Bump version: 0.35.0-beta.0 → 0.35.0-beta.1

ci(nodejs): move Windows builds to larger runner and use ThinLTO (#3634 )
The `build - aarch64-pc-windows-msvc` node build job (and, marginally, the x86_64 one) had started hitting `rustc-LLVM ERROR: out of memory` while linking the `lancedb-nodejs` cdylib — most recently surfaced by #3526, which adds the goosefs backend (and its tonic/prost gRPC subtree) to the default node binary. The peak-memory step is the fat-LTO codegen (`lto=fat`, `codegen-units=1` from `.cargo/config.toml`), which merges the whole crate graph into a single LLVM module and runs single-threaded. It therefore neither parallelizes across cores nor fits in the 16 GB of the standard `windows-latest` runner as the dependency graph grows. This PR: - Moves both `*-pc-windows-msvc` node build jobs to `windows-2025-8x-x64` (more memory + cores). - Overrides the release profile to ThinLTO for just these jobs, via `CARGO_PROFILE_RELEASE_LTO=thin` / `CARGO_PROFILE_RELEASE_CODEGEN_UNITS=16` in `pre_build`. ThinLTO parallelizes the cross-module optimization across the runner's cores and keeps peak memory well under the limit. Scoped so Python wheels and Rust release builds keep fat LTO. The larger runner alone would clear the OOM but waste the added cores on the single-threaded fat-LTO tail; ThinLTO is what makes the extra cores actually reduce wall-clock and gives durable memory headroom for future dependency growth. Tradeoff: ThinLTO can leave a small runtime-perf gap vs fat LTO for the node native binary, but it recovers most of it and is a common release configuration. Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-08-26 07:58:31 +00:00 · 2026-07-10 16:12:51 +00:00 · 2026-07-10 08:50:43 -07:00 · 2026-07-10 05:26:01 +00:00 · 2026-07-10 05:25:24 +00:00 · 2026-07-09 15:36:03 -07:00
76 changed files with 5980 additions and 254 deletions
@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.31.0-beta.5"
+current_version = "0.32.0-beta.0"
 parse = """(?x)
    (?P<major>0|[1-9]\\d*)\\.
    (?P<minor>0|[1-9]\\d*)\\.
@@ -0,0 +1,21 @@
+# CODEOWNERS
+#
+# These owners will be the default owners for everything in the repo.
+# They will be requested for review when someone opens a pull request.
+#
+# See https://docs.github.com/en/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-code-owners
+
+# Default owners for everything
+* @jackye1995 @wjones127
+
+# Release and publish workflows — changes here can affect supply chain security
+/.github/workflows/ @jackye1995 @wjones127 @Xuanwo
+
+# Remote client and auth — sensitive networking and auth code
+/rust/lancedb/src/remote/ @jackye1995 @wjones127
+
+# Python FFI boundary
+/python/src/ @jackye1995 @wjones127 @AyushExel
+
+# NodeJS FFI boundary
+/nodejs/src/ @jackye1995 @wjones127
@@ -34,15 +34,16 @@ runs:
        maturin-version: "1.12.4"
        command: build
        working-directory: python
-        docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/'"
+        docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/' -e PROTOC=/usr/local/bin/protoc"
        target: x86_64-unknown-linux-gnu
        manylinux: ${{ inputs.manylinux }}
        args: ${{ inputs.args }}
        before-script-linux: |
          set -e
-          curl -L https://github.com/protocolbuffers/protobuf/releases/download/v24.4/protoc-24.4-linux-$(uname -m).zip > /tmp/protoc.zip \
-            && unzip /tmp/protoc.zip -d /usr/local \
-            && rm /tmp/protoc.zip
+          curl -fsSL https://github.com/protocolbuffers/protobuf/releases/download/v24.4/protoc-24.4-linux-x86_64.zip -o /tmp/protoc.zip
+          unzip /tmp/protoc.zip -d /usr/local
+          rm /tmp/protoc.zip
+          /usr/local/bin/protoc --version
    - name: Build Arm Manylinux Wheel
      if: ${{ inputs.arm-build == 'true' }}
      uses: PyO3/maturin-action@v1
@@ -50,13 +51,14 @@ runs:
        maturin-version: "1.12.4"
        command: build
        working-directory: python
-        docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/'"
+        docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/' -e PROTOC=/usr/local/bin/protoc"
        target: aarch64-unknown-linux-gnu
        manylinux: ${{ inputs.manylinux }}
        args: ${{ inputs.args }}
        before-script-linux: |
          set -e
-          yum install -y clang \
-            && curl -L https://github.com/protocolbuffers/protobuf/releases/download/v24.4/protoc-24.4-linux-aarch_64.zip > /tmp/protoc.zip \
-            && unzip /tmp/protoc.zip -d /usr/local \
-            && rm /tmp/protoc.zip
+          yum install -y clang
+          curl -fsSL https://github.com/protocolbuffers/protobuf/releases/download/v24.4/protoc-24.4-linux-aarch_64.zip -o /tmp/protoc.zip
+          unzip /tmp/protoc.zip -d /usr/local
+          rm /tmp/protoc.zip
+          /usr/local/bin/protoc --version
@@ -103,7 +103,7 @@ jobs:
            features: fp16kernels
            pre_build: brew install protobuf
          - target: x86_64-pc-windows-msvc
-            host: windows-latest
+            host: windows-2025-8x-x64
            features: ","
            pre_build: |-
              choco install --no-progress protoc ninja nasm
@@ -111,12 +111,21 @@ jobs:
              # There is an issue where choco doesn't add nasm to the path
              export PATH="$PATH:/c/Program Files/NASM"
              nasm -v
+              # Fat LTO of the cdylib is single-threaded and the peak-memory
+              # step of the build, and had started hitting rustc-LLVM OOM on the
+              # Windows runners. ThinLTO parallelizes it across the runner's
+              # cores and keeps peak memory well under the limit.
+              export CARGO_PROFILE_RELEASE_LTO=thin
+              export CARGO_PROFILE_RELEASE_CODEGEN_UNITS=16
          - target: aarch64-pc-windows-msvc
-            host: windows-latest
+            host: windows-2025-8x-x64
            features: ","
            pre_build: |-
                choco install --no-progress protoc
                rustup target add aarch64-pc-windows-msvc
+                # See ThinLTO note on the x86_64-pc-windows-msvc target 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
@@ -2039,9 +2039,9 @@ dependencies = [

 [[package]]
 name = "crossbeam-epoch"
-version = "0.9.18"
+version = "0.9.20"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5b82ac4a3c2ca9c3460964f020e1402edd5753411d7737aa39c3714ad1b5420e"
+checksum = "2d6914041f254d6e9176c01941b21115dcfb7089e55135a35411081bd106ef3f"
 dependencies = [
 "crossbeam-utils",
 ]
@@ -3151,6 +3151,12 @@ dependencies = [
 "encoding_rs",
 ]

+[[package]]
+name = "endian-type"
+version = "0.1.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "c34f04666d835ff5d62e058c3995147c06f42fe86ff053337632bca83e42702d"
+
 [[package]]
 name = "enum-as-inner"
 version = "0.6.1"
@@ -3423,8 +3429,8 @@ checksum = "42703706b716c37f96a77aea830392ad231f44c9e9a67872fa5548707e11b11c"

 [[package]]
 name = "fsst"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow-array",
 "rand 0.9.4",
@@ -3779,6 +3785,30 @@ dependencies = [
 "wasm-bindgen",
 ]

+[[package]]
+name = "goosefs-sdk"
+version = "0.1.5"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "9ae079b88ffe7772d12cfc5c40a5a324babb357893d95b5e3a22ae857f236c5f"
+dependencies = [
+ "async-trait",
+ "bytes",
+ "dashmap",
+ "hostname",
+ "prost",
+ "prost-types",
+ "rand 0.9.4",
+ "reqwest 0.12.28",
+ "serde",
+ "thiserror 2.0.18",
+ "tokio",
+ "tokio-stream",
+ "tonic",
+ "tonic-prost",
+ "tracing",
+ "uuid",
+]
+
 [[package]]
 name = "group"
 version = "0.12.1"
@@ -3990,6 +4020,17 @@ dependencies = [
 "windows-sys 0.61.2",
 ]

+[[package]]
+name = "hostname"
+version = "0.4.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "617aaa3557aef3810a6369d0a99fac8a080891b68bd9f9812a1eeda0c0730cbd"
+dependencies = [
+ "cfg-if 1.0.4",
+ "libc",
+ "windows-link",
+]
+
 [[package]]
 name = "http"
 version = "0.2.12"
@@ -4150,6 +4191,19 @@ dependencies = [
 "webpki-roots 1.0.7",
 ]

+[[package]]
+name = "hyper-timeout"
+version = "0.5.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "2b90d566bffbce6a75bd8b09a05aa8c2cb1fabb6cb348f8840c9e4c90a0d83b0"
+dependencies = [
+ "hyper 1.9.0",
+ "hyper-util",
+ "pin-project-lite",
+ "tokio",
+ "tower-service",
+]
+
 [[package]]
 name = "hyper-util"
 version = "0.1.20"
@@ -4673,7 +4727,7 @@ dependencies = [
 "jiff",
 "nom 8.0.0",
 "num-traits",
- "ordered-float",
+ "ordered-float 5.3.0",
 "rand 0.9.4",
 "serde",
 "serde_json",
@@ -4726,8 +4780,8 @@ checksum = "e037a2e1d8d5fdbd49b16a4ea09d5d6401c1f29eca5ff29d03d3824dba16256a"

 [[package]]
 name = "lance"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arc-swap",
 "arrow",
@@ -4801,8 +4855,8 @@ dependencies = [

 [[package]]
 name = "lance-arrow"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -4811,6 +4865,7 @@ dependencies = [
 "arrow-ord",
 "arrow-schema",
 "arrow-select",
+ "bytemuck",
 "bytes",
 "futures",
 "getrandom 0.2.17",
@@ -4823,7 +4878,7 @@ dependencies = [
 [[package]]
 name = "lance-arrow-scalar"
 version = "58.0.0"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -4837,7 +4892,7 @@ dependencies = [
 [[package]]
 name = "lance-arrow-stats"
 version = "58.0.0"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow-array",
 "arrow-schema",
@@ -4846,8 +4901,8 @@ dependencies = [

 [[package]]
 name = "lance-bitpacking"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrayref",
 "crunchy",
@@ -4857,8 +4912,8 @@ dependencies = [

 [[package]]
 name = "lance-core"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -4896,8 +4951,8 @@ dependencies = [

 [[package]]
 name = "lance-datafusion"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow",
 "arrow-array",
@@ -4927,8 +4982,8 @@ dependencies = [

 [[package]]
 name = "lance-datagen"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow",
 "arrow-array",
@@ -4945,8 +5000,8 @@ dependencies = [

 [[package]]
 name = "lance-derive"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "proc-macro2",
 "quote",
@@ -4955,8 +5010,8 @@ dependencies = [

 [[package]]
 name = "lance-encoding"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow-arith",
 "arrow-array",
@@ -4991,8 +5046,8 @@ dependencies = [

 [[package]]
 name = "lance-file"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow-arith",
 "arrow-array",
@@ -5022,8 +5077,8 @@ dependencies = [

 [[package]]
 name = "lance-index"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arc-swap",
 "arrow",
@@ -5088,8 +5143,8 @@ dependencies = [

 [[package]]
 name = "lance-io"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow",
 "arrow-arith",
@@ -5113,6 +5168,7 @@ dependencies = [
 "lance-core",
 "lance-namespace",
 "log",
+ "metrics",
 "moka",
 "object_store",
 "object_store_opendal",
@@ -5130,8 +5186,8 @@ dependencies = [

 [[package]]
 name = "lance-linalg"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -5147,8 +5203,8 @@ dependencies = [

 [[package]]
 name = "lance-namespace"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow",
 "async-trait",
@@ -5160,8 +5216,8 @@ dependencies = [

 [[package]]
 name = "lance-namespace-impls"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow",
 "arrow-ipc",
@@ -5184,7 +5240,7 @@ dependencies = [
 "lance-table",
 "log",
 "object_store",
- "quick-xml 0.38.4",
+ "quick-xml 0.40.1",
 "rand 0.9.4",
 "reqwest 0.12.28",
 "roaring",
@@ -5215,8 +5271,8 @@ dependencies = [

 [[package]]
 name = "lance-select"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -5231,8 +5287,8 @@ dependencies = [

 [[package]]
 name = "lance-table"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow",
 "arrow-array",
@@ -5271,22 +5327,22 @@ dependencies = [

 [[package]]
 name = "lance-testing"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "arrow-array",
 "arrow-schema",
 "criterion",
 "lance-arrow",
 "num-traits",
- "pprof",
+ "pprof 0.15.0",
 "rand 0.9.4",
 ]

 [[package]]
 name = "lance-tokenizer"
-version = "9.0.0-beta.10"
-source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.10#e25b71e74b89d10c57b412d111bde087117383f3"
+version = "9.0.0-beta.19"
+source = "git+https://github.com/lance-format/lance.git?tag=v9.0.0-beta.19#8f0e6d3a7c53438275b134c0ac1afbc80600616e"
 dependencies = [
 "icu_segmenter",
 "jieba-rs",
@@ -5299,7 +5355,7 @@ dependencies = [

 [[package]]
 name = "lancedb"
-version = "0.31.0-beta.5"
+version = "0.32.0-beta.0"
 dependencies = [
 "ahash",
 "anyhow",
@@ -5355,12 +5411,15 @@ dependencies = [
 "lance-testing",
 "lazy_static",
 "log",
+ "metrics",
+ "metrics-util",
 "moka",
 "num-traits",
 "object_store",
 "pin-project",
 "polars",
 "polars-arrow",
+ "pprof 0.14.1",
 "rand 0.9.4",
 "random_word",
 "regex",
@@ -5384,7 +5443,7 @@ dependencies = [

 [[package]]
 name = "lancedb-nodejs"
-version = "0.31.0-beta.5"
+version = "0.32.0-beta.0"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -5409,7 +5468,7 @@ dependencies = [

 [[package]]
 name = "lancedb-python"
-version = "0.34.0-beta.5"
+version = "0.35.0-beta.0"
 dependencies = [
 "arrow",
 "async-trait",
@@ -5811,6 +5870,36 @@ dependencies = [
 "stable_deref_trait",
 ]

+[[package]]
+name = "metrics"
+version = "0.24.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "89550ee9f79e88fef3119de263694973a8adb26c21d75322164fb8c493039fe2"
+dependencies = [
+ "portable-atomic",
+ "rapidhash",
+]
+
+[[package]]
+name = "metrics-util"
+version = "0.19.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "b8496cc523d1f94c1385dd8f0f0c2c480b2b8aeccb5b7e4485ad6365523ae376"
+dependencies = [
+ "aho-corasick",
+ "crossbeam-epoch",
+ "crossbeam-utils",
+ "hashbrown 0.15.5",
+ "indexmap 2.14.0",
+ "metrics",
+ "ordered-float 4.6.0",
+ "quanta",
+ "radix_trie",
+ "rand 0.9.4",
+ "rand_xoshiro",
+ "sketches-ddsketch",
+]
+
 [[package]]
 name = "mime"
 version = "0.3.17"
@@ -5952,9 +6041,9 @@ dependencies = [

 [[package]]
 name = "napi"
-version = "3.9.4"
+version = "3.10.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b41bda2ac390efb5e8d22025d925ccc3f3807d8c1bea6d19b36127247c4b8f83"
+checksum = "0c71997d6f7ad4a756966e452426848ac27d3b37a295302d63afbbcce0270f93"
 dependencies = [
 "bitflags 2.11.1",
 "chrono",
@@ -5977,9 +6066,9 @@ checksum = "c9c366d2c8c60b86fa632df75f745509b52f9128f91a6bad4c796e44abb505e1"

 [[package]]
 name = "napi-derive"
-version = "3.5.7"
+version = "3.5.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "61d66f70256ad5aef58659966064471d0ad90e2897bc36a5a5e0389c85aabc1e"
+checksum = "d4ba572deef53e2c386759a8c2014175a62679d74ff83adc205c8bc0e0285727"
 dependencies = [
 "convert_case",
 "ctor 1.0.5",
@@ -5991,9 +6080,9 @@ dependencies = [

 [[package]]
 name = "napi-derive-backend"
-version = "5.0.5"
+version = "5.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "81b4b08f15eed7a2a20c3f4c6314013fc3ac890a3afa9892b594485299ebdb2d"
+checksum = "ddd961eb2aa8965e3f29722d754f3a86907eb1984e2fbcbe3fe87b9a02d6bfba"
 dependencies = [
 "convert_case",
 "proc-macro2",
@@ -6026,6 +6115,15 @@ dependencies = [
 "rawpointer",
 ]

+[[package]]
+name = "nibble_vec"
+version = "0.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "77a5d83df9f36fe23f0c3648c6bbb8b0298bb5f1939c8f2704431371f4b84d43"
+dependencies = [
+ "smallvec",
+]
+
 [[package]]
 name = "nix"
 version = "0.26.4"
@@ -6341,7 +6439,9 @@ dependencies = [
 "opendal-layer-timeout",
 "opendal-service-azblob",
 "opendal-service-azdls",
+ "opendal-service-cos",
 "opendal-service-gcs",
+ "opendal-service-goosefs",
 "opendal-service-hf",
 "opendal-service-oss",
 "opendal-service-s3",
@@ -6469,6 +6569,23 @@ dependencies = [
 "opendal-core",
 ]

+[[package]]
+name = "opendal-service-cos"
+version = "0.57.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "aa8cafe9729213375c7331019b0cb756ad3e1aff7f45cd32c45eae91ebde8901"
+dependencies = [
+ "bytes",
+ "http 1.4.2",
+ "log",
+ "opendal-core",
+ "quick-xml 0.39.4",
+ "reqsign-core",
+ "reqsign-file-read-tokio",
+ "reqsign-tencent-cos",
+ "serde",
+]
+
 [[package]]
 name = "opendal-service-gcs"
 version = "0.57.0"
@@ -6490,6 +6607,20 @@ dependencies = [
 "tokio",
 ]

+[[package]]
+name = "opendal-service-goosefs"
+version = "0.57.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "69e43048bde419947ba826fbdc2f134d6c03f44ebf48bd33a03b72f9fc45fcb4"
+dependencies = [
+ "bytes",
+ "goosefs-sdk",
+ "log",
+ "opendal-core",
+ "serde",
+ "tokio",
+]
+
 [[package]]
 name = "opendal-service-hf"
 version = "0.57.0"
@@ -6557,6 +6688,15 @@ version = "0.2.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "04744f49eae99ab78e0d5c0b603ab218f515ea8cfe5a456d7629ad883a3b6e7d"

+[[package]]
+name = "ordered-float"
+version = "4.6.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "7bb71e1b3fa6ca1c61f383464aaf2bb0e2f8e772a1f01d486832464de363b951"
+dependencies = [
+ "num-traits",
+]
+
 [[package]]
 name = "ordered-float"
 version = "5.3.0"
@@ -7326,6 +7466,28 @@ version = "0.2.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "439ee305def115ba05938db6eb1644ff94165c5ab5e9420d1c1bcedbba909391"

+[[package]]
+name = "pprof"
+version = "0.14.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "afad4d4df7b31280028245f152d5a575083e2abb822d05736f5e47653e77689f"
+dependencies = [
+ "aligned-vec",
+ "backtrace",
+ "cfg-if 1.0.4",
+ "findshlibs",
+ "inferno",
+ "libc",
+ "log",
+ "nix",
+ "once_cell",
+ "smallvec",
+ "spin 0.10.0",
+ "symbolic-demangle",
+ "tempfile",
+ "thiserror 1.0.69",
+]
+
 [[package]]
 name = "pprof"
 version = "0.15.0"
@@ -7575,19 +7737,25 @@ dependencies = [
 ]

 [[package]]
-name = "quick-xml"
-version = "0.26.0"
+name = "quanta"
+version = "0.12.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7f50b1c63b38611e7d4d7f68b82d3ad0cc71a2ad2e7f61fc10f1328d917c93cd"
+checksum = "f3ab5a9d756f0d97bdc89019bd2e4ea098cf9cde50ee7564dde6b81ccc8f06c7"
 dependencies = [
- "memchr",
+ "crossbeam-utils",
+ "libc",
+ "once_cell",
+ "raw-cpuid",
+ "wasi 0.11.1+wasi-snapshot-preview1",
+ "web-sys",
+ "winapi",
 ]

 [[package]]
 name = "quick-xml"
-version = "0.38.4"
+version = "0.26.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b66c2058c55a409d601666cffe35f04333cf1013010882cec174a7467cd4e21c"
+checksum = "7f50b1c63b38611e7d4d7f68b82d3ad0cc71a2ad2e7f61fc10f1328d917c93cd"
 dependencies = [
 "memchr",
 ]
@@ -7602,6 +7770,15 @@ dependencies = [
 "serde",
 ]

+[[package]]
+name = "quick-xml"
+version = "0.40.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "2474bd2e5029e7ccb6abb2ba48cf2383a333851dedf495901544281590c7da7f"
+dependencies = [
+ "memchr",
+]
+
 [[package]]
 name = "quinn"
 version = "0.11.9"
@@ -7685,6 +7862,16 @@ version = "0.7.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "dc33ff2d4973d518d823d61aa239014831e521c75da58e3df4840d3f47749d09"

+[[package]]
+name = "radix_trie"
+version = "0.2.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "c069c179fcdc6a2fe24d8d18305cf085fdbd4f922c041943e203685d6a1c58fd"
+dependencies = [
+ "endian-type",
+ "nibble_vec",
+]
+
 [[package]]
 name = "rancor"
 version = "0.1.1"
@@ -7819,6 +8006,15 @@ version = "1.7.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "973443cf09a9c8656b574a866ab68dfa19f0867d0340648c7d2f6a71b8a8ea68"

+[[package]]
+name = "rapidhash"
+version = "4.5.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "5da7e78a036ce858e8d55b7e7dc8ba3a88b78350fd2155d3591bbd966b58589e"
+dependencies = [
+ "rustversion",
+]
+
 [[package]]
 name = "raw-cpuid"
 version = "11.6.0"
@@ -8103,6 +8299,21 @@ dependencies = [
 "tokio",
 ]

+[[package]]
+name = "reqsign-tencent-cos"
+version = "3.0.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "e128f19525861dbded59e1e7c17653a8ed63d573ca04aed708d552dbef5bb32a"
+dependencies = [
+ "anyhow",
+ "http 1.4.2",
+ "log",
+ "percent-encoding",
+ "reqsign-core",
+ "serde",
+ "serde_json",
+]
+
 [[package]]
 name = "reqwest"
 version = "0.12.28"
@@ -8981,6 +9192,12 @@ version = "1.0.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "8ee5873ec9cce0195efcb7a4e9507a04cd49aec9c83d0389df45b1ef7ba2e649"

+[[package]]
+name = "sketches-ddsketch"
+version = "0.3.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "0c6f73aeb92d671e0cc4dca167e59b2deb6387c375391bc99ee743f326994a2b"
+
 [[package]]
 name = "slab"
 version = "0.4.12"
@@ -9788,6 +10005,45 @@ dependencies = [
 "winnow",
 ]

+[[package]]
+name = "tonic"
+version = "0.14.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "ac2a5518c70fa84342385732db33fb3f44bc4cc748936eb5833d2df34d6445ef"
+dependencies = [
+ "async-trait",
+ "base64 0.22.1",
+ "bytes",
+ "h2 0.4.14",
+ "http 1.4.2",
+ "http-body 1.0.1",
+ "http-body-util",
+ "hyper 1.9.0",
+ "hyper-timeout",
+ "hyper-util",
+ "percent-encoding",
+ "pin-project",
+ "socket2 0.6.3",
+ "sync_wrapper",
+ "tokio",
+ "tokio-stream",
+ "tower",
+ "tower-layer",
+ "tower-service",
+ "tracing",
+]
+
+[[package]]
+name = "tonic-prost"
+version = "0.14.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "50849f68853be452acf590cde0b146665b8d507b3b8af17261df47e02c209ea0"
+dependencies = [
+ "bytes",
+ "prost",
+ "tonic",
+]
+
 [[package]]
 name = "tower"
 version = "0.5.3"
@@ -9796,9 +10052,12 @@ checksum = "ebe5ef63511595f1344e2d5cfa636d973292adc0eec1f0ad45fae9f0851ab1d4"
 dependencies = [
 "futures-core",
 "futures-util",
+ "indexmap 2.14.0",
 "pin-project-lite",
+ "slab",
 "sync_wrapper",
 "tokio",
+ "tokio-util",
 "tower-layer",
 "tower-service",
 "tracing",
@@ -13,20 +13,20 @@ categories = ["database-implementations"]
 rust-version = "1.91.0"

 [workspace.dependencies]
-lance = { "version" = "=9.0.0-beta.10", default-features = false, "tag" = "v9.0.0-beta.10", "git" = "https://github.com/lance-format/lance.git" }
-lance-core = { "version" = "=9.0.0-beta.10", "tag" = "v9.0.0-beta.10", "git" = "https://github.com/lance-format/lance.git" }
-lance-datagen = { "version" = "=9.0.0-beta.10", "tag" = "v9.0.0-beta.10", "git" = "https://github.com/lance-format/lance.git" }
-lance-file = { "version" = "=9.0.0-beta.10", "tag" = "v9.0.0-beta.10", "git" = "https://github.com/lance-format/lance.git" }
-lance-io = { "version" = "=9.0.0-beta.10", default-features = false, "tag" = "v9.0.0-beta.10", "git" = "https://github.com/lance-format/lance.git" }
-lance-index = { "version" = "=9.0.0-beta.10", "tag" = "v9.0.0-beta.10", "git" = "https://github.com/lance-format/lance.git" }
-lance-linalg = { "version" = "=9.0.0-beta.10", "tag" = "v9.0.0-beta.10", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace = { "version" = "=9.0.0-beta.10", "tag" = "v9.0.0-beta.10", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace-impls = { "version" = "=9.0.0-beta.10", default-features = false, "tag" = "v9.0.0-beta.10", "git" = "https://github.com/lance-format/lance.git" }
-lance-table = { "version" = "=9.0.0-beta.10", "tag" = "v9.0.0-beta.10", "git" = "https://github.com/lance-format/lance.git" }
-lance-testing = { "version" = "=9.0.0-beta.10", "tag" = "v9.0.0-beta.10", "git" = "https://github.com/lance-format/lance.git" }
-lance-datafusion = { "version" = "=9.0.0-beta.10", "tag" = "v9.0.0-beta.10", "git" = "https://github.com/lance-format/lance.git" }
-lance-encoding = { "version" = "=9.0.0-beta.10", "tag" = "v9.0.0-beta.10", "git" = "https://github.com/lance-format/lance.git" }
-lance-arrow = { "version" = "=9.0.0-beta.10", "tag" = "v9.0.0-beta.10", "git" = "https://github.com/lance-format/lance.git" }
+lance = { "version" = "=9.0.0-beta.19", default-features = false, "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
+lance-core = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
+lance-datagen = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
+lance-file = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
+lance-io = { "version" = "=9.0.0-beta.19", default-features = false, "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
+lance-index = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
+lance-linalg = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace-impls = { "version" = "=9.0.0-beta.19", default-features = false, "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
+lance-table = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
+lance-testing = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
+lance-datafusion = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
+lance-encoding = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
+lance-arrow = { "version" = "=9.0.0-beta.19", "tag" = "v9.0.0-beta.19", "git" = "https://github.com/lance-format/lance.git" }
 ahash = "0.8"
 # Note that this one does not include pyarrow
 arrow = { version = "58.0.0", optional = false }
@@ -54,6 +54,8 @@ half = { "version" = "2.7.1", default-features = false, features = [
 ] }
 futures = "0"
 log = "0.4"
+metrics = "0.24"
+metrics-util = "0.19"
 moka = { version = "0.12", features = ["future"] }
 object_store = "0.13.2"
 pin-project = "1.0.7"
@@ -51,18 +51,6 @@ ignore = [
    # https://rustsec.org/advisories/RUSTSEC-2024-0436
    { id = "RUSTSEC-2024-0436", reason = "transitive via datafusion; awaiting ecosystem migration" },

-    # encoding: unmaintained. Reached through lindera-dictionary, which is
-    # required by the native Lindera tokenizer path. Lindera has not migrated
-    # off this crate yet.
-    # https://rustsec.org/advisories/RUSTSEC-2021-0153
-    { id = "RUSTSEC-2021-0153", reason = "transitive via lindera-dictionary for native Lindera tokenizer" },
-
-    # fast-float: unsound and unmaintained. Reached only through polars-arrow
-    # from the optional Polars integration; replacement requires a Polars
-    # dependency upgrade.
-    # https://rustsec.org/advisories/RUSTSEC-2024-0379
-    { id = "RUSTSEC-2024-0379", reason = "transitive via polars-arrow; waiting on Polars migration" },
-
    # tantivy: segfault on malformed input due to missing bounds check.
    # Pulled in via lance for full-text search. We only feed tantivy
    # documents we construct ourselves, not attacker-controlled bytes.
@@ -80,18 +68,6 @@ ignore = [
    # https://rustsec.org/advisories/RUSTSEC-2025-0119
    { id = "RUSTSEC-2025-0119", reason = "transitive via hf-hub/indicatif; cosmetic formatting crate" },

-    # bincode: unmaintained. Reached through lindera and lindera-dictionary,
-    # which are required by the native Lindera tokenizer path. Lindera has not
-    # migrated to another serialization format yet.
-    # https://rustsec.org/advisories/RUSTSEC-2025-0141
-    { id = "RUSTSEC-2025-0141", reason = "transitive via lindera/lindera-dictionary for native Lindera tokenizer" },
-
-    # lru: soundness issue in IterMut. Reached only through aws-sdk-s3 in
-    # LanceDB's dev-dependency graph; LanceDB does not use that iterator
-    # directly. Clearing this requires the AWS SDK chain to update lru.
-    # https://rustsec.org/advisories/RUSTSEC-2026-0002
-    { id = "RUSTSEC-2026-0002", reason = "transitive via aws-sdk-s3 dev-dependency; waiting on AWS SDK lru upgrade" },
-
    # rustls-webpki 0.101.7 (old major line): name-constraint checks for
    # URI / wildcard names. Pulled in only via the legacy rustls 0.21 chain
    # from aws-smithy-http-client. The 0.103 line we actively use is patched.
@@ -108,17 +84,23 @@ ignore = [
    # https://rustsec.org/advisories/RUSTSEC-2026-0104
    { id = "RUSTSEC-2026-0104", reason = "only affects rustls-webpki 0.101 from legacy aws-smithy/rustls 0.21 chain" },

-    # rand 0.8.5: soundness issue only when ThreadRng reseeds inside a custom
-    # logger. Reached through several transitive chains. LanceDB does not use
-    # rand from a custom logger; upgrade once all pinned chains accept 0.8.6+.
-    # https://rustsec.org/advisories/RUSTSEC-2026-0097
-    { id = "RUSTSEC-2026-0097", reason = "transitive rand 0.8.5; LanceDB does not call ThreadRng from custom logging" },
-
    # pyo3 advisories in the Python bindings; tracked pending a patched pyo3 release.
    # https://rustsec.org/advisories/RUSTSEC-2026-0176
    # https://rustsec.org/advisories/RUSTSEC-2026-0177
    { id = "RUSTSEC-2026-0176", reason = "pyo3 in Python bindings; awaiting patched pyo3 release" },
    { id = "RUSTSEC-2026-0177", reason = "pyo3 in Python bindings; awaiting patched pyo3 release" },
+
+    # quick-xml < 0.41.0: quadratic runtime on duplicate attribute names (DoS).
+    # quick-xml < 0.41.0: unbounded namespace-declaration allocation in NsReader (DoS).
+    # Pulled in transitively by inferno (dev-only flame-graph dep), lance-namespace-impls
+    # (git dep from lance), and opendal/reqsign (cloud storage XML parsing). The XML
+    # parsed by opendal/reqsign comes from trusted cloud-storage endpoints (S3, GCS,
+    # Azure), not attacker-controlled input. Clearing requires upstream crates to migrate
+    # to quick-xml >= 0.41.0.
+    # https://rustsec.org/advisories/RUSTSEC-2026-0194
+    # https://rustsec.org/advisories/RUSTSEC-2026-0195
+    { id = "RUSTSEC-2026-0194", reason = "transitive via inferno/lance/opendal; XML from trusted cloud endpoints, not attacker-controlled" },
+    { id = "RUSTSEC-2026-0195", reason = "transitive via inferno/lance/opendal; XML from trusted cloud endpoints, not attacker-controlled" },
 ]

 # ---------------------------------------------------------------------------
@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
 <dependency>
    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-core</artifactId>
-    <version>0.31.0-beta.5</version>
+    <version>0.32.0-beta.0</version>
 </dependency>
 ```

@@ -398,6 +398,26 @@ Drop an index from the table.

 ***

+### getLsmWriteSpec()
+
+```ts
+abstract getLsmWriteSpec(): Promise<undefined | LsmWriteSpec>
+```
+
+Read the [LsmWriteSpec](../interfaces/LsmWriteSpec.md) currently installed on this table.
+
+Resolves to `undefined` when the MemWAL LSM write path is not enabled (no
+spec has been set, or it was removed with [Table#unsetLsmWriteSpec](Table.md#unsetlsmwritespec)).
+The returned spec — including its `maintainedIndexes` and
+`writerConfigDefaults` — mirrors what was passed to
+[Table#setLsmWriteSpec](Table.md#setlsmwritespec).
+
+#### Returns
+
+`Promise`&lt;`undefined` \| [`LsmWriteSpec`](../interfaces/LsmWriteSpec.md)&gt;
+
+***
+
 ### indexStats()

 ```ts
@@ -0,0 +1,42 @@
+[**@lancedb/lancedb**](../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../globals.md) / instrumentLanceDbMetrics
+
+# Function: instrumentLanceDbMetrics()
+
+```ts
+function instrumentLanceDbMetrics(meterProvider?): boolean
+```
+
+Register LanceDB metrics as OpenTelemetry observable instruments.
+
+Installs a process-global metrics recorder and creates one observable
+instrument per LanceDB metric (currently object store request counts, bytes,
+latency, errors, and throttles) on the given (or global) `MeterProvider`. The
+configured `MetricReader` then collects them on its own schedule.
+
+Counters and gauges map directly to observable counters/gauges. Because
+OpenTelemetry has no asynchronous histogram instrument, each histogram is
+exported Prometheus-style as cumulative `le` bucket counts (`<name>_bucket`,
+with an `le` attribute) plus `<name>_count` and `<name>_sum`.
+
+Requires `@opentelemetry/api` (a dependency) and, to actually export, an
+OpenTelemetry SDK such as `@opentelemetry/sdk-metrics`.
+
+## Parameters
+
+* **meterProvider?**: `MeterProvider`
+    The provider to register instruments on. Defaults to the
+    global provider from `@opentelemetry/api`.
+
+## Returns
+
+`boolean`
+
+`true` if the recorder is installed and instruments are registered.
+  `false` if a different `metrics` recorder is already installed in this
+  process (only one global recorder is permitted), in which case a warning is
+  emitted and no instruments are created. Calling this more than once is safe;
+  instruments are created only on the first successful call.
@@ -131,6 +131,7 @@
 - [RecordBatchIterator](functions/RecordBatchIterator.md)
 - [connect](functions/connect.md)
 - [connectNamespace](functions/connectNamespace.md)
+- [instrumentLanceDbMetrics](functions/instrumentLanceDbMetrics.md)
 - [makeArrowTable](functions/makeArrowTable.md)
 - [packBits](functions/packBits.md)
 - [permutationBuilder](functions/permutationBuilder.md)
@@ -8,6 +8,14 @@

 ## Properties

+### clumpSize?
+
+```ts
+optional clumpSize: number;
+```
+
+***
+
 ### counts?

 ```ts
@@ -8,7 +8,7 @@
    <parent>
      <groupId>com.lancedb</groupId>
      <artifactId>lancedb-parent</artifactId>
-      <version>0.31.0-beta.5</version>
+      <version>0.32.0-beta.0</version>
      <relativePath>../pom.xml</relativePath>
    </parent>

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

    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-parent</artifactId>
-    <version>0.31.0-beta.5</version>
+    <version>0.32.0-beta.0</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>9.0.0-beta.10</lance-core.version>
+        <lance-core.version>9.0.0-beta.19</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 = "0.31.0-beta.5"
+version = "0.32.0-beta.0"
 publish = false
 license.workspace = true
 description.workspace = true
@@ -44,6 +44,6 @@ aws-lc-rs = "=1.16.3"
 napi-build = "2.3.1"

 [features]
-default = ["remote", "lancedb/aws", "lancedb/gcs", "lancedb/azure", "lancedb/dynamodb", "lancedb/oss", "lancedb/huggingface"]
+default = ["remote", "lancedb/aws", "lancedb/gcs", "lancedb/azure", "lancedb/dynamodb", "lancedb/oss", "lancedb/huggingface", "lancedb/goosefs", "lancedb/metrics-otel"]
 fp16kernels = ["lancedb/fp16kernels"]
 remote = ["lancedb/remote"]
@@ -0,0 +1,114 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+import {
+  MeterProvider,
+  type MetricData,
+  MetricReader,
+} from "@opentelemetry/sdk-metrics";
+import * as tmp from "tmp";
+import { connect, instrumentLanceDbMetrics } from "../lancedb";
+// snapshotLancedbMetrics is internal plumbing (not part of the public API), so
+// it is imported from the native module rather than the package entry point.
+import { snapshotLancedbMetrics } from "../lancedb/native";
+
+// The metrics recorder is process-global and installed once, so the whole
+// bridge is exercised in a single test to avoid cross-test global-state coupling.
+
+// A minimal pull-based reader whose `collect()` we drive directly, invoking the
+// observable-instrument callbacks. `@opentelemetry/sdk-metrics` ships no
+// in-memory reader, so we subclass the abstract base.
+class TestMetricReader extends MetricReader {
+  protected async onForceFlush(): Promise<void> {
+    // no-op: collection is driven directly via collect()
+  }
+  protected async onShutdown(): Promise<void> {
+    // no-op: nothing to release
+  }
+}
+
+async function metricsByName(
+  reader: TestMetricReader,
+): Promise<Map<string, MetricData>> {
+  const collected = await reader.collect();
+  const result = new Map<string, MetricData>();
+  for (const scope of collected.resourceMetrics.scopeMetrics) {
+    for (const metric of scope.metrics) {
+      result.set(metric.descriptor.name, metric);
+    }
+  }
+  return result;
+}
+
+describe("OpenTelemetry metrics bridge", () => {
+  let tmpDir: tmp.DirResult;
+  beforeEach(() => {
+    tmpDir = tmp.dirSync({ unsafeCleanup: true });
+  });
+  afterEach(() => tmpDir.removeCallback());
+
+  it("snapshot is safe to call regardless of install state", () => {
+    expect(Array.isArray(snapshotLancedbMetrics())).toBe(true);
+  });
+
+  it("exports object store metrics via observable instruments", async () => {
+    const reader = new TestMetricReader();
+    const provider = new MeterProvider({ readers: [reader] });
+    expect(instrumentLanceDbMetrics(provider)).toBe(true);
+
+    // Generate object store activity on the local filesystem (scheme "file").
+    const db = await connect(tmpDir.name);
+    const data = Array.from({ length: 256 }, (_, i) => ({ id: i }));
+    const table = await db.createTable("t", data);
+    expect(await table.countRows()).toBe(256);
+
+    const metrics = await metricsByName(reader);
+
+    const requests = metrics.get("lance_object_store_requests_total");
+    expect(requests).toBeDefined();
+    // biome-ignore lint/suspicious/noExplicitAny: SDK point shape
+    const requestPoints = (requests!.dataPoints as any[]) ?? [];
+    expect(requestPoints.length).toBeGreaterThan(0);
+    for (const p of requestPoints) {
+      // Labelled by `operation` and `base` (the store scheme by default).
+      expect(p.attributes).toHaveProperty("base");
+      expect(p.attributes).toHaveProperty("operation");
+    }
+    const totalRequests = requestPoints.reduce((acc, p) => acc + p.value, 0);
+    expect(totalRequests).toBeGreaterThan(0);
+
+    // Histograms are decomposed into bucket / count / sum observable counters.
+    const bucket = metrics.get(
+      "lance_object_store_request_duration_seconds_bucket",
+    );
+    expect(bucket).toBeDefined();
+    // biome-ignore lint/suspicious/noExplicitAny: SDK point shape
+    const bucketPoints = (bucket!.dataPoints as any[]) ?? [];
+    expect(bucketPoints.length).toBeGreaterThan(0);
+    expect(bucketPoints.every((p) => "le" in p.attributes)).toBe(true);
+    // The implicit +Inf bucket must be present.
+    expect(bucketPoints.some((p) => p.attributes.le === "+Inf")).toBe(true);
+
+    const count = metrics.get(
+      "lance_object_store_request_duration_seconds_count",
+    );
+    expect(count).toBeDefined();
+    // biome-ignore lint/suspicious/noExplicitAny: SDK point shape
+    const countPoints = (count!.dataPoints as any[]) ?? [];
+    expect(countPoints.reduce((acc, p) => acc + p.value, 0)).toBeGreaterThan(0);
+
+    const sum = metrics.get("lance_object_store_request_duration_seconds_sum");
+    expect(sum).toBeDefined();
+    // biome-ignore lint/suspicious/noExplicitAny: SDK point shape
+    const sumPoints = (sum!.dataPoints as any[]) ?? [];
+    expect(sumPoints.reduce((acc, p) => acc + p.value, 0)).toBeGreaterThan(0);
+
+    // Unit handling: only `_sum` keeps the histogram's unit (seconds); `_bucket`
+    // and `_count` observe cumulative counts and are unitless.
+    expect(sum!.descriptor.unit).toBe("s");
+    expect(bucket!.descriptor.unit).toBe("");
+    expect(count!.descriptor.unit).toBe("");
+
+    await provider.shutdown();
+  });
+});
@@ -2992,6 +2992,56 @@ describe("setLsmWriteSpec / unsetLsmWriteSpec", () => {
      }),
    ).rejects.toThrow();
  });
+
+  it("reads back the installed spec via getLsmWriteSpec", async () => {
+    const conn = await connect(tmpDir.name);
+    const table = await makeTable(conn);
+    await table.setUnenforcedPrimaryKey("id");
+
+    // Nothing installed yet.
+    expect(await table.getLsmWriteSpec()).toBeUndefined();
+
+    // A real scalar index is needed to name it as a maintained index.
+    await table.add([{ id: 1 }, { id: 2 }, { id: 3 }]);
+    await table.createIndex("id");
+    const indexName = (await table.listIndices())[0].name;
+
+    // Bucket spec round-trips, including maintained indexes and writer config
+    // defaults. Lance writer-config keys are canonically snake_case.
+    // biome-ignore lint/style/useNamingConvention: Lance writer-config keys are snake_case
+    const writerConfigDefaults = { durable_write: "false" };
+    await table.setLsmWriteSpec({
+      specType: "bucket",
+      column: "id",
+      numBuckets: 4,
+      maintainedIndexes: [indexName],
+      writerConfigDefaults,
+    });
+    const spec = await table.getLsmWriteSpec();
+    expect(spec).toBeDefined();
+    expect(spec?.specType).toBe("bucket");
+    expect(spec?.column).toBe("id");
+    expect(spec?.numBuckets).toBe(4);
+    expect(spec?.maintainedIndexes).toEqual([indexName]);
+    expect(spec?.writerConfigDefaults).toEqual(writerConfigDefaults);
+
+    // After unset, undefined again.
+    await table.unsetLsmWriteSpec();
+    expect(await table.getLsmWriteSpec()).toBeUndefined();
+
+    // Identity round-trips (column recovered from the schema).
+    await table.setLsmWriteSpec({ specType: "identity", column: "id" });
+    const identity = await table.getLsmWriteSpec();
+    expect(identity?.specType).toBe("identity");
+    expect(identity?.column).toBe("id");
+    await table.unsetLsmWriteSpec();
+
+    // Unsharded round-trips (no routing column).
+    await table.setLsmWriteSpec({ specType: "unsharded" });
+    const unsharded = await table.getLsmWriteSpec();
+    expect(unsharded?.specType).toBe("unsharded");
+    expect(unsharded?.column).toBeFalsy();
+  });
 });

 describe("LSM merge insert", () => {
@@ -20,6 +20,11 @@ import { HeaderProvider } from "./header";
 // Re-export native header provider for use with connectWithHeaderProvider
 export { JsHeaderProvider as NativeJsHeaderProvider } from "./native.js";

+// OpenTelemetry metrics bridge. Only the high-level entry point is public; the
+// underlying recorder/catalog/snapshot functions remain internal plumbing that
+// `otel.ts` consumes from the native module.
+export { instrumentLanceDbMetrics } from "./otel";
+
 export {
  AddColumnsSql,
  ConnectionOptions,
@@ -0,0 +1,137 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+import {
+  type Attributes,
+  type MeterProvider,
+  type ObservableResult,
+  metrics,
+} from "@opentelemetry/api";
+
+import {
+  lancedbMetricsCatalog,
+  registerLancedbMetricsRecorder,
+  snapshotLancedbMetrics,
+} from "./native";
+
+let instrumented = false;
+
+/**
+ * Register LanceDB metrics as OpenTelemetry observable instruments.
+ *
+ * Installs a process-global metrics recorder and creates one observable
+ * instrument per LanceDB metric (currently object store request counts, bytes,
+ * latency, errors, and throttles) on the given (or global) `MeterProvider`. The
+ * configured `MetricReader` then collects them on its own schedule.
+ *
+ * Counters and gauges map directly to observable counters/gauges. Because
+ * OpenTelemetry has no asynchronous histogram instrument, each histogram is
+ * exported Prometheus-style as cumulative `le` bucket counts (`<name>_bucket`,
+ * with an `le` attribute) plus `<name>_count` and `<name>_sum`.
+ *
+ * Requires `@opentelemetry/api` (a dependency) and, to actually export, an
+ * OpenTelemetry SDK such as `@opentelemetry/sdk-metrics`.
+ *
+ * @param meterProvider The provider to register instruments on. Defaults to the
+ *   global provider from `@opentelemetry/api`.
+ * @returns `true` if the recorder is installed and instruments are registered.
+ *   `false` if a different `metrics` recorder is already installed in this
+ *   process (only one global recorder is permitted), in which case a warning is
+ *   emitted and no instruments are created. Calling this more than once is safe;
+ *   instruments are created only on the first successful call.
+ */
+export function instrumentLanceDbMetrics(
+  meterProvider?: MeterProvider,
+): boolean {
+  if (!registerLancedbMetricsRecorder()) {
+    console.warn(
+      "Could not install the LanceDB metrics recorder: another `metrics` " +
+        "recorder is already installed in this process. LanceDB metrics will " +
+        "not be exported via OpenTelemetry.",
+    );
+    return false;
+  }
+
+  if (instrumented) {
+    return true;
+  }
+
+  const provider = meterProvider ?? metrics.getMeterProvider();
+  const meter = provider.getMeter("lancedb");
+
+  const scalarCallback = (metricName: string) => (result: ObservableResult) => {
+    for (const point of snapshotLancedbMetrics()) {
+      if (point.name === metricName && point.value != null) {
+        result.observe(point.value, point.attributes);
+      }
+    }
+  };
+
+  const bucketCallback = (metricName: string) => (result: ObservableResult) => {
+    for (const point of snapshotLancedbMetrics()) {
+      if (point.name !== metricName || point.buckets == null) {
+        continue;
+      }
+      for (const bucket of point.buckets) {
+        const attributes: Attributes = {
+          ...point.attributes,
+          le: bucket.le,
+        };
+        result.observe(bucket.cumulativeCount, attributes);
+      }
+    }
+  };
+
+  const fieldCallback =
+    (metricName: string, field: "count" | "sum") =>
+    (result: ObservableResult) => {
+      for (const point of snapshotLancedbMetrics()) {
+        if (point.name !== metricName) {
+          continue;
+        }
+        const value = point[field];
+        if (value != null) {
+          result.observe(value, point.attributes);
+        }
+      }
+    };
+
+  for (const desc of lancedbMetricsCatalog()) {
+    const unit = desc.unit ?? "";
+    if (desc.kind === "counter") {
+      const counter = meter.createObservableCounter(desc.name, {
+        unit,
+        description: desc.description,
+      });
+      counter.addCallback(scalarCallback(desc.name));
+    } else if (desc.kind === "gauge") {
+      const gauge = meter.createObservableGauge(desc.name, {
+        unit,
+        description: desc.description,
+      });
+      gauge.addCallback(scalarCallback(desc.name));
+    } else if (desc.kind === "histogram") {
+      // `_bucket` and `_count` observe cumulative sample counts, not the
+      // histogram's measured quantity, so they are unitless; only `_sum`
+      // carries the histogram's unit.
+      const bucket = meter.createObservableCounter(`${desc.name}_bucket`, {
+        description: `${desc.description} (cumulative buckets)`,
+      });
+      bucket.addCallback(bucketCallback(desc.name));
+
+      const count = meter.createObservableCounter(`${desc.name}_count`, {
+        description: `${desc.description} (count)`,
+      });
+      count.addCallback(fieldCallback(desc.name, "count"));
+
+      const sum = meter.createObservableCounter(`${desc.name}_sum`, {
+        unit,
+        description: `${desc.description} (sum)`,
+      });
+      sum.addCallback(fieldCallback(desc.name, "sum"));
+    }
+  }
+
+  instrumented = true;
+  return true;
+}
@@ -585,6 +585,17 @@ export abstract class Table {
   * @returns {Promise<void>}
   */
  abstract unsetLsmWriteSpec(): Promise<void>;
+  /**
+   * Read the {@link LsmWriteSpec} currently installed on this table.
+   *
+   * Resolves to `undefined` when the MemWAL LSM write path is not enabled (no
+   * spec has been set, or it was removed with {@link Table#unsetLsmWriteSpec}).
+   * The returned spec — including its `maintainedIndexes` and
+   * `writerConfigDefaults` — mirrors what was passed to
+   * {@link Table#setLsmWriteSpec}.
+   * @returns {Promise<LsmWriteSpec | undefined>}
+   */
+  abstract getLsmWriteSpec(): Promise<LsmWriteSpec | undefined>;
  /**
   * Drain and close any cached MemWAL shard writers held for this table.
   *
@@ -1091,6 +1102,15 @@ export class LocalTable extends Table {
    return await this.inner.unsetLsmWriteSpec();
  }

+  async getLsmWriteSpec(): Promise<LsmWriteSpec | undefined> {
+    // The native binding types `specType` as a plain `string`; narrow it back
+    // to the public union. The Rust `From` impl only ever emits one of the
+    // three valid values, so the cast is safe.
+    return ((await this.inner.getLsmWriteSpec()) ?? undefined) as
+      | LsmWriteSpec
+      | undefined;
+  }
+
  async closeLsmWriters(): Promise<void> {
    return await this.inner.closeLsmWriters();
  }
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.31.0-beta.5",
+	"version": "0.32.0-beta.0",
 	"os": ["darwin"],
 	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-	"version": "0.31.0-beta.5",
+	"version": "0.32.0-beta.0",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-gnu.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-musl",
-	"version": "0.31.0-beta.5",
+	"version": "0.32.0-beta.0",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-musl.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-gnu",
-	"version": "0.31.0-beta.5",
+	"version": "0.32.0-beta.0",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-gnu.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-musl",
-	"version": "0.31.0-beta.5",
+	"version": "0.32.0-beta.0",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-musl.node",
@@ -1,6 +1,6 @@
 {
  "name": "@lancedb/lancedb-win32-arm64-msvc",
-  "version": "0.31.0-beta.5",
+  "version": "0.32.0-beta.0",
  "os": [
    "win32"
  ],
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.31.0-beta.5",
+	"version": "0.32.0-beta.0",
 	"os": ["win32"],
 	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",
@@ -1,12 +1,12 @@
 {
  "name": "@lancedb/lancedb",
-  "version": "0.31.0-beta.5",
+  "version": "0.32.0-beta.0",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "@lancedb/lancedb",
-      "version": "0.31.0-beta.5",
+      "version": "0.32.0-beta.0",
      "cpu": [
        "x64",
        "arm64"
@@ -18,6 +18,7 @@
        "win32"
      ],
      "dependencies": {
+        "@opentelemetry/api": "^1.9.0",
        "reflect-metadata": "^0.2.2"
      },
      "devDependencies": {
@@ -27,6 +28,7 @@
        "@biomejs/biome": "^1.7.3",
        "@jest/globals": "^29.7.0",
        "@napi-rs/cli": "3.7.0",
+        "@opentelemetry/sdk-metrics": "^1.30.0",
        "@types/axios": "^0.14.0",
        "@types/jest": "^29.1.2",
        "@types/node": "22.7.4",
@@ -4148,6 +4150,75 @@
        "@octokit/openapi-types": "^27.0.0"
      }
    },
+    "node_modules/@opentelemetry/api": {
+      "version": "1.9.1",
+      "resolved": "https://registry.npmjs.org/@opentelemetry/api/-/api-1.9.1.tgz",
+      "integrity": "sha512-gLyJlPHPZYdAk1JENA9LeHejZe1Ti77/pTeFm/nMXmQH/HFZlcS/O2XJB+L8fkbrNSqhdtlvjBVjxwUYanNH5Q==",
+      "license": "Apache-2.0",
+      "engines": {
+        "node": ">=8.0.0"
+      }
+    },
+    "node_modules/@opentelemetry/core": {
+      "version": "1.30.1",
+      "resolved": "https://registry.npmjs.org/@opentelemetry/core/-/core-1.30.1.tgz",
+      "integrity": "sha512-OOCM2C/QIURhJMuKaekP3TRBxBKxG/TWWA0TL2J6nXUtDnuCtccy49LUJF8xPFXMX+0LMcxFpCo8M9cGY1W6rQ==",
+      "dev": true,
+      "license": "Apache-2.0",
+      "dependencies": {
+        "@opentelemetry/semantic-conventions": "1.28.0"
+      },
+      "engines": {
+        "node": ">=14"
+      },
+      "peerDependencies": {
+        "@opentelemetry/api": ">=1.0.0 <1.10.0"
+      }
+    },
+    "node_modules/@opentelemetry/resources": {
+      "version": "1.30.1",
+      "resolved": "https://registry.npmjs.org/@opentelemetry/resources/-/resources-1.30.1.tgz",
+      "integrity": "sha512-5UxZqiAgLYGFjS4s9qm5mBVo433u+dSPUFWVWXmLAD4wB65oMCoXaJP1KJa9DIYYMeHu3z4BZcStG3LC593cWA==",
+      "dev": true,
+      "license": "Apache-2.0",
+      "dependencies": {
+        "@opentelemetry/core": "1.30.1",
+        "@opentelemetry/semantic-conventions": "1.28.0"
+      },
+      "engines": {
+        "node": ">=14"
+      },
+      "peerDependencies": {
+        "@opentelemetry/api": ">=1.0.0 <1.10.0"
+      }
+    },
+    "node_modules/@opentelemetry/sdk-metrics": {
+      "version": "1.30.1",
+      "resolved": "https://registry.npmjs.org/@opentelemetry/sdk-metrics/-/sdk-metrics-1.30.1.tgz",
+      "integrity": "sha512-q9zcZ0Okl8jRgmy7eNW3Ku1XSgg3sDLa5evHZpCwjspw7E8Is4K/haRPDJrBcX3YSn/Y7gUvFnByNYEKQNbNog==",
+      "dev": true,
+      "license": "Apache-2.0",
+      "dependencies": {
+        "@opentelemetry/core": "1.30.1",
+        "@opentelemetry/resources": "1.30.1"
+      },
+      "engines": {
+        "node": ">=14"
+      },
+      "peerDependencies": {
+        "@opentelemetry/api": ">=1.3.0 <1.10.0"
+      }
+    },
+    "node_modules/@opentelemetry/semantic-conventions": {
+      "version": "1.28.0",
+      "resolved": "https://registry.npmjs.org/@opentelemetry/semantic-conventions/-/semantic-conventions-1.28.0.tgz",
+      "integrity": "sha512-lp4qAiMTD4sNWW4DbKLBkfiMZ4jbAboJIGOQr5DvciMRI494OapieI9qiODpOt0XBr1LjIDy1xAGAnVs5supTA==",
+      "dev": true,
+      "license": "Apache-2.0",
+      "engines": {
+        "node": ">=14"
+      }
+    },
    "node_modules/@protobufjs/aspromise": {
      "version": "1.1.2",
      "resolved": "https://registry.npmjs.org/@protobufjs/aspromise/-/aspromise-1.1.2.tgz",
@@ -11,7 +11,7 @@
    "ann"
  ],
  "private": false,
-  "version": "0.31.0-beta.5",
+  "version": "0.32.0-beta.0",
  "main": "dist/index.js",
  "exports": {
    ".": "./dist/index.js",
@@ -44,6 +44,7 @@
    "@biomejs/biome": "^1.7.3",
    "@jest/globals": "^29.7.0",
    "@napi-rs/cli": "3.7.0",
+    "@opentelemetry/sdk-metrics": "^1.30.0",
    "@types/axios": "^0.14.0",
    "@types/jest": "^29.1.2",
    "@types/node": "22.7.4",
@@ -92,6 +93,7 @@
    "version": "napi version"
  },
  "dependencies": {
+    "@opentelemetry/api": "^1.9.0",
    "reflect-metadata": "^0.2.2"
  },
  "optionalDependencies": {
@@ -8,6 +8,9 @@ importers:

  .:
    dependencies:
+      '@opentelemetry/api':
+        specifier: ^1.9.0
+        version: 1.9.1
      apache-arrow:
        specifier: '>=15.0.0 <=18.1.0'
        version: 18.1.0
@@ -33,6 +36,9 @@ importers:
      '@napi-rs/cli':
        specifier: 3.7.0
        version: 3.7.0(@emnapi/core@1.10.0)(@emnapi/runtime@1.10.0)(@types/node@22.7.4)
+      '@opentelemetry/sdk-metrics':
+        specifier: ^1.30.0
+        version: 1.30.1(@opentelemetry/api@1.9.1)
      '@types/axios':
        specifier: ^0.14.0
        version: 0.14.4
@@ -1307,6 +1313,32 @@ packages:
  '@octokit/types@16.0.0':
    resolution: {integrity: sha512-sKq+9r1Mm4efXW1FCk7hFSeJo4QKreL/tTbR0rz/qx/r1Oa2VV83LTA/H/MuCOX7uCIJmQVRKBcbmWoySjAnSg==}

+  '@opentelemetry/api@1.9.1':
+    resolution: {integrity: sha512-gLyJlPHPZYdAk1JENA9LeHejZe1Ti77/pTeFm/nMXmQH/HFZlcS/O2XJB+L8fkbrNSqhdtlvjBVjxwUYanNH5Q==}
+    engines: {node: '>=8.0.0'}
+
+  '@opentelemetry/core@1.30.1':
+    resolution: {integrity: sha512-OOCM2C/QIURhJMuKaekP3TRBxBKxG/TWWA0TL2J6nXUtDnuCtccy49LUJF8xPFXMX+0LMcxFpCo8M9cGY1W6rQ==}
+    engines: {node: '>=14'}
+    peerDependencies:
+      '@opentelemetry/api': '>=1.0.0 <1.10.0'
+
+  '@opentelemetry/resources@1.30.1':
+    resolution: {integrity: sha512-5UxZqiAgLYGFjS4s9qm5mBVo433u+dSPUFWVWXmLAD4wB65oMCoXaJP1KJa9DIYYMeHu3z4BZcStG3LC593cWA==}
+    engines: {node: '>=14'}
+    peerDependencies:
+      '@opentelemetry/api': '>=1.0.0 <1.10.0'
+
+  '@opentelemetry/sdk-metrics@1.30.1':
+    resolution: {integrity: sha512-q9zcZ0Okl8jRgmy7eNW3Ku1XSgg3sDLa5evHZpCwjspw7E8Is4K/haRPDJrBcX3YSn/Y7gUvFnByNYEKQNbNog==}
+    engines: {node: '>=14'}
+    peerDependencies:
+      '@opentelemetry/api': '>=1.3.0 <1.10.0'
+
+  '@opentelemetry/semantic-conventions@1.28.0':
+    resolution: {integrity: sha512-lp4qAiMTD4sNWW4DbKLBkfiMZ4jbAboJIGOQr5DvciMRI494OapieI9qiODpOt0XBr1LjIDy1xAGAnVs5supTA==}
+    engines: {node: '>=14'}
+
  '@protobufjs/aspromise@1.1.2':
    resolution: {integrity: sha512-j+gKExEuLmKwvz3OgROXtrJ2UG2x8Ch2YZUxahh+s1F2HZ+wAceUNLkvy6zKCPVRkU++ZWQrdxsUeQXmcg4uoQ==}

@@ -4925,6 +4957,27 @@ snapshots:
    dependencies:
      '@octokit/openapi-types': 27.0.0

+  '@opentelemetry/api@1.9.1': {}
+
+  '@opentelemetry/core@1.30.1(@opentelemetry/api@1.9.1)':
+    dependencies:
+      '@opentelemetry/api': 1.9.1
+      '@opentelemetry/semantic-conventions': 1.28.0
+
+  '@opentelemetry/resources@1.30.1(@opentelemetry/api@1.9.1)':
+    dependencies:
+      '@opentelemetry/api': 1.9.1
+      '@opentelemetry/core': 1.30.1(@opentelemetry/api@1.9.1)
+      '@opentelemetry/semantic-conventions': 1.28.0
+
+  '@opentelemetry/sdk-metrics@1.30.1(@opentelemetry/api@1.9.1)':
+    dependencies:
+      '@opentelemetry/api': 1.9.1
+      '@opentelemetry/core': 1.30.1(@opentelemetry/api@1.9.1)
+      '@opentelemetry/resources': 1.30.1(@opentelemetry/api@1.9.1)
+
+  '@opentelemetry/semantic-conventions@1.28.0': {}
+
  '@protobufjs/aspromise@1.1.2':
    optional: true

@@ -12,6 +12,7 @@ mod header;
 mod index;
 mod iterator;
 pub mod merge;
+pub mod otel;
 pub mod permutation;
 mod query;
 pub mod remote;
@@ -0,0 +1,119 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+//! Node.js bindings over [`lancedb::metrics_otel`].
+//!
+//! The aggregation, catalog, and histogram bucketing all live in the LanceDB
+//! core crate; this module only converts the core snapshot types into napi
+//! objects and exposes the three entry points to JavaScript, where
+//! `lancedb/otel.ts` bridges them into the user's OpenTelemetry `MeterProvider`.
+
+use std::collections::HashMap;
+
+use lancedb::metrics_otel::{MetricPoint as CoreMetricPoint, MetricValue};
+use napi_derive::napi;
+
+/// One cumulative histogram bucket: all samples with value `<= le`.
+#[napi(object)]
+pub struct MetricBucket {
+    /// The inclusive upper bound of the bucket, or `"+Inf"` for the final bucket.
+    pub le: String,
+    /// Cumulative number of samples less than or equal to `le`.
+    pub cumulative_count: f64,
+}
+
+/// One aggregated metric data point. For counters and gauges only `value` is
+/// set; for histograms `buckets` (cumulative `le` counts), `count`, and `sum`
+/// are set.
+#[napi(object)]
+pub struct MetricPoint {
+    pub name: String,
+    pub kind: String,
+    pub attributes: HashMap<String, String>,
+    pub value: Option<f64>,
+    pub buckets: Option<Vec<MetricBucket>>,
+    pub count: Option<f64>,
+    pub sum: Option<f64>,
+}
+
+impl From<CoreMetricPoint> for MetricPoint {
+    fn from(point: CoreMetricPoint) -> Self {
+        let kind = point.kind.as_str().to_string();
+        let (value, buckets, count, sum) = match point.value {
+            MetricValue::Scalar(v) => (Some(v), None, None, None),
+            MetricValue::Histogram {
+                buckets,
+                count,
+                sum,
+            } => (
+                None,
+                Some(
+                    buckets
+                        .into_iter()
+                        // Counts stay well within the f64-exact integer range
+                        // (2^53), so this cast is lossless in practice and keeps
+                        // the values plain JS numbers for OpenTelemetry.
+                        .map(|(le, cumulative_count)| MetricBucket {
+                            le,
+                            cumulative_count: cumulative_count as f64,
+                        })
+                        .collect(),
+                ),
+                Some(count as f64),
+                Some(sum),
+            ),
+        };
+        Self {
+            name: point.name,
+            kind,
+            attributes: point.attributes,
+            value,
+            buckets,
+            count,
+            sum,
+        }
+    }
+}
+
+/// A described metric, used by the JavaScript layer to create instruments up front.
+#[napi(object)]
+pub struct MetricDescription {
+    pub name: String,
+    pub kind: String,
+    pub unit: Option<String>,
+    pub description: String,
+}
+
+/// Install the LanceDB metrics recorder as the process-global `metrics` recorder.
+///
+/// Returns `true` if the recorder is installed (now or previously). Returns
+/// `false` if a *different* recorder is already installed — `metrics` allows
+/// only one global recorder per process, so LanceDB cannot coexist with another.
+#[napi]
+pub fn register_lancedb_metrics_recorder() -> bool {
+    lancedb::metrics_otel::register_metrics_recorder()
+}
+
+/// The catalog of described LanceDB metrics. Empty until the recorder is installed.
+#[napi]
+pub fn lancedb_metrics_catalog() -> Vec<MetricDescription> {
+    lancedb::metrics_otel::metrics_catalog()
+        .into_iter()
+        .map(|desc| MetricDescription {
+            name: desc.name,
+            kind: desc.kind.as_str().to_string(),
+            unit: desc.unit,
+            description: desc.description,
+        })
+        .collect()
+}
+
+/// A point-in-time snapshot of every recorded metric. Empty until the recorder
+/// is installed.
+#[napi]
+pub fn snapshot_lancedb_metrics() -> Vec<MetricPoint> {
+    lancedb::metrics_otel::snapshot_metrics()
+        .into_iter()
+        .map(MetricPoint::from)
+        .collect()
+}
@@ -16,6 +16,7 @@ pub struct SplitRandomOptions {
    pub counts: Option<Vec<i64>>,
    pub fixed: Option<i64>,
    pub seed: Option<i64>,
+    pub clump_size: Option<i64>,
    pub split_names: Option<Vec<String>>,
 }

@@ -125,10 +126,15 @@ impl PermutationBuilder {
        };

        let seed = options.seed.map(|s| s as u64);
+        let clump_size = options.clump_size.map(|c| c as u64);

        self.modify(|builder| {
            builder.with_split_strategy(
-                SplitStrategy::Random { seed, sizes },
+                SplitStrategy::Random {
+                    seed,
+                    sizes,
+                    clump_size,
+                },
                options.split_names.clone(),
            )
        })
@@ -411,6 +411,16 @@ impl Table {
            .default_error()
    }

+    #[napi(catch_unwind)]
+    pub async fn get_lsm_write_spec(&self) -> napi::Result<Option<LsmWriteSpec>> {
+        let spec = self
+            .inner_ref()?
+            .get_lsm_write_spec()
+            .await
+            .default_error()?;
+        Ok(spec.map(LsmWriteSpec::from))
+    }
+
    #[napi(catch_unwind)]
    pub async fn close_lsm_writers(&self) -> napi::Result<()> {
        self.inner_ref()?.close_lsm_writers().await.default_error()
@@ -728,6 +738,47 @@ impl TryFrom<LsmWriteSpec> for lancedb::table::LsmWriteSpec {
    }
 }

+impl From<lancedb::table::LsmWriteSpec> for LsmWriteSpec {
+    fn from(spec: lancedb::table::LsmWriteSpec) -> Self {
+        use lancedb::table::LsmWriteSpec as Native;
+        match spec {
+            Native::Bucket {
+                column,
+                num_buckets,
+                maintained_indexes,
+                writer_config_defaults,
+            } => Self {
+                spec_type: "bucket".to_string(),
+                column: Some(column),
+                num_buckets: Some(num_buckets),
+                maintained_indexes: Some(maintained_indexes),
+                writer_config_defaults: Some(writer_config_defaults),
+            },
+            Native::Identity {
+                column,
+                maintained_indexes,
+                writer_config_defaults,
+            } => Self {
+                spec_type: "identity".to_string(),
+                column: Some(column),
+                num_buckets: None,
+                maintained_indexes: Some(maintained_indexes),
+                writer_config_defaults: Some(writer_config_defaults),
+            },
+            Native::Unsharded {
+                maintained_indexes,
+                writer_config_defaults,
+            } => Self {
+                spec_type: "unsharded".to_string(),
+                column: None,
+                num_buckets: None,
+                maintained_indexes: Some(maintained_indexes),
+                writer_config_defaults: Some(writer_config_defaults),
+            },
+        }
+    }
+}
+
 /// Statistics about a compaction operation.
 #[napi(object)]
 #[derive(Clone, Debug)]
@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.34.0-beta.6"
+current_version = "0.35.0-beta.1"
 parse = """(?x)
    (?P<major>0|[1-9]\\d*)\\.
    (?P<minor>0|[1-9]\\d*)\\.
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-python"
-version = "0.34.0-beta.6"
+version = "0.35.0-beta.1"
 publish = false
 edition.workspace = true
 description = "Python bindings for LanceDB"
@@ -47,6 +47,6 @@ pyo3-build-config = { version = "0.28", features = [
 ] }

 [features]
-default = ["remote",  "lancedb/aws", "lancedb/gcs", "lancedb/azure", "lancedb/dynamodb", "lancedb/oss", "lancedb/huggingface"]
+default = ["remote", "lancedb/aws", "lancedb/gcs", "lancedb/azure", "lancedb/dynamodb", "lancedb/oss", "lancedb/huggingface", "lancedb/cos", "lancedb/goosefs", "lancedb/metrics-otel"]
 fp16kernels = ["lancedb/fp16kernels"]
 remote = ["lancedb/remote"]
@@ -0,0 +1,135 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+"""Benchmark for StreamingDataset throughput.
+
+Sweeps read_batch_size from 1 to 16384 to show how amortising the per-request
+overhead scales.  Each row at each chunk size is timed via the real
+StreamingDataset so the numbers reflect production code.
+
+Run with:
+    cd python
+    uv run --extra tests benchmarks/bench_streaming_dataloader.py
+
+Optional env vars:
+    BENCH_NUM_ROWS   — total rows in the table (default 49152 = 24 × 2048)
+    BENCH_NUM_SPLITS — number of splits (default 24)
+    BENCH_STEPS      — round-robin cycles to time per chunk size (default 100)
+    BENCH_ROW_BYTES  — approximate bytes per row padded with a binary column
+                       (default 4096, mimics a small embedding/image patch)
+"""
+
+import os
+import time
+import tempfile
+
+import pyarrow as pa
+import lancedb
+
+from lancedb.streaming import StreamingDataset
+
+# ---------------------------------------------------------------------------
+# Configuration
+# ---------------------------------------------------------------------------
+
+NUM_SPLITS = int(os.environ.get("BENCH_NUM_SPLITS", 24))
+# Default: 2048 rows per split so every chunk size up to 16Ki has ≥1 full
+# chunk (except 16Ki itself which gets a single full-split fetch — still valid).
+NUM_ROWS = int(os.environ.get("BENCH_NUM_ROWS", NUM_SPLITS * 2048))
+STEPS = int(os.environ.get("BENCH_STEPS", 100))
+ROW_BYTES = int(os.environ.get("BENCH_ROW_BYTES", 4096))
+
+assert NUM_ROWS % NUM_SPLITS == 0, "NUM_ROWS must be divisible by NUM_SPLITS"
+
+CHUNK_SIZES = [1, 4, 16, 64, 256, 1024, 4096, 16384]
+
+
+# ---------------------------------------------------------------------------
+# Table helpers
+# ---------------------------------------------------------------------------
+
+
+def make_table(db_path: str) -> lancedb.table.Table:
+    db = lancedb.connect(db_path)
+    payload = b"x" * ROW_BYTES
+    data = pa.table(
+        {
+            "id": pa.array(range(NUM_ROWS), type=pa.int32()),
+            "payload": pa.array([payload] * NUM_ROWS, type=pa.large_binary()),
+        }
+    )
+    return db.create_table("bench", data, mode="overwrite")
+
+
+# ---------------------------------------------------------------------------
+# Timing
+# ---------------------------------------------------------------------------
+
+
+def bench_chunk(table, chunk_size: int, steps: int) -> tuple[int, float]:
+    """Return (rows_drained, elapsed_seconds) for one timed run."""
+    total_rows = steps * NUM_SPLITS
+    ds = StreamingDataset(
+        table, num_splits=NUM_SPLITS, shuffle_seed=42, read_batch_size=chunk_size
+    )
+    count = 0
+    t0 = time.perf_counter()
+    for _ in ds:
+        count += 1
+        if count >= total_rows:
+            break
+    return count, time.perf_counter() - t0
+
+
+# ---------------------------------------------------------------------------
+# Main
+# ---------------------------------------------------------------------------
+
+
+def main() -> None:
+    rows_per_split = NUM_ROWS // NUM_SPLITS
+    print("Benchmark config:")
+    print(
+        f"  NUM_ROWS={NUM_ROWS}  NUM_SPLITS={NUM_SPLITS}  "
+        f"rows/split={rows_per_split}  STEPS={STEPS}  ROW_BYTES={ROW_BYTES}"
+    )
+    print(f"  ~{NUM_ROWS * ROW_BYTES / 1024 / 1024:.1f} MB total table size")
+    print()
+
+    with tempfile.TemporaryDirectory() as tmp:
+        print("Creating table...", flush=True)
+        table = make_table(tmp)
+
+        cols = (
+            f"{'chunk':>6}  {'rows':>6}  {'elapsed':>8}  {'rows/s':>10}  {'ms/step':>9}"
+        )
+        print(f"\n{cols}")
+        print("-" * 52)
+
+        for chunk in CHUNK_SIZES:
+            # Warm-up pass (one step's worth of rows)
+            warmup_ds = StreamingDataset(
+                table, num_splits=NUM_SPLITS, shuffle_seed=42, read_batch_size=chunk
+            )
+            warmup_count = 0
+            for _ in warmup_ds:
+                warmup_count += 1
+                if warmup_count >= NUM_SPLITS:
+                    break
+
+            drained, elapsed = bench_chunk(table, chunk, STEPS)
+            rows_per_sec = drained / elapsed if elapsed > 0 else float("inf")
+            ms_per_step = elapsed / STEPS * 1000
+
+            print(
+                f"{chunk:>6}  {drained:>6}  {elapsed:>7.3f}s  "
+                f"{rows_per_sec:>10.0f}  {ms_per_step:>8.1f}ms"
+            )
+
+    print()
+    print("Done.")
+
+
+if __name__ == "__main__":
+    main()
@@ -47,6 +47,10 @@ repository = "https://github.com/lancedb/lancedb"
 pylance = [
    "pylance>=5.0.0b5",
 ]
+# A library only needs the OpenTelemetry API; the application supplies and
+# configures the SDK (the actual exporter/reader). See
+# https://opentelemetry.io/docs/languages/python/instrumentation/
+otel = ["opentelemetry-api"]
 tests = [
    "aiohttp>=3.9.0",
    "boto3>=1.28.57",
@@ -61,6 +65,7 @@ tests = [
    "pylance>=5.0.0b5",
    "requests>=2.31.0",
    "datafusion>=52,<53",
+    "opentelemetry-sdk>=1.30.0",
 ]
 dev = [
    "ruff>=0.3.0",
@@ -149,8 +149,14 @@ def connect(

    For object storage, use a URI prefix:

-    >>> db = lancedb.connect("s3://my-bucket/lancedb",
-    ...                      storage_options={"aws_access_key_id": "***"})
+    >>> db = lancedb.connect(  # doctest: +SKIP
+    ...     "s3://my-bucket/lancedb",
+    ...     storage_options={
+    ...         "aws_access_key_id": "***",
+    ...         "aws_secret_access_key": "***",
+    ...         "aws_region": "us-east-1",
+    ...     },
+    ... )

    For tests and temporary data, use an in-memory database:

@@ -1,4 +1,5 @@
-from datetime import datetime, timedelta
+from datetime import date, datetime, timedelta
+from decimal import Decimal
 from typing import Dict, List, Optional, Tuple, Any, TypedDict, Union, Literal

 import pyarrow as pa
@@ -29,6 +30,25 @@ IvfHnswPq: type[HnswPq] = HnswPq
 IvfHnswSq: type[HnswSq] = HnswSq
 IvfHnswFlat: type[HnswFlat] = HnswFlat

+class MetricPoint:
+    name: str
+    kind: str
+    attributes: Dict[str, str]
+    value: Optional[float]
+    buckets: Optional[List[Tuple[str, int]]]
+    count: Optional[int]
+    sum: Optional[float]
+
+class MetricDescription:
+    name: str
+    kind: str
+    unit: Optional[str]
+    description: str
+
+def register_lancedb_metrics_recorder() -> bool: ...
+def lancedb_metrics_catalog() -> List[MetricDescription]: ...
+def snapshot_lancedb_metrics() -> List[MetricPoint]: ...
+
 class PyExpr:
    """A type-safe DataFusion expression node (Rust-side handle)."""

@@ -53,7 +73,9 @@ class PyExpr:
    def to_sql(self) -> str: ...

 def expr_col(name: str) -> PyExpr: ...
-def expr_lit(value: Union[bool, int, float, str, bytes]) -> PyExpr: ...
+def expr_lit(
+    value: Union[bool, int, float, str, bytes, date, datetime, Decimal],
+) -> PyExpr: ...
 def expr_func(name: str, args: List[PyExpr]) -> PyExpr: ...

 class Session:
@@ -226,6 +248,7 @@ class Table:
    async def set_unenforced_primary_key(self, columns: List[str]) -> None: ...
    async def set_lsm_write_spec(self, spec: LsmWriteSpec) -> None: ...
    async def unset_lsm_write_spec(self) -> None: ...
+    async def get_lsm_write_spec(self) -> Optional[LsmWriteSpec]: ...
    async def close_lsm_writers(self) -> None: ...
    @property
    def tags(self) -> Tags: ...
@@ -2,7 +2,7 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors

 from functools import cached_property
-from typing import TYPE_CHECKING, List, Optional, Sequence, Union
+from typing import TYPE_CHECKING, Any, List, Optional, Sequence, Union

 import numpy as np

@@ -56,6 +56,16 @@ class OllamaEmbeddings(TextEmbeddingFunction):
        embeddings = self._compute_embedding(texts)
        return list(embeddings)

+    def __getstate__(self) -> dict[str, Any]:
+        state = super().__getstate__()
+        state["__dict__"] = {
+            k: v for k, v in state["__dict__"].items() if k != "_ollama_client"
+        }
+        return state
+
+    def __setstate__(self, state: dict[str, Any]) -> None:
+        super().__setstate__(state)
+
    @cached_property
    def _ollama_client(self) -> "ollama.Client":
        ollama = attempt_import_or_raise("ollama")
@@ -19,6 +19,8 @@ operators::

 from __future__ import annotations

+from datetime import date, datetime
+from decimal import Decimal
 from typing import Iterable, Union

 import pyarrow as pa
@@ -63,7 +65,7 @@ def _coerce(value: "ExprLike") -> "Expr":


 # Type alias used in annotations.
-ExprLike = Union["Expr", bool, int, float, str, bytes]
+ExprLike = Union["Expr", bool, int, float, str, bytes, date, datetime, Decimal]


 class Expr:
@@ -118,10 +120,18 @@ class Expr:
        """Logical AND (``expr_a & expr_b``)."""
        return Expr(self._inner.and_(_coerce(other)._inner))

+    def __rand__(self, other: ExprLike) -> "Expr":
+        """Right-hand logical AND (``True & expr``)."""
+        return Expr(_coerce(other)._inner.and_(self._inner))
+
    def __or__(self, other: "Expr") -> "Expr":
        """Logical OR (``expr_a | expr_b``)."""
        return Expr(self._inner.or_(_coerce(other)._inner))

+    def __ror__(self, other: ExprLike) -> "Expr":
+        """Right-hand logical OR (``False | expr``)."""
+        return Expr(_coerce(other)._inner.or_(self._inner))
+
    def __invert__(self) -> "Expr":
        """Logical NOT (``~expr``)."""
        return Expr(self._inner.not_())
@@ -266,13 +276,14 @@ def col(name: str) -> Expr:
    return Expr(expr_col(name))


-def lit(value: Union[bool, int, float, str, bytes]) -> Expr:
+def lit(value: Union[bool, int, float, str, bytes, date, datetime, Decimal]) -> Expr:
    """Create a literal (constant) value expression.

    Parameters
    ----------
    value:
-        A Python ``bool``, ``int``, ``float``, ``str``, or ``bytes``.
+        A Python ``bool``, ``int``, ``float``, ``str``, ``bytes``, ``date``,
+        ``datetime``, or ``Decimal``.

    Examples
    --------
@@ -280,6 +291,9 @@ def lit(value: Union[bool, int, float, str, bytes]) -> Expr:
    >>> col("price") * lit(1.1)
    Expr((price * 1.1))
    """
+    if not isinstance(value, (bool, int, float, str, bytes, date, datetime, Decimal)):
+        raise TypeError(f"Unsupported literal type: {type(value).__name__}")
+
    return Expr(expr_lit(value))


@@ -0,0 +1,170 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+"""Bridge LanceDB's internal metrics into OpenTelemetry.
+
+LanceDB (through Lance core) publishes metrics (currently object store request
+counts, bytes, latency, errors, and throttles) through the Rust ``metrics``
+facade. This module installs a process-global recorder that aggregates them and
+registers OpenTelemetry observable instruments that report the aggregated values
+into the user's ``MeterProvider``.
+
+The bridge is generic: every metric LanceDB describes is surfaced automatically,
+with no per-metric Python code. Histograms have no asynchronous OpenTelemetry
+instrument, so each is exported Prometheus-style as cumulative ``le`` buckets
+plus ``_count`` and ``_sum`` observable counters.
+"""
+
+from __future__ import annotations
+
+import warnings
+from typing import TYPE_CHECKING, Optional
+
+from ._lancedb import (
+    lancedb_metrics_catalog,
+    register_lancedb_metrics_recorder,
+    snapshot_lancedb_metrics,
+)
+
+if TYPE_CHECKING:
+    from opentelemetry.metrics import MeterProvider
+
+_INSTRUMENTED = False
+
+
+def instrument_lancedb_metrics(
+    meter_provider: Optional["MeterProvider"] = None,
+) -> bool:
+    """Register LanceDB metrics as OpenTelemetry observable instruments.
+
+    Installs a process-global metrics recorder and creates one observable
+    instrument per LanceDB metric on the given (or global) ``MeterProvider``. The
+    user's configured ``MetricReader`` then collects them on its own schedule.
+
+    Counters and gauges map directly to observable counters/gauges. Each
+    histogram is exported as cumulative ``le`` bucket counts (``<name>_bucket``,
+    with an ``le`` attribute) plus ``<name>_count`` and ``<name>_sum``.
+
+    Parameters
+    ----------
+    meter_provider : opentelemetry.metrics.MeterProvider, optional
+        The provider to register instruments on. Defaults to the global provider
+        from ``opentelemetry.metrics.get_meter_provider()``.
+
+    Returns
+    -------
+    bool
+        ``True`` if the recorder is installed and instruments are registered.
+        ``False`` if a different ``metrics`` recorder is already installed in
+        this process (``metrics`` permits only one global recorder), in which
+        case a warning is emitted and no instruments are created.
+
+    Notes
+    -----
+    Requires the OpenTelemetry API (``pip install lancedb[otel]``) and, to
+    actually export, an OpenTelemetry SDK (``pip install opentelemetry-sdk``)
+    configured by the application. Calling this more than once is safe;
+    instruments are created only on the first successful call.
+    """
+    global _INSTRUMENTED
+
+    try:
+        from opentelemetry.metrics import Observation, get_meter_provider
+    except ImportError as exc:
+        raise ImportError(
+            "instrument_lancedb_metrics requires the OpenTelemetry API/SDK. "
+            "Install it with `pip install lancedb[otel]` or "
+            "`pip install opentelemetry-sdk`."
+        ) from exc
+
+    if not register_lancedb_metrics_recorder():
+        warnings.warn(
+            "Could not install the LanceDB metrics recorder: another `metrics` "
+            "recorder is already installed in this process. LanceDB metrics will "
+            "not be exported via OpenTelemetry.",
+            stacklevel=2,
+        )
+        return False
+
+    if _INSTRUMENTED:
+        return True
+
+    provider = meter_provider or get_meter_provider()
+    meter = provider.get_meter("lancedb")
+
+    def scalar_callback(metric_name: str):
+        def callback(_options):
+            return [
+                Observation(point.value, point.attributes)
+                for point in snapshot_lancedb_metrics()
+                if point.name == metric_name and point.value is not None
+            ]
+
+        return callback
+
+    def bucket_callback(metric_name: str):
+        def callback(_options):
+            observations = []
+            for point in snapshot_lancedb_metrics():
+                if point.name != metric_name or point.buckets is None:
+                    continue
+                for le, cumulative in point.buckets:
+                    attributes = dict(point.attributes)
+                    attributes["le"] = le
+                    observations.append(Observation(cumulative, attributes))
+            return observations
+
+        return callback
+
+    def field_callback(metric_name: str, field: str):
+        def callback(_options):
+            observations = []
+            for point in snapshot_lancedb_metrics():
+                if point.name != metric_name:
+                    continue
+                value = getattr(point, field)
+                if value is not None:
+                    observations.append(Observation(value, point.attributes))
+            return observations
+
+        return callback
+
+    for desc in lancedb_metrics_catalog():
+        unit = desc.unit or ""
+        if desc.kind == "counter":
+            meter.create_observable_counter(
+                desc.name,
+                callbacks=[scalar_callback(desc.name)],
+                unit=unit,
+                description=desc.description,
+            )
+        elif desc.kind == "gauge":
+            meter.create_observable_gauge(
+                desc.name,
+                callbacks=[scalar_callback(desc.name)],
+                unit=unit,
+                description=desc.description,
+            )
+        elif desc.kind == "histogram":
+            # `_bucket` and `_count` observe cumulative sample counts, not the
+            # histogram's measured quantity, so they are unitless; only `_sum`
+            # carries the histogram's unit.
+            meter.create_observable_counter(
+                f"{desc.name}_bucket",
+                callbacks=[bucket_callback(desc.name)],
+                description=f"{desc.description} (cumulative buckets)",
+            )
+            meter.create_observable_counter(
+                f"{desc.name}_count",
+                callbacks=[field_callback(desc.name, "count")],
+                description=f"{desc.description} (count)",
+            )
+            meter.create_observable_counter(
+                f"{desc.name}_sum",
+                callbacks=[field_callback(desc.name, "sum")],
+                unit=unit,
+                description=f"{desc.description} (sum)",
+            )
+
+    _INSTRUMENTED = True
+    return True
@@ -11,7 +11,7 @@ import pyarrow as pa
 from ._lancedb import async_permutation_builder, PermutationReader
 from .table import LanceTable, Table
 from .background_loop import LOOP
-from .util import batch_to_tensor, batch_to_tensor_rows
+from .util import batch_to_tensor, batch_to_tensor_dict, batch_to_tensor_rows
 from typing import Any, Callable, Iterator, Literal, Optional, TYPE_CHECKING, Union

 if TYPE_CHECKING:
@@ -65,6 +65,7 @@ class PermutationBuilder:
        counts: Optional[list[int]] = None,
        fixed: Optional[int] = None,
        seed: Optional[int] = None,
+        clump_size: Optional[int] = None,
        split_names: Optional[list[str]] = None,
    ) -> "PermutationBuilder":
        """
@@ -87,6 +88,9 @@ class PermutationBuilder:
        Rows will be randomly assigned to splits.  The optional seed can be provided to
        make the assignment deterministic.

+        If clump_size is provided, rows are shuffled as contiguous groups of that size,
+        preserving I/O locality while still randomising the split assignment.
+
        The optional split_names can be provided to name the splits.  If not provided,
        the splits can only be referenced by their index.
        """
@@ -95,6 +99,7 @@ class PermutationBuilder:
            counts=counts,
            fixed=fixed,
            seed=seed,
+            clump_size=clump_size,
            split_names=split_names,
        )
        return self
@@ -941,6 +946,7 @@ class Permutation:
            "pandas",
            "arrow",
            "torch",
+            "torch_row",
            "torch_col",
            "polars",
        ],
@@ -956,15 +962,19 @@ class Permutation:
        - "python_col" - the batch will be a dict of lists (one entry per column)
        - "pandas" - the batch will be a pandas DataFrame
        - "arrow" - the batch will be a pyarrow RecordBatch
-        - "torch" - the batch will be a list of tensors, one per row
+        - "torch" - the batch will be a list of per-row dicts mapping column
+          name to a 0-D torch tensor. Works with the default
+          ``torch.utils.data.DataLoader`` collate, which stacks the per-row
+          dicts back into a dict of batched tensors.
+        - "torch_row" - the batch will be a list of tensors, one per row
        - "torch_col" - the batch will be a 2D torch tensor (first dim indexes columns)
        - "polars" - the batch will be a polars DataFrame

        Conversion may or may not involve a data copy.  Lance uses Arrow internally
        and so it is able to zero-copy to the arrow and polars formats.

-        Conversion to torch_col will be zero-copy but will only support a subset of data
-        types (numeric types).
+        Conversion to torch and torch_col will be zero-copy but will only support a
+        subset of data types (numeric types).

        Conversion to numpy and/or pandas will typically be zero-copy for numeric
        types.  Conversion of strings, lists, and structs will require creating python
@@ -985,6 +995,8 @@ class Permutation:
        elif format == "arrow":
            return self.with_transform(Transforms.arrow2arrow)
        elif format == "torch":
+            return self.with_transform(batch_to_tensor_dict)
+        elif format == "torch_row":
            return self.with_transform(batch_to_tensor_rows)
        elif format == "torch_col":
            return self.with_transform(batch_to_tensor)
@@ -912,6 +912,10 @@ class RemoteTable(Table):
        """Not supported on LanceDB Cloud."""
        return LOOP.run(self._table.unset_lsm_write_spec())

+    def get_lsm_write_spec(self) -> Optional["LsmWriteSpec"]:
+        """Read the installed LsmWriteSpec, or ``None``."""
+        return LOOP.run(self._table.get_lsm_write_spec())
+
    def close_lsm_writers(self) -> None:
        """No-op on LanceDB Cloud (no local shard writers)."""
        return LOOP.run(self._table.close_lsm_writers())
@@ -0,0 +1,607 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+"""Elastic streaming dataloader for PyTorch.
+
+Provides StreamingDataset, a PyTorch IterableDataset that guarantees:
+
+- **Elastic determinism**: for a fixed (num_splits, shuffle_seed, epoch) the set
+  of samples that forms each global training step is identical regardless of
+  world_size or num_workers.
+- **Resumability**: state_dict / load_state_dict capture per-split consumption
+  counts so training can resume from an exact mid-epoch position even when the
+  distributed topology changes between runs.
+"""
+
+import ctypes
+import logging
+import os
+import random
+import threading
+import time
+from collections import deque
+from concurrent.futures import ThreadPoolExecutor
+from multiprocessing import RawArray
+from typing import Any, Callable, Iterator, Optional
+
+from torch.utils.data import IterableDataset, get_worker_info
+
+from .permutation import (
+    Permutation,
+    Transforms,
+    permutation_builder,
+    _table_from_pickle_state,
+    _table_to_pickle_state,
+)
+
+logger = logging.getLogger(__name__)
+
+# Multiplier used to combine shuffle_seed and epoch into a single permutation
+# seed.  Chosen to be a large prime so different (seed, epoch) pairs produce
+# distinct seeds for any practically encountered epoch count.
+_EPOCH_PRIME = 100003
+
+DEFAULT_READ_BATCH_SIZE = 64
+DEFAULT_PREFETCH_BATCHES = 4
+
+
+class StreamingDataset(IterableDataset):
+    """An elastic, resumable PyTorch IterableDataset backed by a LanceDB table.
+
+    The table is partitioned into ``num_splits`` fixed splits using a
+    deterministic random shuffle controlled by ``shuffle_seed`` and ``epoch``.
+    Each rank is assigned a contiguous block of splits, and within a rank each
+    DataLoader worker is assigned a contiguous sub-block.  Samples are yielded
+    by round-robining over the assigned splits, one sample per split per cycle.
+
+    Internally ``__iter__`` runs a two-stage pipeline:
+
+    - **Stage 1 (I/O)**: one thread pool with ``num_splits * prefetch_batches``
+      workers fetches raw ``RecordBatch`` objects from LanceDB in parallel
+      across all splits and places them in a per-split raw-batch queue.
+    - **Stage 2 (transform)**: a second thread pool with ``os.cpu_count()``
+      workers picks up raw batches, applies the transform, and places the
+      results in a per-split cooked-row queue.
+
+    The main thread round-robins over the cooked queues, yielding one row per
+    split per cycle.
+
+    Parameters
+    ----------
+    table:
+        LanceDB table to stream from.
+    num_splits:
+        Number of fixed splits to partition the table into.  Must be divisible
+        by ``world_size``.  When used with DataLoader workers it must also be
+        divisible by ``world_size * num_workers``.  Defaults to ``world_size``.
+        If the row count (after any ``filter``) is not evenly divisible by
+        ``num_splits``, the surplus rows — at most ``num_splits - 1`` per epoch
+        — are silently dropped to keep all splits the same length.
+    shuffle:
+        Whether to randomly assign rows to splits.  When ``True`` (the
+        default) rows are shuffled using ``shuffle_seed`` and ``epoch``.
+        When ``False`` rows are divided into splits sequentially in storage
+        order, which can be useful for deterministic debugging or evaluation.
+    shuffle_seed:
+        Base seed for the random permutation.  Combined with ``epoch`` so
+        each epoch produces a different ordering.  Pass ``None`` to generate
+        a random seed at construction time.
+    epoch:
+        Current training epoch.  Combined with ``shuffle_seed`` so that each
+        epoch produces a different sample ordering.
+    rank:
+        This process's rank in the distributed training group.
+    world_size:
+        Total number of processes in the distributed training group.
+    read_batch_size:
+        Number of rows fetched from each split in a single ``take_offsets``
+        call.  Larger values amortise per-request overhead (critical on object
+        storage) at the cost of higher memory usage per split buffer.  Defaults
+        to ``DEFAULT_READ_BATCH_SIZE`` (64).
+    prefetch_batches:
+        Number of I/O batches to keep in flight per split.  Higher values
+        overlap storage latency with transform and training compute at the cost
+        of more memory and threads.  Defaults to ``DEFAULT_PREFETCH_BATCHES``
+        (4).
+    columns:
+        Optional list of column names to read.  When set, only those columns
+        are fetched from storage; all others are omitted.  ``None`` (the
+        default) reads every column.
+    shuffle_clump_size:
+        When set, rows are shuffled in contiguous groups of this size rather
+        than individually.  Larger clumps improve I/O locality (important on
+        object storage) at the cost of reduced randomness.  ``None`` (the
+        default) shuffles rows individually.
+    filter:
+        Optional SQL filter expression (e.g. ``"label = 'dog'"``).  Only rows
+        that satisfy the predicate are included in the permutation.  The filter
+        is applied during permutation construction so split sizes reflect the
+        filtered row count.
+    transform:
+        Optional callable applied to each ``pyarrow.RecordBatch`` before rows
+        are yielded.  Receives one batch at a time and must return an iterable
+        whose length equals the number of rows in the batch.  When ``None``
+        (the default) rows are returned as plain Python dicts.
+    worker_info_override:
+        If set, used in place of ``torch.utils.data.get_worker_info()`` to
+        determine the DataLoader worker assignment.  Intended for unit tests
+        that need to simulate multiple workers without spawning real processes.
+        If both this and the real worker info are non-None a warning is logged
+        and the override takes precedence.
+    """
+
+    def __init__(
+        self,
+        table,
+        *,
+        num_splits: Optional[int] = None,
+        shuffle: bool = True,
+        shuffle_seed: Optional[int] = 0,
+        epoch: int = 0,
+        rank: int = 0,
+        world_size: int = 1,
+        read_batch_size: int = DEFAULT_READ_BATCH_SIZE,
+        prefetch_batches: int = DEFAULT_PREFETCH_BATCHES,
+        columns: Optional[list[str]] = None,
+        shuffle_clump_size: Optional[int] = None,
+        filter: Optional[str] = None,
+        transform: Optional[Callable] = None,
+        connection_factory: Optional[Callable[[str], Any]] = None,
+        worker_info_override=None,
+    ):
+        super().__init__()
+        if num_splits is None:
+            num_splits = world_size
+        if shuffle_seed is None:
+            shuffle_seed = random.randrange(2**32)
+        if num_splits % world_size != 0:
+            raise ValueError(
+                f"num_splits ({num_splits}) must be divisible by "
+                f"world_size ({world_size})"
+            )
+
+        self._table = table
+        self._num_splits = num_splits
+        self._shuffle = shuffle
+        self._shuffle_seed = shuffle_seed
+        self._epoch = epoch
+        self._rank = rank
+        self._world_size = world_size
+        self._read_batch_size = read_batch_size
+        self._prefetch_batches = prefetch_batches
+        self._columns = columns
+        self._shuffle_clump_size = shuffle_clump_size
+        self._filter = filter
+        self._transform = transform
+        self._connection_factory = connection_factory
+        self._worker_info_override = worker_info_override
+
+        # Live references to pipeline state, set only while __iter__ is running
+        # in the same process.  Used by the observability properties when the
+        # DataLoader runs with num_workers=0.
+        self._raw_batches_ref: Optional[list[deque]] = None
+        self._cooked_ref: Optional[list[deque]] = None
+        self._fetch_head_ref: Optional[list[int]] = None
+        self._split_sizes_ref: Optional[list[int]] = None
+        self._local_consumed_ref: Optional[list[int]] = None
+
+        # Shared-memory counters written by __iter__ (which may run in a
+        # DataLoader worker process) and read by the observability properties
+        # in the main process.  RawArray is picklable via the forkserver
+        # reduction protocol so it survives the dataset pickle round-trip.
+        # Layout: [unscanned_rows, raw_rows, cooked_rows, consumed_rows,
+        #          bytes_loaded, fetch_time_us, transform_time_us]
+        self._worker_stats: RawArray = RawArray(ctypes.c_int64, 7)
+
+        # Cumulative bytes of Arrow buffer data fetched across all iterations.
+        self._bytes_loaded: int = 0
+        # Cumulative seconds spent in LanceDB I/O and in transform functions.
+        self._fetch_time: float = 0.0
+        self._transform_time: float = 0.0
+
+        # Number of samples each split has already been consumed.  At global
+        # step boundaries all splits have consumed this many samples, so a
+        # single scalar captures the topology-independent checkpoint state.
+        self._resume_offset: int = 0
+
+        # Build the permutation table once, deterministically.
+        builder = permutation_builder(table)
+        if filter is not None:
+            builder = builder.filter(filter)
+        if shuffle:
+            perm_seed = shuffle_seed + epoch * _EPOCH_PRIME
+            self._perm_table = builder.split_random(
+                fixed=num_splits, seed=perm_seed, clump_size=shuffle_clump_size
+            ).execute()
+        else:
+            self._perm_table = builder.split_sequential(fixed=num_splits).execute()
+
+        # Contiguous block of global split indices assigned to this rank.
+        splits_per_rank = num_splits // world_size
+        rank_start = rank * splits_per_rank
+        self._rank_splits: list[int] = list(
+            range(rank_start, rank_start + splits_per_rank)
+        )
+
+    def _resolve_my_splits(self) -> list[int]:
+        """Return the split indices this instance should read in __iter__."""
+        torch_worker_info = get_worker_info()
+        if self._worker_info_override is not None:
+            if torch_worker_info is not None:
+                logger.warning(
+                    "worker_info_override is set but get_worker_info() also returned a "
+                    "non-None value; ignoring the real torch worker info and using the "
+                    "override instead.  This may lead to duplicated or incorrect data "
+                    "from the dataset."
+                )
+            worker_info = self._worker_info_override
+        else:
+            worker_info = torch_worker_info
+
+        if worker_info is None:
+            return self._rank_splits
+
+        num_workers: int = worker_info.num_workers
+        worker_id: int = worker_info.id
+        n_rank_splits = len(self._rank_splits)
+        if n_rank_splits % num_workers != 0:
+            raise ValueError(
+                f"Number of rank splits ({n_rank_splits}) must be divisible by "
+                f"num_workers ({num_workers})"
+            )
+        splits_per_worker = n_rank_splits // num_workers
+        start = worker_id * splits_per_worker
+        return self._rank_splits[start : start + splits_per_worker]
+
+    def __iter__(self) -> Iterator[dict[str, Any]]:
+        if self._raw_batches_ref is not None:
+            raise RuntimeError(
+                "StreamingDataset does not support concurrent iteration. "
+                "Only one active iterator per dataset instance is allowed."
+            )
+        my_splits = self._resolve_my_splits()
+        if not my_splits:
+            return
+
+        # Set identity transform on each Permutation so __getitems__ returns
+        # the raw RecordBatch.  Stage 2 applies the real transform.
+        permutations: list[Permutation] = []
+        for split_idx in my_splits:
+            perm = Permutation.from_tables(
+                self._table, self._perm_table, split=split_idx
+            )
+            if self._columns is not None:
+                perm = perm.select_columns(self._columns)
+            perm = perm.with_transform(lambda batch: batch)
+            if self._resume_offset > 0:
+                perm = perm.with_skip(self._resume_offset)
+            permutations.append(perm)
+
+        n = len(permutations)
+        split_sizes = [perm.num_rows for perm in permutations]
+        initial_offset = self._resume_offset
+        local_consumed = [0] * n
+
+        batch_size = self._read_batch_size
+        max_prefetch = self._prefetch_batches
+        cpu_workers = os.cpu_count() or 1
+        final_transform = (
+            self._transform if self._transform is not None else Transforms.arrow2python
+        )
+
+        # Per-split pipeline state.
+        fetch_head = [0] * n
+        io_pending = [deque() for _ in range(n)]  # Future[RecordBatch]
+        raw_batches = [deque() for _ in range(n)]  # RecordBatch — fetched, awaiting tx
+        tx_pending = [deque() for _ in range(n)]  # Future[list[Any]]
+        cooked = [deque() for _ in range(n)]  # rows ready to yield
+
+        # Limit simultaneous transforms to cpu_workers across all splits.
+        tx_semaphore = threading.Semaphore(cpu_workers)
+
+        # ── Stage 1 helpers ───────────────────────────────────────────────────
+
+        def _io_call(perm, indices):
+            t0 = time.perf_counter()
+            batch = perm.__getitems__(indices)
+            self._bytes_loaded += batch.nbytes
+            self._fetch_time += time.perf_counter() - t0
+            return batch
+
+        def _submit_io(i: int) -> None:
+            remaining = split_sizes[i] - fetch_head[i]
+            if remaining <= 0:
+                return
+            fetch = min(batch_size, remaining)
+            start = fetch_head[i]
+            fetch_head[i] += fetch
+            perm_i = permutations[i]
+            indices = list(range(start, start + fetch))
+            io_pending[i].append(io_pool.submit(_io_call, perm_i, indices))
+
+        def _fill_io(i: int) -> None:
+            while len(io_pending[i]) < max_prefetch and fetch_head[i] < split_sizes[i]:
+                _submit_io(i)
+
+        def _drain_io(i: int) -> None:
+            """Move completed I/O futures into raw_batches non-blockingly."""
+            while io_pending[i] and io_pending[i][0].done():
+                raw_batches[i].append(io_pending[i].popleft().result())
+
+        # ── Stage 2 helpers ───────────────────────────────────────────────────
+
+        def _tx_call_guarded(batch):
+            try:
+                t0 = time.perf_counter()
+                result = final_transform(batch)
+                self._transform_time += time.perf_counter() - t0
+                return result
+            finally:
+                tx_semaphore.release()
+
+        def _try_submit_tx(i: int) -> None:
+            """Submit transforms for raw_batches[i] up to available capacity."""
+            while raw_batches[i] and tx_semaphore.acquire(blocking=False):
+                batch = raw_batches[i].popleft()
+                tx_pending[i].append(tx_pool.submit(_tx_call_guarded, batch))
+
+        def _drain_tx(i: int) -> None:
+            """Move completed transform futures into cooked non-blockingly."""
+            while tx_pending[i] and tx_pending[i][0].done():
+                cooked[i].extend(tx_pending[i].popleft().result())
+
+        # ── Combined advance ──────────────────────────────────────────────────
+
+        def _advance(i: int) -> None:
+            """Non-blocking pipeline pump for split i."""
+            _drain_io(i)
+            _drain_tx(i)
+            _try_submit_tx(i)
+            _fill_io(i)
+
+        def _ensure_cooked(i: int) -> None:
+            """Ensure cooked[i] has at least one row, blocking if necessary."""
+            _advance(i)
+            while not cooked[i]:
+                if tx_pending[i]:
+                    # Wait for the oldest in-flight transform.
+                    cooked[i].extend(tx_pending[i].popleft().result())
+                    _advance(i)
+                elif raw_batches[i]:
+                    # Acquire a transform slot (may block briefly if all
+                    # cpu_workers are busy with other splits).
+                    tx_semaphore.acquire()
+                    batch = raw_batches[i].popleft()
+                    tx_pending[i].append(tx_pool.submit(_tx_call_guarded, batch))
+                elif io_pending[i]:
+                    # Block on the oldest in-flight I/O fetch.
+                    raw_batches[i].append(io_pending[i].popleft().result())
+                    _advance(i)
+                else:
+                    break  # split exhausted
+
+        # ── Main loop ─────────────────────────────────────────────────────────
+
+        with ThreadPoolExecutor(max_workers=n * max_prefetch) as io_pool:
+            with ThreadPoolExecutor(max_workers=cpu_workers) as tx_pool:
+                self._raw_batches_ref = raw_batches
+                self._cooked_ref = cooked
+                self._fetch_head_ref = fetch_head
+                self._split_sizes_ref = split_sizes
+                self._local_consumed_ref = local_consumed
+                try:
+                    for i in range(n):
+                        _fill_io(i)
+
+                    while True:
+                        # Stop when any split is exhausted (all exhaust
+                        # simultaneously: equal split sizes + round-robin).
+                        if any(local_consumed[i] >= split_sizes[i] for i in range(n)):
+                            break
+
+                        for i in range(n):
+                            _ensure_cooked(i)
+                            row = cooked[i].popleft()
+                            local_consumed[i] += 1
+                            _advance(i)
+
+                            # After the last split in each cycle: update the
+                            # global offset and refresh the shared-memory stats
+                            # so the main process can observe pipeline depth
+                            # even when __iter__ runs in a worker process.
+                            if i == n - 1:
+                                self._resume_offset = initial_offset + local_consumed[i]
+                                ws = self._worker_stats
+                                ws[0] = sum(
+                                    split_sizes[j] - fetch_head[j] for j in range(n)
+                                )
+                                ws[1] = sum(
+                                    batch.num_rows for q in raw_batches for batch in q
+                                )
+                                ws[2] = sum(len(q) for q in cooked)
+                                ws[3] = sum(local_consumed)
+                                ws[4] = self._bytes_loaded
+                                ws[5] = int(self._fetch_time * 1_000_000)
+                                ws[6] = int(self._transform_time * 1_000_000)
+
+                            yield row
+                finally:
+                    self._raw_batches_ref = None
+                    self._cooked_ref = None
+                    self._fetch_head_ref = None
+                    self._split_sizes_ref = None
+                    self._local_consumed_ref = None
+
+    @property
+    def bytes_loaded(self) -> int:
+        """Cumulative bytes of raw Arrow buffer data fetched from storage.
+
+        Measured on the ``RecordBatch`` before any transform is applied, so
+        the value reflects actual I/O rather than the size of transformed
+        output.  Accumulates across multiple iterations of the same dataset
+        instance and is never reset automatically.
+        """
+        if self._raw_batches_ref is not None:
+            return self._bytes_loaded
+        return int(self._worker_stats[4])
+
+    @property
+    def fetch_time(self) -> float:
+        """Cumulative seconds spent waiting for data from LanceDB.
+
+        Measured per batch in the Stage 1 I/O threads as the total elapsed
+        time of the ``take_offsets`` call.  Accumulates across all splits and
+        all iterations.
+        """
+        if self._raw_batches_ref is not None:
+            return self._fetch_time
+        return self._worker_stats[5] / 1_000_000
+
+    @property
+    def transform_time(self) -> float:
+        """Cumulative seconds spent applying the transform.
+
+        Measured per batch in the Stage 2 transform threads as the elapsed
+        time inside the transform callable (or the default ``arrow2python``
+        conversion when no transform is set).  Accumulates across all splits
+        and all iterations.
+        """
+        if self._raw_batches_ref is not None:
+            return self._transform_time
+        return self._worker_stats[6] / 1_000_000
+
+    @property
+    def raw_queue_depth(self) -> int:
+        """Number of raw rows waiting for a transform thread across all splits.
+
+        A persistently non-zero value means Stage 2 (transform) is the
+        bottleneck: I/O is completing faster than transforms can consume
+        batches.  Returns 0 when not iterating.
+        """
+        if self._raw_batches_ref is not None:
+            return sum(batch.num_rows for q in self._raw_batches_ref for batch in q)
+        return int(self._worker_stats[1])
+
+    @property
+    def prefetch_queue_depth(self) -> int:
+        """Number of rows transformed and ready to yield across all splits.
+
+        Counts rows whose transform has completed and are sitting in memory
+        waiting for the main thread — rows that can be handed off with no
+        I/O or CPU wait.  Returns 0 when not iterating.
+        """
+        if self._cooked_ref is not None:
+            return sum(len(q) for q in self._cooked_ref)
+        return int(self._worker_stats[2])
+
+    @property
+    def unscanned_rows(self) -> int:
+        """Number of rows not yet submitted to the I/O stage across all splits.
+
+        Decreases as the I/O stage submits fetch requests.  When this reaches
+        zero all data has been requested from storage (though it may not have
+        arrived yet).  Returns 0 when not iterating.
+        """
+        if self._fetch_head_ref is not None:
+            return sum(
+                size - head
+                for size, head in zip(self._split_sizes_ref, self._fetch_head_ref)
+            )
+        return int(self._worker_stats[0])
+
+    @property
+    def consumed_rows(self) -> int:
+        """Number of rows already yielded to the caller across all splits.
+
+        Monotonically increases throughout iteration.  Returns 0 when not
+        iterating.
+        """
+        if self._local_consumed_ref is not None:
+            return sum(self._local_consumed_ref)
+        return int(self._worker_stats[3])
+
+    def __getstate__(self):
+        """Support pickling for multi-worker DataLoader (forkserver / spawn).
+
+        The live LanceDB table object contains non-picklable connection state
+        (sockets, Rust-backed PyO3 objects).  If a ``connection_factory`` was
+        supplied only the table name is serialised; the factory is called in
+        the worker to reopen the connection without embedding any credentials.
+        Without a factory the table's own picklable reopen state is captured
+        via ``_table_to_pickle_state`` (mirrors the ``Permutation`` approach).
+        """
+        state = self.__dict__.copy()
+        # _table: replace with reconnect info (credentials must not be embedded).
+        state["_table_name"] = self._table.name
+        if self._connection_factory is not None:
+            state["_table"] = None
+        else:
+            state["_table"] = _table_to_pickle_state(self._table)
+        # _perm_table: always in-memory; serialise as Arrow data (mirrors
+        # how Permutation.__getstate__ handles its permutation_table).
+        state["_perm_table"] = (
+            self._perm_table.name,
+            self._perm_table.to_arrow(),
+        )
+        for key in (
+            "_raw_batches_ref",
+            "_cooked_ref",
+            "_fetch_head_ref",
+            "_split_sizes_ref",
+            "_local_consumed_ref",
+        ):
+            state[key] = None
+        return state
+
+    def __setstate__(self, state):
+        """Reconnect to LanceDB after unpickling in a worker process."""
+        from . import connect as _connect
+
+        table_name = state.pop("_table_name")
+        table_state = state.pop("_table")
+        perm_name, perm_data = state.pop("_perm_table")
+        self.__dict__.update(state)
+        if self._connection_factory is not None:
+            self._table = self._connection_factory(table_name)
+        else:
+            self._table = _table_from_pickle_state(table_state)
+        self._perm_table = _connect("memory://").create_table(perm_name, perm_data)
+
+    def state_dict(self) -> dict:
+        """Snapshot the dataset's consumption state.
+
+        The returned dict is topology-independent: at global step boundaries
+        every split has been consumed the same number of times (by the
+        round-robin design), so the per-split count is a single uniform value
+        that is identical across all ranks and DataLoader workers.
+        """
+        return {
+            "shuffle_seed": self._shuffle_seed,
+            "num_splits": self._num_splits,
+            "epoch": self._epoch,
+            "samples_consumed_per_split": [self._resume_offset] * self._num_splits,
+        }
+
+    def load_state_dict(self, state: dict) -> None:
+        """Resume from a previously snapshotted state.
+
+        Raises ``ValueError`` if ``num_splits`` or ``shuffle_seed`` differ
+        from the checkpoint, since a different split structure or shuffle order
+        makes mid-epoch resumption meaningless.
+        """
+        if state["num_splits"] != self._num_splits:
+            raise ValueError(
+                f"num_splits mismatch: checkpoint has {state['num_splits']}, "
+                f"current dataset has {self._num_splits}"
+            )
+        if state["shuffle_seed"] != self._shuffle_seed:
+            raise ValueError(
+                f"shuffle_seed mismatch: checkpoint has {state['shuffle_seed']}, "
+                f"current dataset has {self._shuffle_seed}"
+            )
+        consumed = state["samples_consumed_per_split"]
+        # All entries are equal at step boundaries; use the first.
+        if isinstance(consumed, list):
+            self._resume_offset = consumed[0] if consumed else 0
+        else:
+            self._resume_offset = int(consumed)
@@ -651,6 +651,16 @@ def _append_vector_columns(
                    col_data = func.compute_source_embeddings_with_retry(
                        batch[conf.source_column]
                    )
+                    # Replace vectors with wrong length (including empty lists
+                    # returned for inputs like empty strings) with None so that
+                    # _handle_bad_vectors can process them according to the
+                    # on_bad_vectors policy instead of crashing when PyArrow
+                    # tries to cast them into a fixed-size list array.
+                    expected_ndims = conf.function.ndims()
+                    col_data = [
+                        v if v is not None and len(v) == expected_ndims else None
+                        for v in col_data
+                    ]
                    if no_vector_column:
                        batch = batch.append_column(
                            schema.field(vector_column),
@@ -3749,6 +3759,11 @@ class LanceTable(Table):
        [`AsyncTable.unset_lsm_write_spec`][lancedb.AsyncTable.unset_lsm_write_spec]."""
        return LOOP.run(self._table.unset_lsm_write_spec())

+    def get_lsm_write_spec(self) -> Optional["LsmWriteSpec"]:
+        """Read the installed LsmWriteSpec, or ``None``. See
+        [`AsyncTable.get_lsm_write_spec`][lancedb.AsyncTable.get_lsm_write_spec]."""
+        return LOOP.run(self._table.get_lsm_write_spec())
+
    def close_lsm_writers(self) -> None:
        """Close cached MemWAL shard writers. See
        [`AsyncTable.close_lsm_writers`][lancedb.AsyncTable.close_lsm_writers]."""
@@ -4020,7 +4035,16 @@ def _handle_bad_vector_column(
        dim = _infer_vector_dim(vec_arr)
        if dim is None:
            return data
-    has_wrong_dim = pc.not_equal(pc.list_value_length(vec_arr), dim)
+
+    is_null = pc.is_null(vec_arr)
+    # pc.list_value_length returns null for null list entries, so
+    # pc.not_equal(null, dim) also returns null. Use or_kleene so that
+    # True OR null = True (Kleene three-valued logic), ensuring null vectors
+    # are counted as wrong-dim.
+    has_wrong_dim = pc.or_kleene(
+        is_null,
+        pc.not_equal(pc.list_value_length(vec_arr), dim),
+    )

    has_bad_vectors = pc.any(has_nan).as_py() or pc.any(has_wrong_dim).as_py()

@@ -4398,6 +4422,17 @@ class AsyncTable:
        """
        await self._inner.unset_lsm_write_spec()

+    async def get_lsm_write_spec(self) -> Optional["LsmWriteSpec"]:
+        """Read the LsmWriteSpec currently installed on this table.
+
+        Returns ``None`` when the MemWAL LSM write path is not enabled (no
+        spec has been set, or it was removed with `unset_lsm_write_spec`).
+        The returned spec — including its ``maintained_indexes`` and
+        ``writer_config_defaults`` — mirrors what was passed to
+        `set_lsm_write_spec`.
+        """
+        return await self._inner.get_lsm_write_spec()
+
    async def close_lsm_writers(self) -> None:
        """Drain and close any cached MemWAL shard writers for this table.

@@ -177,7 +177,10 @@ def flatten_columns(tbl: pa.Table, flatten: Optional[Union[int, bool]] = None):
                continue
            else:
                break
-    elif isinstance(flatten, int):
+    # `bool` is a subclass of `int`, so guard against it explicitly: `flatten=False`
+    # (and `None`) must mean "do not flatten" rather than falling into the integer
+    # branch and raising on the `flatten <= 0` check.
+    elif isinstance(flatten, int) and not isinstance(flatten, bool):
        if flatten <= 0:
            raise ValueError(
                "Please specify a positive integer for flatten or the boolean "
@@ -515,3 +518,38 @@ def batch_to_tensor_rows(batch: pa.RecordBatch):
    stacked = torch.tensor(numpy.column_stack(columns))
    rows = list(stacked.unbind(dim=0))
    return rows
+
+
+def batch_to_tensor_dict(batch: pa.RecordBatch):
+    """
+    Convert a PyArrow RecordBatch to a list of per-row dicts of PyTorch Tensors.
+
+    Each column is first converted to a 1-D tensor (zero-copy via DLPack), then
+    sliced per row. The result is a list whose length is ``batch.num_rows`` and
+    whose items are dicts keyed by column name. This shape composes directly
+    with PyTorch's default ``DataLoader`` collate, which stacks the per-row
+    dicts back into a dict of batched tensors.
+
+    Fails if torch is not installed.
+    Fails if a column's data type is not supported by PyTorch.
+
+    Parameters
+    ----------
+    batch : pa.RecordBatch
+        The record batch to convert.
+
+    Returns
+    -------
+    list[dict[str, torch.Tensor]]
+        One per-row dict per row in the batch. Each dict maps column name to a
+        0-D tensor view into the column.
+    """
+    torch = attempt_import_or_raise("torch", "torch")
+    tensors = {
+        name: torch.from_dlpack(col)
+        for name, col in zip(batch.schema.names, batch.columns)
+    }
+    return [
+        {name: tensor[i] for name, tensor in tensors.items()}
+        for i in range(batch.num_rows)
+    ]
@@ -2,6 +2,7 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors

 import os
+import pickle
 from typing import List, Optional, Union
 from unittest.mock import MagicMock, patch

@@ -242,6 +243,49 @@ def test_embedding_with_bad_results(tmp_path):
    assert tbl["vector"].null_count == 1


+def test_embedding_with_empty_output_vectors(tmp_path):
+    """Regression test for issue #1672.
+
+    When an embedding function returns an empty list (e.g. for empty-string
+    inputs), _append_vector_columns used to crash because PyArrow cannot cast
+    [] into a fixed-size list element.  The fix replaces wrong-length vectors
+    with None before building the Arrow array so that _handle_bad_vectors can
+    process them normally.
+    """
+
+    @register("empty-vec-embedding")
+    class EmptyVecEmbeddingFunction(TextEmbeddingFunction):
+        def ndims(self):
+            return 128
+
+        def generate_embeddings(self, texts: Union[List[str], np.ndarray]) -> list:
+            # Simulate a model that returns an empty list for blank inputs
+            return [
+                [] if text.strip() == "" else np.random.randn(self.ndims()).tolist()
+                for text in texts
+            ]
+
+    db = lancedb.connect(tmp_path)
+    registry = EmbeddingFunctionRegistry.get_instance()
+    model = registry.get("empty-vec-embedding").create()
+
+    class Schema(LanceModel):
+        text: str = model.SourceField()
+        vector: Vector(model.ndims()) = model.VectorField()
+
+    table = db.create_table("test_empty_vec", schema=Schema, mode="overwrite")
+
+    # Should not crash; the row with the empty string should be dropped
+    table.add(
+        [{"text": "hello world"}, {"text": ""}, {"text": "foo"}],
+        on_bad_vectors="drop",
+    )
+
+    assert len(table) == 2
+    texts = table.to_arrow()["text"].to_pylist()
+    assert "" not in texts
+
+
 def test_with_existing_vectors(tmp_path):
    @register("mock-embedding")
    class MockEmbeddingFunction(TextEmbeddingFunction):
@@ -548,6 +592,22 @@ def test_openai_no_retry_on_401(mock_sleep):
    assert mock_sleep.call_count == 0


+def test_ollama_embeddings_pickle():
+    """OllamaEmbeddings must pickle even after the cached client is created."""
+    registry = get_registry()
+    model = registry.get("ollama").create(name="nomic-embed-text")
+
+    # Simulate accessing the cached client, which stores it on the instance.
+    model.__dict__["_ollama_client"] = MagicMock()
+
+    pickled = pickle.dumps(model)
+    restored = pickle.loads(pickled)
+
+    assert restored.name == "nomic-embed-text"
+    assert restored.host == "http://localhost:11434"
+    assert "_ollama_client" not in restored.__dict__
+
+
 def test_url_retrieve_downloads_image():
    """
    Embedding functions like open-clip, siglip, and jinaai use url_retrieve()
@@ -3,10 +3,14 @@

 """Tests for the type-safe expression builder API."""

-import pytest
+from datetime import date, datetime, timedelta, timezone
+from decimal import Decimal
+
 import pyarrow as pa
+import pytest
+
 import lancedb
-from lancedb.expr import Expr, col, lit, func
+from lancedb.expr import Expr, col, func, lit


 # ── unit tests for Expr construction ─────────────────────────────────────────
@@ -54,6 +58,28 @@ class TestExprConstruction:
        with pytest.raises(Exception):
            func("not_a_real_function", col("x"))

+    def test_lit_date(self):
+        e = lit(date(2024, 1, 1))
+        assert isinstance(e, Expr)
+
+    def test_lit_datetime(self):
+        # Naive datetime
+        e = lit(datetime(2024, 1, 1, 10, 0))
+        assert isinstance(e, Expr)
+
+    def test_lit_datetime_tz(self):
+        # Timezone-aware datetime
+        tz = timezone(timedelta(hours=5))
+        dt = datetime(2024, 1, 1, 10, 0, tzinfo=tz)
+        e = lit(dt)
+        assert isinstance(e, Expr)
+
+    def test_lit_decimal_precision(self):
+        # High precision Decimal that would be rounded if converted to float
+        d = Decimal("1.234567890123456789")
+        e = lit(d)
+        assert isinstance(e, Expr)
+

 class TestExprOperators:
    def test_eq_operator(self):
@@ -142,6 +168,20 @@ class TestExprOperators:
        assert isinstance(e, Expr)
        assert e.to_sql() == "(name = 'alice')"

+    def test_reflexive_comparisons(self):
+        # 10 < col("age") swaps to col("age") > 10
+        assert (10 < col("age")).to_sql() == "(age > 10)"
+        assert (10 <= col("age")).to_sql() == "(age >= 10)"
+        assert (10 > col("age")).to_sql() == "(age < 10)"
+        assert (10 >= col("age")).to_sql() == "(age <= 10)"
+        assert (10 == col("age")).to_sql() == "(age = 10)"
+        assert (10 != col("age")).to_sql() == "(age <> 10)"
+
+    def test_reflexive_logical(self):
+        # True & Expr calls Expr.__rand__(True)
+        assert (True & (col("age") > 18)).to_sql() == "(true AND (age > 18))"
+        assert (False | (col("age") > 18)).to_sql() == "(false OR (age > 18))"
+

 class TestExprBytesLiteral:
    def test_bytes_to_sql(self):
@@ -282,6 +322,40 @@ class TestExprRepr:
            {e: 1}


+class TestExprReflexive:
+    def test_reflexive_eq(self):
+        e = 1 == col("x")
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(x = 1)"
+
+    def test_reflexive_ne(self):
+        e = 1 != col("x")
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(x <> 1)"
+
+    def test_reflexive_lt(self):
+        # 1 < x  =>  (x > 1)
+        e = 1 < col("x")
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(x > 1)"
+
+    def test_reflexive_gt(self):
+        # 1 > x  =>  (x < 1)
+        e = 1 > col("x")
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(x < 1)"
+
+    def test_reflexive_and(self):
+        e = True & col("active")
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(true AND active)"
+
+    def test_reflexive_or(self):
+        e = False | col("inactive")
+        assert isinstance(e, Expr)
+        assert e.to_sql() == "(false OR inactive)"
+
+
 # ── integration tests: end-to-end query against a real table ─────────────────


@@ -432,6 +506,72 @@ class TestColNamingIntegration:
        assert sorted(result["upper_name"].to_pylist()) == ["ALICE", "BOB", "CHARLIE"]


+@pytest.fixture
+def type_check_table(tmp_path):
+    """Fixture that creates a table with Date32 and Decimal128 columns."""
+    db = lancedb.connect(str(tmp_path))
+    schema = pa.schema(
+        [
+            ("date", pa.date32()),
+            ("decimal", pa.decimal128(10, 2)),
+            ("binary", pa.binary()),
+        ]
+    )
+    data = pa.table(
+        {
+            "date": [date(2024, 1, 1), date(2024, 1, 2)],
+            "decimal": [Decimal("10.50"), Decimal("20.75")],
+            "binary": [b"\x01", b"\x02"],
+        },
+        schema=schema,
+    )
+    return db.create_table("extended_types", data)
+
+
+class TestExtendedTypeIntegration:
+    """Integration tests verifying that typed literals work correctly in filters."""
+
+    def test_date_integration(self, type_check_table):
+        """Verify that Date32 literals are correctly parsed and filtered."""
+        result = (
+            type_check_table.search()
+            .where(col("date") == lit(date(2024, 1, 1)))
+            .to_arrow()
+        )
+        assert result.num_rows == 1
+        assert result["date"][0].as_py() == date(2024, 1, 1)
+
+    def test_decimal_integration(self, tmp_path):
+        """A Decimal literal must retain full 128-bit precision in a filter.
+
+        1.234567890123456789 and 1.234567890123456790 differ only in the last
+        digit and are indistinguishable once truncated to f64.  The filter
+        therefore returns the single expected row only if ``lit(Decimal)``
+        produces a true ``Decimal128`` scalar rather than being coerced to f64.
+        """
+        low = Decimal("1.234567890123456789")
+        high = Decimal("1.234567890123456790")
+
+        db = lancedb.connect(str(tmp_path / "decimal_precision"))
+        schema = pa.schema([("val", pa.decimal128(19, 18))])
+        table = db.create_table(
+            "decimal_precision",
+            pa.table({"val": [low, high]}, schema=schema),
+        )
+
+        result = table.search().where(col("val") < lit(high)).to_arrow()
+        assert result.num_rows == 1
+        assert result["val"][0].as_py() == low
+
+    def test_binary_integration(self, type_check_table):
+        """Verify that Binary literals are correctly filtered."""
+        result = (
+            type_check_table.search().where(col("binary") == lit(b"\x01")).to_arrow()
+        )
+        assert result.num_rows == 1
+        assert result["binary"][0].as_py() == b"\x01"
+
+
 # ── bytes / binary column integration tests ───────────────────────────────────


@@ -11,6 +11,7 @@ import lancedb
 import pyarrow as pa
 import pytest
 from lancedb._lancedb import LsmWriteSpec
+from lancedb.index import BTree

 SCHEMA = pa.schema(
    [
@@ -136,3 +137,76 @@ def test_lsm_write_spec_identity_and_writer_config_defaults():
    s = s.with_writer_config_defaults({"durable_write": "false"})
    assert s.writer_config_defaults == {"durable_write": "false"}
    assert "durable_write" in repr(s)
+
+
+def test_get_lsm_write_spec(tmp_path):
+    _db, table = _make_table(tmp_path)
+    table.set_unenforced_primary_key("id")
+
+    # None when nothing is installed.
+    assert table.get_lsm_write_spec() is None
+
+    # A real scalar index is needed to name it as a maintained index.
+    table.create_index("id", config=BTree())
+    idx_name = table.list_indices()[0].name
+
+    # Bucket spec round-trips, including maintained indexes and writer config
+    # defaults.
+    table.set_lsm_write_spec(
+        LsmWriteSpec.bucket("id", 4)
+        .with_maintained_indexes([idx_name])
+        .with_writer_config_defaults({"durable_write": "false"})
+    )
+    spec = table.get_lsm_write_spec()
+    assert spec is not None
+    assert spec.spec_type == "bucket"
+    assert spec.column == "id"
+    assert spec.num_buckets == 4
+    assert spec.maintained_indexes == [idx_name]
+    assert spec.writer_config_defaults == {"durable_write": "false"}
+
+    # After unset, None again.
+    table.unset_lsm_write_spec()
+    assert table.get_lsm_write_spec() is None
+
+    # Identity round-trips (column recovered from the schema).
+    table.set_lsm_write_spec(LsmWriteSpec.identity("id"))
+    spec = table.get_lsm_write_spec()
+    assert spec.spec_type == "identity"
+    assert spec.column == "id"
+    table.unset_lsm_write_spec()
+
+    # Unsharded round-trips (no routing column).
+    table.set_lsm_write_spec(LsmWriteSpec.unsharded())
+    spec = table.get_lsm_write_spec()
+    assert spec.spec_type == "unsharded"
+    assert spec.column is None
+
+
+@pytest.mark.asyncio
+async def test_async_get_lsm_write_spec(tmp_path):
+    db = await lancedb.connect_async(
+        tmp_path, read_consistency_interval=timedelta(seconds=0)
+    )
+    table = await db.create_table(
+        "t",
+        pa.RecordBatchReader.from_batches(SCHEMA, [_batch(["seed"], [0])]),
+    )
+
+    assert await table.get_lsm_write_spec() is None
+
+    # A real scalar index is needed to name it as a maintained index.
+    await table.create_index("id", config=BTree())
+    idx_name = (await table.list_indices())[0].name
+
+    await table.set_lsm_write_spec(
+        LsmWriteSpec.bucket("id", 8).with_maintained_indexes([idx_name])
+    )
+    spec = await table.get_lsm_write_spec()
+    assert spec is not None
+    assert spec.spec_type == "bucket"
+    assert spec.column == "id"
+    assert spec.num_buckets == 8
+    assert spec.maintained_indexes == [idx_name]
+    await table.unset_lsm_write_spec()
+    assert await table.get_lsm_write_spec() is None
@@ -935,14 +935,41 @@ def test_transform_fn(mem_db):
    try:
        import torch

-        torch_result = list(
-            permutation.with_format("torch").iter(10, skip_last_batch=False)
+        # "torch" returns a list of per-row dicts. Default DataLoader collate
+        # stacks the per-row dicts back into a dict of batched tensors.
+        torch_perm = permutation.with_format("torch")
+        torch_batch = list(torch_perm.iter(10, skip_last_batch=False))[0]
+        assert isinstance(torch_batch, list)
+        assert len(torch_batch) == 10
+        assert isinstance(torch_batch[0], dict)
+        assert set(torch_batch[0].keys()) == {"id", "value"}
+        assert isinstance(torch_batch[0]["id"], torch.Tensor)
+        assert torch_batch[0]["id"].dtype == torch.int64
+
+        rows = torch_perm.__getitems__([0, 1, 2])
+        assert isinstance(rows, list)
+        assert len(rows) == 3
+        assert isinstance(rows[0], dict)
+        assert set(rows[0].keys()) == {"id", "value"}
+        assert isinstance(rows[0]["id"], torch.Tensor)
+
+        # "torch_row" returns a list of tensors, one per row.
+        torch_rows = list(
+            permutation.with_format("torch_row").iter(10, skip_last_batch=False)
        )[0]
-        assert isinstance(torch_result, list)
-        assert len(torch_result) == 10
-        assert isinstance(torch_result[0], torch.Tensor)
-        assert torch_result[0].shape == (2,)
-        assert torch_result[0].dtype == torch.int64
+        assert isinstance(torch_rows, list)
+        assert len(torch_rows) == 10
+        assert isinstance(torch_rows[0], torch.Tensor)
+        assert torch_rows[0].shape == (2,)
+        assert torch_rows[0].dtype == torch.int64
+
+        # "torch_col" stacks columns into a single 2D tensor.
+        torch_col = list(
+            permutation.with_format("torch_col").iter(10, skip_last_batch=False)
+        )[0]
+        assert isinstance(torch_col, torch.Tensor)
+        assert torch_col.shape == (2, 10)
+        assert torch_col.dtype == torch.int64
    except ImportError:
        # Skip check if torch is not installed
        pass
@@ -412,10 +412,12 @@ def test_remote_permutation_is_picklable():
            content_len = int(request.headers.get("Content-Length"))
            body = json.loads(request.rfile.read(content_len))
            if "filter" in body:
-                match = re.search(r"_rowoffset in \((.*?)\)", body["filter"])
-                offsets = [int(offset.strip()) for offset in match.group(1).split(",")]
+                match = re.search(
+                    r"_rowoffset\s+in\s+\((.*?)\)", body["filter"], re.IGNORECASE
+                )
+                offsets = [int(o.strip()) for o in match.group(1).split(",")]
            else:
-                offsets = rows
+                offsets = list(range(len(rows)))
            table = pa.table({"a": [rows[offset] for offset in offsets]})

            request.send_response(200)
@@ -7,7 +7,8 @@ Tests for S3 bucket names containing dots.
 Related issue: https://github.com/lancedb/lancedb/issues/1898

 These tests validate the early error checking for S3 bucket names with dots.
-No actual S3 connection is made - validation happens before connection.
+When validation succeeds, eager namespace initialization may still fail later
+because these tests intentionally do not provide real S3 credentials.
 """

 import pytest
@@ -20,6 +21,13 @@ BUCKET_WITH_DOTS_AND_AWS_REGION = ("s3://my.bucket.name", {"aws_region": "us-eas
 BUCKET_WITHOUT_DOTS = "s3://my-bucket/path"


+def assert_not_rejected_for_bucket_dots(connect):
+    try:
+        connect()
+    except ValueError as err:
+        assert "contains dots" not in str(err)
+
+
 class TestS3BucketWithDotsSync:
    """Tests for connect()."""

@@ -27,19 +35,22 @@ class TestS3BucketWithDotsSync:
        with pytest.raises(ValueError, match="contains dots"):
            lancedb.connect(BUCKET_WITH_DOTS)

-    def test_bucket_with_dots_and_region_passes(self):
+    def test_bucket_with_dots_and_region_is_not_rejected(self):
        uri, opts = BUCKET_WITH_DOTS_AND_REGION
-        db = lancedb.connect(uri, storage_options=opts)
-        assert db is not None
+        assert_not_rejected_for_bucket_dots(
+            lambda: lancedb.connect(uri, storage_options=opts)
+        )

-    def test_bucket_with_dots_and_aws_region_passes(self):
+    def test_bucket_with_dots_and_aws_region_is_not_rejected(self):
        uri, opts = BUCKET_WITH_DOTS_AND_AWS_REGION
-        db = lancedb.connect(uri, storage_options=opts)
-        assert db is not None
+        assert_not_rejected_for_bucket_dots(
+            lambda: lancedb.connect(uri, storage_options=opts)
+        )

-    def test_bucket_without_dots_passes(self):
-        db = lancedb.connect(BUCKET_WITHOUT_DOTS)
-        assert db is not None
+    def test_bucket_without_dots_is_not_rejected(self):
+        assert_not_rejected_for_bucket_dots(
+            lambda: lancedb.connect(BUCKET_WITHOUT_DOTS)
+        )


 class TestS3BucketWithDotsAsync:
@@ -51,18 +62,24 @@ class TestS3BucketWithDotsAsync:
            await lancedb.connect_async(BUCKET_WITH_DOTS)

    @pytest.mark.asyncio
-    async def test_bucket_with_dots_and_region_passes(self):
+    async def test_bucket_with_dots_and_region_is_not_rejected(self):
        uri, opts = BUCKET_WITH_DOTS_AND_REGION
-        db = await lancedb.connect_async(uri, storage_options=opts)
-        assert db is not None
+        try:
+            await lancedb.connect_async(uri, storage_options=opts)
+        except ValueError as err:
+            assert "contains dots" not in str(err)

    @pytest.mark.asyncio
-    async def test_bucket_with_dots_and_aws_region_passes(self):
+    async def test_bucket_with_dots_and_aws_region_is_not_rejected(self):
        uri, opts = BUCKET_WITH_DOTS_AND_AWS_REGION
-        db = await lancedb.connect_async(uri, storage_options=opts)
-        assert db is not None
+        try:
+            await lancedb.connect_async(uri, storage_options=opts)
+        except ValueError as err:
+            assert "contains dots" not in str(err)

    @pytest.mark.asyncio
-    async def test_bucket_without_dots_passes(self):
-        db = await lancedb.connect_async(BUCKET_WITHOUT_DOTS)
-        assert db is not None
+    async def test_bucket_without_dots_is_not_rejected(self):
+        try:
+            await lancedb.connect_async(BUCKET_WITHOUT_DOTS)
+        except ValueError as err:
+            assert "contains dots" not in str(err)
@@ -148,15 +148,47 @@ def test_permutation_dataloader(mem_db):
    for batch in dataloader:
        assert batch["a"].size(0) == 10

-    permutation = permutation.with_format("torch")
-    dataloader = torch.utils.data.DataLoader(permutation, batch_size=10, shuffle=True)
+    # "torch" produces a list of per-row dicts per batch. The default
+    # DataLoader collate stacks the per-row dicts back into a batched dict.
+    torch_perm = permutation.with_format("torch")
+    batch = next(torch_perm.iter(10, skip_last_batch=False))
+    assert isinstance(batch, list)
+    assert len(batch) == 10
+    assert isinstance(batch[0], dict)
+    assert isinstance(batch[0]["a"], torch.Tensor)
+    rows = torch_perm.__getitems__([0, 1, 2])
+    assert isinstance(rows, list)
+    assert len(rows) == 3
+    assert isinstance(rows[0], dict)
+    assert isinstance(rows[0]["a"], torch.Tensor)
+    dataloader = torch.utils.data.DataLoader(torch_perm, batch_size=10, shuffle=True)
+    for batch in dataloader:
+        assert isinstance(batch, dict)
+        assert batch["a"].shape == (10,)
+    # Spawn-based workers exercise the pickle round-trip path: the new
+    # transform-as-list shape must survive pickling so workers produce the
+    # same per-row dicts the parent does.
+    spawn_loader = torch.utils.data.DataLoader(
+        torch_perm,
+        batch_size=10,
+        num_workers=2,
+        multiprocessing_context="spawn",
+    )
+    for batch in spawn_loader:
+        assert isinstance(batch, dict)
+        assert batch["a"].shape == (10,)
+
+    # "torch_row" returns a list of row tensors. Works with the default
+    # DataLoader collate (stacks rows into 2D).
+    row_perm = permutation.with_format("torch_row")
+    dataloader = torch.utils.data.DataLoader(row_perm, batch_size=10, shuffle=True)
    for batch in dataloader:
        assert batch.size(0) == 10
        assert batch.size(1) == 1

-    permutation = permutation.with_format("torch_col")
+    col_perm = permutation.with_format("torch_col")
    dataloader = torch.utils.data.DataLoader(
-        permutation, collate_fn=lambda x: x, batch_size=10, shuffle=True
+        col_perm, collate_fn=lambda x: x, batch_size=10, shuffle=True
    )
    for batch in dataloader:
        assert batch.size(0) == 1
@@ -25,10 +25,42 @@ import pandas as pd
 import polars as pl
 import pytest
 import lancedb
-from lancedb.util import get_uri_scheme, join_uri, value_to_sql
+from lancedb.util import flatten_columns, get_uri_scheme, join_uri, value_to_sql
 from utils import exception_output


+def _struct_table() -> pa.Table:
+    return pa.table(
+        {
+            "id": [1, 2],
+            "nested": pa.array([{"a": 1, "b": 2}, {"a": 3, "b": 4}]),
+        }
+    )
+
+
+def test_flatten_columns():
+    tbl = _struct_table()
+
+    # None / False mean "do not flatten": the struct column is preserved.
+    # `False` is a regression guard: because bool is a subclass of int it used
+    # to fall into the integer branch and raise ValueError (see issue).
+    for no_flatten in (None, False):
+        result = flatten_columns(tbl, no_flatten)
+        assert result.column_names == ["id", "nested"]
+
+    # True flattens all nested levels.
+    flattened = flatten_columns(tbl, True)
+    assert flattened.column_names == ["id", "nested.a", "nested.b"]
+
+    # A positive integer flattens up to that depth.
+    flattened = flatten_columns(tbl, 1)
+    assert flattened.column_names == ["id", "nested.a", "nested.b"]
+
+    # Non-positive integers are still rejected.
+    with pytest.raises(ValueError):
+        flatten_columns(tbl, 0)
+
+
 def test_normalize_uri():
    uris = [
        "relative/path",
@@ -7,12 +7,14 @@
 //! build type-safe filter / projection expressions that map directly to
 //! DataFusion [`Expr`] nodes, bypassing SQL string parsing.

+use std::ops::{Add, Div, Mul, Not, Sub};
+
 use arrow::{datatypes::DataType, pyarrow::PyArrowType};
 use datafusion_common::ScalarValue;
 use lancedb::expr::{
    DfExpr, col as ldb_col, contains, expr_cast, is_in, lit as df_lit, lower, upper,
 };
-use pyo3::types::PyBytes;
+use pyo3::types::{PyBytes, PyDate, PyDateTime};
 use pyo3::{Bound, PyAny, PyResult, exceptions::PyValueError, prelude::*, pyfunction};

 /// A type-safe DataFusion expression.
@@ -63,30 +65,30 @@ impl PyExpr {
        Self(self.0.clone().or(other.0.clone()))
    }

+    /// Logical NOT.
    fn not_(&self) -> Self {
-        use std::ops::Not;
        Self(self.0.clone().not())
    }

    // ── arithmetic ───────────────────────────────────────────────────────────

+    /// Add expressions.
    fn add(&self, other: &Self) -> Self {
-        use std::ops::Add;
        Self(self.0.clone().add(other.0.clone()))
    }

+    /// Subtract expressions.
    fn sub(&self, other: &Self) -> Self {
-        use std::ops::Sub;
        Self(self.0.clone().sub(other.0.clone()))
    }

+    /// Multiply expressions.
    fn mul(&self, other: &Self) -> Self {
-        use std::ops::Mul;
        Self(self.0.clone().mul(other.0.clone()))
    }

+    /// Divide expressions.
    fn div(&self, other: &Self) -> Self {
-        use std::ops::Div;
        Self(self.0.clone().div(other.0.clone()))
    }

@@ -153,7 +155,8 @@ pub fn expr_col(name: &str) -> PyExpr {

 /// Create a literal value expression.
 ///
-/// Supported Python types: `bool`, `int`, `float`, `str`, `bytes`.
+/// Supported Python types: `bool`, `int`, `float`, `str`, `bytes`, `date`,
+/// `datetime`, `Decimal`.
 #[pyfunction]
 pub fn expr_lit(value: Bound<'_, PyAny>) -> PyResult<PyExpr> {
    // bool must be checked before int because bool is a subclass of int in Python
@@ -163,6 +166,19 @@ pub fn expr_lit(value: Bound<'_, PyAny>) -> PyResult<PyExpr> {
    if let Ok(i) = value.extract::<i64>() {
        return Ok(PyExpr(df_lit(i)));
    }
+    // Decimal must be checked before f64: Python's Decimal implements __float__,
+    // so value.extract::<f64>() would succeed and silently truncate the value to
+    // f64, losing precision. Build a Decimal128 scalar to preserve it instead.
+    if value.get_type().name()? == "Decimal" {
+        let s = value.call_method0("__str__")?.extract::<String>()?;
+        // Parse the decimal string into an i128 value, precision, and scale.
+        let (val, precision, scale) = parse_decimal(&s)?;
+        return Ok(PyExpr(df_lit(ScalarValue::Decimal128(
+            Some(val),
+            precision,
+            scale,
+        ))));
+    }
    if let Ok(f) = value.extract::<f64>() {
        return Ok(PyExpr(df_lit(f)));
    }
@@ -173,12 +189,48 @@ pub fn expr_lit(value: Bound<'_, PyAny>) -> PyResult<PyExpr> {
        let bytes = value.extract::<Vec<u8>>()?;
        return Ok(PyExpr(df_lit(ScalarValue::Binary(Some(bytes)))));
    }
+
+    // datetime.datetime is a subclass of datetime.date, so it must be checked first.
+    if let Ok(dt) = value.cast::<PyDateTime>() {
+        let ts: f64 = dt.call_method0("timestamp")?.extract()?;
+        let micros = (ts * 1_000_000.0).round() as i64;
+        return Ok(PyExpr(df_lit(ScalarValue::TimestampMicrosecond(
+            Some(micros),
+            None,
+        ))));
+    }
+    if let Ok(d) = value.cast::<PyDate>() {
+        let ordinal: i32 = d.call_method0("toordinal")?.extract()?;
+        let days = ordinal - 719163; // Unix epoch is 1970-01-01
+        return Ok(PyExpr(df_lit(ScalarValue::Date32(Some(days)))));
+    }
+
    Err(PyValueError::new_err(format!(
-        "unsupported literal type: {}. Supported: bool, int, float, str, bytes",
+        "unsupported literal type: {}. Supported: bool, int, float, str, bytes, date, datetime, Decimal",
        value.get_type().name()?
    )))
 }

+fn parse_decimal(s: &str) -> PyResult<(i128, u8, i8)> {
+    let s = s.trim();
+    let dot_pos = s.find('.');
+    let scale = if let Some(pos) = dot_pos {
+        (s.len() - pos - 1) as i8
+    } else {
+        0
+    };
+
+    let digits = s.replace('.', "");
+    let val = digits
+        .parse::<i128>()
+        .map_err(|e| PyValueError::new_err(format!("failed to parse decimal digits: {}", e)))?;
+
+    // Precision is total number of digits
+    let precision = digits.trim_start_matches('-').len() as u8;
+
+    Ok((val, precision, scale))
+}
+
 /// Call an arbitrary registered SQL function by name.
 ///
 /// See `lancedb::expr::func` for the list of supported function names.
@@ -27,6 +27,7 @@ pub mod header;
 pub mod index;
 pub mod namespace;
 pub mod oauth;
+pub mod otel;
 pub mod permutation;
 pub mod query;
 pub mod runtime;
@@ -61,6 +62,15 @@ pub fn _lancedb(_py: Python, m: &Bound<'_, PyModule>) -> PyResult<()> {
    m.add_class::<PyAsyncPermutationBuilder>()?;
    m.add_class::<PyPermutationReader>()?;
    m.add_class::<PyExpr>()?;
+    // OpenTelemetry metrics bridge
+    m.add_class::<otel::PyMetricPoint>()?;
+    m.add_class::<otel::PyMetricDescription>()?;
+    m.add_function(wrap_pyfunction!(
+        otel::register_lancedb_metrics_recorder,
+        m
+    )?)?;
+    m.add_function(wrap_pyfunction!(otel::lancedb_metrics_catalog, m)?)?;
+    m.add_function(wrap_pyfunction!(otel::snapshot_lancedb_metrics, m)?)?;
    m.add_function(wrap_pyfunction!(connect, m)?)?;
    m.add_function(wrap_pyfunction!(connect_namespace, m)?)?;
    m.add_function(wrap_pyfunction!(connect_namespace_client, m)?)?;
@@ -0,0 +1,96 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+//! Python-facing wrappers over [`lancedb::metrics_otel`].
+//!
+//! The aggregation, catalog, and histogram bucketing all live in the LanceDB
+//! core crate; this module only converts the core snapshot types into PyO3
+//! classes and exposes the three entry points to Python, where
+//! `lancedb/otel.py` bridges them into the user's OpenTelemetry `MeterProvider`.
+
+use std::collections::HashMap;
+
+use lancedb::metrics_otel::{MetricPoint, MetricValue};
+use pyo3::prelude::*;
+
+/// One metric data point exposed to Python. For counters and gauges only
+/// `value` is set; for histograms `buckets` (cumulative `le` counts), `count`,
+/// and `sum` are set.
+#[pyclass(name = "MetricPoint", get_all)]
+pub struct PyMetricPoint {
+    name: String,
+    kind: String,
+    attributes: HashMap<String, String>,
+    value: Option<f64>,
+    buckets: Option<Vec<(String, u64)>>,
+    count: Option<u64>,
+    sum: Option<f64>,
+}
+
+impl From<MetricPoint> for PyMetricPoint {
+    fn from(point: MetricPoint) -> Self {
+        let kind = point.kind.as_str().to_string();
+        let (value, buckets, count, sum) = match point.value {
+            MetricValue::Scalar(v) => (Some(v), None, None, None),
+            MetricValue::Histogram {
+                buckets,
+                count,
+                sum,
+            } => (None, Some(buckets), Some(count), Some(sum)),
+        };
+        Self {
+            name: point.name,
+            kind,
+            attributes: point.attributes,
+            value,
+            buckets,
+            count,
+            sum,
+        }
+    }
+}
+
+/// A described metric, used by the Python layer to create instruments up front.
+#[pyclass(name = "MetricDescription", get_all)]
+pub struct PyMetricDescription {
+    name: String,
+    kind: String,
+    unit: Option<String>,
+    description: String,
+}
+
+/// Install the LanceDB metrics recorder as the process-global `metrics` recorder.
+///
+/// Returns `True` if the recorder is installed (now or previously). Returns
+/// `False` if a *different* recorder is already installed — `metrics` allows
+/// only one global recorder per process, so LanceDB cannot coexist with another.
+#[pyfunction]
+pub fn register_lancedb_metrics_recorder() -> bool {
+    lancedb::metrics_otel::register_metrics_recorder()
+}
+
+/// The catalog of described LanceDB metrics. Empty until the recorder is installed.
+#[pyfunction]
+pub fn lancedb_metrics_catalog() -> Vec<PyMetricDescription> {
+    lancedb::metrics_otel::metrics_catalog()
+        .into_iter()
+        .map(|desc| PyMetricDescription {
+            name: desc.name,
+            kind: desc.kind.as_str().to_string(),
+            unit: desc.unit,
+            description: desc.description,
+        })
+        .collect()
+}
+
+/// A point-in-time snapshot of every recorded metric. Empty until the recorder
+/// is installed.
+///
+/// The read is lock-free but not O(1): it walks every registered series and
+/// allocates owned copies of their names and labels. The GIL is released across
+/// that work so a periodic collection doesn't stall other Python threads.
+#[pyfunction]
+pub fn snapshot_lancedb_metrics(py: Python<'_>) -> Vec<PyMetricPoint> {
+    let points = py.detach(lancedb::metrics_otel::snapshot_metrics);
+    points.into_iter().map(PyMetricPoint::from).collect()
+}
@@ -79,13 +79,14 @@ impl PyAsyncPermutationBuilder {

 #[pymethods]
 impl PyAsyncPermutationBuilder {
-    #[pyo3(signature = (*, ratios=None, counts=None, fixed=None, seed=None, split_names=None))]
+    #[pyo3(signature = (*, ratios=None, counts=None, fixed=None, seed=None, clump_size=None, split_names=None))]
    pub fn split_random(
        slf: PyRefMut<'_, Self>,
        ratios: Option<Vec<f64>>,
        counts: Option<Vec<u64>>,
        fixed: Option<u64>,
        seed: Option<u64>,
+        clump_size: Option<u64>,
        split_names: Option<Vec<String>>,
    ) -> PyResult<Self> {
        // Check that exactly one split type is provided
@@ -111,7 +112,14 @@ impl PyAsyncPermutationBuilder {
        };

        slf.modify(|builder| {
-            builder.with_split_strategy(SplitStrategy::Random { seed, sizes }, split_names)
+            builder.with_split_strategy(
+                SplitStrategy::Random {
+                    seed,
+                    sizes,
+                    clump_size,
+                },
+                split_names,
+            )
        })
    }

@@ -322,6 +322,12 @@ impl From<LsmWriteSpec> for lancedb::table::LsmWriteSpec {
    }
 }

+impl From<lancedb::table::LsmWriteSpec> for LsmWriteSpec {
+    fn from(inner: lancedb::table::LsmWriteSpec) -> Self {
+        Self { inner }
+    }
+}
+
 #[pyclass(get_all, from_py_object)]
 #[derive(Clone, Debug)]
 pub struct AddColumnsResult {
@@ -1029,6 +1035,14 @@ impl Table {
        })
    }

+    pub fn get_lsm_write_spec(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
+        let inner = self_.inner_ref()?.clone();
+        future_into_py(self_.py(), async move {
+            let spec = inner.get_lsm_write_spec().await.infer_error()?;
+            Ok(spec.map(LsmWriteSpec::from))
+        })
+    }
+
    pub fn close_lsm_writers(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
        let inner = self_.inner_ref()?.clone();
        future_into_py(self_.py(), async move {
@@ -0,0 +1,101 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+import lancedb
+import pyarrow as pa
+import pytest
+
+# The metrics recorder is process-global and installed once, so the whole
+# bridge is exercised in a single test to avoid cross-test global-state coupling.
+
+
+def _metrics_by_name(reader):
+    data = reader.get_metrics_data()
+    result = {}
+    for resource_metrics in data.resource_metrics:
+        for scope_metrics in resource_metrics.scope_metrics:
+            for metric in scope_metrics.metrics:
+                result[metric.name] = metric
+    return result
+
+
+def test_instrument_lancedb_metrics_exports_object_store_metrics(tmp_path):
+    pytest.importorskip("opentelemetry.sdk.metrics")
+    from lancedb.otel import instrument_lancedb_metrics
+    from opentelemetry.sdk.metrics import MeterProvider
+    from opentelemetry.sdk.metrics.export import InMemoryMetricReader
+
+    reader = InMemoryMetricReader()
+    provider = MeterProvider(metric_readers=[reader])
+    assert instrument_lancedb_metrics(provider)
+
+    # The catalog is populated once the recorder is installed.
+    from lancedb._lancedb import lancedb_metrics_catalog
+
+    catalog = {desc.name: desc for desc in lancedb_metrics_catalog()}
+    # Every metric kind emitted by the object store must be described so it is
+    # surfaced by the bridge (counter, histogram, and gauge).
+    assert catalog["lance_object_store_requests_total"].kind == "counter"
+    assert catalog["lance_object_store_request_duration_seconds"].kind == "histogram"
+    assert catalog["lance_object_store_in_flight_requests"].kind == "gauge"
+    assert catalog["lance_object_store_retryable_responses_total"].kind == "counter"
+
+    # Generate object store activity on the local filesystem (scheme "file").
+    db = lancedb.connect(str(tmp_path))
+    table = db.create_table("t", pa.table({"id": pa.array(range(256))}))
+    assert table.count_rows() == 256
+    assert table.to_arrow().num_rows == 256
+
+    metrics = _metrics_by_name(reader)
+
+    requests = metrics["lance_object_store_requests_total"]
+    points = list(requests.data.data_points)
+    assert points, "expected at least one request data point"
+    # Object store metrics are labelled by `operation` and `base` (the store
+    # scheme, e.g. "file", by default).
+    assert all("base" in p.attributes and "operation" in p.attributes for p in points)
+    assert sum(p.value for p in points) > 0
+
+    # Histograms are decomposed into bucket / count / sum observable counters.
+    bucket = metrics["lance_object_store_request_duration_seconds_bucket"]
+    bucket_points = list(bucket.data.data_points)
+    assert bucket_points
+    assert all("le" in p.attributes for p in bucket_points)
+    # The implicit +Inf bucket must be present and is the cumulative maximum.
+    assert any(p.attributes["le"] == "+Inf" for p in bucket_points)
+
+    count = metrics["lance_object_store_request_duration_seconds_count"]
+    assert sum(p.value for p in count.data.data_points) > 0
+
+    # The `_sum` instrument must also be wired and report positive latency.
+    duration_sum = metrics["lance_object_store_request_duration_seconds_sum"]
+    assert sum(p.value for p in duration_sum.data.data_points) > 0
+
+    # Unit handling: only `_sum` keeps the histogram's unit (seconds); `_bucket`
+    # and `_count` observe cumulative counts and are unitless.
+    assert duration_sum.unit == "s"
+    assert bucket.unit == ""
+    assert count.unit == ""
+
+
+def test_snapshot_empty_before_install_is_safe():
+    # snapshot is callable regardless of installation state and never raises.
+    from lancedb._lancedb import snapshot_lancedb_metrics
+
+    assert isinstance(snapshot_lancedb_metrics(), list)
+
+
+def test_instrument_warns_when_recorder_unavailable(monkeypatch):
+    # A foreign `metrics` recorder already installed -> register returns False;
+    # instrument_lancedb_metrics must warn and return False without instrumenting.
+    pytest.importorskip("opentelemetry.sdk.metrics")
+    import lancedb.otel as otel
+    from opentelemetry.sdk.metrics import MeterProvider
+    from opentelemetry.sdk.metrics.export import InMemoryMetricReader
+
+    monkeypatch.setattr(otel, "register_lancedb_metrics_recorder", lambda: False)
+
+    reader = InMemoryMetricReader()
+    provider = MeterProvider(metric_readers=[reader])
+    with pytest.warns(UserWarning, match="recorder"):
+        assert otel.instrument_lancedb_metrics(provider) is False
@@ -780,7 +780,7 @@ name = "cuda-bindings"
 version = "13.3.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "cuda-pathfinder" },
+    { name = "cuda-pathfinder", marker = "(python_full_version < '3.14' and sys_platform == 'emscripten') or (python_full_version < '3.14' and sys_platform == 'win32') or (sys_platform != 'emscripten' and sys_platform != 'win32')" },
 ]
 wheels = [
    { url = "https://files.pythonhosted.org/packages/a9/21/8464d133752951c154feafb3b65c297e7d80f301183d220bec4c830f1441/cuda_bindings-13.3.1-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:120fcc53d57903df529c3486962c56528cba5b7d6c57c99537320ed9922c8b86", size = 6073403, upload-time = "2026-05-29T23:11:36.22Z" },
@@ -815,37 +815,37 @@ wheels = [

 [package.optional-dependencies]
 cublas = [
-    { name = "nvidia-cublas", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cublas", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
 ]
 cudart = [
-    { name = "nvidia-cuda-runtime", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cuda-runtime", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
 ]
 cufft = [
-    { name = "nvidia-cufft", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cufft", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
 ]
 cufile = [
    { name = "nvidia-cufile", marker = "sys_platform == 'linux'" },
 ]
 cupti = [
-    { name = "nvidia-cuda-cupti", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cuda-cupti", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
 ]
 curand = [
-    { name = "nvidia-curand", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-curand", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
 ]
 cusolver = [
-    { name = "nvidia-cusolver", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cusolver", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
 ]
 cusparse = [
-    { name = "nvidia-cusparse", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cusparse", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
 ]
 nvjitlink = [
-    { name = "nvidia-nvjitlink", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-nvjitlink", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
 ]
 nvrtc = [
-    { name = "nvidia-cuda-nvrtc", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-cuda-nvrtc", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
 ]
 nvtx = [
-    { name = "nvidia-nvtx", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
+    { name = "nvidia-nvtx", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
 ]

 [[package]]
@@ -1909,6 +1909,9 @@ embeddings = [
    { name = "sentencepiece" },
    { name = "torch" },
 ]
+otel = [
+    { name = "opentelemetry-api" },
+]
 pylance = [
    { name = "pylance" },
 ]
@@ -1923,6 +1926,7 @@ tests = [
    { name = "boto3" },
    { name = "datafusion" },
    { name = "duckdb" },
+    { name = "opentelemetry-sdk" },
    { name = "pandas", version = "2.2.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
    { name = "pandas", version = "2.3.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11' and python_full_version < '3.14'" },
    { name = "pandas", version = "3.0.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.14'" },
@@ -1963,6 +1967,8 @@ requires-dist = [
    { name = "open-clip-torch", marker = "extra == 'clip'" },
    { name = "open-clip-torch", marker = "extra == 'embeddings'", specifier = ">=2.20.0" },
    { name = "openai", marker = "extra == 'embeddings'", specifier = ">=1.6.1" },
+    { name = "opentelemetry-api", marker = "extra == 'otel'" },
+    { name = "opentelemetry-sdk", marker = "extra == 'tests'", specifier = ">=1.30.0" },
    { name = "overrides", marker = "python_full_version < '3.12'", specifier = ">=0.7" },
    { name = "packaging", specifier = ">=23.0" },
    { name = "pandas", marker = "extra == 'tests'", specifier = ">=1.4" },
@@ -1994,7 +2000,7 @@ requires-dist = [
    { name = "transformers", marker = "extra == 'siglip'", specifier = ">=4.41.0" },
    { name = "typing-extensions", marker = "python_full_version < '3.11' and extra == 'dev'", specifier = ">=4.0.0" },
 ]
-provides-extras = ["azure", "clip", "dev", "docs", "embeddings", "pylance", "siglip", "tests"]
+provides-extras = ["azure", "clip", "dev", "docs", "embeddings", "otel", "pylance", "siglip", "tests"]

 [[package]]
 name = "lomond"
@@ -2775,7 +2781,7 @@ name = "nvidia-cudnn-cu13"
 version = "9.19.0.56"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-cublas" },
+    { name = "nvidia-cublas", marker = "(python_full_version < '3.14' and sys_platform == 'emscripten') or (python_full_version < '3.14' and sys_platform == 'win32') or (sys_platform != 'emscripten' and sys_platform != 'win32')" },
 ]
 wheels = [
    { url = "https://files.pythonhosted.org/packages/f1/84/26025437c1e6b61a707442184fa0c03d083b661adf3a3eecfd6d21677740/nvidia_cudnn_cu13-9.19.0.56-py3-none-manylinux_2_27_aarch64.whl", hash = "sha256:6ed29ffaee1176c612daf442e4dd6cfeb6a0caa43ddcbeb59da94953030b1be4", size = 433781201, upload-time = "2026-02-03T20:40:53.805Z" },
@@ -2787,7 +2793,7 @@ name = "nvidia-cufft"
 version = "12.0.0.61"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-nvjitlink" },
+    { name = "nvidia-nvjitlink", marker = "(python_full_version < '3.14' and sys_platform == 'emscripten') or (python_full_version < '3.14' and sys_platform == 'win32') or (sys_platform != 'emscripten' and sys_platform != 'win32')" },
 ]
 wheels = [
    { url = "https://files.pythonhosted.org/packages/8b/ae/f417a75c0259e85c1d2f83ca4e960289a5f814ed0cea74d18c353d3e989d/nvidia_cufft-12.0.0.61-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:2708c852ef8cd89d1d2068bdbece0aa188813a0c934db3779b9b1faa8442e5f5", size = 214053554, upload-time = "2025-09-04T08:31:38.196Z" },
@@ -2817,9 +2823,9 @@ name = "nvidia-cusolver"
 version = "12.0.4.66"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-cublas" },
-    { name = "nvidia-cusparse" },
-    { name = "nvidia-nvjitlink" },
+    { name = "nvidia-cublas", marker = "(python_full_version < '3.14' and sys_platform == 'emscripten') or (python_full_version < '3.14' and sys_platform == 'win32') or (sys_platform != 'emscripten' and sys_platform != 'win32')" },
+    { name = "nvidia-cusparse", marker = "(python_full_version < '3.14' and sys_platform == 'emscripten') or (python_full_version < '3.14' and sys_platform == 'win32') or (sys_platform != 'emscripten' and sys_platform != 'win32')" },
+    { name = "nvidia-nvjitlink", marker = "(python_full_version < '3.14' and sys_platform == 'emscripten') or (python_full_version < '3.14' and sys_platform == 'win32') or (sys_platform != 'emscripten' and sys_platform != 'win32')" },
 ]
 wheels = [
    { url = "https://files.pythonhosted.org/packages/c8/c3/b30c9e935fc01e3da443ec0116ed1b2a009bb867f5324d3f2d7e533e776b/nvidia_cusolver-12.0.4.66-py3-none-manylinux_2_27_aarch64.whl", hash = "sha256:02c2457eaa9e39de20f880f4bd8820e6a1cfb9f9a34f820eb12a155aa5bc92d2", size = 223467760, upload-time = "2025-09-04T08:33:04.222Z" },
@@ -2831,7 +2837,7 @@ name = "nvidia-cusparse"
 version = "12.6.3.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-nvjitlink" },
+    { name = "nvidia-nvjitlink", marker = "(python_full_version < '3.14' and sys_platform == 'emscripten') or (python_full_version < '3.14' and sys_platform == 'win32') or (sys_platform != 'emscripten' and sys_platform != 'win32')" },
 ]
 wheels = [
    { url = "https://files.pythonhosted.org/packages/f8/94/5c26f33738ae35276672f12615a64bd008ed5be6d1ebcb23579285d960a9/nvidia_cusparse-12.6.3.3-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:80bcc4662f23f1054ee334a15c72b8940402975e0eab63178fc7e670aa59472c", size = 162155568, upload-time = "2025-09-04T08:33:42.864Z" },
@@ -2934,6 +2940,45 @@ wheels = [
    { url = "https://files.pythonhosted.org/packages/f6/46/180e14be801a75bc13f234cb1b594b232adeb9c84e60a9ab1832e8333591/openai-2.40.0-py3-none-any.whl", hash = "sha256:2b205637ff214477f9ce9ab035e9f494db0e3fa8f1e599008953735fbf6ff1ff", size = 1350935, upload-time = "2026-06-01T21:48:21.462Z" },
 ]

+[[package]]
+name = "opentelemetry-api"
+version = "1.43.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ae/cc/e4c9584181f86494df0f6bdec1a4f3280c50db44704dc2a407e994fc87bb/opentelemetry_api-1.43.0.tar.gz", hash = "sha256:107d0d03857ea8fc7c5fcbbbd83f800c281f0d560553d61c1d675fccfd1761c1", size = 73476, upload-time = "2026-06-24T15:19:55.323Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/17/83/6dba32b85f31868400440dc7ad2ca1eab94cbbf3a7b0459ed39f8311a9e2/opentelemetry_api-1.43.0-py3-none-any.whl", hash = "sha256:20acf45e9b21851926835292e4045d290acade1edd2ff3de86d2f069687ba1fd", size = 61912, upload-time = "2026-06-24T15:19:35.434Z" },
+]
+
+[[package]]
+name = "opentelemetry-sdk"
+version = "1.43.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "opentelemetry-api" },
+    { name = "opentelemetry-semantic-conventions" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/3e/eb/5041074274ac0956b03637cc039d434569112468e875eddfcc9a0674ce06/opentelemetry_sdk-1.43.0.tar.gz", hash = "sha256:d8187c81c162df9913e4003dd6485f7390d9a24fc17026ec7387b8b8218b08e9", size = 254744, upload-time = "2026-06-24T15:20:08.467Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/49/e3/b17be23af124201c9f52eececd4cc8ddfed1597d37b4ee771895d325805c/opentelemetry_sdk-1.43.0-py3-none-any.whl", hash = "sha256:d1323a547c1ce69d6a069a17a44b7da82bb8b332051ecb074041f87642c86823", size = 178852, upload-time = "2026-06-24T15:19:52.169Z" },
+]
+
+[[package]]
+name = "opentelemetry-semantic-conventions"
+version = "0.64b0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "opentelemetry-api" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/5a/30/5f26df29509eccd86b99b481ac9ffa39da49ba9577cc69071c552ae30447/opentelemetry_semantic_conventions-0.64b0.tar.gz", hash = "sha256:72f76fb2d1582d9d033dd1fcd84532e961e6ff3d90d24ba6fabc72975a83864c", size = 148340, upload-time = "2026-06-24T15:20:09.267Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/f2/ca/23ba87a221b574a7c5a99d48849d80bfe8b047624681357e2b002e566187/opentelemetry_semantic_conventions-0.64b0-py3-none-any.whl", hash = "sha256:ea77e85e354b8f604ddbe5f3d9135216f982fa4d77e5859ac30f6d8a50505aa6", size = 203713, upload-time = "2026-06-24T15:19:53.339Z" },
+]
+
 [[package]]
 name = "overrides"
 version = "7.7.0"
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.31.0-beta.5"
+version = "0.32.0-beta.0"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true
@@ -49,6 +49,8 @@ lance-encoding = { workspace = true }
 lance-arrow = { workspace = true }
 lance-namespace = { workspace = true }
 lance-namespace-impls = { workspace = true }
+metrics = { workspace = true, optional = true }
+metrics-util = { workspace = true, optional = true }
 moka = { workspace = true }
 pin-project = { workspace = true }
 tokio = { version = "1.23", features = ["rt-multi-thread", "sync"] }
@@ -108,6 +110,8 @@ http-body = "1"                                        # Matching reqwest
 rstest = "0.23.0"
 test-log = "0.2"
 serial_test = "3"
+[target.'cfg(unix)'.dev-dependencies]
+pprof = { version = "0.14", features = ["flamegraph"] }


 [features]
@@ -126,6 +130,12 @@ azure = [
    "lance-namespace-impls/dir-azure",
    "lance-namespace-impls/credential-vendor-azure",
 ]
+cos = ["lance/tencent", "lance-io/tencent"]
+goosefs = [
+    "lance/goosefs",
+    "lance-io/goosefs",
+    "lance-namespace-impls/dir-goosefs",
+]
 huggingface = [
    "lance/huggingface",
    "lance-io/huggingface",
@@ -139,6 +149,15 @@ remote = [
    "lance-namespace-impls/rest",
    "lance-namespace-impls/rest-adapter",
 ]
+# Publish LanceDB's internal metrics (currently object store request counts,
+# bytes, latency, errors, and throttles) through the `metrics` crate facade,
+# and re-export the `metrics` crate as `lancedb::metrics`. Install any
+# `metrics`-compatible recorder to collect them.
+metrics = ["dep:metrics", "lance/metrics", "lance-io/metrics"]
+# Additional adapter on top of `metrics` that installs a process-global recorder
+# and exposes a pull-based snapshot/catalog API (see `lancedb::metrics_otel`)
+# for bridging metrics into OpenTelemetry or other pull-based exporters.
+metrics-otel = ["metrics", "dep:metrics-util"]
 fp16kernels = ["lance-linalg/fp16kernels"]
 s3-test = []
 bedrock = ["dep:aws-sdk-bedrockruntime"]
@@ -164,6 +183,9 @@ required-features = ["sentence-transformers"]
 name = "bedrock"
 required-features = ["bedrock"]

+[[example]]
+name = "bench_streaming_dataloader"
+
 [[example]]
 name = "simple"

@@ -0,0 +1,272 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+//! Benchmark + CPU profiler for the PermutationReader used by the elastic
+//! streaming dataloader.
+//!
+//! Normal sweep:
+//!   cargo run --release --example bench_streaming_dataloader
+//!
+//! Flamegraph (self-contained, no perf/dtrace needed):
+//!   BENCH_PROFILE=1 BENCH_CHUNK=64 cargo run --release \
+//!       --example bench_streaming_dataloader
+//!   # writes flamegraph.svg in the current directory
+//!
+//! Environment variables:
+//!   BENCH_NUM_ROWS   – total rows (default 49152 = 24 × 2048)
+//!   BENCH_NUM_SPLITS – number of splits (default 24)
+//!   BENCH_STEPS      – round-robin cycles per chunk-size trial (default 200)
+//!   BENCH_ROW_BYTES  – bytes of payload per row (default 4096)
+//!   BENCH_CHUNK      – restrict sweep to this single chunk size
+//!   BENCH_PROFILE    – if set to "1", capture a pprof flamegraph SVG
+
+use std::{sync::Arc, time::Instant};
+
+use arrow_array::{Int32Array, LargeBinaryArray, RecordBatch};
+use arrow_schema::{DataType, Field, Schema};
+use lancedb::{
+    Result, Table,
+    arrow::{SendableRecordBatchStream, SimpleRecordBatchStream},
+    connect,
+    dataloader::permutation::{
+        builder::{PermutationBuilder, ShuffleStrategy},
+        reader::PermutationReader,
+        split::{SplitSizes, SplitStrategy},
+    },
+    query::Select,
+};
+
+fn env_usize(key: &str, default: usize) -> usize {
+    std::env::var(key)
+        .ok()
+        .and_then(|v| v.parse().ok())
+        .unwrap_or(default)
+}
+
+// ---------------------------------------------------------------------------
+// Table creation
+// ---------------------------------------------------------------------------
+
+async fn make_base_table(num_rows: usize, row_bytes: usize) -> Result<Table> {
+    let schema = Arc::new(Schema::new(vec![
+        Field::new("id", DataType::Int32, false),
+        Field::new("payload", DataType::LargeBinary, false),
+    ]));
+    let payload = vec![0u8; row_bytes];
+    let ids: Int32Array = (0..num_rows as i32).collect();
+    let payloads: LargeBinaryArray = (0..num_rows).map(|_| Some(payload.as_slice())).collect();
+    let batch = RecordBatch::try_new(schema.clone(), vec![Arc::new(ids), Arc::new(payloads)])?;
+    let stream: SendableRecordBatchStream = Box::pin(SimpleRecordBatchStream::new(
+        futures::stream::once(std::future::ready(Ok(batch))),
+        schema,
+    ));
+    let db = connect("memory:///").execute().await?;
+    db.create_table("base", stream).execute().await
+}
+
+async fn make_permutation_table(base: &Table, num_splits: usize) -> Result<Table> {
+    PermutationBuilder::new(base.clone())
+        .with_split_strategy(
+            SplitStrategy::Random {
+                seed: Some(42),
+                sizes: SplitSizes::Fixed(num_splits as u64),
+                clump_size: None,
+            },
+            None,
+        )
+        .with_shuffle_strategy(ShuffleStrategy::Random {
+            seed: Some(42),
+            clump_size: None,
+        })
+        .build()
+        .await
+}
+
+// ---------------------------------------------------------------------------
+// Round-robin hot loop (mirrors StreamingDataset.__iter__)
+// ---------------------------------------------------------------------------
+
+async fn run_hot_loop(
+    readers: &[PermutationReader],
+    chunk_size: usize,
+    steps: usize,
+) -> Result<(usize, f64)> {
+    let n = readers.len();
+    let split_sizes: Vec<usize> = readers.iter().map(|r| r.count_rows() as usize).collect();
+
+    struct SplitBuf {
+        batch: Option<RecordBatch>,
+        row_in_batch: usize,
+        consumed: usize,
+    }
+    let mut bufs: Vec<SplitBuf> = (0..n)
+        .map(|_| SplitBuf {
+            batch: None,
+            row_in_batch: 0,
+            consumed: 0,
+        })
+        .collect();
+
+    // Pre-fill
+    for i in 0..n {
+        let fetch = chunk_size.min(split_sizes[i]);
+        if fetch > 0 {
+            let offsets: Vec<u64> = (0..fetch as u64).collect();
+            bufs[i].batch = Some(readers[i].take_offsets(&offsets, Select::All).await?);
+        }
+    }
+
+    let mut total_rows = 0usize;
+    let t0 = Instant::now();
+
+    'outer: for _step in 0..steps {
+        for i in 0..n {
+            if bufs[i].consumed >= split_sizes[i] {
+                break 'outer;
+            }
+            let need_refill = bufs[i]
+                .batch
+                .as_ref()
+                .map(|b| bufs[i].row_in_batch >= b.num_rows())
+                .unwrap_or(true);
+            if need_refill {
+                let start = bufs[i].consumed as u64;
+                let remaining = (split_sizes[i] - bufs[i].consumed) as u64;
+                let fetch = chunk_size.min(remaining as usize);
+                let offsets: Vec<u64> = (start..start + fetch as u64).collect();
+                bufs[i].batch = Some(readers[i].take_offsets(&offsets, Select::All).await?);
+                bufs[i].row_in_batch = 0;
+            }
+            bufs[i].row_in_batch += 1;
+            bufs[i].consumed += 1;
+            total_rows += 1;
+        }
+    }
+
+    Ok((total_rows, t0.elapsed().as_secs_f64()))
+}
+
+// ---------------------------------------------------------------------------
+// Main
+// ---------------------------------------------------------------------------
+
+#[tokio::main]
+async fn main() -> Result<()> {
+    let num_splits = env_usize("BENCH_NUM_SPLITS", 24);
+    let num_rows = env_usize("BENCH_NUM_ROWS", num_splits * 2048);
+    let steps = env_usize("BENCH_STEPS", 200);
+    let row_bytes = env_usize("BENCH_ROW_BYTES", 4096);
+    let single_chunk: Option<usize> = std::env::var("BENCH_CHUNK")
+        .ok()
+        .and_then(|v| v.parse().ok());
+    let do_profile = std::env::var("BENCH_PROFILE")
+        .map(|v| v == "1")
+        .unwrap_or(false);
+
+    assert_eq!(
+        num_rows % num_splits,
+        0,
+        "NUM_ROWS must be divisible by NUM_SPLITS"
+    );
+
+    println!("Benchmark config:");
+    println!(
+        "  num_rows={}  num_splits={}  rows/split={}  steps={}  row_bytes={}",
+        num_rows,
+        num_splits,
+        num_rows / num_splits,
+        steps,
+        row_bytes,
+    );
+    println!(
+        "  ~{:.1} MB total",
+        (num_rows * row_bytes) as f64 / (1024.0 * 1024.0)
+    );
+    println!();
+
+    print!("Building base table... ");
+    let _ = std::io::Write::flush(&mut std::io::stdout());
+    let base = make_base_table(num_rows, row_bytes).await?;
+    println!("done");
+
+    print!("Building permutation table... ");
+    let _ = std::io::Write::flush(&mut std::io::stdout());
+    let perm = make_permutation_table(&base, num_splits).await?;
+    println!("done");
+
+    print!("Building {} PermutationReaders... ", num_splits);
+    let _ = std::io::Write::flush(&mut std::io::stdout());
+    let base_inner = base.base_table().clone();
+    let perm_inner = perm.base_table().clone();
+    let mut readers = Vec::with_capacity(num_splits);
+    for split in 0..num_splits {
+        readers.push(
+            PermutationReader::try_from_tables(
+                base_inner.clone(),
+                perm_inner.clone(),
+                split as u64,
+            )
+            .await?,
+        );
+    }
+    println!("done ({} rows/split)", readers[0].count_rows());
+    println!();
+
+    let chunk_sizes: Vec<usize> = if let Some(c) = single_chunk {
+        vec![c]
+    } else {
+        vec![1, 4, 16, 64, 256, 1024, 4096, 16384]
+    };
+
+    if do_profile {
+        #[cfg(unix)]
+        {
+            let chunk = chunk_sizes[0];
+            println!("Profiling chunk={chunk} for {steps} steps...");
+            // Warm-up outside the profiler window
+            let _ = run_hot_loop(&readers, chunk, 1).await?;
+
+            let guard = pprof::ProfilerGuardBuilder::default()
+                .frequency(1000)
+                .build()
+                .unwrap();
+
+            let (rows, elapsed) = run_hot_loop(&readers, chunk, steps).await?;
+
+            if let Ok(report) = guard.report().build() {
+                let svg_path = "flamegraph.svg";
+                let file = std::fs::File::create(svg_path).unwrap();
+                report.flamegraph(file).unwrap();
+                println!("Flamegraph written to {svg_path}");
+            }
+
+            let rows_per_sec = rows as f64 / elapsed;
+            println!("chunk={chunk}  {rows} rows  {elapsed:.3}s  {rows_per_sec:.0} rows/s");
+        }
+        #[cfg(not(unix))]
+        {
+            println!("Flamegraph profiling (BENCH_PROFILE=1) is not supported on this platform.");
+            println!("Run without BENCH_PROFILE to get throughput numbers.");
+        }
+    } else {
+        println!(
+            "{:>6}  {:>7}  {:>8}  {:>11}  {:>10}",
+            "chunk", "rows", "elapsed", "rows/s", "ms/step"
+        );
+        println!("{}", "-".repeat(52));
+
+        for &chunk in &chunk_sizes {
+            let _ = run_hot_loop(&readers, chunk, 1).await?;
+            let (rows, elapsed) = run_hot_loop(&readers, chunk, steps).await?;
+            let rows_per_sec = rows as f64 / elapsed;
+            let ms_per_step = elapsed / steps as f64 * 1000.0;
+            println!(
+                "{:>6}  {:>7}  {:>7.3}s  {:>11.0}  {:>9.1}ms",
+                chunk, rows, elapsed, rows_per_sec, ms_per_step,
+            );
+        }
+    }
+
+    println!("\nDone.");
+    Ok(())
+}
@@ -342,6 +342,19 @@ impl ListingDatabase {
        ))
    }

+    fn storage_base_uri(uri: &str) -> String {
+        let Ok(mut url) = url::Url::parse(uri) else {
+            return uri.to_string();
+        };
+        url.set_query(None);
+        let Some((storage_scheme, _commit_scheme)) = url.scheme().split_once('+') else {
+            return url.to_string();
+        };
+        let storage_scheme = storage_scheme.to_string();
+        let _ = url.set_scheme(&storage_scheme);
+        url.to_string()
+    }
+
    async fn prepare_namespace_root(
        uri: &str,
        storage_options: &HashMap<String, String>,
@@ -520,6 +533,8 @@ impl ListingDatabase {
                // will add a trailing '?' to the url
                url.set_query(None);

+                let storage_base_uri = Self::storage_base_uri(url.as_str());
+
                let table_base_uri = if let Some(store) = engine {
                    static WARN_ONCE: std::sync::Once = std::sync::Once::new();
                    WARN_ONCE.call_once(|| {
@@ -532,8 +547,6 @@ impl ListingDatabase {
                    url.to_string()
                };

-                let plain_uri = url.to_string();
-
                let session = request
                    .session
                    .clone()
@@ -550,13 +563,13 @@ impl ListingDatabase {
                };
                let (object_store, base_path) = ObjectStore::from_uri_and_params(
                    session.store_registry(),
-                    &plain_uri,
+                    &storage_base_uri,
                    &os_params,
                )
                .await?;
                if object_store.is_local() {
-                    Self::try_create_dir(&plain_uri).context(CreateDirSnafu {
-                        path: plain_uri.clone(),
+                    Self::try_create_dir(&storage_base_uri).context(CreateDirSnafu {
+                        path: storage_base_uri.clone(),
                    })?;
                }

@@ -570,7 +583,7 @@ impl ListingDatabase {
                };

                let namespace_database = Self::connect_namespace_database(
-                    &table_base_uri,
+                    &storage_base_uri,
                    options.storage_options.clone(),
                    request.namespace_client_properties.clone(),
                    request.read_consistency_interval,
@@ -1309,6 +1322,60 @@ mod tests {
        (tempdir, db)
    }

+    #[tokio::test]
+    async fn test_listing_database_root_ops_do_not_create_manifest() {
+        let tempdir = tempdir().unwrap();
+        let uri = tempdir.path().to_str().unwrap();
+
+        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: None,
+        };
+
+        let db = ListingDatabase::connect_with_options(&request)
+            .await
+            .unwrap();
+
+        assert!(!tempdir.path().join("__manifest").exists());
+
+        let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
+        db.create_table(CreateTableRequest {
+            name: "root_table".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();
+
+        db.open_table(OpenTableRequest {
+            name: "root_table".to_string(),
+            namespace_path: vec![],
+            index_cache_size: None,
+            lance_read_params: None,
+            location: None,
+            namespace_client: None,
+            managed_versioning: None,
+        })
+        .await
+        .unwrap();
+
+        #[allow(deprecated)]
+        let table_names = db.table_names(TableNamesRequest::default()).await.unwrap();
+
+        assert_eq!(table_names, vec!["root_table".to_string()]);
+        assert!(!tempdir.path().join("__manifest").exists());
+    }
+
    #[tokio::test]
    async fn test_clone_table_basic() {
        let (_tempdir, db) = setup_database().await;
@@ -2283,6 +2350,24 @@ mod tests {
        assert_eq!(captured.as_deref(), Some("foo=bar"));
    }

+    #[test]
+    fn test_storage_base_uri_strips_commit_engine_scheme() {
+        assert_eq!(
+            ListingDatabase::storage_base_uri("s3+ddb://bucket/prefix?ddbTableName=commit_table"),
+            "s3://bucket/prefix"
+        );
+
+        assert_eq!(
+            ListingDatabase::storage_base_uri("s3://bucket/prefix?foo=bar"),
+            "s3://bucket/prefix"
+        );
+
+        assert_eq!(
+            ListingDatabase::storage_base_uri("/tmp/lancedb"),
+            "/tmp/lancedb"
+        );
+    }
+
    /// Regression: connecting via a URL-style URI (which goes through
    /// `url::Url::parse` and the `query_pairs_mut()` path) must not
    /// append a trailing `?` to per-table URIs when the input URI has
@@ -391,6 +391,7 @@ mod tests {
                SplitStrategy::Random {
                    seed: Some(42),
                    sizes: SplitSizes::Percentages(vec![0.05, 0.30]),
+                    clump_size: None,
                },
                None,
            )
@@ -21,6 +21,7 @@ use arrow::compute::concat_batches;
 use arrow::datatypes::UInt64Type;
 use arrow_array::{RecordBatch, UInt64Array};
 use arrow_schema::SchemaRef;
+use datafusion_expr::{Expr, col, lit};
 use futures::{StreamExt, TryStreamExt};
 use lance::dataset::scanner::DatasetRecordBatchStream;
 use lance::io::RecordBatchStream;
@@ -196,17 +197,10 @@ impl PermutationReader {
            .expect_ok()?
            .values();

-        let filter = format!(
-            "_rowid in ({})",
-            row_ids
-                .iter()
-                .map(|o| o.to_string())
-                .collect::<Vec<_>>()
-                .join(",")
-        );
+        let in_list: Vec<Expr> = row_ids.iter().map(|id| lit(*id)).collect();

        let base_query = QueryRequest {
-            filter: Some(QueryFilter::Sql(filter)),
+            filter: Some(QueryFilter::Datafusion(col(ROW_ID).in_list(in_list, false))),
            select: selection,
            with_row_id: true,
            ..Default::default()
@@ -35,9 +35,13 @@ pub enum SplitStrategy {
    /// Rows will be randomly assigned to splits
    ///
    /// A seed can be provided to make the assignment deterministic.
+    ///
+    /// A clump_size can be provided to shuffle contiguous groups of rows together,
+    /// preserving I/O locality while still randomising the split assignment.
    Random {
        seed: Option<u64>,
        sizes: SplitSizes,
+        clump_size: Option<u64>,
    },
    /// Rows will be assigned to splits based on the values in the specified columns.
    ///
@@ -323,13 +327,17 @@ impl Splitter {
                self.apply_sequential(source, num_rows, &SplitSizes::Counts(vec![num_rows]))
                    .await
            }
-            SplitStrategy::Random { seed, sizes } => {
+            SplitStrategy::Random {
+                seed,
+                sizes,
+                clump_size,
+            } => {
                let shuffler = Shuffler::new(ShufflerConfig {
                    seed: *seed,
                    // In this case we are only shuffling row ids so we can use a large max_rows_per_file
                    max_rows_per_file: 10 * 1024 * 1024,
                    temp_dir: self.temp_dir.clone(),
-                    clump_size: None,
+                    clump_size: *clump_size,
                });

                let shuffled = shuffler.shuffle(source, num_rows).await?;
@@ -692,6 +700,7 @@ mod tests {
            SplitStrategy::Random {
                seed: Some(42),
                sizes: SplitSizes::Fixed(3),
+                clump_size: None,
            },
        );

@@ -718,6 +727,7 @@ mod tests {
            SplitStrategy::Random {
                seed: Some(42),
                sizes: SplitSizes::Counts(vec![5, 15, 10]),
+                clump_size: None,
            },
        );

@@ -744,6 +754,7 @@ mod tests {
            SplitStrategy::Random {
                seed: Some(42),
                sizes: SplitSizes::Percentages(vec![0.217, 0.168, 0.17]),
+                clump_size: None,
            },
        );

@@ -33,6 +33,11 @@
 //! - `remote` - Enable remote client to connect to LanceDB cloud.
 //! - `huggingface` - Enable HuggingFace Hub integration for loading datasets from the Hub.
 //! - `fp16kernels` - Enable FP16 kernels for faster vector search on CPU.
+//! - `metrics` - Publish LanceDB's internal metrics through the
+//!   [`metrics`](https://docs.rs/metrics) crate facade and re-export that crate.
+//!   Install any `metrics`-compatible recorder to collect them.
+//! - `metrics-otel` - Add a pull-based adapter (the `metrics_otel` module) over
+//!   the `metrics` facade for bridging metrics into OpenTelemetry or similar.
 //!
 //! ### Quick Start
 //!
@@ -174,6 +179,8 @@ pub mod expr;
 pub mod index;
 pub mod io;
 pub mod ipc;
+#[cfg(feature = "metrics-otel")]
+pub mod metrics_otel;
 #[cfg(feature = "polars")]
 mod polars_arrow_convertors;
 pub mod query;
@@ -194,6 +201,12 @@ pub use connection::{ConnectNamespaceBuilder, Connection};
 pub use error::{Error, Result};
 use lance_index::vector::ApproxMode as LanceApproxMode;
 use lance_linalg::distance::DistanceType as LanceDistanceType;
+/// Re-export of the [`metrics`](https://docs.rs/metrics) crate facade. Enable
+/// the `metrics` feature to publish LanceDB's internal metrics; install any
+/// `metrics`-compatible recorder to collect them. See also [`metrics_otel`] for
+/// a built-in pull-based adapter.
+#[cfg(feature = "metrics")]
+pub use metrics;
 pub use table::Table;

 #[derive(Debug, Copy, Clone, PartialEq, Serialize, Deserialize, Default)]
@@ -0,0 +1,594 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+//! A pull-based adapter over the [`metrics`] crate facade.
+//!
+//! LanceDB (through Lance core) publishes metrics — currently object store
+//! request counts, bytes, latency, errors, and throttles — through the global
+//! [`metrics`] facade without choosing a backend. This module installs a
+//! process-global [`metrics::Recorder`] that aggregates those metrics into
+//! lock-free cumulative storage and exposes that state as a snapshot, so callers
+//! can feed it into a pull-based exporter such as OpenTelemetry.
+//!
+//! The language bindings build their OpenTelemetry integrations on top of the
+//! three public entry points here: [`register_metrics_recorder`],
+//! [`metrics_catalog`], and [`snapshot_metrics`].
+//!
+//! The recorder is *generic*: it records any metric emitted through the facade,
+//! keyed by name and labels. Object store metrics are the first producer, but
+//! nothing here is specific to them. New metrics flow through automatically;
+//! they only need to be described (via the `metrics` `describe_*!` macros) so
+//! callers can discover their name, kind, and unit up front.
+//!
+//! ## Why pull, not push
+//!
+//! OpenTelemetry collects on its own schedule and invokes observable-instrument
+//! callbacks at collection time. Cumulative counters map directly onto OTel's
+//! `ObservableCounter` semantics. So the adapter aggregates in Rust and lets the
+//! collection thread pull a [`snapshot`](snapshot_metrics) on demand.
+//!
+//! ## Histograms
+//!
+//! OpenTelemetry has no asynchronous histogram instrument, so histograms cannot
+//! be pulled as-is. Instead each histogram is aggregated into fixed buckets
+//! (Prometheus style) and exposed as cumulative `le` bucket counts plus a count
+//! and sum, which the caller can surface as observable counters.
+
+use std::collections::HashMap;
+use std::sync::atomic::{AtomicU64, Ordering};
+use std::sync::{Arc, LazyLock, Mutex, OnceLock, RwLock};
+
+use metrics::{Counter, Gauge, Histogram, Key, KeyName, Metadata, Recorder, SharedString, Unit};
+use metrics_util::registry::{Registry, Storage};
+
+/// Bucket boundaries used when a histogram has no registered bounds. Covers a
+/// broad latency range so unknown histograms still produce useful buckets.
+const DEFAULT_BOUNDS: &[f64] = &[
+    0.005, 0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 1.0, 2.5, 5.0, 10.0, 30.0, 60.0, 120.0, 300.0,
+];
+
+/// The kind of a metric, mirroring the three `metrics` instrument types.
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+pub enum MetricKind {
+    Counter,
+    Gauge,
+    Histogram,
+}
+
+impl MetricKind {
+    /// The lowercase name of this kind (`"counter"`, `"gauge"`, `"histogram"`).
+    pub fn as_str(self) -> &'static str {
+        match self {
+            Self::Counter => "counter",
+            Self::Gauge => "gauge",
+            Self::Histogram => "histogram",
+        }
+    }
+}
+
+/// A described metric, used to create one exporter instrument per metric up front.
+#[derive(Debug, Clone)]
+pub struct MetricDescription {
+    /// The metric name (e.g. `lance_object_store_requests_total`).
+    pub name: String,
+    /// Whether the metric is a counter, gauge, or histogram.
+    pub kind: MetricKind,
+    /// The canonical unit label, if the producer described one.
+    pub unit: Option<String>,
+    /// Human-readable help text describing the metric.
+    pub description: String,
+}
+
+/// The aggregated value of a metric at snapshot time.
+#[derive(Debug, Clone)]
+pub enum MetricValue {
+    /// A counter or gauge value.
+    Scalar(f64),
+    /// A histogram, decomposed into cumulative `le` buckets plus count and sum.
+    Histogram {
+        /// Cumulative `(le, count)` buckets, ending in the implicit `+Inf` bucket.
+        buckets: Vec<(String, u64)>,
+        /// Total number of recorded samples.
+        count: u64,
+        /// Sum of all recorded sample values.
+        sum: f64,
+    },
+}
+
+/// One aggregated metric data point exposed to a caller.
+#[derive(Debug, Clone)]
+pub struct MetricPoint {
+    /// The metric name.
+    pub name: String,
+    /// Whether the point is a counter, gauge, or histogram.
+    pub kind: MetricKind,
+    /// The label set for this point (e.g. `operation`, `base`).
+    pub attributes: HashMap<String, String>,
+    /// The aggregated value.
+    pub value: MetricValue,
+}
+
+/// Catalog of described metrics, keyed by metric name.
+static CATALOG: LazyLock<Mutex<HashMap<String, CatalogEntry>>> =
+    LazyLock::new(|| Mutex::new(HashMap::new()));
+
+struct CatalogEntry {
+    kind: MetricKind,
+    unit: Option<String>,
+    description: String,
+}
+
+/// Per-metric histogram bucket boundaries, keyed by metric name. Producers
+/// register their recommended bounds before any metric is recorded.
+static HISTOGRAM_BOUNDS: LazyLock<RwLock<HashMap<String, Arc<[f64]>>>> =
+    LazyLock::new(|| RwLock::new(HashMap::new()));
+
+/// The installed recorder's registry, available once installation succeeds.
+static REGISTRY: OnceLock<Arc<Registry<Key, LanceStorage>>> = OnceLock::new();
+
+fn bounds_for(name: &str) -> Arc<[f64]> {
+    HISTOGRAM_BOUNDS
+        .read()
+        .unwrap()
+        .get(name)
+        .cloned()
+        .unwrap_or_else(|| Arc::from(DEFAULT_BOUNDS))
+}
+
+/// A histogram that buckets samples at record time into fixed boundaries,
+/// keeping a cumulative count and sum. Bucketing eagerly keeps memory bounded
+/// (unlike retaining raw samples) and produces Prometheus-style `le` buckets.
+struct BucketedHistogram {
+    /// Sorted, finite upper bounds. A sample `v` falls in the first bucket whose
+    /// bound is `>= v`; samples above all bounds fall in the implicit `+Inf`
+    /// bucket stored as the final entry of `counts`.
+    bounds: Arc<[f64]>,
+    /// Per-bucket (non-cumulative) counts; length is `bounds.len() + 1`.
+    counts: Box<[AtomicU64]>,
+    count: AtomicU64,
+    /// Running sum of recorded values, stored as `f64` bits (there is no atomic
+    /// f64, so the bit pattern is held in a `u64`; see [`Self::add_to_sum`]).
+    sum_bits: AtomicU64,
+}
+
+// All atomics here use `Ordering::Relaxed`: each metric counter is independent,
+// so no happens-before relationship is needed between them, and a snapshot
+// reader tolerates slightly stale values. This matches `metrics_util`'s
+// `AtomicStorage`.
+
+impl BucketedHistogram {
+    fn new(bounds: Arc<[f64]>) -> Self {
+        let counts = (0..bounds.len() + 1)
+            .map(|_| AtomicU64::new(0))
+            .collect::<Vec<_>>()
+            .into_boxed_slice();
+        Self {
+            bounds,
+            counts,
+            count: AtomicU64::new(0),
+            sum_bits: AtomicU64::new(0),
+        }
+    }
+
+    fn add_to_sum(&self, value: f64) {
+        // No atomic offers an f64 add, so read the current bit pattern, add in
+        // float space, and CAS it back, retrying if another thread won the race.
+        let mut current = self.sum_bits.load(Ordering::Relaxed);
+        loop {
+            let updated = (f64::from_bits(current) + value).to_bits();
+            match self.sum_bits.compare_exchange_weak(
+                current,
+                updated,
+                Ordering::Relaxed,
+                Ordering::Relaxed,
+            ) {
+                Ok(_) => break,
+                Err(actual) => current = actual,
+            }
+        }
+    }
+
+    /// Cumulative `le` buckets, total count, and sum at this instant.
+    fn snapshot(&self) -> MetricValue {
+        let mut cumulative = 0u64;
+        let mut buckets = Vec::with_capacity(self.bounds.len() + 1);
+        for (i, bound) in self.bounds.iter().enumerate() {
+            cumulative += self.counts[i].load(Ordering::Relaxed);
+            buckets.push((format!("{}", bound), cumulative));
+        }
+        cumulative += self.counts[self.bounds.len()].load(Ordering::Relaxed);
+        buckets.push(("+Inf".to_string(), cumulative));
+        MetricValue::Histogram {
+            buckets,
+            count: self.count.load(Ordering::Relaxed),
+            sum: f64::from_bits(self.sum_bits.load(Ordering::Relaxed)),
+        }
+    }
+}
+
+impl metrics::HistogramFn for BucketedHistogram {
+    fn record(&self, value: f64) {
+        let idx = self.bounds.partition_point(|&bound| bound < value);
+        self.counts[idx].fetch_add(1, Ordering::Relaxed);
+        self.count.fetch_add(1, Ordering::Relaxed);
+        self.add_to_sum(value);
+    }
+}
+
+/// Storage backing the registry. Counters and gauges are plain atomics (as in
+/// `metrics_util`'s `AtomicStorage`); histograms use [`BucketedHistogram`].
+struct LanceStorage;
+
+impl Storage<Key> for LanceStorage {
+    type Counter = Arc<AtomicU64>;
+    type Gauge = Arc<AtomicU64>;
+    type Histogram = Arc<BucketedHistogram>;
+
+    fn counter(&self, _key: &Key) -> Self::Counter {
+        Arc::new(AtomicU64::new(0))
+    }
+
+    fn gauge(&self, _key: &Key) -> Self::Gauge {
+        // The `metrics` facade writes the f64 bit pattern into this `u64` (the
+        // snapshot decodes it with `f64::from_bits`), matching `AtomicStorage`.
+        // `0` decodes to `0.0`, the correct initial value.
+        Arc::new(AtomicU64::new(0))
+    }
+
+    fn histogram(&self, key: &Key) -> Self::Histogram {
+        Arc::new(BucketedHistogram::new(bounds_for(key.name())))
+    }
+}
+
+struct LanceRecorder {
+    registry: Arc<Registry<Key, LanceStorage>>,
+}
+
+impl LanceRecorder {
+    fn describe(
+        &self,
+        key: KeyName,
+        kind: MetricKind,
+        unit: Option<Unit>,
+        description: SharedString,
+    ) {
+        CATALOG.lock().unwrap().insert(
+            key.as_str().to_string(),
+            CatalogEntry {
+                kind,
+                unit: unit.map(|u| u.as_canonical_label().to_string()),
+                description: description.into_owned(),
+            },
+        );
+    }
+}
+
+impl Recorder for LanceRecorder {
+    fn describe_counter(&self, key: KeyName, unit: Option<Unit>, description: SharedString) {
+        self.describe(key, MetricKind::Counter, unit, description);
+    }
+
+    fn describe_gauge(&self, key: KeyName, unit: Option<Unit>, description: SharedString) {
+        self.describe(key, MetricKind::Gauge, unit, description);
+    }
+
+    fn describe_histogram(&self, key: KeyName, unit: Option<Unit>, description: SharedString) {
+        self.describe(key, MetricKind::Histogram, unit, description);
+    }
+
+    fn register_counter(&self, key: &Key, _metadata: &Metadata<'_>) -> Counter {
+        self.registry
+            .get_or_create_counter(key, |c| Counter::from_arc(c.clone()))
+    }
+
+    fn register_gauge(&self, key: &Key, _metadata: &Metadata<'_>) -> Gauge {
+        self.registry
+            .get_or_create_gauge(key, |g| Gauge::from_arc(g.clone()))
+    }
+
+    fn register_histogram(&self, key: &Key, _metadata: &Metadata<'_>) -> Histogram {
+        self.registry
+            .get_or_create_histogram(key, |h| Histogram::from_arc(h.clone()))
+    }
+}
+
+/// Register the recommended histogram bounds for every metric-emitting
+/// subsystem. New subsystems add their `histogram_bounds()` here.
+fn register_bounds() {
+    let mut bounds = HISTOGRAM_BOUNDS.write().unwrap();
+    for (name, values) in lance_io::object_store::metrics::histogram_bounds() {
+        bounds.insert((*name).to_string(), Arc::from(*values));
+    }
+}
+
+/// Describe every metric-emitting subsystem so the catalog is populated. Must
+/// run after the recorder is installed. New subsystems add their
+/// `describe_metrics()` here.
+fn describe_all() {
+    lance_io::object_store::metrics::describe_metrics();
+}
+
+fn labels(key: &Key) -> HashMap<String, String> {
+    key.labels()
+        .map(|label| (label.key().to_string(), label.value().to_string()))
+        .collect()
+}
+
+fn collect_points(registry: &Registry<Key, LanceStorage>) -> Vec<MetricPoint> {
+    let mut points = Vec::new();
+    for (key, handle) in registry.get_counter_handles() {
+        points.push(MetricPoint {
+            name: key.name().to_string(),
+            kind: MetricKind::Counter,
+            attributes: labels(&key),
+            // OpenTelemetry observations are float; counts stay well within the
+            // f64-exact integer range (2^53), so this cast is lossless in practice.
+            value: MetricValue::Scalar(handle.load(Ordering::Relaxed) as f64),
+        });
+    }
+    for (key, handle) in registry.get_gauge_handles() {
+        points.push(MetricPoint {
+            name: key.name().to_string(),
+            kind: MetricKind::Gauge,
+            attributes: labels(&key),
+            value: MetricValue::Scalar(f64::from_bits(handle.load(Ordering::Relaxed))),
+        });
+    }
+    for (key, handle) in registry.get_histogram_handles() {
+        points.push(MetricPoint {
+            name: key.name().to_string(),
+            kind: MetricKind::Histogram,
+            attributes: labels(&key),
+            value: handle.snapshot(),
+        });
+    }
+    points
+}
+
+/// Install the LanceDB metrics recorder as the process-global `metrics` recorder.
+///
+/// Returns `true` if the recorder is installed (now or previously). Returns
+/// `false` if a *different* recorder is already installed — `metrics` allows
+/// only one global recorder per process, so LanceDB cannot coexist with another.
+pub fn register_metrics_recorder() -> bool {
+    if REGISTRY.get().is_some() {
+        return true;
+    }
+    let registry = Arc::new(Registry::new(LanceStorage));
+    let recorder = LanceRecorder {
+        registry: registry.clone(),
+    };
+    // Register bounds *before* installing the recorder. Bounds don't depend on
+    // the recorder, and once it is installed a concurrent histogram emission
+    // could otherwise create a handle with the fallback bounds and keep them for
+    // the process lifetime.
+    register_bounds();
+    match metrics::set_global_recorder(recorder) {
+        Ok(()) => {
+            let _ = REGISTRY.set(registry);
+            // Describe metrics only after install so the `describe_*!` macros
+            // route through this recorder and populate the catalog.
+            describe_all();
+            true
+        }
+        Err(_) => false,
+    }
+}
+
+/// The catalog of described LanceDB metrics. Empty until the recorder is installed.
+pub fn metrics_catalog() -> Vec<MetricDescription> {
+    CATALOG
+        .lock()
+        .unwrap()
+        .iter()
+        .map(|(name, entry)| MetricDescription {
+            name: name.clone(),
+            kind: entry.kind,
+            unit: entry.unit.clone(),
+            description: entry.description.clone(),
+        })
+        .collect()
+}
+
+/// A point-in-time snapshot of every recorded metric. Empty until the recorder
+/// is installed. The read is lock-free.
+pub fn snapshot_metrics() -> Vec<MetricPoint> {
+    let Some(registry) = REGISTRY.get() else {
+        return Vec::new();
+    };
+    collect_points(registry)
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use metrics::HistogramFn;
+
+    fn bucket_count(buckets: &[(String, u64)], le: &str) -> u64 {
+        buckets
+            .iter()
+            .find(|(b, _)| b == le)
+            .map(|(_, c)| *c)
+            .unwrap_or_else(|| panic!("no bucket with le={le}"))
+    }
+
+    #[test]
+    fn bucketed_histogram_records_cumulative_buckets() {
+        let hist = BucketedHistogram::new(Arc::from([0.1f64, 1.0, 10.0].as_slice()));
+        hist.record(0.05); // le=0.1
+        hist.record(0.5); // le=1
+        hist.record(0.5); // le=1
+        hist.record(50.0); // +Inf
+
+        let MetricValue::Histogram {
+            buckets,
+            count,
+            sum,
+        } = hist.snapshot()
+        else {
+            panic!("expected histogram");
+        };
+
+        // Buckets are cumulative (Prometheus `le` semantics).
+        assert_eq!(bucket_count(&buckets, "0.1"), 1);
+        assert_eq!(bucket_count(&buckets, "1"), 3);
+        assert_eq!(bucket_count(&buckets, "10"), 3);
+        assert_eq!(bucket_count(&buckets, "+Inf"), 4);
+        assert_eq!(count, 4);
+        assert!((sum - 51.05).abs() < 1e-9);
+    }
+
+    #[test]
+    fn bucketed_histogram_boundary_is_inclusive() {
+        let hist = BucketedHistogram::new(Arc::from([1.0f64].as_slice()));
+        hist.record(1.0); // exactly the bound -> le=1, not +Inf
+        let MetricValue::Histogram { buckets, .. } = hist.snapshot() else {
+            panic!("expected histogram");
+        };
+        assert_eq!(bucket_count(&buckets, "1"), 1);
+        assert_eq!(bucket_count(&buckets, "+Inf"), 1);
+    }
+
+    #[test]
+    fn bucketed_histogram_boundary_is_inclusive_mid_range() {
+        // A value equal to a middle bound lands in that bucket, not the next.
+        let hist = BucketedHistogram::new(Arc::from([0.1f64, 1.0, 10.0].as_slice()));
+        hist.record(1.0);
+        let MetricValue::Histogram { buckets, .. } = hist.snapshot() else {
+            panic!("expected histogram");
+        };
+        assert_eq!(bucket_count(&buckets, "0.1"), 0);
+        assert_eq!(bucket_count(&buckets, "1"), 1);
+        assert_eq!(bucket_count(&buckets, "10"), 1); // cumulative, so still 1
+        assert_eq!(bucket_count(&buckets, "+Inf"), 1);
+    }
+
+    #[test]
+    fn recorder_aggregates_counters_with_labels() {
+        let registry = Arc::new(Registry::new(LanceStorage));
+        let recorder = LanceRecorder {
+            registry: registry.clone(),
+        };
+        metrics::with_local_recorder(&recorder, || {
+            metrics::counter!("test_requests_total", "operation" => "get", "scheme" => "s3")
+                .increment(2);
+            metrics::counter!("test_requests_total", "operation" => "get", "scheme" => "s3")
+                .increment(3);
+            // A distinct label set must produce a separate point, not merge.
+            metrics::counter!("test_requests_total", "operation" => "put", "scheme" => "gs")
+                .increment(7);
+        });
+
+        let scalar = |attrs: &[(&str, &str)]| {
+            let points = collect_points(&registry);
+            let point = points
+                .into_iter()
+                .find(|p| {
+                    p.name == "test_requests_total"
+                        && attrs
+                            .iter()
+                            .all(|(k, v)| p.attributes.get(*k).map(String::as_str) == Some(*v))
+                })
+                .expect("counter recorded for label set");
+            assert_eq!(point.kind, MetricKind::Counter);
+            match point.value {
+                MetricValue::Scalar(v) => v,
+                _ => panic!("expected scalar"),
+            }
+        };
+
+        // Same labels aggregate; distinct labels stay separate.
+        assert!((scalar(&[("operation", "get"), ("scheme", "s3")]) - 5.0).abs() < 1e-9);
+        assert!((scalar(&[("operation", "put"), ("scheme", "gs")]) - 7.0).abs() < 1e-9);
+    }
+
+    #[test]
+    fn recorder_records_gauges() {
+        let registry = Arc::new(Registry::new(LanceStorage));
+        let recorder = LanceRecorder {
+            registry: registry.clone(),
+        };
+        // Gauges store the f64 bit pattern in a u64; the snapshot must decode it.
+        metrics::with_local_recorder(&recorder, || {
+            metrics::gauge!("test_gauge", "scheme" => "s3").set(3.5);
+        });
+
+        let points = collect_points(&registry);
+        let point = points
+            .iter()
+            .find(|p| p.name == "test_gauge")
+            .expect("gauge recorded");
+        assert_eq!(point.kind, MetricKind::Gauge);
+        assert!(matches!(point.value, MetricValue::Scalar(v) if (v - 3.5).abs() < 1e-9));
+    }
+
+    #[test]
+    fn recorder_falls_back_to_default_bounds() {
+        // A histogram with no registered bounds uses DEFAULT_BOUNDS.
+        let name = "test_unregistered_histogram";
+        assert!(!HISTOGRAM_BOUNDS.read().unwrap().contains_key(name));
+
+        let registry = Arc::new(Registry::new(LanceStorage));
+        let recorder = LanceRecorder {
+            registry: registry.clone(),
+        };
+        metrics::with_local_recorder(&recorder, || {
+            metrics::histogram!(name).record(0.02);
+        });
+
+        let points = collect_points(&registry);
+        let point = points.iter().find(|p| p.name == name).expect("recorded");
+        let MetricValue::Histogram { buckets, count, .. } = &point.value else {
+            panic!("expected histogram");
+        };
+        assert_eq!(*count, 1);
+        // DEFAULT_BOUNDS yields one bucket per bound plus the implicit `+Inf`.
+        assert_eq!(buckets.len(), DEFAULT_BOUNDS.len() + 1);
+        // 0.02 falls in the le=0.025 bucket (the third DEFAULT_BOUNDS entry).
+        assert_eq!(bucket_count(buckets, "0.025"), 1);
+        assert_eq!(bucket_count(buckets, "0.01"), 0);
+        assert_eq!(bucket_count(buckets, "+Inf"), 1);
+    }
+
+    #[test]
+    fn recorder_uses_registered_histogram_bounds() {
+        let name = "test_recorder_bounds_seconds";
+        HISTOGRAM_BOUNDS
+            .write()
+            .unwrap()
+            .insert(name.to_string(), Arc::from([0.1f64, 1.0].as_slice()));
+
+        let registry = Arc::new(Registry::new(LanceStorage));
+        let recorder = LanceRecorder {
+            registry: registry.clone(),
+        };
+        metrics::with_local_recorder(&recorder, || {
+            metrics::histogram!(name).record(0.05);
+            metrics::histogram!(name).record(5.0);
+        });
+
+        let points = collect_points(&registry);
+        let point = points.iter().find(|p| p.name == name).expect("recorded");
+        let MetricValue::Histogram { buckets, count, .. } = &point.value else {
+            panic!("expected histogram");
+        };
+        assert_eq!(*count, 2);
+        assert_eq!(bucket_count(buckets, "0.1"), 1);
+        assert_eq!(bucket_count(buckets, "+Inf"), 2);
+    }
+
+    #[test]
+    fn describe_populates_catalog() {
+        let name = "test_describe_catalog_total";
+        let registry = Arc::new(Registry::new(LanceStorage));
+        let recorder = LanceRecorder { registry };
+        metrics::with_local_recorder(&recorder, || {
+            metrics::describe_counter!(name, Unit::Count, "a test counter");
+        });
+
+        let catalog = CATALOG.lock().unwrap();
+        let entry = catalog.get(name).expect("described");
+        assert_eq!(entry.kind, MetricKind::Counter);
+        assert_eq!(entry.description, "a test counter");
+    }
+}
@@ -7,7 +7,7 @@ use std::{future::Future, time::Duration};
 use arrow::compute::concat_batches;
 use arrow_array::{Array, Float16Array, Float32Array, Float64Array, RecordBatch, make_array};
 use arrow_schema::{DataType, SchemaRef};
-use datafusion_expr::Expr;
+use datafusion_expr::{Expr, col, lit};
 use datafusion_physical_plan::ExecutionPlan;
 use futures::{FutureExt, TryFutureExt, TryStreamExt, stream, try_join};
 use half::f16;
@@ -1468,18 +1468,13 @@ impl TakeQuery {
    ///
    /// See [`crate::Table::take_offsets`] for more details.
    pub fn from_offsets(parent: Arc<dyn BaseTable>, offsets: Vec<u64>) -> Self {
-        let filter = format!(
-            "_rowoffset in ({})",
-            offsets
-                .iter()
-                .map(|o| o.to_string())
-                .collect::<Vec<_>>()
-                .join(",")
-        );
+        let in_list: Vec<Expr> = offsets.iter().map(|o| lit(*o)).collect();
        Self {
            parent,
            request: QueryRequest {
-                filter: Some(QueryFilter::Sql(filter)),
+                filter: Some(QueryFilter::Datafusion(
+                    col("_rowoffset").in_list(in_list, false),
+                )),
                ..Default::default()
            },
        }
@@ -1489,18 +1484,11 @@ impl TakeQuery {
    ///
    /// See [`crate::Table::take_row_ids`] for more details.
    pub fn from_row_ids(parent: Arc<dyn BaseTable>, row_ids: Vec<u64>) -> Self {
-        let filter = format!(
-            "_rowid in ({})",
-            row_ids
-                .iter()
-                .map(|o| o.to_string())
-                .collect::<Vec<_>>()
-                .join(",")
-        );
+        let in_list: Vec<Expr> = row_ids.iter().map(|id| lit(*id)).collect();
        Self {
            parent,
            request: QueryRequest {
-                filter: Some(QueryFilter::Sql(filter)),
+                filter: Some(QueryFilter::Datafusion(col(ROW_ID).in_list(in_list, false))),
                ..Default::default()
            },
        }
@@ -20,6 +20,7 @@ use crate::table::AddColumnsResult;
 use crate::table::AddResult;
 use crate::table::DeleteResult;
 use crate::table::DropColumnsResult;
+use crate::table::LsmWriteSpec;
 use crate::table::MergeResult;
 use crate::table::Tags;
 use crate::table::UpdateResult;
@@ -2269,8 +2270,7 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
        })
    }

-    async fn set_lsm_write_spec(&self, spec: crate::table::LsmWriteSpec) -> Result<()> {
-        use crate::table::LsmWriteSpec;
+    async fn set_lsm_write_spec(&self, spec: LsmWriteSpec) -> Result<()> {
        self.check_mutable().await?;

        // Map the spec onto the server's request DTO. `sharding` is internally
@@ -2322,6 +2322,69 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
        Ok(())
    }

+    async fn get_lsm_write_spec(&self) -> Result<Option<LsmWriteSpec>> {
+        // Read counterpart to set/unset, resolved server-side against HEAD. The
+        // server reads the spec from the `__lance_mem_wal` system index (shard
+        // column mapped from its Lance field id against the current schema) and
+        // re-encodes it into the same sophon-owned shape the set endpoint
+        // accepts — no lance/lancedb types cross the wire. `lsm_write_spec` is
+        // null when the LSM write path is not enabled for the table.
+        let request = self.post_read(&format!(
+            "/v1/table/{}/get_lsm_write_spec/",
+            self.identifier
+        ));
+        let (request_id, response) = self.send(request, true).await?;
+        let response = self.check_table_response(&request_id, response).await?;
+        let body = response.text().await.err_to_http(request_id.clone())?;
+
+        // Mirror of sophon's `Sharding` (internally tagged on `mode`) and
+        // `LsmWriteSpecBody` / `GetLsmWriteSpecResponse`.
+        #[derive(Deserialize)]
+        #[serde(tag = "mode", rename_all = "snake_case")]
+        enum Sharding {
+            Unsharded,
+            Bucket { column: String, num_buckets: u32 },
+            Identity { column: String },
+        }
+        #[derive(Deserialize)]
+        struct LsmWriteSpecBody {
+            sharding: Sharding,
+            #[serde(default)]
+            maintained_indexes: Vec<String>,
+            #[serde(default)]
+            writer_config_defaults: std::collections::HashMap<String, String>,
+        }
+        #[derive(Deserialize)]
+        struct GetLsmWriteSpecResponse {
+            lsm_write_spec: Option<LsmWriteSpecBody>,
+        }
+
+        let parsed: GetLsmWriteSpecResponse =
+            serde_json::from_str(&body).map_err(|e| Error::Http {
+                source: format!("Failed to parse get_lsm_write_spec response: {}", e).into(),
+                request_id,
+                status_code: None,
+            })?;
+
+        let Some(body) = parsed.lsm_write_spec else {
+            // The LSM write path is not enabled for this table.
+            return Ok(None);
+        };
+
+        let spec = match body.sharding {
+            Sharding::Bucket {
+                column,
+                num_buckets,
+            } => LsmWriteSpec::bucket(column, num_buckets),
+            Sharding::Identity { column } => LsmWriteSpec::identity(column),
+            Sharding::Unsharded => LsmWriteSpec::unsharded(),
+        }
+        .with_maintained_indexes(body.maintained_indexes)
+        .with_writer_config_defaults(body.writer_config_defaults);
+
+        Ok(Some(spec))
+    }
+
    async fn tags(&self) -> Result<Box<dyn Tags + '_>> {
        Ok(Box::new(RemoteTags { inner: self }))
    }
@@ -5361,6 +5424,74 @@ mod tests {
        table.unset_lsm_write_spec().await.unwrap();
    }

+    #[tokio::test]
+    async fn test_get_lsm_write_spec() {
+        let table = Table::new_with_handler("my_table", |request| {
+            assert_eq!(request.method(), "POST");
+            assert_eq!(
+                request.url().path(),
+                "/v1/table/my_table/get_lsm_write_spec/"
+            );
+
+            // The server resolves the spec and re-encodes it into the same
+            // sophon-owned shape the set endpoint accepts (`Sharding` internally
+            // tagged on `mode`, wrapped in `lsm_write_spec`).
+            let response = serde_json::json!({
+                "lsm_write_spec": {
+                    "sharding": { "mode": "bucket", "column": "id", "num_buckets": 4 },
+                    "maintained_indexes": ["id_idx"],
+                    "writer_config_defaults": { "durable_write": "false" },
+                }
+            });
+            http::Response::builder()
+                .status(200)
+                .body(response.to_string())
+                .unwrap()
+        });
+
+        let spec = table
+            .get_lsm_write_spec()
+            .await
+            .unwrap()
+            .expect("a spec should be reported");
+        match spec {
+            crate::table::LsmWriteSpec::Bucket {
+                column,
+                num_buckets,
+                maintained_indexes,
+                writer_config_defaults,
+            } => {
+                assert_eq!(column, "id");
+                assert_eq!(num_buckets, 4);
+                assert_eq!(maintained_indexes, vec!["id_idx".to_string()]);
+                assert_eq!(
+                    writer_config_defaults
+                        .get("durable_write")
+                        .map(String::as_str),
+                    Some("false")
+                );
+            }
+            other => panic!("expected a bucket spec, got {:?}", other),
+        }
+    }
+
+    #[tokio::test]
+    async fn test_get_lsm_write_spec_absent() {
+        let table = Table::new_with_handler("my_table", |request| {
+            assert_eq!(
+                request.url().path(),
+                "/v1/table/my_table/get_lsm_write_spec/"
+            );
+            // Null spec → the LSM write path is not enabled.
+            let response = serde_json::json!({ "lsm_write_spec": null });
+            http::Response::builder()
+                .status(200)
+                .body(response.to_string())
+                .unwrap()
+        });
+        assert!(table.get_lsm_write_spec().await.unwrap().is_none());
+    }
+
    #[tokio::test]
    async fn test_wait_for_index() {
        let table = _make_table_with_indices(0);
@@ -581,6 +581,16 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
            message: "unset_lsm_write_spec is not supported on this table type".into(),
        })
    }
+    /// Read the [`LsmWriteSpec`] currently installed on this table, returning
+    /// `None` when the MemWAL LSM write path is not enabled.
+    ///
+    /// The default implementation returns `NotSupported`. Implementations that
+    /// support the MemWAL LSM write path must override this.
+    async fn get_lsm_write_spec(&self) -> Result<Option<LsmWriteSpec>> {
+        Err(Error::NotSupported {
+            message: "get_lsm_write_spec is not supported on this table type".into(),
+        })
+    }
    /// Drain and close any cached MemWAL shard writers for this table.
    ///
    /// The default implementation is a no-op; table types that maintain
@@ -1538,6 +1548,29 @@ impl Table {
        self.inner.unset_lsm_write_spec().await
    }

+    /// Read the [`LsmWriteSpec`] currently installed on this table.
+    ///
+    /// Returns `Ok(None)` when the MemWAL LSM write path is not enabled (no
+    /// spec has been set, or it was removed with [`Table::unset_lsm_write_spec`]).
+    /// The returned spec — including its [`LsmWriteSpec::maintained_indexes`] and
+    /// [`LsmWriteSpec::writer_config_defaults`] — mirrors what was passed to
+    /// [`Table::set_lsm_write_spec`].
+    ///
+    /// # Example
+    ///
+    /// ```
+    /// # use lancedb::table::Table;
+    /// # async fn example(table: &Table) -> Result<(), Box<dyn std::error::Error>> {
+    /// if let Some(spec) = table.get_lsm_write_spec().await? {
+    ///     println!("LSM write path enabled: {:?}", spec);
+    /// }
+    /// # Ok(())
+    /// # }
+    /// ```
+    pub async fn get_lsm_write_spec(&self) -> Result<Option<LsmWriteSpec>> {
+        self.inner.get_lsm_write_spec().await
+    }
+
    /// Drain and close any cached MemWAL shard writers held for this table.
    ///
    /// When an [`LsmWriteSpec`] is installed, `merge_insert` opens MemWAL shard
@@ -2850,6 +2883,10 @@ impl BaseTable for NativeTable {
        merge::lsm::unset_lsm_write_spec(self).await
    }

+    async fn get_lsm_write_spec(&self) -> Result<Option<LsmWriteSpec>> {
+        merge::lsm::get_lsm_write_spec(self).await
+    }
+
    async fn close_lsm_writers(&self) -> Result<()> {
        merge::lsm::close_lsm_writers(self).await
    }
@@ -4411,6 +4448,67 @@ mod tests {
        }
    }

+    #[tokio::test]
+    async fn test_get_lsm_write_spec() {
+        let tmp_dir = tempdir().unwrap();
+        let uri = tmp_dir.path().to_str().unwrap();
+
+        let schema = Arc::new(Schema::new(vec![
+            Field::new("id", DataType::Int64, false),
+            Field::new("region", DataType::Utf8, true),
+        ]));
+        let batch = RecordBatch::try_new(
+            schema.clone(),
+            vec![
+                Arc::new(arrow_array::Int64Array::from(vec![1, 2, 3])),
+                Arc::new(StringArray::from(vec!["a", "b", "c"])),
+            ],
+        )
+        .unwrap();
+        let reader: Box<dyn arrow_array::RecordBatchReader + Send> =
+            Box::new(RecordBatchIterator::new(vec![Ok(batch)], schema.clone()));
+        let conn = ConnectBuilder::new(uri)
+            .read_consistency_interval(Duration::from_secs(0))
+            .execute()
+            .await
+            .unwrap();
+        let table = conn.create_table("t", reader).execute().await.unwrap();
+
+        // No spec installed yet.
+        assert_eq!(table.get_lsm_write_spec().await.unwrap(), None);
+
+        // A real scalar index is needed to name it as a maintained index.
+        table
+            .create_index(&["id"], Index::Auto)
+            .execute()
+            .await
+            .unwrap();
+        let idx_name = table.list_indices().await.unwrap()[0].name.clone();
+
+        // Bucket spec round-trips exactly, including the routing column (recovered
+        // from its field id), maintained indexes, and writer config defaults.
+        let spec = LsmWriteSpec::bucket("id", 4)
+            .with_maintained_indexes([idx_name])
+            .with_writer_config_defaults([("durable_write", "false")]);
+        table.set_lsm_write_spec(spec.clone()).await.unwrap();
+        assert_eq!(table.get_lsm_write_spec().await.unwrap(), Some(spec));
+
+        // After unset, no spec is reported.
+        table.unset_lsm_write_spec().await.unwrap();
+        assert_eq!(table.get_lsm_write_spec().await.unwrap(), None);
+
+        // Identity sharding round-trips (column recovered from the schema).
+        let spec = LsmWriteSpec::identity("region");
+        table.set_lsm_write_spec(spec.clone()).await.unwrap();
+        assert_eq!(table.get_lsm_write_spec().await.unwrap(), Some(spec));
+        table.unset_lsm_write_spec().await.unwrap();
+
+        // Unsharded round-trips (no routing column).
+        let spec = LsmWriteSpec::unsharded();
+        table.set_lsm_write_spec(spec.clone()).await.unwrap();
+        assert_eq!(table.get_lsm_write_spec().await.unwrap(), Some(spec));
+    }
+
    #[tokio::test]
    pub async fn test_stats() {
        let tmp_dir = tempdir().unwrap();
@@ -32,7 +32,7 @@ use lance::dataset::mem_wal::{
 };
 use lance::index::DatasetIndexExt;
 use lance_core::datatypes::Schema as LanceSchema;
-use lance_index::mem_wal::{MemWalIndexDetails, ShardingSpec};
+use lance_index::mem_wal::{MemWalIndexDetails, ShardingField, ShardingSpec};
 use tokio::sync::RwLock;
 use uuid::Uuid;

@@ -148,6 +148,97 @@ pub(crate) async fn unset_lsm_write_spec(table: &NativeTable) -> Result<()> {
    Ok(())
 }

+// =============================================================================
+// get_lsm_write_spec
+// =============================================================================
+
+/// Read the [`LsmWriteSpec`] currently installed on the table, if any.
+///
+/// Reconstructs the spec from the MemWAL index's stored details — the same
+/// metadata [`set_lsm_write_spec`] writes — read directly via
+/// [`mem_wal_index_details`](DatasetMemWalExt::mem_wal_index_details) (the raw
+/// manifest record, not the `describe_indices` enrichment path, so it is
+/// unaffected by system-index filtering there). Returns `Ok(None)` when no
+/// MemWAL index is installed.
+#[allow(clippy::redundant_pub_crate)]
+pub(crate) async fn get_lsm_write_spec(table: &NativeTable) -> Result<Option<LsmWriteSpec>> {
+    let dataset = table.dataset.get().await?;
+    let Some(details) = dataset.mem_wal_index_details().await? else {
+        return Ok(None);
+    };
+    let spec = lsm_write_spec_from_details(&details, dataset.schema())?;
+    Ok(Some(spec))
+}
+
+/// Reconstruct the public [`LsmWriteSpec`] from stored MemWAL index details.
+///
+/// The sharding transform and its parameters recover the mode; the routing
+/// column is resolved from the sharding field's source id back to its schema
+/// name (only bucket / identity carry a column). `maintained_indexes` and
+/// `writer_config_defaults` are copied verbatim, so the result round-trips
+/// what `set_lsm_write_spec` installed.
+fn lsm_write_spec_from_details(
+    details: &MemWalIndexDetails,
+    schema: &LanceSchema,
+) -> Result<LsmWriteSpec> {
+    let spec = details
+        .sharding_specs
+        .first()
+        .ok_or_else(|| Error::Runtime {
+            message: "get_lsm_write_spec: MemWAL index has no sharding spec".to_string(),
+        })?;
+    let field = spec.fields.first().ok_or_else(|| Error::Runtime {
+        message: "get_lsm_write_spec: MemWAL index has an empty sharding spec".to_string(),
+    })?;
+
+    let base = match field.transform.as_deref() {
+        Some(BUCKET_TRANSFORM) => {
+            let num_buckets = field
+                .parameters
+                .get(NUM_BUCKETS_PARAM)
+                .and_then(|s| s.parse::<u32>().ok())
+                .filter(|n| *n > 0)
+                .ok_or_else(|| Error::Runtime {
+                    message: "get_lsm_write_spec: MemWAL bucket spec has a missing or invalid num_buckets parameter".to_string(),
+                })?;
+            LsmWriteSpec::bucket(sharding_column(field, schema)?, num_buckets)
+        }
+        Some(IDENTITY_TRANSFORM) => LsmWriteSpec::identity(sharding_column(field, schema)?),
+        Some(UNSHARDED_TRANSFORM) => LsmWriteSpec::unsharded(),
+        other => {
+            return Err(Error::Runtime {
+                message: format!(
+                    "get_lsm_write_spec: MemWAL index has an unsupported sharding transform {:?}",
+                    other
+                ),
+            });
+        }
+    };
+
+    Ok(base
+        .with_maintained_indexes(details.maintained_indexes.clone())
+        .with_writer_config_defaults(details.writer_config_defaults.clone()))
+}
+
+/// Resolve the single routing column name from a sharding field's source id.
+///
+/// `set_lsm_write_spec` records the shard column by its Lance field id, so the
+/// name is recovered by looking that id up in the current schema.
+fn sharding_column(field: &ShardingField, schema: &LanceSchema) -> Result<String> {
+    let source_id = *field.source_ids.first().ok_or_else(|| Error::Runtime {
+        message: "get_lsm_write_spec: sharding field has no source column".to_string(),
+    })?;
+    schema
+        .field_by_id(source_id)
+        .map(|f| f.name.clone())
+        .ok_or_else(|| Error::Runtime {
+            message: format!(
+                "get_lsm_write_spec: sharding source field id {} not found in schema",
+                source_id
+            ),
+        })
+}
+
 // =============================================================================
 // close_lsm_writers
 // =============================================================================