrow().num_rows == 0
-    assert predicate.to_sql() == "false"
-    result = binary_empty_table.update(where=predicate, values={"result": "new"})
-    assert result.rows_updated == 0
-
-
 def test_update_with_arrow_scalar(mem_db: DBConnection):
    schema = pa.schema({"id": pa.int64(), "vector": pa.list_(pa.float32(), 4)})
    table = mem_db.create_table("my_table", schema=schema)
@@ -4087,29 +3929,6 @@ def test_computed_column_rejects_transforms_and_computed_together(tmp_path):
        table.add_columns({"a": "x + 1"}, computed={"b": "x * 2"})


-def test_computed_column_blob_projection_inherits_semantics(tmp_path):
-    schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("image")])
-    db = lancedb.connect(tmp_path)
-    table = db.create_table("computed_column_blob", schema=schema)
-    table.add(
-        [
-            {"id": 1, "image": b"hello"},
-            {"id": 2, "image": b""},
-            {"id": 3, "image": None},
-        ]
-    )
-
-    table.add_columns(computed={"image_copy": "image", "second_copy": "image_copy"})
-    assert table.refresh_column("image_copy").rows_filled == 2
-    assert table.refresh_column("second_copy").rows_filled == 2
-    assert table.blob_columns() == ["image", "image_copy", "second_copy"]
-
-    hits = table.search().with_row_id(True).limit(10).to_arrow()
-    rows = sorted(zip(hits["id"].to_pylist(), hits["_rowid"].to_pylist()))
-    copied = table.fetch_blobs("second_copy", [row_id for _, row_id in rows])
-    assert copied.to_pylist() == [b"hello", b"", None]
-
-
@pytest.mark.asyncio
 async def test_computed_column_async(tmp_path):
    db = await lancedb.connect_async(tmp_path)
@@ -7,7 +7,6 @@ import pathlib
 from typing import Optional

 import lance
-from lance.blob import BlobType as LanceBlobType
 from lancedb.conftest import MockTextEmbeddingFunction
 from lancedb.embeddings.base import EmbeddingFunctionConfig
 from lancedb.embeddings.registry import EmbeddingFunctionRegistry
@@ -908,165 +907,6 @@ def test_cast_to_target_schema():
    assert output == expected


-def test_cast_to_target_schema_coerces_binary_to_blob_v2():
-    data = pa.table({"image": pa.array([b"hello", None], type=pa.binary())})
-    target = pa.schema([lancedb.blob("image")])
-
-    output = _cast_to_target_schema(data.to_reader(), target).read_all()
-
-    image = output["image"].chunk(0)
-    assert type(image.type) is lancedb.BlobType
-    assert image.storage.to_pylist() == [
-        {"data": b"hello", "uri": None, "position": None, "size": None},
-        None,
-    ]
-
-
-def test_cast_to_target_schema_coerces_binary_to_metadata_blob_struct():
-    storage = lancedb.blob("image").type.storage_type
-    target = pa.schema(
-        [
-            pa.field(
-                "image",
-                storage,
-                metadata={
-                    b"ARROW:extension:name": b"lance.blob.v2",
-                    b"ARROW:extension:metadata": b"",
-                },
-            )
-        ]
-    )
-    data = pa.table({"image": pa.array([b"hello", None], type=pa.binary())})
-
-    output = _cast_to_target_schema(data.to_reader(), target).read_all()
-
-    image = output["image"].chunk(0)
-    assert not isinstance(image.type, pa.ExtensionType)
-    assert image.to_pylist() == [
-        {"data": b"hello", "uri": None, "position": None, "size": None},
-        None,
-    ]
-
-
-def test_cast_to_target_schema_coerces_nested_binary_blob():
-    data = pa.table(
-        {
-            "info": pa.array(
-                [{"blob": b"hello"}, {"blob": None}],
-                type=pa.struct([pa.field("blob", pa.binary())]),
-            )
-        }
-    )
-    target = pa.schema([pa.field("info", pa.struct([lancedb.blob("blob")]))])
-
-    output = _cast_to_target_schema(data.to_reader(), target).read_all()
-
-    blob = output["info"].chunk(0).field("blob")
-    assert type(blob.type) is lancedb.BlobType
-    assert blob.storage.to_pylist() == [
-        {"data": b"hello", "uri": None, "position": None, "size": None},
-        None,
-    ]
-
-
-def test_cast_to_target_schema_coerces_list_binary_blob_with_inferred_child_name():
-    data = pa.table(
-        {"images": pa.array([[b"a", b"b"], None], type=pa.list_(pa.binary()))}
-    )
-    target = pa.schema([pa.field("images", pa.list_(lancedb.blob("image")))])
-
-    output = _cast_to_target_schema(data.to_reader(), target).read_all()
-
-    images = output["images"].chunk(0)
-    assert images.type.value_field.name == "image"
-    assert type(images.type.value_type) is lancedb.BlobType
-    assert images.to_pylist()[1] is None
-    assert images.values.storage.to_pylist() == [
-        {"data": b"a", "uri": None, "position": None, "size": None},
-        {"data": b"b", "uri": None, "position": None, "size": None},
-    ]
-
-
-def test_list_blob_coercion_preserves_null_slots_with_nonzero_extent():
-    child = pa.field("image", pa.binary())
-    source = pa.ListArray.from_arrays(
-        pa.array([0, 2, 4], type=pa.int32()),
-        pa.array([b"a", b"b", b"dead", b"beef"], type=pa.binary()),
-        mask=pa.array([False, True]),
-    ).cast(pa.list_(child))
-    target = pa.schema([pa.field("images", pa.list_(lancedb.blob("image")))])
-
-    output = _cast_to_target_schema(
-        pa.table({"images": source}).to_reader(), target
-    ).read_all()
-
-    images = output["images"].chunk(0)
-    assert images.to_pylist()[1] is None
-    assert [b["data"] for b in images.to_pylist()[0]] == [b"a", b"b"]
-
-
-def test_fixed_size_list_blob_coercion_keeps_null_rows():
-    child = pa.field("frame", pa.binary())
-    source = (
-        pa.FixedSizeListArray.from_arrays(
-            pa.array([b"a", b"b", b"c", b"d"], type=pa.binary()), 2
-        )
-        .take(pa.array([0, None], type=pa.int32()))
-        .cast(pa.list_(child, 2))
-    )
-    target = pa.schema([pa.field("frames", pa.list_(lancedb.blob("frame"), 2))])
-
-    output = _cast_to_target_schema(
-        pa.table({"frames": source}).to_reader(), target
-    ).read_all()
-
-    frames = output["frames"].chunk(0)
-    assert frames.to_pylist()[1] is None
-    assert [b["data"] for b in frames.to_pylist()[0]] == [b"a", b"b"]
-
-
-def test_cast_to_target_schema_accepts_pylance_blob_v2():
-    target_type = lancedb.BlobType()
-    source = lance.blob_array([b"hello", None])
-    assert type(source.type) is LanceBlobType
-    assert type(source.type) is type(target_type)
-    data = pa.table({"image": source})
-    target = pa.schema([pa.field("image", target_type)])
-
-    output = _cast_to_target_schema(data.to_reader(), target).read_all()
-
-    image = output["image"].chunk(0)
-    assert type(image.type) is LanceBlobType
-    assert image.type == target_type
-    assert image.storage.to_pylist() == [
-        {"data": b"hello", "uri": None, "position": None, "size": None},
-        None,
-    ]
-
-
-def test_cast_to_target_schema_rejects_different_blob_v2_class():
-    class OtherBlobType(pa.ExtensionType):
-        def __init__(self):
-            super().__init__(lancedb.BlobType().storage_type, "lance.blob.v2")
-
-        def __arrow_ext_serialize__(self) -> bytes:
-            return b""
-
-        @classmethod
-        def __arrow_ext_deserialize__(
-            cls, storage_type: pa.DataType, serialized: bytes
-        ) -> "OtherBlobType":
-            return cls()
-
-    storage = lance.blob_array([b"hello"]).storage
-    source = pa.ExtensionArray.from_storage(OtherBlobType(), storage)
-    data = pa.table({"image": source})
-    target = pa.schema([lancedb.blob("image")])
-
-    with pytest.raises(pa.ArrowTypeError, match="different extension type"):
-        _cast_to_target_schema(data.to_reader(), target).read_all()
-
-
 def test_sanitize_data_stream():
    # Make sure we don't collect the whole stream when running sanitize_data
    schema = pa.schema({"a": pa.int32()})
@@ -629,17 +629,6 @@ impl Connection {
        })
    }

-    pub fn drop_function(
-        self_: PyRef<'_, Self>,
-        name: String,
-        version: String,
-    ) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.get_inner()?.clone();
-        future_into_py(self_.py(), async move {
-            inner.drop_function(name, version).await.infer_error()
-        })
-    }
-
    pub fn list_jobs(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
        let inner = self_.get_inner()?.clone();
        future_into_py(self_.py(), async move {
@@ -666,30 +655,6 @@ impl Connection {
        })
    }

-    pub fn pause_job(self_: PyRef<'_, Self>, job_id: String) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.get_inner()?.clone();
-        future_into_py(self_.py(), async move {
-            let status = inner.pause_job(&job_id).await.infer_error()?;
-            Ok(match status {
-                lancedb::database::PauseJobStatus::Pausing => "pausing",
-                lancedb::database::PauseJobStatus::AlreadyPaused => "already_paused",
-                lancedb::database::PauseJobStatus::Committing => "committing",
-            })
-        })
-    }
-
-    pub fn resume_job(self_: PyRef<'_, Self>, job_id: String) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.get_inner()?.clone();
-        future_into_py(self_.py(), async move {
-            let status = inner.resume_job(&job_id).await.infer_error()?;
-            Ok(match status {
-                lancedb::database::ResumeJobStatus::Resumed => "resumed",
-                lancedb::database::ResumeJobStatus::StillPausing => "still_pausing",
-                lancedb::database::ResumeJobStatus::NotPaused => "not_paused",
-            })
-        })
-    }
-
    #[pyo3(signature = (job_id=None))]
    pub fn job_history(
        self_: PyRef<'_, Self>,
@@ -130,14 +130,6 @@ impl PyExpr {

    // ── utilities ────────────────────────────────────────────────────────────

-    /// Return the referenced column name for a bare column expression.
-    fn column_name(&self) -> Option<String> {
-        match &self.0 {
-            DfExpr::Column(column) if column.relation.is_none() => Some(column.name.clone()),
-            _ => None,
-        }
-    }
-
    /// Render the expression as a SQL string (useful for debugging).
    fn to_sql(&self) -> PyResult<String> {
        lancedb::expr::expr_to_sql_string(&self.0).map_err(|e| PyValueError::new_err(e.to_string()))
@@ -8,7 +8,7 @@ use lancedb::index::vector::{
 };
 use lancedb::index::{
    Index as LanceDbIndex,
-    scalar::{BTreeIndexBuilder, DocumentGranularity, FmIndexBuilder, FtsIndexBuilder},
+    scalar::{BTreeIndexBuilder, FmIndexBuilder, FtsIndexBuilder},
 };
 use pyo3::IntoPyObject;
 use pyo3::types::PyStringMethods;
@@ -60,11 +60,7 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                    .ngram_min_length(params.ngram_min_length)
                    .ngram_max_length(params.ngram_max_length)
                    .ngram_prefix_only(params.prefix_only)
-                    .custom_stop_words(params.custom_stop_words)
-                    .document_granularity(
-                        DocumentGranularity::try_from(params.document_granularity.as_str())
-                            .map_err(|err| PyValueError::new_err(err.to_string()))?,
-                    );
+                    .custom_stop_words(params.custom_stop_words);
                if let Some(memory_limit) = params.memory_limit {
                    inner_opts = inner_opts.memory_limit_mb(memory_limit);
                }
@@ -225,7 +221,6 @@ struct FtsParams {
    block_size: usize,
    memory_limit: Option<u64>,
    num_workers: Option<usize>,
-    document_granularity: String,
 }

 #[derive(FromPyObject)]
@@ -486,7 +481,6 @@ mod tests {
    block_size = 128
    memory_limit = 2048
    num_workers = 7
-    document_granularity = 'row'

 config = FTS()",
                None,
@@ -1,7 +1,6 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors

-use std::collections::HashMap;
 use std::sync::Arc;
 use std::time::Duration;

@@ -17,8 +16,8 @@ use arrow::pyarrow::FromPyArrow;
 use arrow::pyarrow::IntoPyArrow;
 use arrow::pyarrow::ToPyArrow;
 use lancedb::index::scalar::{
-    BooleanQuery, BoostQuery, DocumentGranularity, FtsQuery, FullTextSearchQuery, MatchQuery,
-    MultiMatchQuery, Occur, Operator, PhraseQuery,
+    BooleanQuery, BoostQuery, FtsQuery, FullTextSearchQuery, MatchQuery, MultiMatchQuery, Occur,
+    Operator, PhraseQuery,
 };
 use lancedb::query::AnalyzePlanDistributedMetrics;
 use lancedb::query::QueryBase;
@@ -77,16 +76,8 @@ impl<'a, 'py> FromPyObject<'a, 'py> for PyLanceDB<FtsQuery> {
                let max_expansions = ob.getattr("max_expansions")?.extract()?;
                let operator = ob.getattr("operator")?.extract::<String>()?;
                let prefix_length = ob.getattr("prefix_length")?.extract()?;
-                let document_granularity = ob
-                    .getattr("document_granularity")?
-                    .extract::<Option<String>>()?
-                    .map(|value| {
-                        DocumentGranularity::try_from(value.as_str())
-                            .map_err(|err| PyValueError::new_err(err.to_string()))
-                    })
-                    .transpose()?;

-                let mut query =
+                Ok(Self(
                    MatchQuery::new(query)
                        .with_column(Some(column))
                        .with_boost(boost)
@@ -95,32 +86,21 @@ impl<'a, 'py> FromPyObject<'a, 'py> for PyLanceDB<FtsQuery> {
                        .with_operator(Operator::try_from(operator.as_str()).map_err(|e| {
                            PyValueError::new_err(format!("Invalid operator: {}", e))
                        })?)
-                        .with_prefix_length(prefix_length);
-                if let Some(document_granularity) = document_granularity {
-                    query = query.with_document_granularity(document_granularity);
-                }
-                Ok(Self(query.into()))
+                        .with_prefix_length(prefix_length)
+                        .into(),
+                ))
            }
            "PhraseQuery" => {
                let query = ob.getattr("query")?.extract()?;
                let column = ob.getattr("column")?.extract()?;
                let slop = ob.getattr("slop")?.extract()?;
-                let document_granularity = ob
-                    .getattr("document_granularity")?
-                    .extract::<Option<String>>()?
-                    .map(|value| {
-                        DocumentGranularity::try_from(value.as_str())
-                            .map_err(|err| PyValueError::new_err(err.to_string()))
-                    })
-                    .transpose()?;

-                let mut query = PhraseQuery::new(query)
-                    .with_column(Some(column))
-                    .with_slop(slop);
-                if let Some(document_granularity) = document_granularity {
-                    query = query.with_document_granularity(document_granularity);
-                }
-                Ok(Self(query.into()))
+                Ok(Self(
+                    PhraseQuery::new(query)
+                        .with_column(Some(column))
+                        .with_slop(slop)
+                        .into(),
+                ))
            }
            "BoostQuery" => {
                let positive: Self = ob.getattr("positive")?.extract()?;
@@ -187,13 +167,6 @@ impl<'py> IntoPyObject<'py> for PyLanceDB<FtsQuery> {
                kwargs.set_item("max_expansions", query.max_expansions)?;
                kwargs.set_item::<_, &str>("operator", query.operator.into())?;
                kwargs.set_item("prefix_length", query.prefix_length)?;
-                if let Some(document_granularity) = query.document_granularity {
-                    let value = match document_granularity {
-                        DocumentGranularity::Row => "row",
-                        DocumentGranularity::ListElement => "list_element",
-                    };
-                    kwargs.set_item("document_granularity", value)?;
-                }
                namespace
                    .getattr(intern!(py, "MatchQuery"))?
                    .call((query.terms, query.column.unwrap()), Some(&kwargs))
@@ -201,13 +174,6 @@ impl<'py> IntoPyObject<'py> for PyLanceDB<FtsQuery> {
            FtsQuery::Phrase(query) => {
                let kwargs = PyDict::new(py);
                kwargs.set_item("slop", query.slop)?;
-                if let Some(document_granularity) = query.document_granularity {
-                    let value = match document_granularity {
-                        DocumentGranularity::Row => "row",
-                        DocumentGranularity::ListElement => "list_element",
-                    };
-                    kwargs.set_item("document_granularity", value)?;
-                }
                namespace
                    .getattr(intern!(py, "PhraseQuery"))?
                    .call((query.terms, query.column.unwrap()), Some(&kwargs))
@@ -323,11 +289,9 @@ impl<'py> IntoPyObject<'py> for PyQueryVectors {
 pub struct PyQueryRequest {
    pub limit: Option<usize>,
    pub offset: Option<usize>,
-    pub take_offsets: Option<Vec<u64>>,
    pub filter: Option<PyQueryFilter>,
    pub full_text_search: Option<PyLanceDB<FtsQuery>>,
    pub select: PySelect,
-    pub select_source_columns: Option<HashMap<String, String>>,
    pub fast_search: Option<bool>,
    pub with_row_id: Option<bool>,
    pub use_lsm: Option<bool>,
@@ -354,12 +318,10 @@ impl From<AnyQuery> for PyQueryRequest {
            AnyQuery::Query(query_request) => Self {
                limit: query_request.limit,
                offset: query_request.offset,
-                take_offsets: query_request.take_offsets,
                filter: query_request.filter.map(PyQueryFilter),
                full_text_search: query_request
                    .full_text_search
                    .map(|fts| PyLanceDB(fts.query)),
-                select_source_columns: PySelect::source_columns(&query_request.select),
                select: PySelect(query_request.select),
                fast_search: Some(query_request.fast_search),
                with_row_id: Some(query_request.with_row_id),
@@ -383,10 +345,8 @@ impl From<AnyQuery> for PyQueryRequest {
            AnyQuery::VectorQuery(vector_query) => Self {
                limit: vector_query.base.limit,
                offset: vector_query.base.offset,
-                take_offsets: vector_query.base.take_offsets,
                filter: vector_query.base.filter.map(PyQueryFilter),
                full_text_search: None,
-                select_source_columns: PySelect::source_columns(&vector_query.base.select),
                select: PySelect(vector_query.base.select),
                fast_search: Some(vector_query.base.fast_search),
                with_row_id: Some(vector_query.base.with_row_id),
@@ -419,25 +379,6 @@ impl From<AnyQuery> for PyQueryRequest {
 #[derive(Clone)]
 pub struct PySelect(Select);

-impl PySelect {
-    fn source_columns(select: &Select) -> Option<HashMap<String, String>> {
-        match select {
-            Select::Expr(pairs) => Some(
-                pairs
-                    .iter()
-                    .filter_map(|(output, expr)| match expr {
-                        lancedb::expr::DfExpr::Column(column) if column.relation.is_none() => {
-                            Some((output.clone(), column.name.clone()))
-                        }
-                        _ => None,
-                    })
-                    .collect(),
-            ),
-            _ => None,
-        }
-    }
-}
-
 impl<'py> IntoPyObject<'py> for PySelect {
    type Target = PyAny;
    type Output = Bound<'py, Self::Target>;
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.38.0"
+version = "0.38.0-beta.10"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true
@@ -24,7 +24,7 @@ use crate::data::scannable::Scannable;
 use crate::database::listing::ListingDatabase;
 use crate::database::{
    CloneTableRequest, Database, DatabaseOptions, JobDescription, JobInfo, OpenTableRequest,
-    PauseJobStatus, ReadConsistency, ResumeJobStatus, TableNamesRequest,
+    ReadConsistency, TableNamesRequest,
 };
 use crate::embeddings::{EmbeddingRegistry, MemoryRegistry};
 use crate::error::{Error, Result};
@@ -523,21 +523,6 @@ impl Connection {
            .await
    }

-    /// Drop one exact immutable Function version from the remote catalog.
-    ///
-    /// Returns `true` when the server appended a Dropped transition and
-    /// `false` for an idempotent replay. Local databases return
-    /// [`Error::NotSupported`].
-    pub async fn drop_function(
-        &self,
-        name: impl AsRef<str>,
-        version: impl AsRef<str>,
-    ) -> Result<bool> {
-        self.internal
-            .drop_function(name.as_ref(), version.as_ref())
-            .await
-    }
-
    /// Rename a table in the database.
    ///
    /// This is only supported in LanceDB Cloud.
@@ -590,18 +575,6 @@ impl Connection {
        self.internal.cancel_job(job_id.as_ref()).await
    }

-    /// Pause a server-side job by id. Its workers drain and it stays parked
-    /// until resumed; see [`PauseJobStatus`] for the outcomes.
-    pub async fn pause_job(&self, job_id: impl AsRef<str>) -> Result<PauseJobStatus> {
-        self.internal.pause_job(job_id.as_ref()).await
-    }
-
-    /// Resume a paused server-side job by id. Its workers pick their work
-    /// back up from checkpoints; see [`ResumeJobStatus`] for the outcomes.
-    pub async fn resume_job(&self, job_id: impl AsRef<str>) -> Result<ResumeJobStatus> {
-        self.internal.resume_job(job_id.as_ref()).await
-    }
-
    /// The lifecycle event history of a server-side job (all jobs when
    /// `job_id` is `None`), as recorded Arrow batches.
    pub async fn job_history(&self, job_id: Option<&str>) -> Result<Vec<RecordBatch>> {
@@ -235,29 +235,6 @@ pub struct JobDescription {
    pub failure: Option<crate::error::JobFailure>,
 }

-/// The server's answer to a pause request.
-#[derive(Debug, Clone, Copy, PartialEq, Eq)]
-pub enum PauseJobStatus {
-    /// The pause was accepted; workers drain and the job stays parked.
-    Pausing,
-    /// The job was already paused, so a repeated pause changed nothing.
-    AlreadyPaused,
-    /// The job is finalizing its results and cannot be parked right now.
-    /// The commit is the short tail of a long job; retry shortly.
-    Committing,
-}
-
-/// The server's answer to a resume request.
-#[derive(Debug, Clone, Copy, PartialEq, Eq)]
-pub enum ResumeJobStatus {
-    /// The job re-entered the queue and will run again.
-    Resumed,
-    /// The pause's worker drain is not confirmed yet; retry shortly.
-    StillPausing,
-    /// The job was not paused, so there was nothing to resume.
-    NotPaused,
-}
-
 fn job_op_not_supported<T>(what: &str) -> Result<T> {
    Err(crate::error::Error::NotSupported {
        message: format!("{} is not supported by this database", what),
@@ -330,10 +307,6 @@ pub trait Database:
    ) -> Result<crate::function::FunctionVersion> {
        function_catalog_not_supported()
    }
-    /// Drop one exact immutable Function version from the remote catalog.
-    async fn drop_function(&self, _name: &str, _version: &str) -> Result<bool> {
-        function_catalog_not_supported()
-    }
    /// A [`crate::job::Job`] handle for a server-side job by id, suitable for
    /// waiting on or cancelling the job. The handle is constructed without a
    /// server round trip; an unknown id surfaces when the handle is used.
@@ -354,16 +327,6 @@ pub trait Database:
    async fn cancel_job(&self, _job_id: &str) -> Result<bool> {
        job_op_not_supported("cancel_job")
    }
-    /// Pause a job by id. The job's workers drain and it stays parked until
-    /// resumed; see [`PauseJobStatus`] for the outcomes.
-    async fn pause_job(&self, _job_id: &str) -> Result<PauseJobStatus> {
-        job_op_not_supported("pause_job")
-    }
-    /// Resume a paused job by id. It re-enters the queue and its workers pick
-    /// their work back up from checkpoints; see [`ResumeJobStatus`].
-    async fn resume_job(&self, _job_id: &str) -> Result<ResumeJobStatus> {
-        job_op_not_supported("resume_job")
-    }
    /// The lifecycle event history of a job (all jobs when `job_id` is
    /// `None`), as recorded Arrow batches.
    async fn job_history(&self, _job_id: Option<&str>) -> Result<Vec<RecordBatch>> {
@@ -13,7 +13,7 @@ use lance::dataset::{ReadParams, WriteMode, builder::DatasetBuilder};
 use lance::io::{ObjectStore, ObjectStoreParams, WrappingObjectStore};
 use lance_datafusion::utils::StreamingWriteSource;
 use lance_file::version::LanceFileVersion;
-use lance_io::object_store::{ReadDirOptions, StorageOptionsAccessor, StorageOptionsProvider};
+use lance_io::object_store::{StorageOptionsAccessor, StorageOptionsProvider};
 use lance_table::io::commit::commit_handler_from_url;
 use object_store::local::LocalFileSystem;
 use snafu::ResultExt;
@@ -281,22 +281,6 @@ impl std::fmt::Display for ListingDatabase {
 }

 const LANCE_EXTENSION: &str = "lance";
-
-/// The table a listed child of the database names, or `None` if the child is not a table.
-///
-/// A table is the directory `<name>.lance`; a loose file or any other directory under the
-/// database prefix belongs to something else. `dir_suffix` is `.lance`, built once by the
-/// caller rather than per child.
-/// The table a listed child directory holds, or `None` if it is not a table at all.
-///
-/// Only directories are considered, so a loose object named like a table is not one.
-fn table_name(location: &object_store::path::Path, dir_suffix: &str) -> Option<String> {
-    location
-        .filename()?
-        .strip_suffix(dir_suffix)
-        .map(String::from)
-        .filter(|name| !name.is_empty())
-}
 const ENGINE: &str = "engine";
 const MIRRORED_STORE: &str = "mirroredStore";

@@ -960,72 +944,51 @@ impl Database for ListingDatabase {
        Ok(f)
    }

-    /// List the tables in the database, a page at a time.
-    ///
-    /// The page_token is opaque, unlike the `start_after` parameter of [`Self::table_names()`].
-    ///
-    /// When there are no more results, the returned page_token will be None.
-    ///
-    /// `limit` is the maximum number of tables to return in the response. But it is possible
-    /// for the response to contain fewer than `limit` tables, even when there are more tables
-    /// to return. Clients should check the returned page_token to determine if there are
-    /// more results, rather than relying on the number of tables returned.
-    ///
-    /// The order that results are returned in not guaranteed to be stable across calls,
-    /// so clients should not rely on it.
    async fn list_tables(&self, request: ListTablesRequest) -> Result<ListTablesResponse> {
        if request.id.as_ref().map(|v| !v.is_empty()).unwrap_or(false) {
            return self.namespace_database().list_tables(request).await;
        }
-        let limit = request.limit.map(|limit| limit.max(0) as usize);
-        let dir_suffix = format!(".{LANCE_EXTENSION}");
-        let mut tables = Vec::new();
-        let mut page_token = request.page_token.filter(|token| !token.is_empty());
+        let mut f = self
+            .object_store
+            .read_dir(self.base_path.clone())
+            .await?
+            .iter()
+            .map(Path::new)
+            .filter(|path| {
+                let is_lance = path
+                    .extension()
+                    .and_then(|e| e.to_str())
+                    .map(|e| e == LANCE_EXTENSION);
+                is_lance.unwrap_or(false)
+            })
+            .filter_map(|p| p.file_stem().and_then(|s| s.to_str().map(String::from)))
+            .collect::<Vec<String>>();
+        f.sort();

-        // A page of nothing: the store rejects a limit of zero, and no table was handed over
-        // for a token to resume after.
-        if limit == Some(0) {
-            return Ok(ListTablesResponse {
-                context: None,
-                tables,
-                page_token: None,
-            });
+        // Handle pagination with page_token
+        if let Some(ref page_token) = request.page_token {
+            let index = f
+                .iter()
+                .position(|name| name.as_str() > page_token.as_str())
+                .unwrap_or(f.len());
+            f.drain(0..index);
        }

-        loop {
-            // Ask only for what the page still has room for, so a database holding more
-            // than one page costs one request per page rather than one per table.
-            let listing = self
-                .object_store
-                .read_dir_page(
-                    self.base_path.clone(),
-                    ReadDirOptions {
-                        page_token: page_token.take(),
-                        limit: limit.map(|limit| limit - tables.len()),
-                    },
-                )
-                .await?;
-            page_token = listing.page_token;
-            // Only child directories can be tables, and the store already separates them
-            // out, so the objects in the page are not looked at.
-            tables.extend(
-                listing
-                    .result
-                    .common_prefixes
-                    .iter()
-                    .filter_map(|location| table_name(location, &dir_suffix)),
-            );
-            // Children that are not tables leave the page short of the limit, so keep
-            // going until the page is full or the database runs out.
-            if page_token.is_none() || limit.is_none_or(|limit| tables.len() >= limit) {
-                break;
+        // Determine if there's a next page. The token is the last name of this page,
+        // not the first of the next one: the next page resumes strictly after the
+        // token, so naming the next page's first entry would skip it.
+        let next_page_token = match request.limit {
+            Some(limit) if f.len() > limit as usize => {
+                f.truncate(limit as usize);
+                f.last().cloned()
            }
-        }
+            _ => None,
+        };

        Ok(ListTablesResponse {
            context: None,
-            tables,
-            page_token,
+            tables: f,
+            page_token: next_page_token,
        })
    }

@@ -1513,7 +1476,7 @@ mod tests {
    use crate::table::{AnyQuery, WriteOptions};
    use arrow_array::{Int32Array, RecordBatch, StringArray};
    use arrow_schema::{DataType, Field, Schema, SchemaRef};
-    use futures::{TryStreamExt, future::try_join_all, stream::once};
+    use futures::{TryStreamExt, stream::once};
    use std::path::PathBuf;
    use std::sync::Arc;
    use std::time::Duration;
@@ -1521,182 +1484,6 @@ mod tests {
    use tokio::sync::Barrier;
    use tokio::time::timeout;

-    async fn create_tables(db: &ListingDatabase, names: &[&str]) {
-        let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
-        for name in names {
-            db.create_table(CreateTableRequest {
-                name: name.to_string(),
-                namespace_path: vec![],
-                data: Box::new(RecordBatch::new_empty(schema.clone())) as Box<dyn Scannable>,
-                mode: CreateTableMode::Create,
-                write_options: Default::default(),
-                location: None,
-                namespace_client: None,
-            })
-            .await
-            .unwrap();
-        }
-    }
-
-    /// Every table in the database, taken `limit` at a time, which is how a caller walks a
-    /// listing: the token ends the walk, never a short page.
-    async fn walk(db: &ListingDatabase, limit: Option<i32>) -> Vec<String> {
-        let mut seen = Vec::new();
-        let mut page_token = None;
-        loop {
-            let page = db
-                .list_tables(ListTablesRequest {
-                    limit,
-                    page_token,
-                    ..Default::default()
-                })
-                .await
-                .unwrap();
-            seen.extend(page.tables);
-            page_token = page.page_token;
-            if page_token.is_none() {
-                return seen;
-            }
-            assert!(
-                seen.len() < 100,
-                "the walk is serving tables more than once"
-            );
-        }
-    }
-
-    /// Paging with the returned token has to visit every table exactly once, whatever the
-    /// page size, with nothing lost or repeated at a boundary.
-    #[rstest::rstest]
-    #[tokio::test]
-    async fn test_list_tables_pages_over_every_table_once(#[values(1, 2, 3, 5, 10)] limit: i32) {
-        let (_tempdir, db) = setup_database().await;
-        create_tables(&db, &["a", "b", "c", "d", "e"]).await;
-
-        assert_eq!(walk(&db, Some(limit)).await, vec!["a", "b", "c", "d", "e"]);
-    }
-
-    /// The token is opaque: it is whatever resumes the store the database sits on, not a
-    /// table name. Callers hand it back and nothing else.
-    ///
-    /// Nothing validates a token, so one invented by a caller is read as a position rather
-    /// than refused — which is why the token has to come back from a previous page.
-    #[tokio::test]
-    async fn test_the_page_token_is_not_a_table_name() {
-        let (_tempdir, db) = setup_database().await;
-        create_tables(&db, &["a", "b", "c"]).await;
-
-        let page = db
-            .list_tables(ListTablesRequest {
-                limit: Some(1),
-                ..Default::default()
-            })
-            .await
-            .unwrap();
-
-        assert_eq!(page.tables, vec!["a"]);
-        let token = page.page_token.expect("two tables are still to come");
-        assert_ne!(token, "a");
-
-        // Handing it back is the only thing a caller does with it, and it resumes.
-        let rest = db
-            .list_tables(ListTablesRequest {
-                page_token: Some(token),
-                ..Default::default()
-            })
-            .await
-            .unwrap();
-        assert_eq!(rest.tables, vec!["b", "c"]);
-    }
-
-    /// A limit the listing does not fill leaves no token behind, so a caller paging by token
-    /// stops without asking for an empty page.
-    #[tokio::test]
-    async fn test_a_listing_that_runs_out_has_no_token() {
-        let (_tempdir, db) = setup_database().await;
-        create_tables(&db, &["a", "b"]).await;
-
-        let page = db
-            .list_tables(ListTablesRequest {
-                limit: Some(10),
-                ..Default::default()
-            })
-            .await
-            .unwrap();
-
-        assert_eq!(page.tables, vec!["a", "b"]);
-        assert_eq!(page.page_token, None);
-    }
-
-    /// An empty page token means "from the start", which is how a client looping on a token
-    /// spells its first request.
-    #[tokio::test]
-    async fn test_an_empty_page_token_lists_from_the_start() {
-        let (_tempdir, db) = setup_database().await;
-        create_tables(&db, &["a", "b"]).await;
-
-        let page = db
-            .list_tables(ListTablesRequest {
-                page_token: Some(String::new()),
-                ..Default::default()
-            })
-            .await
-            .unwrap();
-
-        assert_eq!(page.tables, vec!["a", "b"]);
-    }
-
-    /// Listing follows the order the object store lists directories in, so a name that
-    /// extends another comes first: the `-` of `users-archive.lance` sorts below the `.` of
-    /// `users.lance`. Pagination pushes its cursor into the list request, so it cannot report
-    /// an order other than the one it resumes in.
-    #[tokio::test]
-    async fn test_listing_order_follows_the_store_not_the_table_name() {
-        let (_tempdir, db) = setup_database().await;
-        create_tables(&db, &["users", "users-archive", "users.old"]).await;
-
-        assert_eq!(
-            walk(&db, None).await,
-            vec!["users-archive", "users", "users.old"]
-        );
-        // And paging reports the same order, so a walk sees each table once.
-        assert_eq!(
-            walk(&db, Some(1)).await,
-            vec!["users-archive", "users", "users.old"]
-        );
-    }
-
-    /// Only directories named `<name>.lance` are tables; loose files and other directories
-    /// under the database prefix are not. A page spent on them is filled from the next one,
-    /// so a page holding only non-tables does not read as an empty database.
-    #[tokio::test]
-    async fn test_listing_ignores_non_table_children() {
-        let (tempdir, db) = setup_database().await;
-        create_tables(&db, &["real"]).await;
-        std::fs::write(tempdir.path().join("aaa-loose.lance"), b"not a table").unwrap();
-        create_dir_all(tempdir.path().join("aaa-scratch")).unwrap();
-
-        let page = db
-            .list_tables(ListTablesRequest {
-                limit: Some(1),
-                ..Default::default()
-            })
-            .await
-            .unwrap();
-
-        assert_eq!(page.tables, vec!["real"]);
-    }
-
-    #[tokio::test]
-    async fn listing_ignores_empty_table_name() {
-        let (tempdir, db) = setup_database().await;
-        create_dir_all(tempdir.path().join(".lance")).unwrap();
-        let page = db.list_tables(ListTablesRequest::default()).await.unwrap();
-        assert!(
-            page.tables.is_empty(),
-            "invalid empty table name was listed"
-        );
-    }
-
    async fn setup_database() -> (tempfile::TempDir, ListingDatabase) {
        let tempdir = tempdir().unwrap();
        let uri = tempdir.path().to_str().unwrap();
@@ -1827,59 +1614,6 @@ mod tests {
        );
    }

-    #[tokio::test]
-    async fn test_concurrent_open_table_reuses_connection_object_store() {
-        let tempdir = tempdir().unwrap();
-        let uri = tempdir.path().to_str().unwrap();
-        let session = Arc::new(lance::session::Session::default());
-        let request = ConnectRequest {
-            uri: uri.to_string(),
-            #[cfg(feature = "remote")]
-            client_config: Default::default(),
-            options: Default::default(),
-            namespace_client_properties: Default::default(),
-            manifest_enabled: false,
-            read_consistency_interval: None,
-            session: Some(session.clone()),
-        };
-        let db = ListingDatabase::connect_with_options(&request)
-            .await
-            .unwrap();
-        let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
-        db.create_table(CreateTableRequest {
-            name: "test".to_string(),
-            namespace_path: vec![],
-            data: Box::new(RecordBatch::new_empty(schema)) as Box<dyn Scannable>,
-            mode: CreateTableMode::Create,
-            write_options: Default::default(),
-            location: None,
-            namespace_client: None,
-        })
-        .await
-        .unwrap();
-
-        let before = session.store_registry().stats();
-        let opened_tables = try_join_all((0..32).map(|_| {
-            db.open_table(OpenTableRequest {
-                name: "test".to_string(),
-                namespace_path: vec![],
-                index_cache_size: None,
-                lance_read_params: None,
-                location: None,
-                namespace_client: None,
-                managed_versioning: None,
-            })
-        }))
-        .await
-        .unwrap();
-        let after = session.store_registry().stats();
-
-        assert_eq!(opened_tables.len(), 32);
-        assert_eq!(after.misses, before.misses);
-        assert_eq!(after.active_stores, before.active_stores);
-        assert!(after.hits >= before.hits + 32);
-    }
-
    #[tokio::test]
    async fn test_listing_database_root_ops_do_not_create_manifest() {
        let tempdir = tempdir().unwrap();
@@ -539,7 +539,9 @@ impl Database for LanceNamespaceDatabase {
        self.namespace
            .drop_table(drop_request)
            .await
-            .map_err(|e| map_namespace_lance_error(e, name))?;
+            .map_err(|e| Error::Runtime {
+                message: format!("Failed to drop table: {}", e),
+            })?;

        Ok(())
    }
@@ -1493,15 +1495,6 @@ mod tests {
            .expect("Failed to list tables");
        assert!(!table_names_after.contains(&"drop_test".to_string()));

-        let error = conn
-            .drop_table("drop_test", &["test_ns".into()])
-            .await
-            .expect_err("dropping a missing table should fail");
-        assert!(
-            matches!(error, Error::TableNotFound { ref name, .. } if name == "drop_test"),
-            "expected TableNotFound, got: {error:?}"
-        );
-
        // Verify: Cannot open dropped table
        let open_result = conn.open_table("drop_test").execute().await;
        assert!(open_result.is_err());
@@ -31,7 +31,7 @@ use lance::io::RecordBatchStream;
 use lance_arrow::RecordBatchExt;
 use lance_core::ROW_ID;
 use lance_core::error::LanceOptionExt;
-use std::collections::{HashMap, HashSet};
+use std::collections::HashMap;
 use std::sync::Arc;

 /// Reads a permutation of a source table based on row IDs stored in a separate table
@@ -234,14 +234,7 @@ impl PermutationReader {
            .expect_ok()?
            .values();

-        let mut unique_row_ids = HashSet::with_capacity(num_rows);
-        let in_list: Vec<Expr> = row_ids
-            .iter()
-            .copied()
-            .filter(|row_id| unique_row_ids.insert(*row_id))
-            .map(lit)
-            .collect();
-        let num_unique_row_ids = unique_row_ids.len();
+        let in_list: Vec<Expr> = row_ids.iter().map(|id| lit(*id)).collect();

        let base_query = QueryRequest {
            filter: Some(QueryFilter::Datafusion(col(ROW_ID).in_list(in_list, false))),
@@ -254,7 +247,7 @@ impl PermutationReader {
            .query(
                &AnyQuery::Query(base_query),
                QueryExecutionOptions {
-                    max_batch_length: num_unique_row_ids as u32,
+                    max_batch_length: num_rows as u32,
                    ..Default::default()
                },
            )
@@ -269,9 +262,9 @@ impl PermutationReader {
            });
        }

-        if batches.iter().map(|b| b.num_rows()).sum::<usize>() != num_unique_row_ids {
+        if batches.iter().map(|b| b.num_rows()).sum::<usize>() != num_rows {
            return Err(Error::InvalidInput {
-                message: "Base table returned a different number of rows than the number of unique row IDs"
+                message: "Base table returned different number of rows than the number of row IDs"
                    .to_string(),
            });
        }
@@ -511,7 +504,6 @@ impl PermutationReader {
            let table = Table::from(self.base_table.clone());
            let batches = table
                .take_offsets(offsets.to_vec())
-                .preserve_order()
                .select(selection.clone())
                .execute()
                .await?
@@ -811,10 +803,10 @@ mod tests {
        .unwrap();

        // Take offsets in reverse order and verify returned rows match that order
-        let offsets = vec![5, 3, 5, 1, 0];
+        let offsets = vec![5, 3, 1, 0];
        let batch = reader.take_offsets(&offsets, Select::All).await.unwrap();

-        assert_eq!(batch.num_rows(), 5);
+        assert_eq!(batch.num_rows(), 4);

        let idx_values = batch
            .column(0)
@@ -828,52 +820,6 @@ mod tests {
        assert_eq!(idx_values, expected);
    }

-    #[tokio::test]
-    async fn test_take_offsets_preserves_repeated_rows_in_permutation() {
-        let base_table = lance_datagen::gen_batch()
-            .col("idx", lance_datagen::array::step::<Int32Type>())
-            .into_mem_table("tbl", RowCount::from(5), BatchCount::from(1))
-            .await;
-        let base_row_ids = collect_column::<UInt64Type>(&base_table, "_rowid").await;
-        let permutation_row_ids = vec![
-            base_row_ids[3],
-            base_row_ids[1],
-            base_row_ids[3],
-            base_row_ids[2],
-        ];
-        let permutation_batch = RecordBatch::try_new(
-            Arc::new(Schema::new(vec![
-                Field::new("row_id", DataType::UInt64, false),
-                Field::new(SPLIT_ID_COLUMN, DataType::UInt64, false),
-            ])),
-            vec![
-                Arc::new(UInt64Array::from(permutation_row_ids)),
-                Arc::new(UInt64Array::from(vec![0; 4])),
-            ],
-        )
-        .unwrap();
-        let permutation_table = virtual_table("row_ids", &permutation_batch).await;
-        let reader = PermutationReader::try_from_tables(
-            base_table.base_table().clone(),
-            permutation_table.base_table().clone(),
-            0,
-        )
-        .await
-        .unwrap();
-
-        let batch = reader
-            .take_offsets(&[0, 1, 2, 3], Select::All)
-            .await
-            .unwrap();
-        let idx_values = batch
-            .column(0)
-            .as_primitive::<Int32Type>()
-            .values()
-            .to_vec();
-
-        assert_eq!(idx_values, vec![3, 1, 3, 2]);
-    }
-
    #[tokio::test]
    async fn test_take_offsets_with_column_selection() {
        let (base_table, row_ids_table, row_ids) = setup_permutation_tables(10).await;
@@ -937,17 +883,17 @@ mod tests {
            .unwrap();

        // With no permutation table, take_offsets uses the base table directly
-        let offsets = vec![0, 2, 0, 4, 6];
+        let offsets = vec![0, 2, 4, 6];
        let batch = reader.take_offsets(&offsets, Select::All).await.unwrap();

-        assert_eq!(batch.num_rows(), 5);
+        assert_eq!(batch.num_rows(), 4);

        let idx_values = batch
            .column(0)
            .as_primitive::<Int32Type>()
            .values()
            .to_vec();
-        assert_eq!(idx_values, vec![0, 2, 0, 4, 6]);
+        assert_eq!(idx_values, vec![0, 2, 4, 6]);
    }

    #[tokio::test]
@@ -19,7 +19,6 @@

 mod sql;

-pub(crate) use sql::canonicalize_sql_predicate;
 pub use sql::expr_to_sql_string;

 use std::sync::Arc;
@@ -157,7 +156,7 @@ mod tests {
        use datafusion_common::ScalarValue;
        let expr = col("data").eq(lit(ScalarValue::Binary(Some(vec![0xca, 0xfe]))));
        let sql = expr_to_sql_string(&expr).unwrap();
-        assert_eq!(sql, "(`data` = X'CAFE')");
+        assert_eq!(sql, "(data = X'CAFE')");
    }

    #[test]
@@ -167,7 +166,7 @@ mod tests {
        let int_expr = col("id").gt(lit(5i64));
        let combined = bin_expr.and(int_expr);
        let sql = expr_to_sql_string(&combined).unwrap();
-        assert_eq!(sql, "((`data` = X'01') AND (id > 5))");
+        assert_eq!(sql, "((data = X'01') AND (id > 5))");
    }

    #[test]
@@ -185,7 +184,7 @@ mod tests {
        // serialized correctly (regression test for placeholder rewrite path).
        let expr = contains(col("data"), lit(ScalarValue::Binary(Some(vec![0xff]))));
        let sql = expr_to_sql_string(&expr).unwrap();
-        assert_eq!(sql, "contains(`data`, X'FF')");
+        assert_eq!(sql, "contains(data, X'FF')");
    }

    #[test]
@@ -196,7 +195,7 @@ mod tests {
            .eq(lit(ScalarValue::Binary(Some(vec![0xab, 0xcd]))))
            .not();
        let sql = expr_to_sql_string(&expr).unwrap();
-        assert_eq!(sql, "NOT (`data` = X'ABCD')");
+        assert_eq!(sql, "NOT (data = X'ABCD')");
    }

    #[test]
@@ -206,122 +205,6 @@ mod tests {
        assert!(sql.contains("IN"), "expected IN in: {}", sql);
    }

-    #[test]
-    fn test_empty_is_in() {
-        let expr = is_in(col("id"), vec![]);
-        assert_eq!(expr_to_sql_string(&expr).unwrap(), "false");
-    }
-
-    #[test]
-    fn test_empty_is_in_discards_binary_children() {
-        use datafusion_common::ScalarValue;
-
-        let expr = is_in(
-            col("payload").eq(lit(ScalarValue::Binary(Some(vec![0x01])))),
-            vec![],
-        );
-        assert_eq!(expr_to_sql_string(&expr).unwrap(), "false");
-    }
-
-    #[test]
-    fn test_keyword_identifier() {
-        let expr = col("null").eq(lit(1i64));
-        assert_eq!(expr_to_sql_string(&expr).unwrap(), "(`null` = 1)");
-    }
-
-    #[test]
-    fn test_decimal_literal_preserves_type() {
-        use datafusion_common::ScalarValue;
-
-        let expr = col("val").lt(lit(ScalarValue::Decimal128(
-            Some(1_234_567_890_123_456_790),
-            19,
-            18,
-        )));
-        let sql = expr_to_sql_string(&expr).unwrap();
-        assert_eq!(
-            sql,
-            "(val < arrow_cast('1.234567890123456790', 'Decimal128(19, 18)'))"
-        );
-    }
-
-    #[test]
-    fn test_non_finite_float_literal_preserves_type() {
-        let expr = col("x").lt(lit(f64::INFINITY));
-        assert_eq!(
-            expr_to_sql_string(&expr).unwrap(),
-            "(x < arrow_cast('inf', 'Float64'))"
-        );
-    }
-
-    #[test]
-    fn test_cast_uses_arrow_type_name() {
-        let string = expr_cast(col("x"), DataType::Utf8);
-        assert_eq!(
-            expr_to_sql_string(&string).unwrap(),
-            "arrow_cast(x, 'Utf8')"
-        );
-
-        let int32 = expr_cast(col("x"), DataType::Int32);
-        assert_eq!(
-            expr_to_sql_string(&int32).unwrap(),
-            "arrow_cast(x, 'Int32')"
-        );
-
-        let expr = expr_cast(col("x"), DataType::Float16).lt(lit(2.0));
-        assert_eq!(
-            expr_to_sql_string(&expr).unwrap(),
-            "(arrow_cast(x, 'Float16') < 2.0)"
-        );
-
-        let decimal = expr_cast(lit("2.00"), DataType::Decimal256(40, 2));
-        assert_eq!(
-            expr_to_sql_string(&decimal).unwrap(),
-            "arrow_cast('2.00', 'Decimal256(40, 2)')"
-        );
-    }
-
-    #[test]
-    fn test_binary_placeholder_does_not_rewrite_user_string() {
-        use datafusion_common::ScalarValue;
-
-        let marker = "__lancedb_binary_placeholder_0__";
-        let expr = col("payload")
-            .eq(lit(ScalarValue::Binary(Some(vec![0x01]))))
-            .or(col("text").eq(lit(marker)));
-        assert_eq!(
-            expr_to_sql_string(&expr).unwrap(),
-            "((payload = X'01') OR (`text` = '__lancedb_binary_placeholder_0__'))"
-        );
-    }
-
-    #[test]
-    fn test_binary_binding_skips_quoted_identifiers() {
-        use datafusion_common::ScalarValue;
-
-        let expr = col("payload")
-            .eq(lit(ScalarValue::Binary(Some(vec![0x01]))))
-            .and(col("odd'name").eq(lit(1i64)))
-            .and(col("odd`'name").eq(lit(2i64)));
-        assert_eq!(
-            expr_to_sql_string(&expr).unwrap(),
-            "(((payload = X'01') AND (`odd'name` = 1)) AND (`odd``'name` = 2))"
-        );
-    }
-
-    #[test]
-    fn test_binary_placeholder_collision_search_is_linear() {
-        use datafusion_common::ScalarValue;
-
-        let collision_shaped = format!("__lancedb_binary_placeholder_0__{}", "_".repeat(64_000));
-        let expr = col("payload")
-            .eq(lit(ScalarValue::Binary(Some(vec![0x01]))))
-            .and(col("text").eq(lit(collision_shaped.clone())));
-        let sql = expr_to_sql_string(&expr).unwrap();
-        assert!(sql.contains("X'01'"));
-        assert!(sql.contains(&format!("'{collision_shaped}'")));
-    }
-
    #[test]
    fn test_multiple_binary_literals() {
        use datafusion_common::ScalarValue;
@@ -1,27 +1,10 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors

-use std::{
-    any::TypeId,
-    collections::{HashMap, HashSet},
-};
-
-use arrow_array::types::{
-    Decimal32Type, Decimal64Type, Decimal128Type, Decimal256Type, DecimalType,
-};
-use arrow_schema::DataType;
 use datafusion_common::ScalarValue;
 use datafusion_common::tree_node::{Transformed, TreeNode, TreeNodeRecursion};
 use datafusion_expr::Expr;
-use datafusion_functions::core::expr_fn::{
-    arrow_cast as datafusion_arrow_cast, arrow_try_cast as datafusion_arrow_try_cast,
-};
-use datafusion_sql::sqlparser::{
-    dialect::{Dialect as SqlParserDialect, GenericDialect},
-    keywords::ALL_KEYWORDS,
-    tokenizer::{Token, Tokenizer},
-};
-use datafusion_sql::unparser::{self, dialect::Dialect as UnparserDialect};
+use datafusion_sql::unparser::{self, dialect::Dialect};

 /// Unparser dialect that matches the quoting style expected by the Lance SQL
 /// parser.  Lance uses backtick (`` ` ``) as the only delimited-identifier
@@ -36,74 +19,17 @@ use datafusion_sql::unparser::{self, dialect::Dialect as UnparserDialect};
 ///   lower-case by the SQL parser, which would break case-sensitive schemas).
 struct LanceSqlDialect;

-impl UnparserDialect for LanceSqlDialect {
+impl Dialect for LanceSqlDialect {
    fn identifier_quote_style(&self, identifier: &str) -> Option<char> {
-        let identifier_upper = identifier.to_ascii_uppercase();
-        let needs_quote =
-            (identifier_upper != "ID" && ALL_KEYWORDS.contains(&identifier_upper.as_str()))
-                || identifier.chars().any(|c| c.is_ascii_uppercase())
-                || !identifier.chars().enumerate().all(|(i, c)| {
-                    c == '_' || c.is_ascii_alphabetic() || (i > 0 && c.is_ascii_digit())
-                });
+        let needs_quote = identifier.chars().any(|c| c.is_ascii_uppercase())
+            || !identifier
+                .chars()
+                .enumerate()
+                .all(|(i, c)| c == '_' || c.is_ascii_alphabetic() || (i > 0 && c.is_ascii_digit()));
        if needs_quote { Some('`') } else { None }
    }
 }

-/// Lance's tokenizer dialect with SQL-standard double-quoted identifiers added.
-///
-/// Keep this deliberately small: Lance's parser wraps `GenericDialect` and
-/// delegates only identifier recognition, leaving every other dialect option at
-/// its default. In particular, `/*! ... */` remains an ordinary block comment.
-#[derive(Debug, Default)]
-struct PredicateDialect(GenericDialect);
-
-impl SqlParserDialect for PredicateDialect {
-    fn dialect(&self) -> TypeId {
-        self.0.dialect()
-    }
-
-    fn is_identifier_start(&self, ch: char) -> bool {
-        self.0.is_identifier_start(ch)
-    }
-
-    fn is_identifier_part(&self, ch: char) -> bool {
-        self.0.is_identifier_part(ch)
-    }
-
-    fn is_delimited_identifier_start(&self, ch: char) -> bool {
-        ch == '"' || ch == '`'
-    }
-}
-
-/// Canonicalize a raw SQL predicate for Lance's parser.
-///
-/// Lance wraps [`GenericDialect`] for identifier recognition while retaining the
-/// default dialect behavior for every other lexical option. [`PredicateDialect`]
-/// mirrors that contract and additionally recognizes `"` as an identifier
-/// delimiter, allowing this function to rewrite only those identifier tokens.
-pub fn canonicalize_sql_predicate(predicate: &str) -> crate::Result<String> {
-    let dialect = PredicateDialect::default();
-    let tokens = Tokenizer::new(&dialect, predicate)
-        .with_unescape(false)
-        .tokenize()
-        .map_err(|err| crate::Error::InvalidInput {
-            message: format!("invalid SQL predicate: {err}"),
-        })?;
-
-    Ok(tokens
-        .into_iter()
-        .map(|token| match token {
-            Token::Word(word) if word.quote_style == Some('"') => {
-                // with_unescape(false) retains doubled double quotes. Decode
-                // those before escaping any backticks for Lance's delimiter.
-                let identifier = word.value.replace("\"\"", "\"").replace('`', "``");
-                format!("`{identifier}`")
-            }
-            other => other.to_string(),
-        })
-        .collect())
-}
-
 /// Prefix for placeholder strings inserted in place of binary literals.  Chosen
 /// to be extremely unlikely to occur in user data.
 const BINARY_PLACEHOLDER_PREFIX: &str = "__lancedb_binary_placeholder_";
@@ -113,128 +39,24 @@ fn bytes_to_hex_sql(bytes: &[u8]) -> String {
    format!("X'{hex}'")
 }

-fn string_literals(expr: &Expr) -> HashSet<String> {
-    let mut literals = HashSet::new();
+/// Returns true if *expr* contains a `Binary` or `LargeBinary` scalar literal
+/// anywhere in its subtree.  DataFusion's SQL unparser cannot serialize those
+/// variants, so we route such expressions through a placeholder-substitution
+/// path that emits SQL `X'...'` byte-string literals.
+fn has_binary_literal(expr: &Expr) -> bool {
+    let mut found = false;
    let _ = expr.apply(&mut |e: &Expr| {
-        if let Expr::Literal(
-            ScalarValue::Utf8(Some(value))
-            | ScalarValue::LargeUtf8(Some(value))
-            | ScalarValue::Utf8View(Some(value)),
-            _,
-        ) = e
-        {
-            literals.insert(value.clone());
-        }
-        Ok(TreeNodeRecursion::Continue)
-    });
-    literals
-}
-
-fn typed_string_literal(value: String, data_type: DataType) -> Expr {
-    datafusion_arrow_cast(
-        Expr::Literal(ScalarValue::Utf8(Some(value)), None),
-        Expr::Literal(ScalarValue::Utf8(Some(data_type.to_string())), None),
-    )
-}
-
-fn next_binary_placeholder(user_strings: &HashSet<String>, next_id: &mut usize) -> String {
-    loop {
-        let placeholder = format!("{BINARY_PLACEHOLDER_PREFIX}{}__", *next_id);
-        *next_id += 1;
-        if !user_strings.contains(&placeholder) {
-            return placeholder;
-        }
-    }
-}
-
-fn bind_binary_literals(
-    sql: &str,
-    mut bindings: HashMap<String, Vec<u8>>,
-) -> crate::Result<String> {
-    let bytes = sql.as_bytes();
-    let mut output = Vec::with_capacity(bytes.len());
-    let mut index = 0;
-
-    // Walk SQL string tokens once. Placeholders are plain, unescaped string
-    // literals, so this remains linear even when user strings are large or
-    // deliberately resemble the placeholder prefix.
-    while index < bytes.len() {
-        if bytes[index] == b'`' {
-            let identifier_start = index;
-            index += 1;
-            let mut identifier_end = None;
-            while index < bytes.len() {
-                if bytes[index] == b'`' {
-                    if index + 1 < bytes.len() && bytes[index + 1] == b'`' {
-                        index += 2;
-                    } else {
-                        index += 1;
-                        identifier_end = Some(index);
-                        break;
-                    }
-                } else {
-                    index += 1;
-                }
-            }
-
-            let Some(identifier_end) = identifier_end else {
-                return Err(crate::Error::InvalidInput {
-                    message: "unterminated identifier while binding binary literal".to_string(),
-                });
-            };
-            output.extend_from_slice(&bytes[identifier_start..identifier_end]);
-            continue;
-        }
-
-        if bytes[index] != b'\'' {
-            output.push(bytes[index]);
-            index += 1;
-            continue;
-        }
-
-        let literal_start = index;
-        index += 1;
-        let content_start = index;
-        let mut escaped = false;
-        let mut content_end = None;
-        while index < bytes.len() {
-            if bytes[index] == b'\'' {
-                if index + 1 < bytes.len() && bytes[index + 1] == b'\'' {
-                    escaped = true;
-                    index += 2;
-                } else {
-                    content_end = Some(index);
-                    index += 1;
-                    break;
-                }
-            } else {
-                index += 1;
-            }
-        }
-
-        let Some(content_end) = content_end else {
-            return Err(crate::Error::InvalidInput {
-                message: "unterminated string while binding binary literal".to_string(),
-            });
-        };
-
-        let placeholder = &sql[content_start..content_end];
-        if !escaped && let Some(value) = bindings.remove(placeholder) {
-            output.extend_from_slice(bytes_to_hex_sql(&value).as_bytes());
+        if matches!(
+            e,
+            Expr::Literal(ScalarValue::Binary(_) | ScalarValue::LargeBinary(_), _)
+        ) {
+            found = true;
+            Ok(TreeNodeRecursion::Stop)
        } else {
-            output.extend_from_slice(&bytes[literal_start..index]);
+            Ok(TreeNodeRecursion::Continue)
        }
-    }
-
-    if !bindings.is_empty() {
-        return Err(crate::Error::InvalidInput {
-            message: "failed to bind binary literal while serializing expression".to_string(),
-        });
-    }
-
-    String::from_utf8(output).map_err(|e| crate::Error::InvalidInput {
-        message: format!("failed to bind binary literal: {e}"),
-    })
+    });
+    found
 }

 fn run_unparser(expr: &Expr) -> crate::Result<String> {
@@ -247,37 +69,25 @@ fn run_unparser(expr: &Expr) -> crate::Result<String> {
 }

 pub fn expr_to_sql_string(expr: &Expr) -> crate::Result<String> {
-    // DataFusion's unparser needs a few adaptations before its SQL can be
-    // reparsed by Lance without changing the typed expression's semantics:
-    //
-    // * decimal literals need an explicit cast to preserve precision and scale;
-    // * casts need exact Arrow type names rather than SQL type aliases;
-    // * an empty IN list is valid in DataFusion but invalid SQL;
-    // * binary literals are unsupported by the unparser and need placeholders.
-    // Eliminate empty membership expressions before visiting their children.
-    // Otherwise a discarded binary child could leave behind a stale binding.
+    // Fast path: no binary literals — DataFusion's unparser handles everything.
+    if !has_binary_literal(expr) {
+        return run_unparser(expr);
+    }
+
+    // Slow path: DataFusion's unparser cannot serialize `Binary`/`LargeBinary`
+    // scalars, so we rewrite each one to a unique string-literal placeholder,
+    // let the unparser do the rest of the work, then substitute the SQL
+    // `X'...'` byte-string literal back in.  This keeps the operator/function
+    // serialization logic centralized in DataFusion and works for every
+    // expression node type the unparser supports.
+    let mut bindings: Vec<Vec<u8>> = Vec::new();
    let rewritten = expr
        .clone()
-        .transform(|e: Expr| match e {
-            Expr::InList(in_list) if in_list.list.is_empty() => Ok(Transformed::yes(
-                Expr::Literal(ScalarValue::Boolean(Some(in_list.negated)), None),
-            )),
-            other => Ok(Transformed::no(other)),
-        })
-        .map_err(|e| crate::Error::InvalidInput {
-            message: format!("failed to rewrite expression: {e}"),
-        })?
-        .data;
-
-    let user_strings = string_literals(&rewritten);
-    let mut next_placeholder_id = 0;
-    let mut binary_bindings = HashMap::new();
-    let rewritten = rewritten
        .transform(|e: Expr| match e {
            Expr::Literal(ScalarValue::Binary(Some(bytes)), m)
            | Expr::Literal(ScalarValue::LargeBinary(Some(bytes)), m) => {
-                let placeholder = next_binary_placeholder(&user_strings, &mut next_placeholder_id);
-                binary_bindings.insert(placeholder.clone(), bytes);
+                let placeholder = format!("{}{}__", BINARY_PLACEHOLDER_PREFIX, bindings.len());
+                bindings.push(bytes);
                Ok(Transformed::yes(Expr::Literal(
                    ScalarValue::Utf8(Some(placeholder)),
                    m,
@@ -287,57 +97,6 @@ pub fn expr_to_sql_string(expr: &Expr) -> crate::Result<String> {
            | Expr::Literal(ScalarValue::LargeBinary(None), m) => {
                Ok(Transformed::yes(Expr::Literal(ScalarValue::Null, m)))
            }
-            Expr::Literal(ScalarValue::Decimal32(Some(value), precision, scale), _m) => {
-                let value = Decimal32Type::format_decimal(value, precision, scale);
-                Ok(Transformed::yes(typed_string_literal(
-                    value,
-                    DataType::Decimal32(precision, scale),
-                )))
-            }
-            Expr::Literal(ScalarValue::Decimal64(Some(value), precision, scale), _m) => {
-                let value = Decimal64Type::format_decimal(value, precision, scale);
-                Ok(Transformed::yes(typed_string_literal(
-                    value,
-                    DataType::Decimal64(precision, scale),
-                )))
-            }
-            Expr::Literal(ScalarValue::Decimal128(Some(value), precision, scale), _m) => {
-                let value = Decimal128Type::format_decimal(value, precision, scale);
-                Ok(Transformed::yes(typed_string_literal(
-                    value,
-                    DataType::Decimal128(precision, scale),
-                )))
-            }
-            Expr::Literal(ScalarValue::Decimal256(Some(value), precision, scale), _m) => {
-                let value = Decimal256Type::format_decimal(value, precision, scale);
-                Ok(Transformed::yes(typed_string_literal(
-                    value,
-                    DataType::Decimal256(precision, scale),
-                )))
-            }
-            Expr::Literal(ScalarValue::Float16(Some(value)), _m) if !value.is_finite() => Ok(
-                Transformed::yes(typed_string_literal(value.to_string(), DataType::Float16)),
-            ),
-            Expr::Literal(ScalarValue::Float32(Some(value)), _m) if !value.is_finite() => Ok(
-                Transformed::yes(typed_string_literal(value.to_string(), DataType::Float32)),
-            ),
-            Expr::Literal(ScalarValue::Float64(Some(value)), _m) if !value.is_finite() => Ok(
-                Transformed::yes(typed_string_literal(value.to_string(), DataType::Float64)),
-            ),
-            Expr::Cast(cast) => Ok(Transformed::yes(datafusion_arrow_cast(
-                *cast.expr,
-                Expr::Literal(
-                    ScalarValue::Utf8(Some(cast.field.data_type().to_string())),
-                    None,
-                ),
-            ))),
-            Expr::TryCast(cast) => Ok(Transformed::yes(datafusion_arrow_try_cast(
-                *cast.expr,
-                Expr::Literal(
-                    ScalarValue::Utf8(Some(cast.field.data_type().to_string())),
-                    None,
-                ),
-            ))),
            other => Ok(Transformed::no(other)),
        })
        .map_err(|e| crate::Error::InvalidInput {
@@ -345,58 +104,12 @@ pub fn expr_to_sql_string(expr: &Expr) -> crate::Result<String> {
        })?
        .data;

-    let sql = run_unparser(&rewritten)?;
-    if binary_bindings.is_empty() {
-        Ok(sql)
-    } else {
-        bind_binary_literals(&sql, binary_bindings)
-    }
-}
-
-#[cfg(test)]
-mod tests {
-    use super::canonicalize_sql_predicate;
-
-    #[test]
-    fn normalizes_double_quoted_identifiers() {
-        assert_eq!(
-            canonicalize_sql_predicate(r#""PartyAbbrev" = 'D'"#).unwrap(),
-            "`PartyAbbrev` = 'D'"
-        );
-        assert_eq!(
-            canonicalize_sql_predicate(r#""MetaData"."userId" = 5"#).unwrap(),
-            "`MetaData`.`userId` = 5"
-        );
-        assert_eq!(
-            canonicalize_sql_predicate(r#""a""b" = 1"#).unwrap(),
-            "`a\"b` = 1"
-        );
-    }
-
-    #[test]
-    fn preserves_quotes_inside_literals_and_backticks() {
-        let filter = r#"name = 'Alice "Ace"' AND `quoted"field` = 1"#;
-        assert_eq!(canonicalize_sql_predicate(filter).unwrap(), filter);
-    }
-
-    #[test]
-    fn preserves_literals_and_comments_using_lance_dialect_rules() {
-        let predicate = r#"path = '\' AND "PartyAbbrev" = 'D' -- unmatched " in comment"#;
-        assert_eq!(
-            canonicalize_sql_predicate(predicate).unwrap(),
-            r#"path = '\' AND `PartyAbbrev` = 'D' -- unmatched " in comment"#
-        );
-
-        let predicate = r#"id = 1 /* unmatched " in block comment */"#;
-        assert_eq!(canonicalize_sql_predicate(predicate).unwrap(), predicate);
-
-        let predicate = r#"id = 1 /*! OR "PartyAbbrev" = 'D' */"#;
-        assert_eq!(canonicalize_sql_predicate(predicate).unwrap(), predicate);
-    }
-
-    #[test]
-    fn rejects_unterminated_double_quoted_identifier() {
-        let error = canonicalize_sql_predicate(r#""PartyAbbrev = 'D'"#).unwrap_err();
-        assert!(matches!(error, crate::Error::InvalidInput { .. }));
+    let mut sql = run_unparser(&rewritten)?;
+    for (i, bytes) in bindings.iter().enumerate() {
+        // The unparser quotes string literals with single quotes, so the
+        // placeholder appears as `'__lancedb_binary_placeholder_<i>__'`.
+        let quoted = format!("'{}{}__'", BINARY_PLACEHOLDER_PREFIX, i);
+        sql = sql.replace(&quoted, &bytes_to_hex_sql(bytes));
    }
+    Ok(sql)
 }
@@ -15,9 +15,6 @@ use serde_json::Value;

 use crate::{Error, Result};

-/// Semantic Function type for a Blob v2 value.
-pub const FUNCTION_BLOB_V2_TYPE: &str = "blob_v2";
-
 fn invalid_json(error: impl std::fmt::Display) -> Error {
    Error::InvalidInput {
        message: format!("invalid remote Function JSON: {error}"),
@@ -189,9 +186,6 @@ pub struct PythonEnvironmentSpec {
    pub kind: String,
    #[serde(default, skip_serializing_if = "Vec::is_empty")]
    pub packages: Vec<String>,
-    /// Conda channels in priority order; conda environments only.
-    #[serde(default, skip_serializing_if = "Vec::is_empty")]
-    pub channels: Vec<String>,
    #[serde(default, skip_serializing_if = "Option::is_none")]
    pub path: Option<String>,
    #[serde(default, skip_serializing_if = "Vec::is_empty")]
@@ -210,33 +204,6 @@ pub enum PythonRuntimeSpec {
        environment: PythonEnvironmentSpec,
        env: BTreeMap<String, String>,
    },
-    /// The GPU-enabled Sophon-managed Python runtime.
-    ///
-    /// # Examples
-    ///
-    /// ```
-    /// use std::collections::BTreeMap;
-    /// use lancedb::function::{PythonEnvironmentSpec, PythonRuntimeSpec};
-    ///
-    /// let runtime = PythonRuntimeSpec::PythonV2 {
-    ///     python_version: "3.12".to_string(),
-    ///     environment: PythonEnvironmentSpec {
-    ///         kind: "pip".to_string(),
-    ///         packages: vec!["cupy-cuda12x".to_string()],
-    ///         channels: Vec::new(),
-    ///         path: None,
-    ///         modules: Vec::new(),
-    ///         image: None,
-    ///     },
-    ///     env: BTreeMap::new(),
-    /// };
-    /// assert!(runtime.requires_gpu());
-    /// ```
-    PythonV2 {
-        python_version: String,
-        environment: PythonEnvironmentSpec,
-        env: BTreeMap<String, String>,
-    },
    /// A runtime kind introduced by a newer server.
    ///
    /// Unknown payload fields are intentionally not retained because the
@@ -249,27 +216,22 @@ impl PythonRuntimeSpec {
    pub fn kind(&self) -> &str {
        match self {
            Self::Python { .. } => "python",
-            Self::PythonV2 { .. } => "python_v2",
            Self::Unrecognized { kind } => kind,
        }
    }

-    /// The Python version for a known Python runtime, or `None` for an unknown kind.
+    /// The Python version for the V1 runtime, or `None` for an unknown kind.
    pub fn python_version(&self) -> Option<&str> {
        match self {
-            Self::Python { python_version, .. } | Self::PythonV2 { python_version, .. } => {
-                Some(python_version)
-            }
+            Self::Python { python_version, .. } => Some(python_version),
            Self::Unrecognized { .. } => None,
        }
    }

-    /// The Python environment for a known Python runtime, or `None` for an unknown kind.
+    /// The Python environment for the V1 runtime, or `None` for an unknown kind.
    pub fn environment(&self) -> Option<&PythonEnvironmentSpec> {
        match self {
-            Self::Python { environment, .. } | Self::PythonV2 { environment, .. } => {
-                Some(environment)
-            }
+            Self::Python { environment, .. } => Some(environment),
            Self::Unrecognized { .. } => None,
        }
    }
@@ -277,73 +239,38 @@ impl PythonRuntimeSpec {
    /// Environment variables, or `None` for an unknown kind.
    pub fn env(&self) -> Option<&BTreeMap<String, String>> {
        match self {
-            Self::Python { env, .. } | Self::PythonV2 { env, .. } => Some(env),
+            Self::Python { env, .. } => Some(env),
            Self::Unrecognized { .. } => None,
        }
    }
-
-    /// Whether the runtime requires a GPU selected by the execution platform.
-    pub fn requires_gpu(&self) -> bool {
-        matches!(self, Self::PythonV2 { .. })
-    }
 }

 #[derive(Deserialize)]
-struct PythonRuntimeV1Wire {
-    python_version: String,
-    environment: PythonEnvironmentSpec,
+struct PythonRuntimeWire {
+    kind: String,
+    #[serde(default)]
+    python_version: Option<String>,
+    #[serde(default)]
+    environment: Option<PythonEnvironmentSpec>,
    #[serde(default)]
    env: BTreeMap<String, String>,
-    #[serde(default)]
-    gpu: Option<Value>,
-}
-
-#[derive(Deserialize)]
-struct PythonRuntimeV2Wire {
-    python_version: String,
-    environment: PythonEnvironmentSpec,
-    #[serde(default)]
-    env: BTreeMap<String, String>,
-    gpu: bool,
 }

 impl<'de> Deserialize<'de> for PythonRuntimeSpec {
    fn deserialize<D: Deserializer<'de>>(deserializer: D) -> std::result::Result<Self, D::Error> {
-        let value = Value::deserialize(deserializer)?;
-        let kind = value
-            .get("kind")
-            .ok_or_else(|| de::Error::missing_field("kind"))?
-            .as_str()
-            .ok_or_else(|| de::Error::custom("runtime.kind must be a string"))?
-            .to_string();
-        match kind.as_str() {
-            "python" => {
-                let wire: PythonRuntimeV1Wire =
-                    serde_json::from_value(value).map_err(de::Error::custom)?;
-                if wire.gpu.is_some() {
-                    return Err(de::Error::custom(
-                        "python runtime with gpu requires kind='python_v2'",
-                    ));
-                }
-                Ok(Self::Python {
-                    python_version: wire.python_version,
-                    environment: wire.environment,
-                    env: wire.env,
-                })
-            }
-            "python_v2" => {
-                let wire: PythonRuntimeV2Wire =
-                    serde_json::from_value(value).map_err(de::Error::custom)?;
-                if !wire.gpu {
-                    return Err(de::Error::custom("runtime.gpu must be true"));
-                }
-                Ok(Self::PythonV2 {
-                    python_version: wire.python_version,
-                    environment: wire.environment,
-                    env: wire.env,
-                })
-            }
-            _ => Ok(Self::Unrecognized { kind }),
+        let wire = PythonRuntimeWire::deserialize(deserializer)?;
+        if wire.kind == "python" {
+            Ok(Self::Python {
+                python_version: wire
+                    .python_version
+                    .ok_or_else(|| de::Error::missing_field("python_version"))?,
+                environment: wire
+                    .environment
+                    .ok_or_else(|| de::Error::missing_field("environment"))?,
+                env: wire.env,
+            })
+        } else {
+            Ok(Self::Unrecognized { kind: wire.kind })
        }
    }
 }
@@ -357,8 +284,6 @@ impl Serialize for PythonRuntimeSpec {
            environment: &'a PythonEnvironmentSpec,
            #[serde(skip_serializing_if = "BTreeMap::is_empty")]
            env: &'a BTreeMap<String, String>,
-            #[serde(skip_serializing_if = "Option::is_none")]
-            gpu: Option<bool>,
        }

        #[derive(Serialize)]
@@ -376,19 +301,6 @@ impl Serialize for PythonRuntimeSpec {
                python_version,
                environment,
                env,
-                gpu: None,
-            }
-            .serialize(serializer),
-            Self::PythonV2 {
-                python_version,
-                environment,
-                env,
-            } => PythonRuntimeRef {
-                kind: "python_v2",
-                python_version,
-                environment,
-                env,
-                gpu: Some(true),
            }
            .serialize(serializer),
            Self::Unrecognized { kind } => UnrecognizedRuntimeRef { kind }.serialize(serializer),
@@ -398,8 +310,8 @@ impl Serialize for PythonRuntimeSpec {

 /// Immutable Function version returned by the Enterprise catalog.
 ///
-/// The GPU execution requirement is part of this identity. CPU and memory sizing,
-/// priority, concurrency, and retry policy belong to the execution platform.
+/// Scheduling resources, priority, concurrency, and retry policy belong to
+/// the submitting Job and are not part of this identity.
 #[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
 pub struct FunctionVersion {
    name: String,
@@ -671,67 +583,3 @@ impl RefreshColumnResult {
 }

 impl_json!(RefreshColumnResult);
-
-#[cfg(test)]
-mod conda_environment_tests {
-    use super::{PythonEnvironmentSpec, PythonRuntimeSpec};
-
-    #[test]
-    fn conda_channels_round_trip_and_pip_stays_bare() {
-        let conda: PythonEnvironmentSpec = serde_json::from_str(
-            r#"{"kind":"conda","packages":["numpy"],"channels":["conda-forge"]}"#,
-        )
-        .unwrap();
-        assert_eq!(conda.channels, ["conda-forge"]);
-        assert!(
-            serde_json::to_string(&conda)
-                .unwrap()
-                .contains(r#""channels":["conda-forge"]"#)
-        );
-
-        let pip: PythonEnvironmentSpec =
-            serde_json::from_str(r#"{"kind":"pip","packages":["numpy"]}"#).unwrap();
-        assert!(!serde_json::to_string(&pip).unwrap().contains("channels"));
-    }
-
-    #[test]
-    fn gpu_python_runtime_marker_round_trips_and_validates() {
-        let runtime: PythonRuntimeSpec = serde_json::from_str(
-            r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":true}"#,
-        )
-        .unwrap();
-        assert_eq!(runtime.kind(), "python_v2");
-        assert!(runtime.requires_gpu());
-        assert_eq!(
-            super::canonical_json(&runtime).unwrap(),
-            r#"{"environment":{"kind":"pip"},"gpu":true,"kind":"python_v2","python_version":"3.12"}"#
-        );
-
-        for invalid in [
-            r#"{"kind":"python","python_version":"3.12","environment":{"kind":"pip"},"gpu":true}"#,
-            r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"}}"#,
-            r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":1}"#,
-            r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":false}"#,
-            r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":"true"}"#,
-            r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":"H100"}"#,
-        ] {
-            assert!(serde_json::from_str::<PythonRuntimeSpec>(invalid).is_err());
-        }
-    }
-
-    #[test]
-    fn unknown_runtime_discards_payload_before_known_field_validation() {
-        for encoded in [
-            r#"{"kind":"python_v3","gpu":{"model":"H100"}}"#,
-            r#"{"kind":"python_v3","resources":[]}"#,
-            r#"{"kind":"python_v3","python_version":3.15,"environment":{"kind":[]}}"#,
-        ] {
-            let runtime: PythonRuntimeSpec = serde_json::from_str(encoded).unwrap();
-            assert_eq!(runtime.kind(), "python_v3");
-            assert_eq!(
-                super::canonical_json(&runtime).unwrap(),
-                r#"{"kind":"python_v3"}"#
-            );
-        }
-    }
-}
@@ -63,5 +63,4 @@ pub struct FmIndexBuilder {}
 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::DocumentGranularity;
 pub use lance_index::scalar::inverted::query::*;
@@ -10,7 +10,7 @@ use lance::io::WrappingObjectStore;
 use object_store::{
    CopyOptions, Error, GetOptions, GetResult, ListResult, MultipartUpload, ObjectMeta,
    ObjectStore, ObjectStoreExt, PutMultipartOptions, PutOptions, PutPayload, PutResult, Result,
-    UploadPart, list::PaginatedListStore, path::Path,
+    UploadPart, path::Path,
 };

 use async_trait::async_trait;
@@ -187,14 +187,6 @@ impl WrappingObjectStore for MirroringObjectStoreWrapper {
            secondary: self.secondary.clone(),
        })
    }
-
-    fn wrap_paginated(
-        &self,
-        _store_prefix: &str,
-        original: Arc<dyn PaginatedListStore>,
-    ) -> Option<Arc<dyn PaginatedListStore>> {
-        Some(original)
-    }
 }

 // windows pathing can't be simply concatenated
@@ -12,7 +12,7 @@ use lance::io::WrappingObjectStore;
 use object_store::{
    CopyOptions, GetOptions, GetResult, ListResult, MultipartUpload, ObjectMeta, ObjectStore,
    PutMultipartOptions, PutOptions, PutPayload, PutResult, RenameOptions, Result as OSResult,
-    UploadPart, list::PaginatedListStore, path::Path,
+    UploadPart, path::Path,
 };

 #[derive(Debug, Default)]
@@ -57,14 +57,6 @@ impl WrappingObjectStore for IoStatsHolder {
            stats: self.0.clone(),
        })
    }
-
-    fn wrap_paginated(
-        &self,
-        _store_prefix: &str,
-        original: Arc<dyn PaginatedListStore>,
-    ) -> Option<Arc<dyn PaginatedListStore>> {
-        Some(original)
-    }
 }

 impl IoTrackingStore {
@@ -47,10 +47,6 @@ impl TerminalResult {
        }
    }

-    pub(crate) fn value(&self) -> Option<&Value> {
-        self.value.as_ref()
-    }
-
    fn decode<T: DeserializeOwned>(self) -> Result<T> {
        let value = self.value.ok_or_else(|| match &self.request_id {
            Some(request_id) => Error::Http {
@@ -170,15 +170,6 @@ pub(crate) fn plan(
    filter: Option<&str>,
    limit: Option<u64>,
 ) -> Result<(MaterializedViewDefinition, Vec<ArrowField>, Lineage)> {
-    let filter = filter
-        .map(crate::expr::canonicalize_sql_predicate)
-        .transpose()
-        .map_err(|err| match err {
-            Error::InvalidInput { message } => Error::InvalidInput {
-                message: format!("invalid view filter: {message}"),
-            },
-            err => err,
-        })?;
    let projections: Vec<(String, String)> = if projections.is_empty() {
        source_schema
            .fields()
@@ -283,7 +274,7 @@ pub(crate) fn plan(
        declared.push(output);
    }

-    if let Some(filter) = filter.as_deref() {
+    if let Some(filter) = filter {
        let expr = planner
            .parse_filter(filter)
            .map_err(|e| Error::InvalidInput {
@@ -323,7 +314,7 @@ pub(crate) fn plan(
            .into_iter()
            .map(|(output, expression)| ViewProjection { output, expression })
            .collect(),
-        filter,
+        filter: filter.map(String::from),
        limit,
        inputs,
    };
@@ -46,9 +46,8 @@ use lance_table::format::Fragment;
 use serde::{Deserialize, Serialize};

 use super::{
-    DEFINITION_META_KEY, INCARNATION_META_KEY, MaterializedViewDefinition,
-    REFRESHED_AT_MS_META_KEY, SOURCE_ROW_ID_COLUMN, SOURCE_VERSION_META_KEY,
-    definition_to_metadata,
+    INCARNATION_META_KEY, MaterializedViewDefinition, REFRESHED_AT_MS_META_KEY,
+    SOURCE_ROW_ID_COLUMN, SOURCE_VERSION_META_KEY,
 };
 use crate::database::OpenTableRequest;
 use crate::table::{NativeTable, NativeTableExt, Table};
@@ -198,28 +197,8 @@ pub(crate) async fn execute_refresh(
            ),
        });
    }
-    let definition_changed =
-        definition.filter != replanned.filter || definition.inputs != replanned.inputs;
    let definition = &replanned;

-    // A watermark written for a legacy raw filter certifies the rows that
-    // filter produced, not the canonical predicate above. Rebuild instead of
-    // accepting or advancing it, and persist the migrated definition in the
-    // same metadata commit that certifies the replacement rows.
-    if definition_changed {
-        return rebuild(
-            view_native,
-            &view_ds,
-            &source_ds,
-            source_version,
-            source_ts,
-            definition,
-            true,
-            expected_incarnation,
-        )
-        .await;
-    }
-
    let metadata = &view_ds.schema().metadata;
    let watermark: Option<u64> = metadata
        .get(SOURCE_VERSION_META_KEY)
@@ -278,7 +257,6 @@ pub(crate) async fn execute_refresh(
                        source_version,
                        source_ts,
                        definition,
-                        false,
                        expected_incarnation,
                    )
                    .await
@@ -293,7 +271,6 @@ pub(crate) async fn execute_refresh(
                source_version,
                source_ts,
                definition,
-                false,
                expected_incarnation,
            )
            .await
@@ -706,7 +683,6 @@ async fn incremental(
            view_ds.clone(),
            source_version,
            source_ts,
-            None,
            expected_incarnation,
        )
        .await?;
@@ -728,7 +704,6 @@ async fn incremental(
            published,
            source_version,
            source_ts,
-            None,
            expected_incarnation,
        )
        .await?;
@@ -800,7 +775,6 @@ async fn incremental(
            published,
            source_version,
            source_ts,
-            None,
            expected_incarnation,
        )
        .await?;
@@ -850,14 +824,12 @@ async fn incremental(
        appended,
        source_version,
        source_ts,
-        None,
        expected_incarnation,
    )
    .await?;
    Ok(Some(result))
 }

-#[allow(clippy::too_many_arguments)]
 async fn rebuild(
    view_native: &NativeTable,
    view_ds: &Dataset,
@@ -865,7 +837,6 @@ async fn rebuild(
    source_version: u64,
    source_ts: u128,
    definition: &MaterializedViewDefinition,
-    persist_definition: bool,
    expected_incarnation: Option<&str>,
 ) -> Result<RefreshMaterializedViewResult> {
    let rows_written = Arc::new(AtomicU64::new(0));
@@ -896,7 +867,6 @@ async fn rebuild(
        replaced,
        source_version,
        source_ts,
-        persist_definition.then_some(definition),
        expected_incarnation,
    )
    .await?;
@@ -1011,7 +981,6 @@ async fn stamp_watermark(
    mut dataset: Dataset,
    source_version: u64,
    source_ts: u128,
-    definition: Option<&MaterializedViewDefinition>,
    expected_incarnation: Option<&str>,
 ) -> Result<u64> {
    ensure_incarnation(&dataset, expected_incarnation, dataset.uri()).await?;
@@ -1024,32 +993,27 @@ async fn stamp_watermark(
        .get(INCARNATION_META_KEY)
        .cloned()
        .unwrap_or_else(|| uuid::Uuid::new_v4().to_string());
-    let mut metadata = vec![(INCARNATION_META_KEY.to_string(), Some(incarnation))];
-    if let Some(definition) = definition {
-        metadata.push((
-            DEFINITION_META_KEY.to_string(),
-            Some(definition_to_metadata(definition)?),
-        ));
-    }
-    metadata.extend([
-        (
-            SOURCE_VERSION_META_KEY.to_string(),
-            Some(source_version.to_string()),
-        ),
-        (
-            SOURCE_VERSION_TS_META_KEY.to_string(),
-            Some(source_ts.to_string()),
-        ),
-        (
-            REFRESHED_AT_MS_META_KEY.to_string(),
-            Some(now_ms().to_string()),
-        ),
-        (
-            VIEW_VERSION_META_KEY.to_string(),
-            Some(predicted.to_string()),
-        ),
-    ]);
-    dataset.update_schema_metadata(metadata).await?;
+    dataset
+        .update_schema_metadata([
+            (INCARNATION_META_KEY.to_string(), Some(incarnation)),
+            (
+                SOURCE_VERSION_META_KEY.to_string(),
+                Some(source_version.to_string()),
+            ),
+            (
+                SOURCE_VERSION_TS_META_KEY.to_string(),
+                Some(source_ts.to_string()),
+            ),
+            (
+                REFRESHED_AT_MS_META_KEY.to_string(),
+                Some(now_ms().to_string()),
+            ),
+            (
+                VIEW_VERSION_META_KEY.to_string(),
+                Some(predicted.to_string()),
+            ),
+        ])
+        .await?;
    let actual = dataset.version().version;
    if actual != predicted {
        return Err(Error::Runtime {
@@ -1621,106 +1585,6 @@ mod tests {
        assert_eq!(read(view.table(), "x").await, vec![20, 40]);
    }

-    #[tokio::test]
-    async fn test_mixed_case_filter_is_canonicalized_for_lineage_and_refresh() {
-        let conn = connect("memory://").execute().await.unwrap();
-        let batch = record_batch!(
-            ("id", Int32, [1, 2, 3]),
-            ("PartyAbbrev", Utf8, ["D", "R", "D"])
-        )
-        .unwrap();
-        conn.create_table("src", batch)
-            .write_options(crate::materialized_view::tests::stable_row_ids())
-            .execute()
-            .await
-            .unwrap();
-        conn.create_materialized_view("democrats", "src")
-            .select([("id", "id")])
-            .only_if(r#""PartyAbbrev" = 'D'"#)
-            .execute()
-            .await
-            .unwrap();
-
-        // Reopen from schema metadata so these assertions cover the stored
-        // predicate and lineage, not only the declaration-time handle.
-        let view = conn.open_materialized_view("democrats").await.unwrap();
-        assert_eq!(
-            view.definition().filter.as_deref(),
-            Some("`PartyAbbrev` = 'D'")
-        );
-        assert_eq!(view.definition().inputs, ["PartyAbbrev", "id"]);
-
-        let result = view.refresh().execute().await.unwrap();
-        assert_eq!(result.rows_written, 2);
-        assert_eq!(read(view.table(), "id").await, vec![1, 3]);
-    }
-
-    #[tokio::test]
-    async fn test_legacy_raw_filter_rebuilds_and_persists_canonical_definition() {
-        let conn = connect("memory://").execute().await.unwrap();
-        let batch = record_batch!(
-            ("id", Int32, [1, 2, 3]),
-            ("PartyAbbrev", Utf8, ["D", "R", "D"])
-        )
-        .unwrap();
-        conn.create_table("legacy_src", batch)
-            .write_options(crate::materialized_view::tests::stable_row_ids())
-            .execute()
-            .await
-            .unwrap();
-        let view = conn
-            .create_materialized_view("legacy_view", "legacy_src")
-            .select([("id", "id")])
-            .only_if(r#""PartyAbbrev" = 'X'"#)
-            .execute()
-            .await
-            .unwrap();
-        assert_eq!(view.refresh().execute().await.unwrap().rows_written, 0);
-
-        // Model a definition and up-to-date watermark written before filter
-        // canonicalization was applied to materialized views.
-        let mut legacy = view.definition().clone();
-        legacy.filter = Some(r#""PartyAbbrev" = 'D'"#.into());
-        legacy.inputs = vec!["id".into()];
-        let native = view.table().as_native().unwrap();
-        let mut dataset = native.dataset.get().await.unwrap().as_ref().clone();
-        let predicted = dataset.version().version + 1;
-        dataset
-            .update_schema_metadata([
-                (
-                    DEFINITION_META_KEY.to_string(),
-                    Some(definition_to_metadata(&legacy).unwrap()),
-                ),
-                (
-                    VIEW_VERSION_META_KEY.to_string(),
-                    Some(predicted.to_string()),
-                ),
-            ])
-            .await
-            .unwrap();
-        native.dataset.update(dataset);
-
-        let reopened = conn.open_materialized_view("legacy_view").await.unwrap();
-        let result = reopened.refresh().execute().await.unwrap();
-        assert_eq!(result.mode, RefreshMode::Rebuild);
-        assert_eq!(result.rows_written, 2);
-        assert_eq!(read(reopened.table(), "id").await, vec![1, 3]);
-
-        // A fresh handle proves the migration was stored alongside the new
-        // watermark and therefore happens only once.
-        let migrated = conn.open_materialized_view("legacy_view").await.unwrap();
-        assert_eq!(
-            migrated.definition().filter.as_deref(),
-            Some("`PartyAbbrev` = 'D'")
-        );
-        assert_eq!(migrated.definition().inputs, ["PartyAbbrev", "id"]);
-        assert_eq!(
-            migrated.refresh().execute().await.unwrap().mode,
-            RefreshMode::NoOp
-        );
-        assert_eq!(read(migrated.table(), "id").await, vec![1, 3]);
-    }
-
    #[tokio::test]
    async fn test_append_refreshes_incrementally() {
        let (_conn, source, view) = refreshed_doubled(vec![1, 2]).await;
@@ -2903,7 +2767,7 @@ mod tests {
        let stale = view_native.dataset.get().await.unwrap().as_ref().clone();
        view.table().delete("x = 1").await.unwrap();

-        let err = stamp_watermark(view_native, stale, 99, 99, None, None).await;
+        let err = stamp_watermark(view_native, stale, 99, 99, None).await;
        assert!(err.is_err());

        let result = view.refresh().execute().await.unwrap();
@@ -26,9 +26,7 @@ use crate::database::{
 use crate::error::Result;
 use crate::function::{FunctionRegistrationRequest, FunctionVersion};
 use crate::job::Job;
-use crate::remote::job::{
-    DescribeJobResponse, PauseJobResponse, RemoteJob, ResumeJobResponse, job_state_to_client,
-};
+use crate::remote::job::{DescribeJobResponse, RemoteJob, job_state_to_client};
 use crate::remote::util::stream_as_body;
 use crate::table::BaseTable;

@@ -89,10 +87,6 @@ impl ServerVersion {
    pub fn support_blobs(&self) -> bool {
        self.0 >= semver::Version::new(0, 5, 0)
    }
-
-    pub fn support_fts_document_granularity(&self) -> bool {
-        self.0 >= semver::Version::new(0, 6, 0)
-    }
 }

 pub const OPT_REMOTE_PREFIX: &str = "remote_database_";
@@ -535,11 +529,6 @@ struct RemoteListJobsResponse {
    page_token: Option<String>,
 }

-#[derive(serde::Deserialize)]
-struct RemoteDropFunctionResponse {
-    dropped: bool,
-}
-
 /// Bound on `list_jobs` page walking; a warning is logged when the listing
 /// is truncated at this many pages.
 const MAX_LIST_JOBS_PAGES: usize = 100;
@@ -590,20 +579,6 @@ impl<S: HttpSend> Database for RemoteDatabase<S> {
        response.json().await.err_to_http(request_id)
    }

-    async fn drop_function(&self, name: &str, version: &str) -> Result<bool> {
-        let req = self
-            .client
-            .post("/v1/functions/drop")
-            .json(&serde_json::json!({
-                "name": name,
-                "version": version,
-            }));
-        let (request_id, response) = self.client.send(req).await?;
-        let response = self.client.check_response(&request_id, response).await?;
-        let response: RemoteDropFunctionResponse = response.json().await.err_to_http(request_id)?;
-        Ok(response.dropped)
-    }
-
    fn job(&self, job_id: &str) -> Result<crate::job::Job> {
        Ok(crate::job::Job::new(Box::new(super::job::RemoteJob::new(
            self.client.clone(),
@@ -686,40 +661,6 @@ impl<S: HttpSend> Database for RemoteDatabase<S> {
        }
    }

-    async fn pause_job(&self, job_id: &str) -> Result<crate::database::PauseJobStatus> {
-        let req = self
-            .client
-            .post("/v1/jobs/pause")
-            .json(&serde_json::json!({ "job_id": job_id }));
-        let (request_id, rsp) = self.client.send(req).await?;
-        let rsp = self.client.check_response(&request_id, rsp).await?;
-        let body: PauseJobResponse = rsp.json().await.err_to_http(request_id)?;
-        Ok(if body.paused {
-            crate::database::PauseJobStatus::Pausing
-        } else if body.committing {
-            crate::database::PauseJobStatus::Committing
-        } else {
-            crate::database::PauseJobStatus::AlreadyPaused
-        })
-    }
-
-    async fn resume_job(&self, job_id: &str) -> Result<crate::database::ResumeJobStatus> {
-        let req = self
-            .client
-            .post("/v1/jobs/resume")
-            .json(&serde_json::json!({ "job_id": job_id }));
-        let (request_id, rsp) = self.client.send(req).await?;
-        let rsp = self.client.check_response(&request_id, rsp).await?;
-        let body: ResumeJobResponse = rsp.json().await.err_to_http(request_id)?;
-        Ok(if body.resumed {
-            crate::database::ResumeJobStatus::Resumed
-        } else if body.still_pausing {
-            crate::database::ResumeJobStatus::StillPausing
-        } else {
-            crate::database::ResumeJobStatus::NotPaused
-        })
-    }
-
    async fn job_history(&self, job_id: Option<&str>) -> Result<Vec<arrow_array::RecordBatch>> {
        let mut body = serde_json::json!({});
        if let Some(job_id) = job_id {
@@ -2655,45 +2596,6 @@ mod tests {
        assert!(!conn.cancel_job("nope").await.unwrap());
    }

-    #[tokio::test]
-    async fn test_pause_and_resume_job() {
-        use crate::database::{PauseJobStatus, ResumeJobStatus};
-        let conn = Connection::new_with_handler(|request| {
-            assert_eq!(request.url().path(), "/v1/jobs/pause");
-            http::Response::builder()
-                .status(200)
-                .body(r#"{"job_id": "job-1", "paused": true}"#)
-                .unwrap()
-        });
-        assert_eq!(
-            conn.pause_job("job-1").await.unwrap(),
-            PauseJobStatus::Pausing
-        );
-
-        let conn = Connection::new_with_handler(|_| {
-            http::Response::builder()
-                .status(200)
-                .body(r#"{"job_id": "job-1", "paused": false, "committing": true}"#)
-                .unwrap()
-        });
-        assert_eq!(
-            conn.pause_job("job-1").await.unwrap(),
-            PauseJobStatus::Committing
-        );
-
-        let conn = Connection::new_with_handler(|request| {
-            assert_eq!(request.url().path(), "/v1/jobs/resume");
-            http::Response::builder()
-                .status(200)
-                .body(r#"{"job_id": "job-1", "resumed": false, "still_pausing": true}"#)
-                .unwrap()
-        });
-        assert_eq!(
-            conn.resume_job("job-1").await.unwrap(),
-            ResumeJobStatus::StillPausing
-        );
-    }
-
    #[tokio::test]
    async fn test_job_history_parses_arrow_stream() {
        let schema = Arc::new(Schema::new(vec![Field::new(
@@ -2783,25 +2685,6 @@ mod tests {
        assert_eq!(version.version(), "fv_01K3EXACT");
    }

-    #[tokio::test]
-    async fn test_drop_function_sends_exact_version_and_decodes_replay() {
-        let conn = Connection::new_with_handler(|request| {
-            assert_eq!(request.method(), &reqwest::Method::POST);
-            assert_eq!(request.url().path(), "/v1/functions/drop");
-            let body: serde_json::Value =
-                serde_json::from_slice(request.body().unwrap().as_bytes().unwrap()).unwrap();
-            assert_eq!(
-                body,
-                serde_json::json!({"name": "embed", "version": "fv_01K3EXACT"})
-            );
-            http::Response::builder()
-                .status(200)
-                .body(r#"{"dropped":false}"#)
-                .unwrap()
-        });
-        assert!(!conn.drop_function("embed", "fv_01K3EXACT").await.unwrap());
-    }
-
    #[tokio::test]
    async fn test_conn_job_waits_to_done() {
        let polls = Arc::new(AtomicUsize::new(0));
@@ -73,28 +73,6 @@ pub(super) struct ReportedFailure {
    retryable: Option<bool>,
 }

-/// Forward-compatible `/v1/jobs/pause` wire envelope.
-#[derive(Deserialize)]
-pub(super) struct PauseJobResponse {
-    /// False when the job was already paused, so a repeated pause changed
-    /// nothing.
-    #[serde(default)]
-    pub(super) paused: bool,
-    /// The job is finalizing its results and cannot be parked right now.
-    #[serde(default)]
-    pub(super) committing: bool,
-}
-
-/// Forward-compatible `/v1/jobs/resume` wire envelope.
-#[derive(Deserialize)]
-pub(super) struct ResumeJobResponse {
-    #[serde(default)]
-    pub(super) resumed: bool,
-    /// The pause's worker drain is not confirmed yet.
-    #[serde(default)]
-    pub(super) still_pausing: bool,
-}
-
 /// Forward-compatible `/v1/jobs/describe` wire envelope.
 #[derive(Deserialize)]
 pub(super) struct DescribeJobResponse {
@@ -6,7 +6,6 @@
 use std::ops::Range;
 use std::sync::Arc;
 use std::sync::atomic::{AtomicBool, Ordering};
-use std::time::Duration;

 use arrow_array::{Array, LargeBinaryArray};
 use arrow_schema::DataType;
@@ -21,7 +20,7 @@ use crate::error::Result;
 use crate::remote::client::{HttpSend, RequestResultExt, RestfulLanceDbClient};
 use crate::table::BaseTable;

-use super::{FreshnessHeaders, FreshnessState, RemoteTable, freshness_headers_snapshot};
+use super::{FreshnessHeaders, RemoteTable};

 #[derive(Debug, Clone, Copy)]
 enum RangeRequestMode {
@@ -44,10 +43,7 @@ struct TableBlobRangeRequester<S: HttpSend> {
    path: String,
    version: Option<u64>,
    branch: Option<String>,
-    freshness: Arc<std::sync::Mutex<FreshnessState>>,
-    parent_freshness: Arc<std::sync::Mutex<FreshnessState>>,
-    parent_freshness_request: FreshnessHeaders,
-    read_consistency_interval: Option<Duration>,
+    freshness: FreshnessHeaders,
 }

 #[async_trait::async_trait]
@@ -57,9 +53,8 @@ impl<S: HttpSend> BlobRangeRequester for TableBlobRangeRequester<S> {
        range_header: &str,
        mode: RangeRequestMode,
    ) -> Result<(String, Response)> {
-        let freshness_request =
-            freshness_headers_snapshot(&self.freshness, self.read_consistency_interval);
-        let mut request = freshness_request
+        let mut request = self
+            .freshness
            .apply(self.client.get(&self.path))
            .header(header::RANGE, range_header);
        if let Some(version) = self.version {
@@ -76,9 +71,6 @@ impl<S: HttpSend> BlobRangeRequester for TableBlobRangeRequester<S> {
            return Ok((request_id, response));
        }
        let response = self.client.check_response(&request_id, response).await?;
-        freshness_request.observe_headers(&self.freshness, response.headers());
-        self.parent_freshness_request
-            .observe_headers(&self.parent_freshness, response.headers());
        Ok((request_id, response))
    }
 }
@@ -369,21 +361,18 @@ impl<S: HttpSend> RemoteTable<S> {
                message: "fetch_blobs is not supported on this LanceDB Cloud server".into(),
            });
        }
-        let read_snapshot = self.snapshot_read_state().await;
+        let version = self.current_version().await;
        let mut body = serde_json::json!({
-            "version": read_snapshot.version,
+            "version": version,
            "column": column,
            "row_ids": row_ids,
        });
        self.apply_branch_body(&mut body);

        let request = self
-            .client
-            .post(&format!("/v1/table/{}/fetch_blobs/", self.identifier))
+            .post_read(&format!("/v1/table/{}/fetch_blobs/", self.identifier))
            .json(&body);
-        let (request_id, response) = self
-            .send_with_freshness(request, true, read_snapshot.freshness)
-            .await?;
+        let (request_id, response) = self.send(request, true).await?;
        let mut stream = self.read_arrow_response(&request_id, response).await?;

        let mut blob_chunks: Vec<Arc<dyn Array>> = Vec::new();
@@ -459,7 +448,8 @@ impl<S: HttpSend> RemoteTable<S> {
            });
        }

-        let read_snapshot = self.snapshot_read_state().await;
+        let version = self.current_version().await;
+        let freshness = self.snapshot_freshness_headers();
        let encoded_column = urlencoding::encode(column);
        let requesters = row_ids
            .iter()
@@ -471,12 +461,9 @@ impl<S: HttpSend> RemoteTable<S> {
                let requester: Arc<dyn BlobRangeRequester> = Arc::new(TableBlobRangeRequester {
                    client: self.client.clone(),
                    path,
-                    version: read_snapshot.version,
+                    version,
                    branch: self.branch.clone(),
-                    freshness: Arc::new(std::sync::Mutex::new(read_snapshot.freshness_state)),
-                    parent_freshness: self.freshness.clone(),
-                    parent_freshness_request: read_snapshot.freshness,
-                    read_consistency_interval: self.client.read_consistency_interval,
+                    freshness,
                });
                requester
            })
@@ -698,46 +685,6 @@ mod tests {
        assert!(requests.lock().unwrap().contains(&"bytes=5-11".to_string()));
    }

-    #[tokio::test]
-    async fn remote_blob_file_keeps_the_open_timeline_after_parent_checkout() {
-        let range_requests = Arc::new(StdMutex::new(Vec::new()));
-        let captured = range_requests.clone();
-        let table = RemoteTable::new_mock(
-            "my_table".to_string(),
-            move |request| match request.url().path() {
-                "/v1/table/my_table/describe/" => http::Response::builder()
-                    .status(200)
-                    .body(r#"{"version":5,"schema":{"fields":[]}}"#.as_bytes().to_vec())
-                    .unwrap(),
-                "/v1/table/my_table/blob/image/10/bytes" => {
-                    captured.lock().unwrap().push((
-                        request.url().query().unwrap_or_default().to_string(),
-                        request.headers().clone(),
-                    ));
-                    range_response(&request, PAYLOAD)
-                }
-                path => panic!("unexpected path: {path}"),
-            },
-            Some(Version::new(0, 5, 0)),
-        );
-
-        table.checkout(5).await.unwrap();
-        let file = table
-            .fetch_blob_files_impl("image", &[10])
-            .await
-            .unwrap()
-            .pop()
-            .flatten()
-            .unwrap();
-        table.checkout_latest().await.unwrap();
-        file.read_range(5..12).await.unwrap();
-
-        let requests = range_requests.lock().unwrap();
-        let (query, headers) = requests.last().unwrap();
-        assert!(query.contains("version=5"));
-        assert!(!headers.contains_key("x-lancedb-min-timestamp"));
-    }
-
    #[tokio::test]
    async fn remote_blob_file_reuses_sequential_response_until_seek() {
        let requests = Arc::new(StdMutex::new(Vec::new()));
@@ -24,10 +24,7 @@ use lance::io::exec::utils::InstrumentedRecordBatchStreamAdapter;
 use crate::Error;
 use crate::remote::ARROW_STREAM_CONTENT_TYPE;
 use crate::remote::client::{HttpSend, RestfulLanceDbClient, Sender};
-use crate::remote::table::{
-    FreshnessHeaders, FreshnessState, MergeInsertRequest, REQUEST_TIMEOUT_HEADER, RemoteTable,
-    freshness_headers_snapshot,
-};
+use crate::remote::table::{MergeInsertRequest, REQUEST_TIMEOUT_HEADER, RemoteTable};
 use crate::table::datafusion::insert::COUNT_SCHEMA;
 use crate::table::write_progress::WriteProgressTracker;
 use crate::table::{AddResult, MergeResult};
@@ -57,38 +54,6 @@ pub enum WriteResult {
    Merge(MergeResult),
 }

-#[derive(Debug, Clone, Default)]
-struct WriteFreshness {
-    state: Option<Arc<Mutex<FreshnessState>>>,
-    read_consistency_interval: Option<Duration>,
-}
-
-impl WriteFreshness {
-    fn prepare(
-        &self,
-        request: reqwest::RequestBuilder,
-    ) -> (reqwest::RequestBuilder, Option<FreshnessHeaders>) {
-        match &self.state {
-            Some(state) => {
-                let freshness_request =
-                    freshness_headers_snapshot(state, self.read_consistency_interval);
-                (freshness_request.apply(request), Some(freshness_request))
-            }
-            None => (request, None),
-        }
-    }
-
-    fn observe(
-        &self,
-        freshness_request: Option<FreshnessHeaders>,
-        headers: &reqwest::header::HeaderMap,
-    ) {
-        if let (Some(state), Some(freshness_request)) = (&self.state, freshness_request) {
-            freshness_request.observe_headers(state, headers);
-        }
-    }
-}
-
 /// ExecutionPlan for streaming a write (add or merge_insert) to a remote
 /// LanceDB table.
 ///
@@ -106,7 +71,6 @@ pub struct RemoteWriteExec<S: HttpSend = Sender> {
    table_name: String,
    identifier: String,
    client: RestfulLanceDbClient<S>,
-    freshness: WriteFreshness,
    input: Arc<dyn ExecutionPlan>,
    op: WriteOp,
    properties: Arc<PlanProperties>,
@@ -206,7 +170,6 @@ impl<S: HttpSend + 'static> RemoteWriteExec<S> {
            table_name,
            identifier,
            client,
-            freshness: WriteFreshness::default(),
            input,
            op,
            properties: Arc::new(properties),
@@ -220,18 +183,6 @@ impl<S: HttpSend + 'static> RemoteWriteExec<S> {
        }
    }

-    pub(super) fn with_freshness(
-        mut self,
-        state: Arc<Mutex<FreshnessState>>,
-        read_consistency_interval: Option<Duration>,
-    ) -> Self {
-        self.freshness = WriteFreshness {
-            state: Some(state),
-            read_consistency_interval,
-        };
-        self
-    }
-
    /// Get the add result after execution, if this exec ran an insert.
    pub fn add_result(&self) -> Option<AddResult> {
        match self
@@ -334,7 +285,6 @@ impl<S: HttpSend + 'static> RemoteWriteExec<S> {
 /// each threading the same handful of arguments.
 struct PartRequestCtx<'a, S: HttpSend> {
    client: &'a RestfulLanceDbClient<S>,
-    freshness: &'a WriteFreshness,
    identifier: &'a str,
    table_name: &'a str,
    upload_id: &'a str,
@@ -402,11 +352,7 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
    }

    /// Build the `/insert` request for a single multipart part.
-    fn build_part_request(
-        &self,
-        part_id: &str,
-        body: reqwest::Body,
-    ) -> (reqwest::RequestBuilder, Option<FreshnessHeaders>) {
+    fn build_part_request(&self, part_id: &str, body: reqwest::Body) -> reqwest::RequestBuilder {
        let mut request = self
            .client
            .post(&format!("/v1/table/{}/insert/", self.identifier))
@@ -422,16 +368,12 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
        if let Some(b) = self.branch {
            request = request.query(&[("branch", b)]);
        }
-        self.freshness.prepare(request.body(body))
+        request.body(body)
    }

    /// Send a single part's request and drain the response, mapping HTTP and
    /// table-not-found errors into `DataFusionError`.
-    async fn send_part_request(
-        &self,
-        request: reqwest::RequestBuilder,
-        freshness_request: Option<FreshnessHeaders>,
-    ) -> DataFusionResult<()> {
+    async fn send_part_request(&self, request: reqwest::RequestBuilder) -> DataFusionResult<()> {
        let (request_id, response) = self
            .client
            .send(request)
@@ -446,8 +388,6 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
            .check_response(&request_id, response)
            .await
            .map_err(|e| DataFusionError::External(Box::new(e)))?;
-        self.freshness
-            .observe(freshness_request, response.headers());
        response.bytes().await.map_err(|e| {
            DataFusionError::External(Box::new(Error::Http {
                source: Box::new(e),
@@ -479,7 +419,7 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
        let body = reqwest::Body::wrap_stream(chunk_rx);

        let part_id = uuid::Uuid::new_v4().to_string();
-        let (request, freshness_request) = self.build_part_request(&part_id, body);
+        let request = self.build_part_request(&part_id, body);

        // Measured from just before the request is sent, matching the window the
        // client read timeout applies to the upload.
@@ -555,7 +495,7 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
            Ok::<bool, DataFusionError>(input_ended)
        };

-        let send = self.send_part_request(request, freshness_request);
+        let send = self.send_part_request(request);

        // `join!` rather than `tokio::spawn`: the producer borrows `input` (and
        // `schema`), so it cannot satisfy the `'static` bound a spawned task
@@ -629,7 +569,7 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
        // Building a fresh exec (with a new, empty `result`) is what makes the
        // outer rescannable retry loop work: `reset_state()` clears the captured
        // result so a re-execution starts clean.
-        let mut exec = Self::new_inner(
+        Ok(Arc::new(Self::new_inner(
            self.table_name.clone(),
            self.identifier.clone(),
            self.client.clone(),
@@ -640,9 +580,7 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
            self.branch.clone(),
            self.max_bytes_per_request,
            self.max_request_duration,
-        );
-        exec.freshness = self.freshness.clone();
-        Ok(Arc::new(exec))
+        )))
    }

    fn execute(
@@ -675,7 +613,6 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
                &self.metrics,
            ));
        let client = self.client.clone();
-        let freshness = self.freshness.clone();
        let identifier = self.identifier.clone();
        let op = self.op.clone();
        let result_slot = self.result.clone();
@@ -697,7 +634,6 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
                let overwrite = matches!(op, WriteOp::Insert { overwrite: true });
                let ctx = PartRequestCtx {
                    client: &client,
-                    freshness: &freshness,
                    identifier: &identifier,
                    table_name: &table_name,
                    upload_id,
@@ -752,7 +688,7 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {

            let (error_tx, mut error_rx) = tokio::sync::oneshot::channel();
            let body = Self::stream_as_http_body(input_stream, error_tx, tracker)?;
-            let (request, freshness_request) = freshness.prepare(request.body(body));
+            let request = request.body(body);

            let result: DataFusionResult<(String, _)> = async {
                let (request_id, response) = client
@@ -772,7 +708,6 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
                    .check_response(&request_id, response)
                    .await
                    .map_err(|e| DataFusionError::External(Box::new(e)))?;
-                freshness.observe(freshness_request, response.headers());

                Ok((request_id, response))
            }
@@ -59,9 +59,7 @@ use crate::index::{IndexConfig, IndexStatisticsImpl, IndexType};
 use crate::job::Job;
 use crate::query::{IntoQueryVector, Query, QueryExecutionOptions, TakeQuery, VectorQuery};
 use crate::table::datafusion::insert::InsertExec;
-use crate::utils::{
-    PatchReadParam, PatchWriteParam, public_fts_field_path_by_id, resolve_arrow_field_path,
-};
+use crate::utils::{PatchReadParam, PatchWriteParam, resolve_arrow_field_path};

 use self::dataset::DatasetConsistencyWrapper;
 use self::merge::MergeInsertBuilder;
@@ -562,13 +560,6 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
    fn id(&self) -> &str;
    /// Get the arrow [Schema] of the table.
    async fn schema(&self) -> Result<SchemaRef>;
-    /// Create a read-only handle pinned to the table's current active revision.
-    ///
-    /// The returned handle is independent from later refreshes or checkouts on
-    /// this handle.  This is used by bindings that must prepare client-side
-    /// query state from the same revision that the query will execute against.
-    #[doc(hidden)]
-    async fn query_snapshot(&self) -> Result<Arc<dyn BaseTable>>;
    /// Count the number of rows in this table.
    async fn count_rows(&self, filter: Option<Filter>) -> Result<usize>;
    /// Create a physical plan for the query.
@@ -595,14 +586,6 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
        query: &AnyQuery,
        options: QueryExecutionOptions,
    ) -> Result<String>;
-    /// Whether [`BaseTable::analyze_plan`] is provided by a remote service.
-    ///
-    /// Client-side query wrappers use this to preserve backend metrics and
-    /// distributed-analysis options instead of replacing them with a local plan.
-    #[doc(hidden)]
-    fn analyze_plan_is_remote(&self) -> bool {
-        false
-    }

    /// Add new records to the table.
    async fn add(&self, add: AddDataBuilder) -> Result<AddResult>;
@@ -758,8 +741,8 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
    /// Declare computed columns, each defined by a SQL expression.
    ///
    /// Where the declaration is planned depends on the backend: a local table
-    /// validates and types the expression itself, while a remote one sends the
-    /// expression for the server to plan.
+    /// validates and types the expression itself, a remote one sends the text
+    /// for the server to plan.
    async fn add_computed_columns(
        &self,
        _columns: &[(String, String)],
@@ -1156,26 +1139,13 @@ impl Table {
        self.inner.schema().await
    }

-    /// Create a read-only handle pinned to the current active revision.
-    #[doc(hidden)]
-    pub async fn query_snapshot(&self) -> Result<Self> {
-        Ok(Self {
-            inner: self.inner.query_snapshot().await?,
-            database: self.database.clone(),
-            embedding_registry: self.embedding_registry.clone(),
-        })
-    }
-
    /// Count the number of rows in this dataset.
    ///
    /// # Arguments
    ///
    /// * `filter` if present, only count rows matching the filter
    pub async fn count_rows(&self, filter: Option<String>) -> Result<usize> {
-        let filter = filter
-            .map(|predicate| crate::expr::canonicalize_sql_predicate(&predicate).map(Filter::Sql))
-            .transpose()?;
-        self.inner.count_rows(filter).await
+        self.inner.count_rows(filter.map(Filter::Sql)).await
    }

    /// Names of the blob v2 columns in this table, in declaration order.
@@ -1375,13 +1345,7 @@ impl Table {
    /// # });
    /// ```
    pub async fn delete(&self, predicate: impl Into<Predicate<'_>>) -> Result<DeleteResult> {
-        match predicate.into() {
-            Predicate::String(predicate) => {
-                let predicate = crate::expr::canonicalize_sql_predicate(predicate)?;
-                self.inner.delete(Predicate::String(&predicate)).await
-            }
-            predicate @ Predicate::Expr(_) => self.inner.delete(predicate).await,
-        }
+        self.inner.delete(predicate.into()).await
    }

    /// Create an index on the provided column(s).
@@ -1660,9 +1624,9 @@ impl Table {
    /// Offsets are useful for sampling as the set of all valid offsets is easily
    /// known in advance to be [0, len(table)).
    ///
-    /// No guarantees are made regarding the order in which results are returned.
-    /// Repeated offsets produce repeated rows, which makes this method suitable for
-    /// sampling with replacement.
+    /// No guarantees are made regarding the order in which results are returned.  If you
+    /// desire an output order that matches the order of the given offsets, you will need
+    /// to add the row offset column to the output and align it yourself.
    ///
    /// Parameters
    /// ----------
@@ -1794,23 +1758,7 @@ impl Table {
        self.inner.alter_columns(alterations).await
    }

-    /// Update per-field (column) metadata.
-    ///
-    /// Each [`FieldMetadataUpdate`] is merged into the field's existing metadata
-    /// by default; use [`FieldMetadataUpdate::remove`] to delete a key, or
-    /// [`FieldMetadataUpdate::replace`] to swap the field's entire metadata map.
-    ///
-    /// The following keys are treated specially, by convention, and should be
-    /// used when appropriate:
-    ///
-    /// - `lancedb:description`: for a human-readable description of a field.
-    /// - `lancedb:tag:<name>`: for a user-defined key-value tag, where the suffix
-    ///   names the tag category; e.g. `lancedb:tag:model: "clip"`.
-    /// - `lancedb:logical-column`: for a column grouping; e.g. `feature_v1` and
-    ///   `feature_v2` might be in the same logical column.
-    /// - `lancedb:status`: for status options (`production`, `candidate`,
-    ///   `deprecated`, `archived`) to designate the current life cycle state of
-    ///   this column.
+    /// Update per-field metadata (merges by default).
    pub async fn update_field_metadata(
        &self,
        updates: &[FieldMetadataUpdate],
@@ -3111,17 +3059,6 @@ impl BaseTable for NativeTable {
        &self.id
    }

-    async fn query_snapshot(&self) -> Result<Arc<dyn BaseTable>> {
-        let snapshot = self.dataset.new_query_snapshot().await?;
-        let mut table = self.with_dataset(snapshot);
-        // QueryTable requests do not carry a revision. A pinned snapshot must
-        // execute locally until the namespace API can accept that revision.
-        table
-            .pushdown_operations
-            .remove(&NamespaceClientPushdownOperation::QueryTable);
-        Ok(Arc::new(table))
-    }
-
    async fn version(&self) -> Result<u64> {
        Ok(self.dataset.get().await?.version().version)
    }
@@ -3256,10 +3193,7 @@ impl BaseTable for NativeTable {
        let dataset = self.dataset.get().await?;
        match filter {
            None => Ok(dataset.count_rows(None).await?),
-            Some(Filter::Sql(sql)) => {
-                let sql = crate::expr::canonicalize_sql_predicate(&sql)?;
-                Ok(dataset.count_rows(Some(sql)).await?)
-            }
+            Some(Filter::Sql(sql)) => Ok(dataset.count_rows(Some(sql)).await?),
            Some(Filter::Datafusion(_)) => Err(Error::NotSupported {
                message: "Datafusion filters are not yet supported".to_string(),
            }),
@@ -3597,14 +3531,7 @@ impl BaseTable for NativeTable {
                let field_ids = idx_desc.field_ids();
                let mut columns = Vec::with_capacity(field_ids.len());
                for field_id in field_ids {
-                    let field_path = match if index_type == crate::index::IndexType::FTS {
-                        public_fts_field_path_by_id(dataset.schema(), *field_id as i32)
-                    } else {
-                        dataset
-                            .schema()
-                            .field_path(*field_id as i32)
-                            .map_err(Into::into)
-                    } {
+                    let field_path = match dataset.schema().field_path(*field_id as i32) {
                        Ok(field_path) => field_path,
                        Err(e) => {
                            log::warn!(
@@ -4191,14 +4118,6 @@ mod tests {
                parent_list_calls: self.parent_list_calls.clone(),
            })
        }
-
-        fn wrap_paginated(
-            &self,
-            _store_prefix: &str,
-            _original: Arc<dyn object_store::list::PaginatedListStore>,
-        ) -> Option<Arc<dyn object_store::list::PaginatedListStore>> {
-            None
-        }
    }

    #[tokio::test]
@@ -4302,14 +4221,6 @@ mod tests {
            self.called.store(true, Ordering::Relaxed);
            original
        }
-
-        fn wrap_paginated(
-            &self,
-            _store_prefix: &str,
-            original: Arc<dyn object_store::list::PaginatedListStore>,
-        ) -> Option<Arc<dyn object_store::list::PaginatedListStore>> {
-            Some(original)
-        }
    }

    #[tokio::test]
@@ -5771,13 +5682,6 @@ mod tests {
        assert!(index_bytes > 0);
        assert_eq!(with_index, data_only + index_bytes);

-        // Release builds reject unstable overlay datasets unless explicitly opted in.
-        if !lance_table::feature_flags::can_read_dataset(
-            lance_table::feature_flags::FLAG_UNSTABLE_DATA_OVERLAY_FILES,
-        ) {
-            return;
-        }
-
        // Commit an overlay file supplying new `foo` values for the first three
        // rows of fragment 0. There is no high-level API that writes overlays
        // yet, so write the overlay's data file and commit the `DataOverlay`
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Xuanwo	8f843a8469	Merge branch 'main' into gatekeeper/fix-2085-1	2026-08-26 05:09:04 +08:00
Gatefixer	1f4eea1f17	Merge origin/main into gatekeeper/fix-2085-1	2026-08-08 20:10:35 +00:00
Gatefixer	4ba24bf64b	test(rust): detect indexed delete compilation regressions	2026-08-08 12:35:32 +00:00
Gatefixer	28b365fc62	Merge remote-tracking branch 'origin/main' into gatekeeper/fix-2085-1	2026-08-08 12:12:43 +00:00
Gatefixer	267577989b	test(rust): cover large indexed deletes	2026-08-05 23:26:26 +00:00