Compare commits

...

22 Commits

Author SHA1 Message Date
Lance Release
c89240b16c Bump version: 0.30.0-beta.6 → 0.30.0 2026-03-16 22:46:19 +00:00
Lance Release
099ff355a4 Bump version: 0.30.0-beta.5 → 0.30.0-beta.6 2026-03-16 22:46:17 +00:00
Weston Pace
c5995fda67 feat: update lance dependency to 3.0.0 release (#3137)
## Summary
- Update all 14 lance crates from `3.0.0-rc.3` (git source) to `3.0.0`
(crates.io release)
- Remove git/tag source references since 3.0.0 is published on crates.io

## Test plan
- [x] `cargo check --features remote --tests --examples` passes
- [x] `cargo clippy --features remote --tests --examples` passes
- [ ] CI passes

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-16 15:29:18 -07:00
Weston Pace
25eb1fbfa4 fix: restore storage options on copy in localstack tests (#3148) 2026-03-16 14:02:19 -07:00
Weston Pace
4ac41c5c3f fix(ci): upgrade LocalStack to 4.0 for S3 integration tests (#3147)
## Summary
- Upgrade LocalStack from 3.3 to 4.0 in `docker-compose.yml` to fix S3
integration test failures in CI
- Version 3.3 has compatibility issues with newer Python 3.13 and
updated boto3 dependencies
- Matches the LocalStack version used successfully in the lance
repository

## Test plan
- [ ] Verify `docker compose up --detach --wait` completes successfully
in CI
- [ ] All tests in `test_s3.py` pass (5 tests)
- [ ] All `@pytest.mark.s3_test` tests in
`test_namespace_integration.py` pass (7 tests)
- [ ] No regressions in non-integration test jobs (Mac, Windows)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-16 09:02:11 -07:00
Will Jones
9a5b0398ec chore: fix ci (#3139)
* Move away from buildjet, which is shutting down runners for GHA [^1]
* Add `Cargo.lock` to build jobs, so when we upgrade locked dependencies
we check the builds actually pass. CI started failing because
dependencies were changed in #3116 without running all build jobs.
* Add fixes for aws-lc-rs build in NodeJS.

[^1]: https://buildjet.com/for-github-actions/blog/we-are-shutting-down

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-16 06:25:40 -07:00
Pratik Dey
d1d720d08a feat(nodejs): support field/data type input in add_columns() method (#3114)
Add support for passing field/data type information into add_columns()
method, bringing parity with Python bindings. The method now accepts:

- AddColumnsSql[] - SQL expressions (existing functionality)
- Field - single Arrow field with explicit data type
- Field[] - array of Arrow fields with explicit data types
- Schema - Arrow schema with explicit data types

New columns added via Field/Schema are initialized with null values. All
field-based columns must be nullable due to null initialization.

Resolves #3107

---------

Signed-off-by: Pratik <pratikrocks.dey11@gmail.com>
Co-authored-by: Claude <noreply@anthropic.com>
2026-03-13 12:57:14 -07:00
Mesut-Doner
c2e543f1b7 feat(rust): support Expr in projection query (#3069)
Referred and followed [`Select::Dynamic`] implementation. 

Closes #3039
2026-03-13 12:54:26 -07:00
Weston Pace
216c1b5f77 docs: remove experimental label from optimize and warn about delete_unverified (#3128)
## Summary
- Removes the "Experimental API" section from `optimize` method
documentation across Rust, Python, and TypeScript
- Adds a warning to `delete_unverified` documentation in all bindings:
this should only be set to true if you can guarantee no other process is
working on the dataset, otherwise it could be corrupted
- Fixes a typo ("shoudl" → "should")

Closes #3125


🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-12 14:37:42 +08:00
Xin Sun
fc1867da83 chore: remove the duplicate snafu-derive dependency in the lockfile (#3124) 2026-03-10 21:43:51 -07:00
Esteban Gutierrez
f951da2b00 feat: support prewarm_index and prewarm_data on remote tables (#3110)
## Summary

- Implement `RemoteTable.prewarm_data(columns)` calling `POST
/v1/table/{id}/page_cache/prewarm/`
- Implement `RemoteTable.prewarm_index(name)` calling `POST
/v1/table/{id}/index/{name}/prewarm/` (previously returned
`NotSupported`)
- Add `BaseTable::prewarm_data(columns)` trait method and `Table` public
API in Rust core
- Add PyO3 bindings and Python API (`AsyncTable`, `LanceTable`,
`RemoteTable`) for `prewarm_data`
- Add type stubs for `prewarm_index` and `prewarm_data` in
`_lancedb.pyi`
- Upgrade Lance to 3.0.0-rc.3 with breaking change fixes

Co-authored-by: Will Jones <willjones127@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-10 15:39:39 -05:00
Esteban Gutierrez
6530d82690 chore: dependency updates and security fixes (#3116)
## Summary

- Update dependencies across Rust, Python, Node.js, Java, Docker, and
docs
- Pin unpinned dependency lower bounds to prevent silent downgrades
- Bump CI actions to current major versions

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-09 20:04:27 -07:00
Lance Release
b3fc9c444f Bump version: 0.27.0-beta.4 → 0.27.0-beta.5 2026-03-09 19:58:12 +00:00
Lance Release
6de8f42dcd Bump version: 0.30.0-beta.4 → 0.30.0-beta.5 2026-03-09 19:56:15 +00:00
Will Jones
5c3bd68e58 feat: upgrade Lance to 3.0.0-rc.3 (#3104)
Co-authored-by: Jack Ye <yezhaoqin@gmail.com>
2026-03-09 12:55:20 -07:00
Weston Pace
4be85444f0 feat: infer js native arrays (#3119)
When we create tables without using Arrow by parsing JS records we
always infer to float64. Many times embeddings are not float64 and it
would be nice to be able to use the native type without requiring users
to pull in Arrow. We can utilize JS's builtin Float32Array to do this.
This PR also adds support for UInt8/16/32 and Int8/16/32 arrays as well.

Closes #3115
2026-03-09 10:13:59 -07:00
Xuanwo
68c07f333f chore: unify component README titles (#3066) 2026-03-09 21:47:58 +08:00
Lance Release
814a379e08 Bump version: 0.27.0-beta.3 → 0.27.0-beta.4 2026-03-09 08:47:17 +00:00
Lance Release
f31561c5bb Bump version: 0.30.0-beta.3 → 0.30.0-beta.4 2026-03-09 08:45:25 +00:00
Jack Ye
e0c5ceac03 fix: propagate managed versioning for namespace connection (#3111)
Without this fix, if user directly use the native table to do operations
like `add_columns`, even if it is configured to use namespace db
connection, it is not really propagated through.

The fix is to bring lancedb's python binding up to date and do a similar
implementation as https://github.com/lance-format/lance/pull/5968, and
make sure the namespace is fully propagated through all the related
calls.

---------

Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-03-09 01:44:31 -07:00
Prashanth Rao
e93bb3355a docs: add meth/func names to mkdocstrings (#3101)
LanceDB's SDK API docs do not currently show method names under any
given object, and this makes it harder to quickly understand and find
relevant method names for a given class. Geneva docs show the available
methods in the right navigation.

This PR standardizes the appearance of the LanceDB SDK API in the docs
to be more similar to Geneva's.
<img width="1386" height="792" alt="image"
src="https://github.com/user-attachments/assets/30816591-d6d5-495d-886d-e234beeb6059"
/>

<img width="897" height="540" alt="image"
src="https://github.com/user-attachments/assets/d5491b6b-c7bf-4d3b-8b15-1a1a7700e7c9"
/>
2026-03-06 08:54:45 -08:00
Will Jones
b75991eb07 fix: propagate cast errors in add() (#3075)
When we write data with `add()`, we can input data to the table's
schema. However, we were using "safe" mode, which propagates errors as
nulls. For example, if you pass `u64::max` into a field that is a `u32`,
it will just write null instead of giving overflow error. Now it
propagates the overflow. This is the same behavior as other systems like
DuckDB.

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-05 20:24:50 -08:00
70 changed files with 3963 additions and 3813 deletions

View File

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

View File

@@ -15,7 +15,7 @@ jobs:
name: Label PR
runs-on: ubuntu-latest
steps:
- uses: srvaroa/labeler@master
- uses: srvaroa/labeler@v1
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
commitlint:
@@ -24,7 +24,7 @@ jobs:
name: Verify PR title / description conforms to semantic-release
runs-on: ubuntu-latest
steps:
- uses: actions/setup-node@v3
- uses: actions/setup-node@v4
with:
node-version: "18"
# These rules are disabled because Github will always ensure there
@@ -47,7 +47,7 @@ jobs:
${{ github.event.pull_request.body }}
- if: failure()
uses: actions/github-script@v6
uses: actions/github-script@v7
with:
script: |
const message = `**ACTION NEEDED**

View File

@@ -53,7 +53,7 @@ jobs:
python -m pip install --extra-index-url https://pypi.fury.io/lance-format/ --extra-index-url https://pypi.fury.io/lancedb/ -e .
python -m pip install --extra-index-url https://pypi.fury.io/lance-format/ --extra-index-url https://pypi.fury.io/lancedb/ -r ../docs/requirements.txt
- name: Set up node
uses: actions/setup-node@v3
uses: actions/setup-node@v4
with:
node-version: 20
cache: 'npm'
@@ -68,7 +68,7 @@ jobs:
run: |
PYTHONPATH=. mkdocs build
- name: Setup Pages
uses: actions/configure-pages@v2
uses: actions/configure-pages@v5
- name: Upload artifact
uses: actions/upload-pages-artifact@v3
with:

View File

@@ -7,6 +7,7 @@ on:
pull_request:
paths:
- Cargo.toml
- Cargo.lock
- nodejs/**
- rust/**
- docs/src/js/**
@@ -37,7 +38,7 @@ jobs:
with:
fetch-depth: 0
lfs: true
- uses: actions/setup-node@v3
- uses: actions/setup-node@v4
with:
node-version: 20
cache: 'npm'
@@ -77,7 +78,7 @@ jobs:
with:
fetch-depth: 0
lfs: true
- uses: actions/setup-node@v3
- uses: actions/setup-node@v4
name: Setup Node.js 20 for build
with:
# @napi-rs/cli v3 requires Node >= 20.12 (via @inquirer/prompts@8).
@@ -94,7 +95,7 @@ jobs:
run: |
npm ci --include=optional
npm run build:debug -- --profile ci
- uses: actions/setup-node@v3
- uses: actions/setup-node@v4
name: Setup Node.js ${{ matrix.node-version }} for test
with:
node-version: ${{ matrix.node-version }}
@@ -143,7 +144,7 @@ jobs:
with:
fetch-depth: 0
lfs: true
- uses: actions/setup-node@v3
- uses: actions/setup-node@v4
with:
node-version: 20
cache: 'npm'

View File

@@ -19,6 +19,7 @@ on:
paths:
- .github/workflows/npm-publish.yml
- Cargo.toml # Change in dependency frequently breaks builds
- Cargo.lock
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
@@ -124,7 +125,12 @@ jobs:
pre_build: |-
set -e &&
apt-get update &&
apt-get install -y protobuf-compiler pkg-config
apt-get install -y protobuf-compiler pkg-config &&
# The base image (manylinux2014-cross) sets TARGET_CC to the old
# GCC 4.8 cross-compiler. aws-lc-sys checks TARGET_CC before CC,
# so it picks up GCC even though the napi-rs image sets CC=clang.
# Override to use the image's clang-18 which supports -fuse-ld=lld.
export TARGET_CC=clang TARGET_CXX=clang++
- target: x86_64-unknown-linux-musl
# This one seems to need some extra memory
host: ubuntu-2404-8x-x64
@@ -144,9 +150,10 @@ jobs:
set -e &&
apt-get update &&
apt-get install -y protobuf-compiler pkg-config &&
# https://github.com/aws/aws-lc-rs/issues/737#issuecomment-2725918627
ln -s /usr/aarch64-unknown-linux-gnu/lib/gcc/aarch64-unknown-linux-gnu/4.8.5/crtbeginS.o /usr/aarch64-unknown-linux-gnu/aarch64-unknown-linux-gnu/sysroot/usr/lib/crtbeginS.o &&
ln -s /usr/aarch64-unknown-linux-gnu/lib/gcc /usr/aarch64-unknown-linux-gnu/aarch64-unknown-linux-gnu/sysroot/usr/lib/gcc &&
export TARGET_CC=clang TARGET_CXX=clang++ &&
# The manylinux2014 sysroot has glibc 2.17 headers which lack
# AT_HWCAP2 (added in Linux 3.17). Define it for aws-lc-sys.
export CFLAGS="$CFLAGS -DAT_HWCAP2=26" &&
rustup target add aarch64-unknown-linux-gnu
- target: aarch64-unknown-linux-musl
host: ubuntu-2404-8x-x64
@@ -266,7 +273,7 @@ jobs:
- target: x86_64-unknown-linux-gnu
host: ubuntu-latest
- target: aarch64-unknown-linux-gnu
host: buildjet-16vcpu-ubuntu-2204-arm
host: ubuntu-2404-8x-arm64
node:
- '20'
runs-on: ${{ matrix.settings.host }}

View File

@@ -9,6 +9,7 @@ on:
paths:
- .github/workflows/pypi-publish.yml
- Cargo.toml # Change in dependency frequently breaks builds
- Cargo.lock
env:
PIP_EXTRA_INDEX_URL: "https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/"

View File

@@ -7,6 +7,7 @@ on:
pull_request:
paths:
- Cargo.toml
- Cargo.lock
- python/**
- rust/**
- .github/workflows/python.yml

View File

@@ -7,6 +7,7 @@ on:
pull_request:
paths:
- Cargo.toml
- Cargo.lock
- rust/**
- .github/workflows/rust.yml

425
Cargo.lock generated

File diff suppressed because it is too large Load Diff

View File

@@ -15,20 +15,20 @@ categories = ["database-implementations"]
rust-version = "1.91.0"
[workspace.dependencies]
lance = { "version" = "=3.0.0-rc.2", default-features = false, "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
lance-core = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
lance-datagen = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
lance-file = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
lance-io = { "version" = "=3.0.0-rc.2", default-features = false, "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
lance-index = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
lance-linalg = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace-impls = { "version" = "=3.0.0-rc.2", default-features = false, "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
lance-table = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
lance-testing = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
lance-datafusion = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
lance-encoding = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
lance-arrow = { "version" = "=3.0.0-rc.2", "tag" = "v3.0.0-rc.2", "git" = "https://github.com/lance-format/lance.git" }
lance = { version = "=3.0.0", default-features = false }
lance-core = { version = "=3.0.0" }
lance-datagen = { version = "=3.0.0" }
lance-file = { version = "=3.0.0" }
lance-io = { version = "=3.0.0", default-features = false }
lance-index = { version = "=3.0.0" }
lance-linalg = { version = "=3.0.0" }
lance-namespace = { version = "=3.0.0" }
lance-namespace-impls = { version = "=3.0.0", default-features = false }
lance-table = { version = "=3.0.0" }
lance-testing = { version = "=3.0.0" }
lance-datafusion = { version = "=3.0.0" }
lance-encoding = { version = "=3.0.0" }
lance-arrow = { version = "=3.0.0" }
ahash = "0.8"
# Note that this one does not include pyarrow
arrow = { version = "57.2", optional = false }

View File

@@ -1,7 +1,7 @@
version: "3.9"
services:
localstack:
image: localstack/localstack:3.3
image: localstack/localstack:4.0
ports:
- 4566:4566
environment:

View File

@@ -1,27 +1,27 @@
#Simple base dockerfile that supports basic dependencies required to run lance with FTS and Hybrid Search
#Usage docker build -t lancedb:latest -f Dockerfile .
FROM python:3.10-slim-buster
# Simple base dockerfile that supports basic dependencies required to run lance with FTS and Hybrid Search
# Usage: docker build -t lancedb:latest -f Dockerfile .
FROM python:3.12-slim-bookworm
# Install Rust
RUN apt-get update && apt-get install -y curl build-essential && \
curl https://sh.rustup.rs -sSf | sh -s -- -y
# Set the environment variable for Rust
ENV PATH="/root/.cargo/bin:${PATH}"
# Install protobuf compiler
RUN apt-get install -y protobuf-compiler && \
# Install build dependencies in a single layer
RUN apt-get update && \
apt-get install -y --no-install-recommends \
curl \
build-essential \
protobuf-compiler \
git \
ca-certificates && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN apt-get -y update &&\
apt-get -y upgrade && \
apt-get -y install git
# Install Rust (pinned installer, non-interactive)
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y --default-toolchain stable --profile minimal
# Set the environment variable for Rust
ENV PATH="/root/.cargo/bin:${PATH}"
# Verify installations
RUN python --version && \
rustc --version && \
protoc --version
RUN pip install tantivy lancedb
RUN pip install --no-cache-dir tantivy lancedb

View File

@@ -52,14 +52,21 @@ plugins:
options:
docstring_style: numpy
heading_level: 3
show_source: true
show_symbol_type_in_heading: true
show_signature_annotations: true
show_root_heading: true
show_docstring_examples: true
show_docstring_attributes: false
show_docstring_other_parameters: true
show_symbol_type_heading: true
show_labels: false
show_if_no_docstring: true
show_source: false
members_order: source
docstring_section_style: list
signature_crossrefs: true
separate_signature: true
filters:
- "!^_"
import:
# for cross references
- https://arrow.apache.org/docs/objects.inv
@@ -113,7 +120,7 @@ markdown_extensions:
emoji_index: !!python/name:material.extensions.emoji.twemoji
emoji_generator: !!python/name:material.extensions.emoji.to_svg
- markdown.extensions.toc:
toc_depth: 3
toc_depth: 4
permalink: true
permalink_title: Anchor link to this section

View File

@@ -1,9 +1,9 @@
mkdocs==1.5.3
mkdocs-jupyter==0.24.1
mkdocs-material==9.5.3
mkdocs-autorefs<=1.0
mkdocs-autorefs>=0.5,<=1.0
mkdocstrings[python]==0.25.2
griffe
mkdocs-render-swagger-plugin
pydantic
mkdocs-redirects
griffe>=0.40,<1.0
mkdocs-render-swagger-plugin>=0.1.0
pydantic>=2.0,<3.0
mkdocs-redirects>=1.2.0

View File

@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
<dependency>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-core</artifactId>
<version>0.27.0-beta.3</version>
<version>0.27.0-beta.5</version>
</dependency>
```

View File

@@ -71,11 +71,12 @@ Add new columns with defined values.
#### Parameters
* **newColumnTransforms**: [`AddColumnsSql`](../interfaces/AddColumnsSql.md)[]
pairs of column names and
the SQL expression to use to calculate the value of the new column. These
expressions will be evaluated for each row in the table, and can
reference existing columns in the table.
* **newColumnTransforms**: `Field`&lt;`any`&gt; \| `Field`&lt;`any`&gt;[] \| `Schema`&lt;`any`&gt; \| [`AddColumnsSql`](../interfaces/AddColumnsSql.md)[]
Either:
- An array of objects with column names and SQL expressions to calculate values
- A single Arrow Field defining one column with its data type (column will be initialized with null values)
- An array of Arrow Fields defining columns with their data types (columns will be initialized with null values)
- An Arrow Schema defining columns with their data types (columns will be initialized with null values)
#### Returns
@@ -484,19 +485,7 @@ Modeled after ``VACUUM`` in PostgreSQL.
- Prune: Removes old versions of the dataset
- Index: Optimizes the indices, adding new data to existing indices
Experimental API
----------------
The optimization process is undergoing active development and may change.
Our goal with these changes is to improve the performance of optimization and
reduce the complexity.
That being said, it is essential today to run optimize if you want the best
performance. It should be stable and safe to use in production, but it our
hope that the API may be simplified (or not even need to be called) in the
future.
The frequency an application shoudl call optimize is based on the frequency of
The frequency an application should call optimize is based on the frequency of
data modifications. If data is frequently added, deleted, or updated then
optimize should be run frequently. A good rule of thumb is to run optimize if
you have added or modified 100,000 or more records or run more than 20 data

View File

@@ -37,3 +37,12 @@ tbl.optimize({cleanupOlderThan: new Date()});
```ts
deleteUnverified: boolean;
```
Because they may be part of an in-progress transaction, files newer than
7 days old are not deleted by default. If you are sure that there are no
in-progress transactions, then you can set this to true to delete all
files older than `cleanupOlderThan`.
**WARNING**: This should only be set to true if you can guarantee that
no other process is currently working on this dataset. Otherwise the
dataset could be put into a corrupted state.

View File

@@ -1,4 +1,4 @@
# LanceDB Java SDK
# LanceDB Java Enterprise Client
## Configuration and Initialization

View File

@@ -8,7 +8,7 @@
<parent>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.27.0-beta.3</version>
<version>0.27.0-beta.5</version>
<relativePath>../pom.xml</relativePath>
</parent>
@@ -56,21 +56,21 @@
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-slf4j2-impl</artifactId>
<version>2.24.3</version>
<version>2.25.3</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-core</artifactId>
<version>2.24.3</version>
<version>2.25.3</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-api</artifactId>
<version>2.24.3</version>
<version>2.25.3</version>
<scope>test</scope>
</dependency>
</dependencies>

View File

@@ -6,7 +6,7 @@
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.27.0-beta.3</version>
<version>0.27.0-beta.5</version>
<packaging>pom</packaging>
<name>${project.artifactId}</name>
<description>LanceDB Java SDK Parent POM</description>
@@ -111,7 +111,7 @@
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-source-plugin</artifactId>
<version>2.2.1</version>
<version>3.3.1</version>
<executions>
<execution>
<id>attach-sources</id>
@@ -124,7 +124,7 @@
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-javadoc-plugin</artifactId>
<version>2.9.1</version>
<version>3.11.2</version>
<executions>
<execution>
<id>attach-javadocs</id>
@@ -178,15 +178,15 @@
<plugins>
<plugin>
<artifactId>maven-clean-plugin</artifactId>
<version>3.1.0</version>
<version>3.4.1</version>
</plugin>
<plugin>
<artifactId>maven-resources-plugin</artifactId>
<version>3.0.2</version>
<version>3.3.1</version>
</plugin>
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.8.1</version>
<version>3.14.0</version>
<configuration>
<compilerArgs>
<arg>-h</arg>
@@ -205,11 +205,11 @@
</plugin>
<plugin>
<artifactId>maven-jar-plugin</artifactId>
<version>3.0.2</version>
<version>3.4.2</version>
</plugin>
<plugin>
<artifactId>maven-install-plugin</artifactId>
<version>2.5.2</version>
<version>3.1.3</version>
</plugin>
<plugin>
<groupId>com.diffplug.spotless</groupId>
@@ -327,7 +327,7 @@
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-gpg-plugin</artifactId>
<version>1.5</version>
<version>3.2.7</version>
<executions>
<execution>
<id>sign-artifacts</id>

View File

@@ -1,7 +1,7 @@
[package]
name = "lancedb-nodejs"
edition.workspace = true
version = "0.27.0-beta.3"
version = "0.27.0-beta.5"
license.workspace = true
description.workspace = true
repository.workspace = true
@@ -25,12 +25,12 @@ napi = { version = "3.8.3", default-features = false, features = [
] }
napi-derive = "3.5.2"
# Prevent dynamic linking of lzma, which comes from datafusion
lzma-sys = { version = "*", features = ["static"] }
lzma-sys = { version = "0.1", features = ["static"] }
log.workspace = true
# Workaround for build failure until we can fix it.
aws-lc-sys = "=0.28.0"
aws-lc-rs = "=1.13.0"
# Pin to resolve build failures; update periodically for security patches.
aws-lc-sys = "=0.38.0"
aws-lc-rs = "=1.16.1"
[build-dependencies]
napi-build = "2.3.1"

View File

@@ -63,6 +63,7 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
tableFromIPC,
DataType,
Dictionary,
Uint8: ArrowUint8,
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
} = <any>arrow;
type Schema = ApacheArrow["Schema"];
@@ -362,6 +363,38 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
).toEqual(new Float64().toString());
});
it("will infer FixedSizeList<Float32> from Float32Array values", async function () {
const table = makeArrowTable([
{ id: "a", vector: new Float32Array([0.1, 0.2, 0.3]) },
{ id: "b", vector: new Float32Array([0.4, 0.5, 0.6]) },
]);
expect(DataType.isFixedSizeList(table.getChild("vector")?.type)).toBe(
true,
);
const vectorType = table.getChild("vector")?.type;
expect(vectorType.listSize).toBe(3);
expect(vectorType.children[0].type.toString()).toEqual(
new Float32().toString(),
);
});
it("will infer FixedSizeList<Uint8> from Uint8Array values", async function () {
const table = makeArrowTable([
{ id: "a", vector: new Uint8Array([1, 2, 3]) },
{ id: "b", vector: new Uint8Array([4, 5, 6]) },
]);
expect(DataType.isFixedSizeList(table.getChild("vector")?.type)).toBe(
true,
);
const vectorType = table.getChild("vector")?.type;
expect(vectorType.listSize).toBe(3);
expect(vectorType.children[0].type.toString()).toEqual(
new ArrowUint8().toString(),
);
});
it("will use dictionary encoded strings if asked", async function () {
const table = makeArrowTable([{ str: "hello" }]);
expect(DataType.isUtf8(table.getChild("str")?.type)).toBe(true);

View File

@@ -1259,6 +1259,98 @@ describe("schema evolution", function () {
expect(await table.schema()).toEqual(expectedSchema);
});
it("can add columns with schema for explicit data types", async function () {
const con = await connect(tmpDir.name);
const table = await con.createTable("vectors", [
{ id: 1n, vector: [0.1, 0.2] },
]);
// Define schema for new columns with explicit data types
// Note: All columns must be nullable when using addColumns with Schema
// because they are initially populated with null values
const newColumnsSchema = new Schema([
new Field("price", new Float64(), true),
new Field("category", new Utf8(), true),
new Field("rating", new Int32(), true),
]);
const result = await table.addColumns(newColumnsSchema);
expect(result).toHaveProperty("version");
expect(result.version).toBe(2);
const expectedSchema = new Schema([
new Field("id", new Int64(), true),
new Field(
"vector",
new FixedSizeList(2, new Field("item", new Float32(), true)),
true,
),
new Field("price", new Float64(), true),
new Field("category", new Utf8(), true),
new Field("rating", new Int32(), true),
]);
expect(await table.schema()).toEqual(expectedSchema);
// Verify that new columns are populated with null values
const results = await table.query().toArray();
expect(results).toHaveLength(1);
expect(results[0].price).toBeNull();
expect(results[0].category).toBeNull();
expect(results[0].rating).toBeNull();
});
it("can add a single column using Field", async function () {
const con = await connect(tmpDir.name);
const table = await con.createTable("vectors", [
{ id: 1n, vector: [0.1, 0.2] },
]);
// Add a single field
const priceField = new Field("price", new Float64(), true);
const result = await table.addColumns(priceField);
expect(result).toHaveProperty("version");
expect(result.version).toBe(2);
const expectedSchema = new Schema([
new Field("id", new Int64(), true),
new Field(
"vector",
new FixedSizeList(2, new Field("item", new Float32(), true)),
true,
),
new Field("price", new Float64(), true),
]);
expect(await table.schema()).toEqual(expectedSchema);
});
it("can add multiple columns using array of Fields", async function () {
const con = await connect(tmpDir.name);
const table = await con.createTable("vectors", [
{ id: 1n, vector: [0.1, 0.2] },
]);
// Add multiple fields as array
const fields = [
new Field("price", new Float64(), true),
new Field("category", new Utf8(), true),
];
const result = await table.addColumns(fields);
expect(result).toHaveProperty("version");
expect(result.version).toBe(2);
const expectedSchema = new Schema([
new Field("id", new Int64(), true),
new Field(
"vector",
new FixedSizeList(2, new Field("item", new Float32(), true)),
true,
),
new Field("price", new Float64(), true),
new Field("category", new Utf8(), true),
]);
expect(await table.schema()).toEqual(expectedSchema);
});
it("can alter the columns in the schema", async function () {
const con = await connect(tmpDir.name);
const schema = new Schema([
@@ -2204,3 +2296,36 @@ describe("when creating an empty table", () => {
expect((actualSchema.fields[1].type as Float64).precision).toBe(2);
});
});
// Ensure we can create float32 arrays without using Arrow
// by utilizing native JS TypedArray support
//
// https://github.com/lancedb/lancedb/issues/3115
describe("when creating a table with Float32Array vectors", () => {
let tmpDir: tmp.DirResult;
beforeEach(() => {
tmpDir = tmp.dirSync({ unsafeCleanup: true });
});
afterEach(() => {
tmpDir.removeCallback();
});
it("should persist Float32Array as FixedSizeList<Float32> in the LanceDB schema", async () => {
const db = await connect(tmpDir.name);
const table = await db.createTable("test", [
{ id: "a", vector: new Float32Array([0.1, 0.2, 0.3]) },
{ id: "b", vector: new Float32Array([0.4, 0.5, 0.6]) },
]);
const schema = await table.schema();
const vectorField = schema.fields.find((f) => f.name === "vector");
expect(vectorField).toBeDefined();
expect(vectorField!.type).toBeInstanceOf(FixedSizeList);
const fsl = vectorField!.type as FixedSizeList;
expect(fsl.listSize).toBe(3);
expect(fsl.children[0].type.typeId).toBe(Type.Float);
// precision: HALF=0, SINGLE=1, DOUBLE=2
expect((fsl.children[0].type as Float32).precision).toBe(1);
});
});

View File

@@ -30,12 +30,15 @@
"x64",
"arm64"
],
"dev": true,
"license": "Apache-2.0",
"optional": true,
"os": [
"darwin",
"linux",
"win32"
],
"peer": true,
"dependencies": {
"reflect-metadata": "^0.2.2"
},
@@ -91,14 +94,15 @@
}
},
"node_modules/@babel/code-frame": {
"version": "7.26.2",
"resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.26.2.tgz",
"integrity": "sha512-RJlIHRueQgwWitWgF8OdFYGZX328Ax5BCemNGlqHfplnRT9ESi8JkFlvaVYbS+UubVY6dpv87Fs2u5M29iNFVQ==",
"version": "7.29.0",
"resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.29.0.tgz",
"integrity": "sha512-9NhCeYjq9+3uxgdtp20LSiJXJvN0FeCtNGpJxuMFZ1Kv3cWUNb6DOhJwUvcVCzKGR66cw4njwM6hrJLqgOwbcw==",
"dev": true,
"license": "MIT",
"dependencies": {
"@babel/helper-validator-identifier": "^7.25.9",
"@babel/helper-validator-identifier": "^7.28.5",
"js-tokens": "^4.0.0",
"picocolors": "^1.0.0"
"picocolors": "^1.1.1"
},
"engines": {
"node": ">=6.9.0"
@@ -233,19 +237,21 @@
}
},
"node_modules/@babel/helper-string-parser": {
"version": "7.25.9",
"resolved": "https://registry.npmjs.org/@babel/helper-string-parser/-/helper-string-parser-7.25.9.tgz",
"integrity": "sha512-4A/SCr/2KLd5jrtOMFzaKjVtAei3+2r/NChoBNoZ3EyP/+GlhoaEGoWOZUmFmoITP7zOJyHIMm+DYRd8o3PvHA==",
"version": "7.27.1",
"resolved": "https://registry.npmjs.org/@babel/helper-string-parser/-/helper-string-parser-7.27.1.tgz",
"integrity": "sha512-qMlSxKbpRlAridDExk92nSobyDdpPijUq2DW6oDnUqd0iOGxmQjyqhMIihI9+zv4LPyZdRje2cavWPbCbWm3eA==",
"dev": true,
"license": "MIT",
"engines": {
"node": ">=6.9.0"
}
},
"node_modules/@babel/helper-validator-identifier": {
"version": "7.25.9",
"resolved": "https://registry.npmjs.org/@babel/helper-validator-identifier/-/helper-validator-identifier-7.25.9.tgz",
"integrity": "sha512-Ed61U6XJc3CVRfkERJWDz4dJwKe7iLmmJsbOGu9wSloNSFttHV0I8g6UAgb7qnK5ly5bGLPd4oXZlxCdANBOWQ==",
"version": "7.28.5",
"resolved": "https://registry.npmjs.org/@babel/helper-validator-identifier/-/helper-validator-identifier-7.28.5.tgz",
"integrity": "sha512-qSs4ifwzKJSV39ucNjsvc6WVHs6b7S03sOh2OcHF9UHfVPqWWALUsNUVzhSBiItjRZoLHx7nIarVjqKVusUZ1Q==",
"dev": true,
"license": "MIT",
"engines": {
"node": ">=6.9.0"
}
@@ -260,25 +266,27 @@
}
},
"node_modules/@babel/helpers": {
"version": "7.26.0",
"resolved": "https://registry.npmjs.org/@babel/helpers/-/helpers-7.26.0.tgz",
"integrity": "sha512-tbhNuIxNcVb21pInl3ZSjksLCvgdZy9KwJ8brv993QtIVKJBBkYXz4q4ZbAv31GdnC+R90np23L5FbEBlthAEw==",
"version": "7.28.6",
"resolved": "https://registry.npmjs.org/@babel/helpers/-/helpers-7.28.6.tgz",
"integrity": "sha512-xOBvwq86HHdB7WUDTfKfT/Vuxh7gElQ+Sfti2Cy6yIWNW05P8iUslOVcZ4/sKbE+/jQaukQAdz/gf3724kYdqw==",
"dev": true,
"license": "MIT",
"dependencies": {
"@babel/template": "^7.25.9",
"@babel/types": "^7.26.0"
"@babel/template": "^7.28.6",
"@babel/types": "^7.28.6"
},
"engines": {
"node": ">=6.9.0"
}
},
"node_modules/@babel/parser": {
"version": "7.26.2",
"resolved": "https://registry.npmjs.org/@babel/parser/-/parser-7.26.2.tgz",
"integrity": "sha512-DWMCZH9WA4Maitz2q21SRKHo9QXZxkDsbNZoVD62gusNtNBBqDg9i7uOhASfTfIGNzW+O+r7+jAlM8dwphcJKQ==",
"version": "7.29.0",
"resolved": "https://registry.npmjs.org/@babel/parser/-/parser-7.29.0.tgz",
"integrity": "sha512-IyDgFV5GeDUVX4YdF/3CPULtVGSXXMLh1xVIgdCgxApktqnQV0r7/8Nqthg+8YLGaAtdyIlo2qIdZrbCv4+7ww==",
"dev": true,
"license": "MIT",
"dependencies": {
"@babel/types": "^7.26.0"
"@babel/types": "^7.29.0"
},
"bin": {
"parser": "bin/babel-parser.js"
@@ -510,14 +518,15 @@
}
},
"node_modules/@babel/template": {
"version": "7.25.9",
"resolved": "https://registry.npmjs.org/@babel/template/-/template-7.25.9.tgz",
"integrity": "sha512-9DGttpmPvIxBb/2uwpVo3dqJ+O6RooAFOS+lB+xDqoE2PVCE8nfoHMdZLpfCQRLwvohzXISPZcgxt80xLfsuwg==",
"version": "7.28.6",
"resolved": "https://registry.npmjs.org/@babel/template/-/template-7.28.6.tgz",
"integrity": "sha512-YA6Ma2KsCdGb+WC6UpBVFJGXL58MDA6oyONbjyF/+5sBgxY/dwkhLogbMT2GXXyU84/IhRw/2D1Os1B/giz+BQ==",
"dev": true,
"license": "MIT",
"dependencies": {
"@babel/code-frame": "^7.25.9",
"@babel/parser": "^7.25.9",
"@babel/types": "^7.25.9"
"@babel/code-frame": "^7.28.6",
"@babel/parser": "^7.28.6",
"@babel/types": "^7.28.6"
},
"engines": {
"node": ">=6.9.0"
@@ -542,13 +551,14 @@
}
},
"node_modules/@babel/types": {
"version": "7.26.0",
"resolved": "https://registry.npmjs.org/@babel/types/-/types-7.26.0.tgz",
"integrity": "sha512-Z/yiTPj+lDVnF7lWeKCIJzaIkI0vYO87dMpZ4bg4TDrFe4XXLFWL1TbXU27gBP3QccxV9mZICCrnjnYlJjXHOA==",
"version": "7.29.0",
"resolved": "https://registry.npmjs.org/@babel/types/-/types-7.29.0.tgz",
"integrity": "sha512-LwdZHpScM4Qz8Xw2iKSzS+cfglZzJGvofQICy7W7v4caru4EaAmyUuO6BGrbyQ2mYV11W0U8j5mBhd14dd3B0A==",
"dev": true,
"license": "MIT",
"dependencies": {
"@babel/helper-string-parser": "^7.25.9",
"@babel/helper-validator-identifier": "^7.25.9"
"@babel/helper-string-parser": "^7.27.1",
"@babel/helper-validator-identifier": "^7.28.5"
},
"engines": {
"node": ">=6.9.0"
@@ -1151,95 +1161,6 @@
"url": "https://opencollective.com/libvips"
}
},
"node_modules/@isaacs/cliui": {
"version": "8.0.2",
"resolved": "https://registry.npmjs.org/@isaacs/cliui/-/cliui-8.0.2.tgz",
"integrity": "sha512-O8jcjabXaleOG9DQ0+ARXWZBTfnP4WNAqzuiJK7ll44AmxGKv/J2M4TPjxjY3znBCfvBXFzucm1twdyFybFqEA==",
"dependencies": {
"string-width": "^5.1.2",
"string-width-cjs": "npm:string-width@^4.2.0",
"strip-ansi": "^7.0.1",
"strip-ansi-cjs": "npm:strip-ansi@^6.0.1",
"wrap-ansi": "^8.1.0",
"wrap-ansi-cjs": "npm:wrap-ansi@^7.0.0"
},
"engines": {
"node": ">=12"
}
},
"node_modules/@isaacs/cliui/node_modules/ansi-regex": {
"version": "6.1.0",
"resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-6.1.0.tgz",
"integrity": "sha512-7HSX4QQb4CspciLpVFwyRe79O3xsIZDDLER21kERQ71oaPodF8jL725AgJMFAYbooIqolJoRLuM81SpeUkpkvA==",
"engines": {
"node": ">=12"
},
"funding": {
"url": "https://github.com/chalk/ansi-regex?sponsor=1"
}
},
"node_modules/@isaacs/cliui/node_modules/ansi-styles": {
"version": "6.2.1",
"resolved": "https://registry.npmjs.org/ansi-styles/-/ansi-styles-6.2.1.tgz",
"integrity": "sha512-bN798gFfQX+viw3R7yrGWRqnrN2oRkEkUjjl4JNn4E8GxxbjtG3FbrEIIY3l8/hrwUwIeCZvi4QuOTP4MErVug==",
"engines": {
"node": ">=12"
},
"funding": {
"url": "https://github.com/chalk/ansi-styles?sponsor=1"
}
},
"node_modules/@isaacs/cliui/node_modules/emoji-regex": {
"version": "9.2.2",
"resolved": "https://registry.npmjs.org/emoji-regex/-/emoji-regex-9.2.2.tgz",
"integrity": "sha512-L18DaJsXSUk2+42pv8mLs5jJT2hqFkFE4j21wOmgbUqsZ2hL72NsUU785g9RXgo3s0ZNgVl42TiHp3ZtOv/Vyg=="
},
"node_modules/@isaacs/cliui/node_modules/string-width": {
"version": "5.1.2",
"resolved": "https://registry.npmjs.org/string-width/-/string-width-5.1.2.tgz",
"integrity": "sha512-HnLOCR3vjcY8beoNLtcjZ5/nxn2afmME6lhrDrebokqMap+XbeW8n9TXpPDOqdGK5qcI3oT0GKTW6wC7EMiVqA==",
"dependencies": {
"eastasianwidth": "^0.2.0",
"emoji-regex": "^9.2.2",
"strip-ansi": "^7.0.1"
},
"engines": {
"node": ">=12"
},
"funding": {
"url": "https://github.com/sponsors/sindresorhus"
}
},
"node_modules/@isaacs/cliui/node_modules/strip-ansi": {
"version": "7.1.0",
"resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-7.1.0.tgz",
"integrity": "sha512-iq6eVVI64nQQTRYq2KtEg2d2uU7LElhTJwsH4YzIHZshxlgZms/wIc4VoDQTlG/IvVIrBKG06CrZnp0qv7hkcQ==",
"dependencies": {
"ansi-regex": "^6.0.1"
},
"engines": {
"node": ">=12"
},
"funding": {
"url": "https://github.com/chalk/strip-ansi?sponsor=1"
}
},
"node_modules/@isaacs/cliui/node_modules/wrap-ansi": {
"version": "8.1.0",
"resolved": "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-8.1.0.tgz",
"integrity": "sha512-si7QWI6zUMq56bESFvagtmzMdGOtoxfR+Sez11Mobfc7tm+VkUckk9bW2UeffTGVUbOksxmSw0AA2gs8g71NCQ==",
"dependencies": {
"ansi-styles": "^6.1.0",
"string-width": "^5.0.1",
"strip-ansi": "^7.0.1"
},
"engines": {
"node": ">=12"
},
"funding": {
"url": "https://github.com/chalk/wrap-ansi?sponsor=1"
}
},
"node_modules/@isaacs/fs-minipass": {
"version": "4.0.1",
"resolved": "https://registry.npmjs.org/@isaacs/fs-minipass/-/fs-minipass-4.0.1.tgz",
@@ -1606,15 +1527,6 @@
"resolved": "../dist",
"link": true
},
"node_modules/@pkgjs/parseargs": {
"version": "0.11.0",
"resolved": "https://registry.npmjs.org/@pkgjs/parseargs/-/parseargs-0.11.0.tgz",
"integrity": "sha512-+1VkjdD0QBLPodGrJUeqarH8VAIvQODIbwh9XpP5Syisf7YoQgsJKPNFoqqLQlu+VQ/tVSshMR6loPMn8U+dPg==",
"optional": true,
"engines": {
"node": ">=14"
}
},
"node_modules/@protobufjs/aspromise": {
"version": "1.1.2",
"resolved": "https://registry.npmjs.org/@protobufjs/aspromise/-/aspromise-1.1.2.tgz",
@@ -1846,6 +1758,7 @@
"version": "5.0.1",
"resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-5.0.1.tgz",
"integrity": "sha512-quJQXlTSUGL2LH9SUXo8VwsY4soanhgo6LNSm84E1LBcE8s3O0wpdiRzyR9z/ZZJMlMWv37qOOb9pdJlMUEKFQ==",
"dev": true,
"engines": {
"node": ">=8"
}
@@ -1854,6 +1767,7 @@
"version": "4.3.0",
"resolved": "https://registry.npmjs.org/ansi-styles/-/ansi-styles-4.3.0.tgz",
"integrity": "sha512-zbB9rCJAT1rbjiVDb2hqKFHNYLxgtk8NURxZ3IZwD3F6NtxbXZQCnnSi1Lkx+IDohdPlFp222wVALIheZJQSEg==",
"dev": true,
"dependencies": {
"color-convert": "^2.0.1"
},
@@ -2019,13 +1933,15 @@
"node_modules/balanced-match": {
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"url": "https://github.com/sponsors/isaacs"
}
},
"node_modules/ms": {
"version": "2.1.3",
"resolved": "https://registry.npmjs.org/ms/-/ms-2.1.3.tgz",
@@ -4010,11 +4034,6 @@
"node": ">=6"
}
},
"node_modules/package-json-from-dist": {
"version": "1.0.1",
"resolved": "https://registry.npmjs.org/package-json-from-dist/-/package-json-from-dist-1.0.1.tgz",
"integrity": "sha512-UEZIS3/by4OC8vL3P2dTXRETpebLI2NiI5vIrjaD/5UtrkFX/tNbwjTSRAGC/+7CAo2pIcBaRgWmcBBHcsaCIw=="
},
"node_modules/parse-json": {
"version": "5.2.0",
"resolved": "https://registry.npmjs.org/parse-json/-/parse-json-5.2.0.tgz",
@@ -4055,6 +4074,7 @@
"version": "3.1.1",
"resolved": "https://registry.npmjs.org/path-key/-/path-key-3.1.1.tgz",
"integrity": "sha512-ojmeN0qd+y0jszEtoY48r0Peq5dwMEkIlCOu6Q5f41lfkswXuKtYrhgoTpLnyIcHm24Uhqx+5Tqm2InSwLhE6Q==",
"dev": true,
"engines": {
"node": ">=8"
}
@@ -4065,26 +4085,6 @@
"integrity": "sha512-LDJzPVEEEPR+y48z93A0Ed0yXb8pAByGWo/k5YYdYgpY2/2EsOsksJrq7lOHxryrVOn1ejG6oAp8ahvOIQD8sw==",
"dev": true
},
"node_modules/path-scurry": {
"version": "1.11.1",
"resolved": "https://registry.npmjs.org/path-scurry/-/path-scurry-1.11.1.tgz",
"integrity": "sha512-Xa4Nw17FS9ApQFJ9umLiJS4orGjm7ZzwUrwamcGQuHSzDyth9boKDaycYdDcZDuqYATXw4HFXgaqWTctW/v1HA==",
"dependencies": {
"lru-cache": "^10.2.0",
"minipass": "^5.0.0 || ^6.0.2 || ^7.0.0"
},
"engines": {
"node": ">=16 || 14 >=14.18"
},
"funding": {
"url": "https://github.com/sponsors/isaacs"
}
},
"node_modules/path-scurry/node_modules/lru-cache": {
"version": "10.4.3",
"resolved": "https://registry.npmjs.org/lru-cache/-/lru-cache-10.4.3.tgz",
"integrity": "sha512-JNAzZcXrCt42VGLuYz0zfAzDfAvJWW6AfYlDBQyDV5DClI2m5sAmK+OIO7s59XfsRsWHp02jAJrRadPRGTt6SQ=="
},
"node_modules/picocolors": {
"version": "1.1.1",
"resolved": "https://registry.npmjs.org/picocolors/-/picocolors-1.1.1.tgz",
@@ -4246,61 +4246,6 @@
"node": ">=10"
}
},
"node_modules/rimraf": {
"version": "5.0.10",
"resolved": "https://registry.npmjs.org/rimraf/-/rimraf-5.0.10.tgz",
"integrity": "sha512-l0OE8wL34P4nJH/H2ffoaniAokM2qSmrtXHmlpvYr5AVVX8msAyW0l8NVJFDxlSK4u3Uh/f41cQheDVdnYijwQ==",
"dependencies": {
"glob": "^10.3.7"
},
"bin": {
"rimraf": "dist/esm/bin.mjs"
},
"funding": {
"url": "https://github.com/sponsors/isaacs"
}
},
"node_modules/rimraf/node_modules/brace-expansion": {
"version": "2.0.1",
"resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-2.0.1.tgz",
"integrity": "sha512-XnAIvQ8eM+kC6aULx6wuQiwVsnzsi9d3WxzV3FpWTGA19F621kwdbsAcFKXgKUHZWsy+mY6iL1sHTxWEFCytDA==",
"dependencies": {
"balanced-match": "^1.0.0"
}
},
"node_modules/rimraf/node_modules/glob": {
"version": "10.4.5",
"resolved": "https://registry.npmjs.org/glob/-/glob-10.4.5.tgz",
"integrity": "sha512-7Bv8RF0k6xjo7d4A/PxYLbUCfb6c+Vpd2/mB2yRDlew7Jb5hEXiCD9ibfO7wpk8i4sevK6DFny9h7EYbM3/sHg==",
"dependencies": {
"foreground-child": "^3.1.0",
"jackspeak": "^3.1.2",
"minimatch": "^9.0.4",
"minipass": "^7.1.2",
"package-json-from-dist": "^1.0.0",
"path-scurry": "^1.11.1"
},
"bin": {
"glob": "dist/esm/bin.mjs"
},
"funding": {
"url": "https://github.com/sponsors/isaacs"
}
},
"node_modules/rimraf/node_modules/minimatch": {
"version": "9.0.5",
"resolved": "https://registry.npmjs.org/minimatch/-/minimatch-9.0.5.tgz",
"integrity": "sha512-G6T0ZX48xgozx7587koeX9Ys2NYy6Gmv//P89sEte9V9whIapMNF4idKxnW2QtCcLiTWlb/wfCabAtAFWhhBow==",
"dependencies": {
"brace-expansion": "^2.0.1"
},
"engines": {
"node": ">=16 || 14 >=14.17"
},
"funding": {
"url": "https://github.com/sponsors/isaacs"
}
},
"node_modules/semver": {
"version": "7.6.3",
"resolved": "https://registry.npmjs.org/semver/-/semver-7.6.3.tgz",
@@ -4354,6 +4299,7 @@
"version": "2.0.0",
"resolved": "https://registry.npmjs.org/shebang-command/-/shebang-command-2.0.0.tgz",
"integrity": "sha512-kHxr2zZpYtdmrN1qDjrrX/Z1rR1kG8Dx+gkpK1G4eXmvXswmcE1hTWBWYUzlraYw1/yZp6YuDY77YtvbN0dmDA==",
"dev": true,
"dependencies": {
"shebang-regex": "^3.0.0"
},
@@ -4365,6 +4311,7 @@
"version": "3.0.0",
"resolved": "https://registry.npmjs.org/shebang-regex/-/shebang-regex-3.0.0.tgz",
"integrity": "sha512-7++dFhtcx3353uBaq8DDR4NuxBetBzC7ZQOhmTQInHEd6bSrXdiEyzCvG07Z44UYdLShWUyXt5M/yhz8ekcb1A==",
"dev": true,
"engines": {
"node": ">=8"
}
@@ -4452,20 +4399,7 @@
"version": "4.2.3",
"resolved": "https://registry.npmjs.org/string-width/-/string-width-4.2.3.tgz",
"integrity": "sha512-wKyQRQpjJ0sIp62ErSZdGsjMJWsap5oRNihHhu6G7JVO/9jIB6UyevL+tXuOqrng8j/cxKTWyWUwvSTriiZz/g==",
"dependencies": {
"emoji-regex": "^8.0.0",
"is-fullwidth-code-point": "^3.0.0",
"strip-ansi": "^6.0.1"
},
"engines": {
"node": ">=8"
}
},
"node_modules/string-width-cjs": {
"name": "string-width",
"version": "4.2.3",
"resolved": "https://registry.npmjs.org/string-width/-/string-width-4.2.3.tgz",
"integrity": "sha512-wKyQRQpjJ0sIp62ErSZdGsjMJWsap5oRNihHhu6G7JVO/9jIB6UyevL+tXuOqrng8j/cxKTWyWUwvSTriiZz/g==",
"dev": true,
"dependencies": {
"emoji-regex": "^8.0.0",
"is-fullwidth-code-point": "^3.0.0",
@@ -4479,18 +4413,7 @@
"version": "6.0.1",
"resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.1.tgz",
"integrity": "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A==",
"dependencies": {
"ansi-regex": "^5.0.1"
},
"engines": {
"node": ">=8"
}
},
"node_modules/strip-ansi-cjs": {
"name": "strip-ansi",
"version": "6.0.1",
"resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.1.tgz",
"integrity": "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A==",
"dev": true,
"dependencies": {
"ansi-regex": "^5.0.1"
},
@@ -4541,15 +4464,15 @@
}
},
"node_modules/tar": {
"version": "7.4.3",
"resolved": "https://registry.npmjs.org/tar/-/tar-7.4.3.tgz",
"integrity": "sha512-5S7Va8hKfV7W5U6g3aYxXmlPoZVAwUMy9AOKyF2fVuZa2UD3qZjg578OrLRt8PcNN1PleVaL/5/yYATNL0ICUw==",
"version": "7.5.10",
"resolved": "https://registry.npmjs.org/tar/-/tar-7.5.10.tgz",
"integrity": "sha512-8mOPs1//5q/rlkNSPcCegA6hiHJYDmSLEI8aMH/CdSQJNWztHC9WHNam5zdQlfpTwB9Xp7IBEsHfV5LKMJGVAw==",
"license": "BlueOak-1.0.0",
"dependencies": {
"@isaacs/fs-minipass": "^4.0.0",
"chownr": "^3.0.0",
"minipass": "^7.1.2",
"minizlib": "^3.0.1",
"mkdirp": "^3.0.1",
"minizlib": "^3.1.0",
"yallist": "^5.0.0"
},
"engines": {
@@ -4782,6 +4705,7 @@
"version": "2.0.2",
"resolved": "https://registry.npmjs.org/which/-/which-2.0.2.tgz",
"integrity": "sha512-BLI3Tl1TW3Pvl70l3yq3Y64i+awpwXqsGBYWkkqMtnbXgrMD+yj7rhW0kuEDxzJaYXGjEW5ogapKNMEKNMjibA==",
"dev": true,
"dependencies": {
"isexe": "^2.0.0"
},
@@ -4809,23 +4733,6 @@
"url": "https://github.com/chalk/wrap-ansi?sponsor=1"
}
},
"node_modules/wrap-ansi-cjs": {
"name": "wrap-ansi",
"version": "7.0.0",
"resolved": "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-7.0.0.tgz",
"integrity": "sha512-YVGIj2kamLSTxw6NsZjoBxfSwsn0ycdesmc4p+Q21c5zPuZ1pl+NfxVdxPtdHvmNVOQ6XSYG4AUtyt/Fi7D16Q==",
"dependencies": {
"ansi-styles": "^4.0.0",
"string-width": "^4.1.0",
"strip-ansi": "^6.0.0"
},
"engines": {
"node": ">=10"
},
"funding": {
"url": "https://github.com/chalk/wrap-ansi?sponsor=1"
}
},
"node_modules/wrappy": {
"version": "1.0.2",
"resolved": "https://registry.npmjs.org/wrappy/-/wrappy-1.0.2.tgz",

View File

@@ -20,6 +20,8 @@ import {
Float32,
Float64,
Int,
Int8,
Int16,
Int32,
Int64,
LargeBinary,
@@ -35,6 +37,8 @@ import {
Timestamp,
Type,
Uint8,
Uint16,
Uint32,
Utf8,
Vector,
makeVector as arrowMakeVector,
@@ -529,7 +533,8 @@ function isObject(value: unknown): value is Record<string, unknown> {
!(value instanceof Date) &&
!(value instanceof Set) &&
!(value instanceof Map) &&
!(value instanceof Buffer)
!(value instanceof Buffer) &&
!ArrayBuffer.isView(value)
);
}
@@ -588,6 +593,13 @@ function inferType(
return new Bool();
} else if (value instanceof Buffer) {
return new Binary();
} else if (ArrayBuffer.isView(value) && !(value instanceof DataView)) {
const info = typedArrayToArrowType(value);
if (info !== undefined) {
const child = new Field("item", info.elementType, true);
return new FixedSizeList(info.length, child);
}
return undefined;
} else if (Array.isArray(value)) {
if (value.length === 0) {
return undefined; // Without any values we can't infer the type
@@ -746,6 +758,32 @@ function makeListVector(lists: unknown[][]): Vector<unknown> {
return listBuilder.finish().toVector();
}
/**
* Map a JS TypedArray instance to the corresponding Arrow element DataType
* and its length. Returns undefined if the value is not a recognized TypedArray.
*/
function typedArrayToArrowType(
value: ArrayBufferView,
): { elementType: DataType; length: number } | undefined {
if (value instanceof Float32Array)
return { elementType: new Float32(), length: value.length };
if (value instanceof Float64Array)
return { elementType: new Float64(), length: value.length };
if (value instanceof Uint8Array)
return { elementType: new Uint8(), length: value.length };
if (value instanceof Uint16Array)
return { elementType: new Uint16(), length: value.length };
if (value instanceof Uint32Array)
return { elementType: new Uint32(), length: value.length };
if (value instanceof Int8Array)
return { elementType: new Int8(), length: value.length };
if (value instanceof Int16Array)
return { elementType: new Int16(), length: value.length };
if (value instanceof Int32Array)
return { elementType: new Int32(), length: value.length };
return undefined;
}
/** Helper function to convert an Array of JS values to an Arrow Vector */
function makeVector(
values: unknown[],
@@ -814,6 +852,16 @@ function makeVector(
"makeVector cannot infer the type if all values are null or undefined",
);
}
if (ArrayBuffer.isView(sampleValue) && !(sampleValue instanceof DataView)) {
const info = typedArrayToArrowType(sampleValue);
if (info !== undefined) {
const fslType = new FixedSizeList(
info.length,
new Field("item", info.elementType, true),
);
return vectorFromArray(values, fslType);
}
}
if (Array.isArray(sampleValue)) {
// Default Arrow inference doesn't handle list types
return makeListVector(values as unknown[][]);

View File

@@ -5,12 +5,15 @@ import {
Table as ArrowTable,
Data,
DataType,
Field,
IntoVector,
MultiVector,
Schema,
dataTypeToJson,
fromDataToBuffer,
fromTableToBuffer,
isMultiVector,
makeEmptyTable,
tableFromIPC,
} from "./arrow";
@@ -84,6 +87,16 @@ export interface OptimizeOptions {
* tbl.optimize({cleanupOlderThan: new Date()});
*/
cleanupOlderThan: Date;
/**
* Because they may be part of an in-progress transaction, files newer than
* 7 days old are not deleted by default. If you are sure that there are no
* in-progress transactions, then you can set this to true to delete all
* files older than `cleanupOlderThan`.
*
* **WARNING**: This should only be set to true if you can guarantee that
* no other process is currently working on this dataset. Otherwise the
* dataset could be put into a corrupted state.
*/
deleteUnverified: boolean;
}
@@ -381,15 +394,16 @@ export abstract class Table {
abstract vectorSearch(vector: IntoVector | MultiVector): VectorQuery;
/**
* Add new columns with defined values.
* @param {AddColumnsSql[]} newColumnTransforms pairs of column names and
* the SQL expression to use to calculate the value of the new column. These
* expressions will be evaluated for each row in the table, and can
* reference existing columns in the table.
* @param {AddColumnsSql[] | Field | Field[] | Schema} newColumnTransforms Either:
* - An array of objects with column names and SQL expressions to calculate values
* - A single Arrow Field defining one column with its data type (column will be initialized with null values)
* - An array of Arrow Fields defining columns with their data types (columns will be initialized with null values)
* - An Arrow Schema defining columns with their data types (columns will be initialized with null values)
* @returns {Promise<AddColumnsResult>} A promise that resolves to an object
* containing the new version number of the table after adding the columns.
*/
abstract addColumns(
newColumnTransforms: AddColumnsSql[],
newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
): Promise<AddColumnsResult>;
/**
@@ -501,19 +515,7 @@ export abstract class Table {
* - Index: Optimizes the indices, adding new data to existing indices
*
*
* Experimental API
* ----------------
*
* The optimization process is undergoing active development and may change.
* Our goal with these changes is to improve the performance of optimization and
* reduce the complexity.
*
* That being said, it is essential today to run optimize if you want the best
* performance. It should be stable and safe to use in production, but it our
* hope that the API may be simplified (or not even need to be called) in the
* future.
*
* The frequency an application shoudl call optimize is based on the frequency of
* The frequency an application should call optimize is based on the frequency of
* data modifications. If data is frequently added, deleted, or updated then
* optimize should be run frequently. A good rule of thumb is to run optimize if
* you have added or modified 100,000 or more records or run more than 20 data
@@ -806,9 +808,40 @@ export class LocalTable extends Table {
// TODO: Support BatchUDF
async addColumns(
newColumnTransforms: AddColumnsSql[],
newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
): Promise<AddColumnsResult> {
return await this.inner.addColumns(newColumnTransforms);
// Handle single Field -> convert to array of Fields
if (newColumnTransforms instanceof Field) {
newColumnTransforms = [newColumnTransforms];
}
// Handle array of Fields -> convert to Schema
if (
Array.isArray(newColumnTransforms) &&
newColumnTransforms.length > 0 &&
newColumnTransforms[0] instanceof Field
) {
const fields = newColumnTransforms as Field[];
newColumnTransforms = new Schema(fields);
}
// Handle Schema -> use schema-based approach
if (newColumnTransforms instanceof Schema) {
const schema = newColumnTransforms;
// Convert schema to buffer using Arrow IPC format
const emptyTable = makeEmptyTable(schema);
const schemaBuf = await fromTableToBuffer(emptyTable);
return await this.inner.addColumnsWithSchema(schemaBuf);
}
// Handle SQL expressions (existing functionality)
if (Array.isArray(newColumnTransforms)) {
return await this.inner.addColumns(
newColumnTransforms as AddColumnsSql[],
);
}
throw new Error("Invalid input type for addColumns");
}
async alterColumns(

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-darwin-arm64",
"version": "0.27.0-beta.3",
"version": "0.27.0-beta.5",
"os": ["darwin"],
"cpu": ["arm64"],
"main": "lancedb.darwin-arm64.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-arm64-gnu",
"version": "0.27.0-beta.3",
"version": "0.27.0-beta.5",
"os": ["linux"],
"cpu": ["arm64"],
"main": "lancedb.linux-arm64-gnu.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-arm64-musl",
"version": "0.27.0-beta.3",
"version": "0.27.0-beta.5",
"os": ["linux"],
"cpu": ["arm64"],
"main": "lancedb.linux-arm64-musl.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-x64-gnu",
"version": "0.27.0-beta.3",
"version": "0.27.0-beta.5",
"os": ["linux"],
"cpu": ["x64"],
"main": "lancedb.linux-x64-gnu.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-x64-musl",
"version": "0.27.0-beta.3",
"version": "0.27.0-beta.5",
"os": ["linux"],
"cpu": ["x64"],
"main": "lancedb.linux-x64-musl.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-win32-arm64-msvc",
"version": "0.27.0-beta.3",
"version": "0.27.0-beta.5",
"os": [
"win32"
],

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-win32-x64-msvc",
"version": "0.27.0-beta.3",
"version": "0.27.0-beta.5",
"os": ["win32"],
"cpu": ["x64"],
"main": "lancedb.win32-x64-msvc.node",

4289
nodejs/package-lock.json generated

File diff suppressed because it is too large Load Diff

View File

@@ -11,7 +11,7 @@
"ann"
],
"private": false,
"version": "0.27.0-beta.3",
"version": "0.27.0-beta.5",
"main": "dist/index.js",
"exports": {
".": "./dist/index.js",

View File

@@ -3,7 +3,7 @@
use std::collections::HashMap;
use lancedb::ipc::ipc_file_to_batches;
use lancedb::ipc::{ipc_file_to_batches, ipc_file_to_schema};
use lancedb::table::{
AddDataMode, ColumnAlteration as LanceColumnAlteration, Duration, NewColumnTransform,
OptimizeAction, OptimizeOptions, Table as LanceDbTable,
@@ -279,6 +279,23 @@ impl Table {
Ok(res.into())
}
#[napi(catch_unwind)]
pub async fn add_columns_with_schema(
&self,
schema_buf: Buffer,
) -> napi::Result<AddColumnsResult> {
let schema = ipc_file_to_schema(schema_buf.to_vec())
.map_err(|e| napi::Error::from_reason(format!("Failed to read IPC schema: {}", e)))?;
let transforms = NewColumnTransform::AllNulls(schema);
let res = self
.inner_ref()?
.add_columns(transforms, None)
.await
.default_error()?;
Ok(res.into())
}
#[napi(catch_unwind)]
pub async fn alter_columns(
&self,

View File

@@ -1,5 +1,5 @@
[tool.bumpversion]
current_version = "0.30.0-beta.3"
current_version = "0.30.0"
parse = """(?x)
(?P<major>0|[1-9]\\d*)\\.
(?P<minor>0|[1-9]\\d*)\\.

View File

@@ -1,6 +1,6 @@
[package]
name = "lancedb-python"
version = "0.30.0-beta.3"
version = "0.30.0"
edition.workspace = true
description = "Python bindings for LanceDB"
license.workspace = true
@@ -16,9 +16,11 @@ crate-type = ["cdylib"]
[dependencies]
arrow = { version = "57.2", features = ["pyarrow"] }
async-trait = "0.1"
bytes = "1"
lancedb = { path = "../rust/lancedb", default-features = false }
lance-core.workspace = true
lance-namespace.workspace = true
lance-namespace-impls.workspace = true
lance-io.workspace = true
env_logger.workspace = true
pyo3 = { version = "0.26", features = ["extension-module", "abi3-py39"] }
@@ -28,6 +30,8 @@ pyo3-async-runtimes = { version = "0.26", features = [
] }
pin-project = "1.1.5"
futures.workspace = true
serde = "1"
serde_json = "1"
snafu.workspace = true
tokio = { version = "1.40", features = ["sync"] }

View File

@@ -1,4 +1,4 @@
# LanceDB
# LanceDB Python SDK
A Python library for [LanceDB](https://github.com/lancedb/lancedb).

View File

@@ -3,10 +3,10 @@ name = "lancedb"
# version in Cargo.toml
dynamic = ["version"]
dependencies = [
"deprecation",
"numpy",
"deprecation>=2.1.0",
"numpy>=1.24.0",
"overrides>=0.7; python_version<'3.12'",
"packaging",
"packaging>=23.0",
"pyarrow>=16",
"pydantic>=1.10",
"tqdm>=4.27.0",
@@ -45,51 +45,51 @@ repository = "https://github.com/lancedb/lancedb"
[project.optional-dependencies]
pylance = [
"pylance>=1.0.0b14",
"pylance>=4.0.0b7",
]
tests = [
"aiohttp",
"boto3",
"aiohttp>=3.9.0",
"boto3>=1.28.57",
"pandas>=1.4",
"pytest",
"pytest-mock",
"pytest-asyncio",
"duckdb",
"pytz",
"pytest>=7.0",
"pytest-mock>=3.10",
"pytest-asyncio>=0.21",
"duckdb>=0.9.0",
"pytz>=2023.3",
"polars>=0.19, <=1.3.0",
"tantivy",
"pyarrow-stubs",
"pylance>=1.0.0b14,<3.0.0",
"requests",
"datafusion<52",
"tantivy>=0.20.0",
"pyarrow-stubs>=16.0",
"pylance>=4.0.0b7",
"requests>=2.31.0",
"datafusion>=52,<53",
]
dev = [
"ruff",
"pre-commit",
"pyright",
"ruff>=0.3.0",
"pre-commit>=3.5.0",
"pyright>=1.1.350",
'typing-extensions>=4.0.0; python_version < "3.11"',
]
docs = ["mkdocs", "mkdocs-jupyter", "mkdocs-material", "mkdocstrings-python"]
clip = ["torch", "pillow", "open-clip-torch"]
siglip = ["torch", "pillow", "transformers>=4.41.0","sentencepiece"]
clip = ["torch", "pillow>=12.1.1", "open-clip-torch"]
siglip = ["torch", "pillow>=12.1.1", "transformers>=4.41.0","sentencepiece"]
embeddings = [
"requests>=2.31.0",
"openai>=1.6.1",
"sentence-transformers",
"torch",
"pillow",
"open-clip-torch",
"cohere",
"sentence-transformers>=2.2.0",
"torch>=2.0.0",
"pillow>=12.1.1",
"open-clip-torch>=2.20.0",
"cohere>=4.0",
"colpali-engine>=0.3.10",
"huggingface_hub",
"InstructorEmbedding",
"google.generativeai",
"huggingface_hub>=0.19.0",
"InstructorEmbedding>=1.0.1",
"google.generativeai>=0.3.0",
"boto3>=1.28.57",
"awscli>=1.29.57",
"awscli>=1.44.38",
"botocore>=1.31.57",
'ibm-watsonx-ai>=1.1.2; python_version >= "3.10"',
"ollama>=0.3.0",
"sentencepiece"
"sentencepiece>=0.1.99"
]
azure = ["adlfs>=2024.2.0"]

View File

@@ -166,6 +166,8 @@ class Table:
async def checkout(self, version: Union[int, str]): ...
async def checkout_latest(self): ...
async def restore(self, version: Optional[Union[int, str]] = None): ...
async def prewarm_index(self, index_name: str) -> None: ...
async def prewarm_data(self, columns: Optional[List[str]] = None) -> None: ...
async def list_indices(self) -> list[IndexConfig]: ...
async def delete(self, filter: str) -> DeleteResult: ...
async def add_columns(self, columns: list[tuple[str, str]]) -> AddColumnsResult: ...

View File

@@ -8,7 +8,7 @@ from abc import abstractmethod
from datetime import timedelta
from pathlib import Path
import sys
from typing import TYPE_CHECKING, Dict, Iterable, List, Literal, Optional, Union
from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Literal, Optional, Union
if sys.version_info >= (3, 12):
from typing import override
@@ -1541,6 +1541,8 @@ class AsyncConnection(object):
storage_options_provider: Optional["StorageOptionsProvider"] = None,
index_cache_size: Optional[int] = None,
location: Optional[str] = None,
namespace_client: Optional[Any] = None,
managed_versioning: Optional[bool] = None,
) -> AsyncTable:
"""Open a Lance Table in the database.
@@ -1573,6 +1575,9 @@ class AsyncConnection(object):
The explicit location (URI) of the table. If provided, the table will be
opened from this location instead of deriving it from the database URI
and table name.
managed_versioning: bool, optional
Whether managed versioning is enabled for this table. If provided,
avoids a redundant describe_table call when namespace_client is set.
Returns
-------
@@ -1587,6 +1592,8 @@ class AsyncConnection(object):
storage_options_provider=storage_options_provider,
index_cache_size=index_cache_size,
location=location,
namespace_client=namespace_client,
managed_versioning=managed_versioning,
)
return AsyncTable(table)

View File

@@ -12,7 +12,7 @@ from __future__ import annotations
import asyncio
import sys
from typing import Dict, Iterable, List, Optional, Union
from typing import Any, Dict, Iterable, List, Optional, Union
if sys.version_info >= (3, 12):
from typing import override
@@ -240,7 +240,7 @@ class LanceNamespaceDBConnection(DBConnection):
session : Optional[Session]
A session to use for this connection
"""
self._ns = namespace
self._namespace_client = namespace
self.read_consistency_interval = read_consistency_interval
self.storage_options = storage_options or {}
self.session = session
@@ -269,7 +269,7 @@ class LanceNamespaceDBConnection(DBConnection):
if namespace is None:
namespace = []
request = ListTablesRequest(id=namespace, page_token=page_token, limit=limit)
response = self._ns.list_tables(request)
response = self._namespace_client.list_tables(request)
return response.tables if response.tables else []
@override
@@ -309,7 +309,9 @@ class LanceNamespaceDBConnection(DBConnection):
# Try to describe the table first to see if it exists
try:
describe_request = DescribeTableRequest(id=table_id)
describe_response = self._ns.describe_table(describe_request)
describe_response = self._namespace_client.describe_table(
describe_request
)
location = describe_response.location
namespace_storage_options = describe_response.storage_options
except Exception:
@@ -323,7 +325,7 @@ class LanceNamespaceDBConnection(DBConnection):
location=None,
properties=self.storage_options if self.storage_options else None,
)
declare_response = self._ns.declare_table(declare_request)
declare_response = self._namespace_client.declare_table(declare_request)
if not declare_response.location:
raise ValueError(
@@ -353,7 +355,7 @@ class LanceNamespaceDBConnection(DBConnection):
# Only create if namespace returned storage_options (not None)
if storage_options_provider is None and namespace_storage_options is not None:
storage_options_provider = LanceNamespaceStorageOptionsProvider(
namespace=self._ns,
namespace=self._namespace_client,
table_id=table_id,
)
@@ -371,6 +373,7 @@ class LanceNamespaceDBConnection(DBConnection):
storage_options=merged_storage_options,
storage_options_provider=storage_options_provider,
location=location,
namespace_client=self._namespace_client,
)
return tbl
@@ -389,7 +392,7 @@ class LanceNamespaceDBConnection(DBConnection):
namespace = []
table_id = namespace + [name]
request = DescribeTableRequest(id=table_id)
response = self._ns.describe_table(request)
response = self._namespace_client.describe_table(request)
# Merge storage options: self.storage_options < user options < namespace options
merged_storage_options = dict(self.storage_options)
@@ -402,10 +405,14 @@ class LanceNamespaceDBConnection(DBConnection):
# Only create if namespace returned storage_options (not None)
if storage_options_provider is None and response.storage_options is not None:
storage_options_provider = LanceNamespaceStorageOptionsProvider(
namespace=self._ns,
namespace=self._namespace_client,
table_id=table_id,
)
# Pass managed_versioning to avoid redundant describe_table call in Rust.
# Convert None to False since we already have the answer from describe_table.
managed_versioning = response.managed_versioning is True
return self._lance_table_from_uri(
name,
response.location,
@@ -413,6 +420,8 @@ class LanceNamespaceDBConnection(DBConnection):
storage_options=merged_storage_options,
storage_options_provider=storage_options_provider,
index_cache_size=index_cache_size,
namespace_client=self._namespace_client,
managed_versioning=managed_versioning,
)
@override
@@ -422,7 +431,7 @@ class LanceNamespaceDBConnection(DBConnection):
namespace = []
table_id = namespace + [name]
request = DropTableRequest(id=table_id)
self._ns.drop_table(request)
self._namespace_client.drop_table(request)
@override
def rename_table(
@@ -484,7 +493,7 @@ class LanceNamespaceDBConnection(DBConnection):
request = ListNamespacesRequest(
id=namespace, page_token=page_token, limit=limit
)
response = self._ns.list_namespaces(request)
response = self._namespace_client.list_namespaces(request)
return ListNamespacesResponse(
namespaces=response.namespaces if response.namespaces else [],
page_token=response.page_token,
@@ -520,7 +529,7 @@ class LanceNamespaceDBConnection(DBConnection):
mode=_normalize_create_namespace_mode(mode),
properties=properties,
)
response = self._ns.create_namespace(request)
response = self._namespace_client.create_namespace(request)
return CreateNamespaceResponse(
properties=response.properties if hasattr(response, "properties") else None
)
@@ -555,7 +564,7 @@ class LanceNamespaceDBConnection(DBConnection):
mode=_normalize_drop_namespace_mode(mode),
behavior=_normalize_drop_namespace_behavior(behavior),
)
response = self._ns.drop_namespace(request)
response = self._namespace_client.drop_namespace(request)
return DropNamespaceResponse(
properties=(
response.properties if hasattr(response, "properties") else None
@@ -581,7 +590,7 @@ class LanceNamespaceDBConnection(DBConnection):
Response containing the namespace properties.
"""
request = DescribeNamespaceRequest(id=namespace)
response = self._ns.describe_namespace(request)
response = self._namespace_client.describe_namespace(request)
return DescribeNamespaceResponse(
properties=response.properties if hasattr(response, "properties") else None
)
@@ -615,7 +624,7 @@ class LanceNamespaceDBConnection(DBConnection):
if namespace is None:
namespace = []
request = ListTablesRequest(id=namespace, page_token=page_token, limit=limit)
response = self._ns.list_tables(request)
response = self._namespace_client.list_tables(request)
return ListTablesResponse(
tables=response.tables if response.tables else [],
page_token=response.page_token,
@@ -630,6 +639,8 @@ class LanceNamespaceDBConnection(DBConnection):
storage_options: Optional[Dict[str, str]] = None,
storage_options_provider: Optional[StorageOptionsProvider] = None,
index_cache_size: Optional[int] = None,
namespace_client: Optional[Any] = None,
managed_versioning: Optional[bool] = None,
) -> LanceTable:
# Open a table directly from a URI using the location parameter
# Note: storage_options should already be merged by the caller
@@ -643,6 +654,8 @@ class LanceNamespaceDBConnection(DBConnection):
)
# Open the table using the temporary connection with the location parameter
# Pass namespace_client to enable managed versioning support
# Pass managed_versioning to avoid redundant describe_table call
return LanceTable.open(
temp_conn,
name,
@@ -651,6 +664,8 @@ class LanceNamespaceDBConnection(DBConnection):
storage_options_provider=storage_options_provider,
index_cache_size=index_cache_size,
location=table_uri,
namespace_client=namespace_client,
managed_versioning=managed_versioning,
)
@@ -685,7 +700,7 @@ class AsyncLanceNamespaceDBConnection:
session : Optional[Session]
A session to use for this connection
"""
self._ns = namespace
self._namespace_client = namespace
self.read_consistency_interval = read_consistency_interval
self.storage_options = storage_options or {}
self.session = session
@@ -713,7 +728,7 @@ class AsyncLanceNamespaceDBConnection:
if namespace is None:
namespace = []
request = ListTablesRequest(id=namespace, page_token=page_token, limit=limit)
response = self._ns.list_tables(request)
response = self._namespace_client.list_tables(request)
return response.tables if response.tables else []
async def create_table(
@@ -750,7 +765,9 @@ class AsyncLanceNamespaceDBConnection:
# Try to describe the table first to see if it exists
try:
describe_request = DescribeTableRequest(id=table_id)
describe_response = self._ns.describe_table(describe_request)
describe_response = self._namespace_client.describe_table(
describe_request
)
location = describe_response.location
namespace_storage_options = describe_response.storage_options
except Exception:
@@ -764,7 +781,7 @@ class AsyncLanceNamespaceDBConnection:
location=None,
properties=self.storage_options if self.storage_options else None,
)
declare_response = self._ns.declare_table(declare_request)
declare_response = self._namespace_client.declare_table(declare_request)
if not declare_response.location:
raise ValueError(
@@ -797,7 +814,7 @@ class AsyncLanceNamespaceDBConnection:
and namespace_storage_options is not None
):
provider = LanceNamespaceStorageOptionsProvider(
namespace=self._ns,
namespace=self._namespace_client,
table_id=table_id,
)
else:
@@ -817,6 +834,7 @@ class AsyncLanceNamespaceDBConnection:
storage_options=merged_storage_options,
storage_options_provider=provider,
location=location,
namespace_client=self._namespace_client,
)
lance_table = await asyncio.to_thread(_create_table)
@@ -837,7 +855,7 @@ class AsyncLanceNamespaceDBConnection:
namespace = []
table_id = namespace + [name]
request = DescribeTableRequest(id=table_id)
response = self._ns.describe_table(request)
response = self._namespace_client.describe_table(request)
# Merge storage options: self.storage_options < user options < namespace options
merged_storage_options = dict(self.storage_options)
@@ -849,10 +867,14 @@ class AsyncLanceNamespaceDBConnection:
# Create a storage options provider if not provided by user
if storage_options_provider is None and response.storage_options is not None:
storage_options_provider = LanceNamespaceStorageOptionsProvider(
namespace=self._ns,
namespace=self._namespace_client,
table_id=table_id,
)
# Capture managed_versioning from describe response.
# Convert None to False since we already have the answer from describe_table.
managed_versioning = response.managed_versioning is True
# Open table in a thread
def _open_table():
temp_conn = LanceDBConnection(
@@ -870,6 +892,8 @@ class AsyncLanceNamespaceDBConnection:
storage_options_provider=storage_options_provider,
index_cache_size=index_cache_size,
location=response.location,
namespace_client=self._namespace_client,
managed_versioning=managed_versioning,
)
lance_table = await asyncio.to_thread(_open_table)
@@ -881,7 +905,7 @@ class AsyncLanceNamespaceDBConnection:
namespace = []
table_id = namespace + [name]
request = DropTableRequest(id=table_id)
self._ns.drop_table(request)
self._namespace_client.drop_table(request)
async def rename_table(
self,
@@ -943,7 +967,7 @@ class AsyncLanceNamespaceDBConnection:
request = ListNamespacesRequest(
id=namespace, page_token=page_token, limit=limit
)
response = self._ns.list_namespaces(request)
response = self._namespace_client.list_namespaces(request)
return ListNamespacesResponse(
namespaces=response.namespaces if response.namespaces else [],
page_token=response.page_token,
@@ -978,7 +1002,7 @@ class AsyncLanceNamespaceDBConnection:
mode=_normalize_create_namespace_mode(mode),
properties=properties,
)
response = self._ns.create_namespace(request)
response = self._namespace_client.create_namespace(request)
return CreateNamespaceResponse(
properties=response.properties if hasattr(response, "properties") else None
)
@@ -1012,7 +1036,7 @@ class AsyncLanceNamespaceDBConnection:
mode=_normalize_drop_namespace_mode(mode),
behavior=_normalize_drop_namespace_behavior(behavior),
)
response = self._ns.drop_namespace(request)
response = self._namespace_client.drop_namespace(request)
return DropNamespaceResponse(
properties=(
response.properties if hasattr(response, "properties") else None
@@ -1039,7 +1063,7 @@ class AsyncLanceNamespaceDBConnection:
Response containing the namespace properties.
"""
request = DescribeNamespaceRequest(id=namespace)
response = self._ns.describe_namespace(request)
response = self._namespace_client.describe_namespace(request)
return DescribeNamespaceResponse(
properties=response.properties if hasattr(response, "properties") else None
)
@@ -1072,7 +1096,7 @@ class AsyncLanceNamespaceDBConnection:
if namespace is None:
namespace = []
request = ListTablesRequest(id=namespace, page_token=page_token, limit=limit)
response = self._ns.list_tables(request)
response = self._namespace_client.list_tables(request)
return ListTablesResponse(
tables=response.tables if response.tables else [],
page_token=response.page_token,

View File

@@ -640,6 +640,45 @@ class RemoteTable(Table):
def drop_index(self, index_name: str):
return LOOP.run(self._table.drop_index(index_name))
def prewarm_index(self, name: str) -> None:
"""Prewarm an index in the table.
This is a hint to the database that the index will be accessed in the
future and should be loaded into memory if possible. This can reduce
cold-start latency for subsequent queries.
This call initiates prewarming and returns once the request is accepted.
It is idempotent and safe to call from multiple clients concurrently.
Parameters
----------
name: str
The name of the index to prewarm
"""
return LOOP.run(self._table.prewarm_index(name))
def prewarm_data(self, columns: Optional[List[str]] = None) -> None:
"""Prewarm data for the table.
This is a hint to the database that the given columns will be accessed
in the future and the database should prefetch the data if possible.
Currently only supported on remote tables.
This call initiates prewarming and returns once the request is accepted.
It is idempotent and safe to call from multiple clients concurrently.
This operation has a large upfront cost but can speed up future queries
that need to fetch the given columns. Large columns such as embeddings
or binary data may not be practical to prewarm. This feature is intended
for workloads that issue many queries against the same columns.
Parameters
----------
columns: list of str, optional
The columns to prewarm. If None, all columns are prewarmed.
"""
return LOOP.run(self._table.prewarm_data(columns))
def wait_for_index(
self, index_names: Iterable[str], timeout: timedelta = timedelta(seconds=300)
):

View File

@@ -1506,22 +1506,17 @@ class Table(ABC):
in-progress operation (e.g. appending new data) and these files will not
be deleted unless they are at least 7 days old. If delete_unverified is True
then these files will be deleted regardless of their age.
.. warning::
This should only be set to True if you can guarantee that no other
process is currently working on this dataset. Otherwise the dataset
could be put into a corrupted state.
retrain: bool, default False
This parameter is no longer used and is deprecated.
Experimental API
----------------
The optimization process is undergoing active development and may change.
Our goal with these changes is to improve the performance of optimization and
reduce the complexity.
That being said, it is essential today to run optimize if you want the best
performance. It should be stable and safe to use in production, but it our
hope that the API may be simplified (or not even need to be called) in the
future.
The frequency an application shoudl call optimize is based on the frequency of
The frequency an application should call optimize is based on the frequency of
data modifications. If data is frequently added, deleted, or updated then
optimize should be run frequently. A good rule of thumb is to run optimize if
you have added or modified 100,000 or more records or run more than 20 data
@@ -1746,6 +1741,8 @@ class LanceTable(Table):
storage_options_provider: Optional["StorageOptionsProvider"] = None,
index_cache_size: Optional[int] = None,
location: Optional[str] = None,
namespace_client: Optional[Any] = None,
managed_versioning: Optional[bool] = None,
_async: AsyncTable = None,
):
if namespace is None:
@@ -1753,6 +1750,7 @@ class LanceTable(Table):
self._conn = connection
self._namespace = namespace
self._location = location # Store location for use in _dataset_path
self._namespace_client = namespace_client
if _async is not None:
self._table = _async
else:
@@ -1764,6 +1762,8 @@ class LanceTable(Table):
storage_options_provider=storage_options_provider,
index_cache_size=index_cache_size,
location=location,
namespace_client=namespace_client,
managed_versioning=managed_versioning,
)
)
@@ -1806,6 +1806,8 @@ class LanceTable(Table):
storage_options_provider: Optional["StorageOptionsProvider"] = None,
index_cache_size: Optional[int] = None,
location: Optional[str] = None,
namespace_client: Optional[Any] = None,
managed_versioning: Optional[bool] = None,
):
if namespace is None:
namespace = []
@@ -1817,6 +1819,8 @@ class LanceTable(Table):
storage_options_provider=storage_options_provider,
index_cache_size=index_cache_size,
location=location,
namespace_client=namespace_client,
managed_versioning=managed_versioning,
)
# check the dataset exists
@@ -1848,6 +1852,16 @@ class LanceTable(Table):
"Please install with `pip install pylance`."
)
if self._namespace_client is not None:
table_id = self._namespace + [self.name]
return lance.dataset(
version=self.version,
storage_options=self._conn.storage_options,
namespace=self._namespace_client,
table_id=table_id,
**kwargs,
)
return lance.dataset(
self._dataset_path,
version=self.version,
@@ -2200,12 +2214,18 @@ class LanceTable(Table):
def prewarm_index(self, name: str) -> None:
"""
Prewarms an index in the table
Prewarm an index in the table.
This loads the entire index into memory
This is a hint to the database that the index will be accessed in the
future and should be loaded into memory if possible. This can reduce
cold-start latency for subsequent queries.
If the index does not fit into the available cache this call
may be wasteful
This call initiates prewarming and returns once the request is accepted.
It is idempotent and safe to call from multiple clients concurrently.
It is generally wasteful to call this if the index does not fit into the
available cache. Not all index types support prewarming; unsupported
indices will silently ignore the request.
Parameters
----------
@@ -2214,6 +2234,29 @@ class LanceTable(Table):
"""
return LOOP.run(self._table.prewarm_index(name))
def prewarm_data(self, columns: Optional[List[str]] = None) -> None:
"""
Prewarm data for the table.
This is a hint to the database that the given columns will be accessed
in the future and the database should prefetch the data if possible.
Currently only supported on remote tables.
This call initiates prewarming and returns once the request is accepted.
It is idempotent and safe to call from multiple clients concurrently.
This operation has a large upfront cost but can speed up future queries
that need to fetch the given columns. Large columns such as embeddings
or binary data may not be practical to prewarm. This feature is intended
for workloads that issue many queries against the same columns.
Parameters
----------
columns: list of str, optional
The columns to prewarm. If None, all columns are prewarmed.
"""
return LOOP.run(self._table.prewarm_data(columns))
def wait_for_index(
self, index_names: Iterable[str], timeout: timedelta = timedelta(seconds=300)
) -> None:
@@ -2713,6 +2756,7 @@ class LanceTable(Table):
data_storage_version: Optional[str] = None,
enable_v2_manifest_paths: Optional[bool] = None,
location: Optional[str] = None,
namespace_client: Optional[Any] = None,
):
"""
Create a new table.
@@ -2773,6 +2817,7 @@ class LanceTable(Table):
self._conn = db
self._namespace = namespace
self._location = location
self._namespace_client = namespace_client
if data_storage_version is not None:
warnings.warn(
@@ -2997,22 +3042,17 @@ class LanceTable(Table):
in-progress operation (e.g. appending new data) and these files will not
be deleted unless they are at least 7 days old. If delete_unverified is True
then these files will be deleted regardless of their age.
.. warning::
This should only be set to True if you can guarantee that no other
process is currently working on this dataset. Otherwise the dataset
could be put into a corrupted state.
retrain: bool, default False
This parameter is no longer used and is deprecated.
Experimental API
----------------
The optimization process is undergoing active development and may change.
Our goal with these changes is to improve the performance of optimization and
reduce the complexity.
That being said, it is essential today to run optimize if you want the best
performance. It should be stable and safe to use in production, but it our
hope that the API may be simplified (or not even need to be called) in the
future.
The frequency an application shoudl call optimize is based on the frequency of
The frequency an application should call optimize is based on the frequency of
data modifications. If data is frequently added, deleted, or updated then
optimize should be run frequently. A good rule of thumb is to run optimize if
you have added or modified 100,000 or more records or run more than 20 data
@@ -3613,19 +3653,47 @@ class AsyncTable:
"""
Prewarm an index in the table.
This is a hint to the database that the index will be accessed in the
future and should be loaded into memory if possible. This can reduce
cold-start latency for subsequent queries.
This call initiates prewarming and returns once the request is accepted.
It is idempotent and safe to call from multiple clients concurrently.
It is generally wasteful to call this if the index does not fit into the
available cache. Not all index types support prewarming; unsupported
indices will silently ignore the request.
Parameters
----------
name: str
The name of the index to prewarm
Notes
-----
This will load the index into memory. This may reduce the cold-start time for
future queries. If the index does not fit in the cache then this call may be
wasteful.
"""
await self._inner.prewarm_index(name)
async def prewarm_data(self, columns: Optional[List[str]] = None) -> None:
"""
Prewarm data for the table.
This is a hint to the database that the given columns will be accessed
in the future and the database should prefetch the data if possible.
Currently only supported on remote tables.
This call initiates prewarming and returns once the request is accepted.
It is idempotent and safe to call from multiple clients concurrently.
This operation has a large upfront cost but can speed up future queries
that need to fetch the given columns. Large columns such as embeddings
or binary data may not be practical to prewarm. This feature is intended
for workloads that issue many queries against the same columns.
Parameters
----------
columns: list of str, optional
The columns to prewarm. If None, all columns are prewarmed.
"""
await self._inner.prewarm_data(columns)
async def wait_for_index(
self, index_names: Iterable[str], timeout: timedelta = timedelta(seconds=300)
) -> None:
@@ -4552,22 +4620,17 @@ class AsyncTable:
in-progress operation (e.g. appending new data) and these files will not
be deleted unless they are at least 7 days old. If delete_unverified is True
then these files will be deleted regardless of their age.
.. warning::
This should only be set to True if you can guarantee that no other
process is currently working on this dataset. Otherwise the dataset
could be put into a corrupted state.
retrain: bool, default False
This parameter is no longer used and is deprecated.
Experimental API
----------------
The optimization process is undergoing active development and may change.
Our goal with these changes is to improve the performance of optimization and
reduce the complexity.
That being said, it is essential today to run optimize if you want the best
performance. It should be stable and safe to use in production, but it our
hope that the API may be simplified (or not even need to be called) in the
future.
The frequency an application shoudl call optimize is based on the frequency of
The frequency an application should call optimize is based on the frequency of
data modifications. If data is frequently added, deleted, or updated then
optimize should be run frequently. A good rule of thumb is to run optimize if
you have added or modified 100,000 or more records or run more than 20 data

View File

@@ -147,7 +147,12 @@ class TrackingNamespace(LanceNamespace):
This simulates a credential rotation system where each call returns
new credentials that expire after credential_expires_in_seconds.
"""
modified = copy.deepcopy(storage_options) if storage_options else {}
# Start from base storage options (endpoint, region, allow_http, etc.)
# because DirectoryNamespace returns None for storage_options from
# describe_table/declare_table when no credential vendor is configured.
modified = copy.deepcopy(self.base_storage_options)
if storage_options:
modified.update(storage_options)
# Increment credentials to simulate rotation
modified["aws_access_key_id"] = f"AKID_{count}"

View File

@@ -326,6 +326,24 @@ def test_add_struct(mem_db: DBConnection):
table = mem_db.create_table("test2", schema=schema)
table.add(data)
struct_type = pa.struct(
[
("b", pa.int64()),
("a", pa.int64()),
]
)
expected = pa.table(
{
"s_list": [
[
pa.scalar({"b": 1, "a": 2}, type=struct_type),
pa.scalar({"b": 4, "a": None}, type=struct_type),
]
],
}
)
assert table.to_arrow() == expected
def test_add_subschema(mem_db: DBConnection):
schema = pa.schema(

View File

@@ -17,7 +17,8 @@ use pyo3::{
use pyo3_async_runtimes::tokio::future_into_py;
use crate::{
error::PythonErrorExt, storage_options::py_object_to_storage_options_provider, table::Table,
error::PythonErrorExt, namespace::extract_namespace_arc,
storage_options::py_object_to_storage_options_provider, table::Table,
};
#[pyclass]
@@ -182,7 +183,8 @@ impl Connection {
})
}
#[pyo3(signature = (name, namespace=vec![], storage_options = None, storage_options_provider=None, index_cache_size = None, location=None))]
#[allow(clippy::too_many_arguments)]
#[pyo3(signature = (name, namespace=vec![], storage_options = None, storage_options_provider=None, index_cache_size = None, location=None, namespace_client=None, managed_versioning=None))]
pub fn open_table(
self_: PyRef<'_, Self>,
name: String,
@@ -191,11 +193,13 @@ impl Connection {
storage_options_provider: Option<Py<PyAny>>,
index_cache_size: Option<u32>,
location: Option<String>,
namespace_client: Option<Py<PyAny>>,
managed_versioning: Option<bool>,
) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.get_inner()?.clone();
let mut builder = inner.open_table(name);
builder = builder.namespace(namespace);
builder = builder.namespace(namespace.clone());
if let Some(storage_options) = storage_options {
builder = builder.storage_options(storage_options);
}
@@ -209,6 +213,20 @@ impl Connection {
if let Some(location) = location {
builder = builder.location(location);
}
// Extract namespace client from Python object if provided
let ns_client = if let Some(ns_obj) = namespace_client {
let py = self_.py();
Some(extract_namespace_arc(py, ns_obj)?)
} else {
None
};
if let Some(ns_client) = ns_client {
builder = builder.namespace_client(ns_client);
}
// Pass managed_versioning if provided to avoid redundant describe_table call
if let Some(enabled) = managed_versioning {
builder = builder.managed_versioning(enabled);
}
future_into_py(self_.py(), async move {
let table = builder.execute().await.infer_error()?;

View File

@@ -23,6 +23,7 @@ pub mod connection;
pub mod error;
pub mod header;
pub mod index;
pub mod namespace;
pub mod permutation;
pub mod query;
pub mod session;

696
python/src/namespace.rs Normal file
View File

@@ -0,0 +1,696 @@
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
//! Namespace utilities for Python bindings
use std::collections::HashMap;
use std::sync::Arc;
use async_trait::async_trait;
use bytes::Bytes;
use lance_namespace::LanceNamespace as LanceNamespaceTrait;
use lance_namespace::models::*;
use pyo3::prelude::*;
use pyo3::types::PyDict;
/// Wrapper that allows any Python object implementing LanceNamespace protocol
/// to be used as a Rust LanceNamespace.
///
/// This is similar to PyLanceNamespace in lance's Python bindings - it wraps a Python
/// object and calls back into Python when namespace methods are invoked.
pub struct PyLanceNamespace {
py_namespace: Arc<Py<PyAny>>,
namespace_id: String,
}
impl PyLanceNamespace {
/// Create a new PyLanceNamespace wrapper around a Python namespace object.
pub fn new(_py: Python<'_>, py_namespace: &Bound<'_, PyAny>) -> PyResult<Self> {
let namespace_id = py_namespace
.call_method0("namespace_id")?
.extract::<String>()?;
Ok(Self {
py_namespace: Arc::new(py_namespace.clone().unbind()),
namespace_id,
})
}
/// Create an Arc<dyn LanceNamespace> from a Python namespace object.
pub fn create_arc(
py: Python<'_>,
py_namespace: &Bound<'_, PyAny>,
) -> PyResult<Arc<dyn LanceNamespaceTrait>> {
let wrapper = Self::new(py, py_namespace)?;
Ok(Arc::new(wrapper))
}
}
impl std::fmt::Debug for PyLanceNamespace {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
write!(f, "PyLanceNamespace {{ id: {} }}", self.namespace_id)
}
}
/// Get or create the DictWithModelDump class in Python.
/// This class acts like a dict but also has model_dump() method.
/// This allows it to work with both:
/// - depythonize (which expects a dict/Mapping)
/// - Python code that calls .model_dump() (like DirectoryNamespace wrapper)
fn get_dict_with_model_dump_class(py: Python<'_>) -> PyResult<Bound<'_, PyAny>> {
// Use a module-level cache via __builtins__
let builtins = py.import("builtins")?;
if builtins.hasattr("_DictWithModelDump")? {
return builtins.getattr("_DictWithModelDump");
}
// Create the class using exec
let locals = PyDict::new(py);
py.run(
c"class DictWithModelDump(dict):
def model_dump(self):
return dict(self)",
None,
Some(&locals),
)?;
let class = locals.get_item("DictWithModelDump")?.ok_or_else(|| {
pyo3::exceptions::PyRuntimeError::new_err("Failed to create DictWithModelDump class")
})?;
// Cache it
builtins.setattr("_DictWithModelDump", &class)?;
Ok(class)
}
/// Helper to call a Python namespace method with JSON serialization.
/// For methods that take a request and return a response.
/// Uses DictWithModelDump to pass a dict that also has model_dump() method,
/// making it compatible with both depythonize and Python wrappers.
async fn call_py_method<Req, Resp>(
py_namespace: Arc<Py<PyAny>>,
method_name: &'static str,
request: Req,
) -> lance_core::Result<Resp>
where
Req: serde::Serialize + Send + 'static,
Resp: serde::de::DeserializeOwned + Send + 'static,
{
let request_json = serde_json::to_string(&request).map_err(|e| {
lance_core::Error::io(format!(
"Failed to serialize request for {}: {}",
method_name, e
))
})?;
let response_json = tokio::task::spawn_blocking(move || {
Python::attach(|py| {
let json_module = py.import("json")?;
let request_dict = json_module.call_method1("loads", (&request_json,))?;
// Wrap dict in DictWithModelDump so it works with both depythonize and .model_dump()
let dict_class = get_dict_with_model_dump_class(py)?;
let request_arg = dict_class.call1((request_dict,))?;
// Call the Python method
let result = py_namespace.call_method1(py, method_name, (request_arg,))?;
// Convert response to dict, then to JSON
// Pydantic models have model_dump() method
let result_dict = if result.bind(py).hasattr("model_dump")? {
result.call_method0(py, "model_dump")?
} else {
result
};
let response_json: String = json_module
.call_method1("dumps", (result_dict,))?
.extract()?;
Ok::<_, PyErr>(response_json)
})
})
.await
.map_err(|e| lance_core::Error::io(format!("Task join error for {}: {}", method_name, e)))?
.map_err(|e: PyErr| lance_core::Error::io(format!("Python error in {}: {}", method_name, e)))?;
serde_json::from_str(&response_json).map_err(|e| {
lance_core::Error::io(format!(
"Failed to deserialize response from {}: {}",
method_name, e
))
})
}
/// Helper for methods that return () on success
async fn call_py_method_unit<Req>(
py_namespace: Arc<Py<PyAny>>,
method_name: &'static str,
request: Req,
) -> lance_core::Result<()>
where
Req: serde::Serialize + Send + 'static,
{
let request_json = serde_json::to_string(&request).map_err(|e| {
lance_core::Error::io(format!(
"Failed to serialize request for {}: {}",
method_name, e
))
})?;
tokio::task::spawn_blocking(move || {
Python::attach(|py| {
let json_module = py.import("json")?;
let request_dict = json_module.call_method1("loads", (&request_json,))?;
// Wrap dict in DictWithModelDump
let dict_class = get_dict_with_model_dump_class(py)?;
let request_arg = dict_class.call1((request_dict,))?;
// Call the Python method
py_namespace.call_method1(py, method_name, (request_arg,))?;
Ok::<_, PyErr>(())
})
})
.await
.map_err(|e| lance_core::Error::io(format!("Task join error for {}: {}", method_name, e)))?
.map_err(|e: PyErr| lance_core::Error::io(format!("Python error in {}: {}", method_name, e)))
}
/// Helper for methods that return a primitive type
async fn call_py_method_primitive<Req, Resp>(
py_namespace: Arc<Py<PyAny>>,
method_name: &'static str,
request: Req,
) -> lance_core::Result<Resp>
where
Req: serde::Serialize + Send + 'static,
Resp: for<'py> pyo3::FromPyObject<'py> + Send + 'static,
{
let request_json = serde_json::to_string(&request).map_err(|e| {
lance_core::Error::io(format!(
"Failed to serialize request for {}: {}",
method_name, e
))
})?;
tokio::task::spawn_blocking(move || {
Python::attach(|py| {
let json_module = py.import("json")?;
let request_dict = json_module.call_method1("loads", (&request_json,))?;
// Wrap dict in DictWithModelDump
let dict_class = get_dict_with_model_dump_class(py)?;
let request_arg = dict_class.call1((request_dict,))?;
// Call the Python method
let result = py_namespace.call_method1(py, method_name, (request_arg,))?;
let value: Resp = result.extract(py)?;
Ok::<_, PyErr>(value)
})
})
.await
.map_err(|e| lance_core::Error::io(format!("Task join error for {}: {}", method_name, e)))?
.map_err(|e: PyErr| lance_core::Error::io(format!("Python error in {}: {}", method_name, e)))
}
/// Helper for methods that return Bytes
async fn call_py_method_bytes<Req>(
py_namespace: Arc<Py<PyAny>>,
method_name: &'static str,
request: Req,
) -> lance_core::Result<Bytes>
where
Req: serde::Serialize + Send + 'static,
{
let request_json = serde_json::to_string(&request).map_err(|e| {
lance_core::Error::io(format!(
"Failed to serialize request for {}: {}",
method_name, e
))
})?;
tokio::task::spawn_blocking(move || {
Python::attach(|py| {
let json_module = py.import("json")?;
let request_dict = json_module.call_method1("loads", (&request_json,))?;
// Wrap dict in DictWithModelDump
let dict_class = get_dict_with_model_dump_class(py)?;
let request_arg = dict_class.call1((request_dict,))?;
// Call the Python method
let result = py_namespace.call_method1(py, method_name, (request_arg,))?;
let bytes_data: Vec<u8> = result.extract(py)?;
Ok::<_, PyErr>(Bytes::from(bytes_data))
})
})
.await
.map_err(|e| lance_core::Error::io(format!("Task join error for {}: {}", method_name, e)))?
.map_err(|e: PyErr| lance_core::Error::io(format!("Python error in {}: {}", method_name, e)))
}
/// Helper for methods that take request + data and return a response
async fn call_py_method_with_data<Req, Resp>(
py_namespace: Arc<Py<PyAny>>,
method_name: &'static str,
request: Req,
data: Bytes,
) -> lance_core::Result<Resp>
where
Req: serde::Serialize + Send + 'static,
Resp: serde::de::DeserializeOwned + Send + 'static,
{
let request_json = serde_json::to_string(&request).map_err(|e| {
lance_core::Error::io(format!(
"Failed to serialize request for {}: {}",
method_name, e
))
})?;
let response_json = tokio::task::spawn_blocking(move || {
Python::attach(|py| {
let json_module = py.import("json")?;
let request_dict = json_module.call_method1("loads", (&request_json,))?;
// Wrap dict in DictWithModelDump
let dict_class = get_dict_with_model_dump_class(py)?;
let request_arg = dict_class.call1((request_dict,))?;
// Pass request and bytes to Python method
let py_bytes = pyo3::types::PyBytes::new(py, &data);
let result = py_namespace.call_method1(py, method_name, (request_arg, py_bytes))?;
// Convert response dict to JSON
let response_json: String = json_module.call_method1("dumps", (result,))?.extract()?;
Ok::<_, PyErr>(response_json)
})
})
.await
.map_err(|e| lance_core::Error::io(format!("Task join error for {}: {}", method_name, e)))?
.map_err(|e: PyErr| lance_core::Error::io(format!("Python error in {}: {}", method_name, e)))?;
serde_json::from_str(&response_json).map_err(|e| {
lance_core::Error::io(format!(
"Failed to deserialize response from {}: {}",
method_name, e
))
})
}
#[async_trait]
impl LanceNamespaceTrait for PyLanceNamespace {
fn namespace_id(&self) -> String {
self.namespace_id.clone()
}
async fn list_namespaces(
&self,
request: ListNamespacesRequest,
) -> lance_core::Result<ListNamespacesResponse> {
call_py_method(self.py_namespace.clone(), "list_namespaces", request).await
}
async fn describe_namespace(
&self,
request: DescribeNamespaceRequest,
) -> lance_core::Result<DescribeNamespaceResponse> {
call_py_method(self.py_namespace.clone(), "describe_namespace", request).await
}
async fn create_namespace(
&self,
request: CreateNamespaceRequest,
) -> lance_core::Result<CreateNamespaceResponse> {
call_py_method(self.py_namespace.clone(), "create_namespace", request).await
}
async fn drop_namespace(
&self,
request: DropNamespaceRequest,
) -> lance_core::Result<DropNamespaceResponse> {
call_py_method(self.py_namespace.clone(), "drop_namespace", request).await
}
async fn namespace_exists(&self, request: NamespaceExistsRequest) -> lance_core::Result<()> {
call_py_method_unit(self.py_namespace.clone(), "namespace_exists", request).await
}
async fn list_tables(
&self,
request: ListTablesRequest,
) -> lance_core::Result<ListTablesResponse> {
call_py_method(self.py_namespace.clone(), "list_tables", request).await
}
async fn describe_table(
&self,
request: DescribeTableRequest,
) -> lance_core::Result<DescribeTableResponse> {
call_py_method(self.py_namespace.clone(), "describe_table", request).await
}
async fn register_table(
&self,
request: RegisterTableRequest,
) -> lance_core::Result<RegisterTableResponse> {
call_py_method(self.py_namespace.clone(), "register_table", request).await
}
async fn table_exists(&self, request: TableExistsRequest) -> lance_core::Result<()> {
call_py_method_unit(self.py_namespace.clone(), "table_exists", request).await
}
async fn drop_table(&self, request: DropTableRequest) -> lance_core::Result<DropTableResponse> {
call_py_method(self.py_namespace.clone(), "drop_table", request).await
}
async fn deregister_table(
&self,
request: DeregisterTableRequest,
) -> lance_core::Result<DeregisterTableResponse> {
call_py_method(self.py_namespace.clone(), "deregister_table", request).await
}
async fn count_table_rows(&self, request: CountTableRowsRequest) -> lance_core::Result<i64> {
call_py_method_primitive(self.py_namespace.clone(), "count_table_rows", request).await
}
async fn create_table(
&self,
request: CreateTableRequest,
request_data: Bytes,
) -> lance_core::Result<CreateTableResponse> {
call_py_method_with_data(
self.py_namespace.clone(),
"create_table",
request,
request_data,
)
.await
}
async fn declare_table(
&self,
request: DeclareTableRequest,
) -> lance_core::Result<DeclareTableResponse> {
call_py_method(self.py_namespace.clone(), "declare_table", request).await
}
async fn insert_into_table(
&self,
request: InsertIntoTableRequest,
request_data: Bytes,
) -> lance_core::Result<InsertIntoTableResponse> {
call_py_method_with_data(
self.py_namespace.clone(),
"insert_into_table",
request,
request_data,
)
.await
}
async fn merge_insert_into_table(
&self,
request: MergeInsertIntoTableRequest,
request_data: Bytes,
) -> lance_core::Result<MergeInsertIntoTableResponse> {
call_py_method_with_data(
self.py_namespace.clone(),
"merge_insert_into_table",
request,
request_data,
)
.await
}
async fn update_table(
&self,
request: UpdateTableRequest,
) -> lance_core::Result<UpdateTableResponse> {
call_py_method(self.py_namespace.clone(), "update_table", request).await
}
async fn delete_from_table(
&self,
request: DeleteFromTableRequest,
) -> lance_core::Result<DeleteFromTableResponse> {
call_py_method(self.py_namespace.clone(), "delete_from_table", request).await
}
async fn query_table(&self, request: QueryTableRequest) -> lance_core::Result<Bytes> {
call_py_method_bytes(self.py_namespace.clone(), "query_table", request).await
}
async fn create_table_index(
&self,
request: CreateTableIndexRequest,
) -> lance_core::Result<CreateTableIndexResponse> {
call_py_method(self.py_namespace.clone(), "create_table_index", request).await
}
async fn list_table_indices(
&self,
request: ListTableIndicesRequest,
) -> lance_core::Result<ListTableIndicesResponse> {
call_py_method(self.py_namespace.clone(), "list_table_indices", request).await
}
async fn describe_table_index_stats(
&self,
request: DescribeTableIndexStatsRequest,
) -> lance_core::Result<DescribeTableIndexStatsResponse> {
call_py_method(
self.py_namespace.clone(),
"describe_table_index_stats",
request,
)
.await
}
async fn describe_transaction(
&self,
request: DescribeTransactionRequest,
) -> lance_core::Result<DescribeTransactionResponse> {
call_py_method(self.py_namespace.clone(), "describe_transaction", request).await
}
async fn alter_transaction(
&self,
request: AlterTransactionRequest,
) -> lance_core::Result<AlterTransactionResponse> {
call_py_method(self.py_namespace.clone(), "alter_transaction", request).await
}
async fn create_table_scalar_index(
&self,
request: CreateTableIndexRequest,
) -> lance_core::Result<CreateTableScalarIndexResponse> {
call_py_method(
self.py_namespace.clone(),
"create_table_scalar_index",
request,
)
.await
}
async fn drop_table_index(
&self,
request: DropTableIndexRequest,
) -> lance_core::Result<DropTableIndexResponse> {
call_py_method(self.py_namespace.clone(), "drop_table_index", request).await
}
async fn list_all_tables(
&self,
request: ListTablesRequest,
) -> lance_core::Result<ListTablesResponse> {
call_py_method(self.py_namespace.clone(), "list_all_tables", request).await
}
async fn restore_table(
&self,
request: RestoreTableRequest,
) -> lance_core::Result<RestoreTableResponse> {
call_py_method(self.py_namespace.clone(), "restore_table", request).await
}
async fn rename_table(
&self,
request: RenameTableRequest,
) -> lance_core::Result<RenameTableResponse> {
call_py_method(self.py_namespace.clone(), "rename_table", request).await
}
async fn list_table_versions(
&self,
request: ListTableVersionsRequest,
) -> lance_core::Result<ListTableVersionsResponse> {
call_py_method(self.py_namespace.clone(), "list_table_versions", request).await
}
async fn create_table_version(
&self,
request: CreateTableVersionRequest,
) -> lance_core::Result<CreateTableVersionResponse> {
call_py_method(self.py_namespace.clone(), "create_table_version", request).await
}
async fn describe_table_version(
&self,
request: DescribeTableVersionRequest,
) -> lance_core::Result<DescribeTableVersionResponse> {
call_py_method(self.py_namespace.clone(), "describe_table_version", request).await
}
async fn batch_delete_table_versions(
&self,
request: BatchDeleteTableVersionsRequest,
) -> lance_core::Result<BatchDeleteTableVersionsResponse> {
call_py_method(
self.py_namespace.clone(),
"batch_delete_table_versions",
request,
)
.await
}
async fn update_table_schema_metadata(
&self,
request: UpdateTableSchemaMetadataRequest,
) -> lance_core::Result<UpdateTableSchemaMetadataResponse> {
call_py_method(
self.py_namespace.clone(),
"update_table_schema_metadata",
request,
)
.await
}
async fn get_table_stats(
&self,
request: GetTableStatsRequest,
) -> lance_core::Result<GetTableStatsResponse> {
call_py_method(self.py_namespace.clone(), "get_table_stats", request).await
}
async fn explain_table_query_plan(
&self,
request: ExplainTableQueryPlanRequest,
) -> lance_core::Result<String> {
call_py_method_primitive(
self.py_namespace.clone(),
"explain_table_query_plan",
request,
)
.await
}
async fn analyze_table_query_plan(
&self,
request: AnalyzeTableQueryPlanRequest,
) -> lance_core::Result<String> {
call_py_method_primitive(
self.py_namespace.clone(),
"analyze_table_query_plan",
request,
)
.await
}
async fn alter_table_add_columns(
&self,
request: AlterTableAddColumnsRequest,
) -> lance_core::Result<AlterTableAddColumnsResponse> {
call_py_method(
self.py_namespace.clone(),
"alter_table_add_columns",
request,
)
.await
}
async fn alter_table_alter_columns(
&self,
request: AlterTableAlterColumnsRequest,
) -> lance_core::Result<AlterTableAlterColumnsResponse> {
call_py_method(
self.py_namespace.clone(),
"alter_table_alter_columns",
request,
)
.await
}
async fn alter_table_drop_columns(
&self,
request: AlterTableDropColumnsRequest,
) -> lance_core::Result<AlterTableDropColumnsResponse> {
call_py_method(
self.py_namespace.clone(),
"alter_table_drop_columns",
request,
)
.await
}
async fn list_table_tags(
&self,
request: ListTableTagsRequest,
) -> lance_core::Result<ListTableTagsResponse> {
call_py_method(self.py_namespace.clone(), "list_table_tags", request).await
}
async fn create_table_tag(
&self,
request: CreateTableTagRequest,
) -> lance_core::Result<CreateTableTagResponse> {
call_py_method(self.py_namespace.clone(), "create_table_tag", request).await
}
async fn delete_table_tag(
&self,
request: DeleteTableTagRequest,
) -> lance_core::Result<DeleteTableTagResponse> {
call_py_method(self.py_namespace.clone(), "delete_table_tag", request).await
}
async fn update_table_tag(
&self,
request: UpdateTableTagRequest,
) -> lance_core::Result<UpdateTableTagResponse> {
call_py_method(self.py_namespace.clone(), "update_table_tag", request).await
}
async fn get_table_tag_version(
&self,
request: GetTableTagVersionRequest,
) -> lance_core::Result<GetTableTagVersionResponse> {
call_py_method(self.py_namespace.clone(), "get_table_tag_version", request).await
}
}
/// Convert Python dict to HashMap<String, String>
#[allow(dead_code)]
fn dict_to_hashmap(dict: &Bound<'_, PyDict>) -> PyResult<HashMap<String, String>> {
let mut map = HashMap::new();
for (key, value) in dict.iter() {
let key_str: String = key.extract()?;
let value_str: String = value.extract()?;
map.insert(key_str, value_str);
}
Ok(map)
}
/// Extract an Arc<dyn LanceNamespace> from a Python namespace object.
///
/// This function wraps any Python namespace object with PyLanceNamespace.
/// The PyLanceNamespace wrapper uses DictWithModelDump to pass requests,
/// which works with both:
/// - Native namespaces (DirectoryNamespace, RestNamespace) that use depythonize (expects dict)
/// - Custom Python implementations that call .model_dump() on the request
pub fn extract_namespace_arc(
py: Python<'_>,
ns: Py<PyAny>,
) -> PyResult<Arc<dyn LanceNamespaceTrait>> {
let ns_ref = ns.bind(py);
PyLanceNamespace::create_arc(py, ns_ref)
}

View File

@@ -316,6 +316,19 @@ impl<'py> IntoPyObject<'py> for PySelect {
Select::All => Ok(py.None().into_bound(py).into_any()),
Select::Columns(columns) => Ok(columns.into_pyobject(py)?.into_any()),
Select::Dynamic(columns) => Ok(columns.into_pyobject(py)?.into_any()),
Select::Expr(pairs) => {
// Serialize DataFusion Expr -> SQL string so Python sees the same
// format as Select::Dynamic: a list of (name, sql_string) tuples.
let sql_pairs: PyResult<Vec<(String, String)>> = pairs
.into_iter()
.map(|(name, expr)| {
lancedb::expr::expr_to_sql_string(&expr)
.map(|sql| (name, sql))
.map_err(|e| PyRuntimeError::new_err(e.to_string()))
})
.collect();
Ok(sql_pairs?.into_pyobject(py)?.into_any())
}
}
}
}

View File

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

View File

@@ -426,6 +426,17 @@ impl Table {
})
}
pub fn prewarm_data(
self_: PyRef<'_, Self>,
columns: Option<Vec<String>>,
) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
inner.prewarm_data(columns).await.infer_error()?;
Ok(())
})
}
pub fn list_indices(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {

4
python/uv.lock generated
View File

@@ -2006,7 +2006,7 @@ requires-dist = [
{ name = "botocore", marker = "extra == 'embeddings'", specifier = ">=1.31.57" },
{ name = "cohere", marker = "extra == 'embeddings'" },
{ name = "colpali-engine", marker = "extra == 'embeddings'", specifier = ">=0.3.10" },
{ name = "datafusion", marker = "extra == 'tests'" },
{ name = "datafusion", marker = "extra == 'tests'", specifier = "<52" },
{ name = "deprecation" },
{ name = "duckdb", marker = "extra == 'tests'" },
{ name = "google-generativeai", marker = "extra == 'embeddings'" },
@@ -2035,7 +2035,7 @@ requires-dist = [
{ name = "pyarrow-stubs", marker = "extra == 'tests'" },
{ name = "pydantic", specifier = ">=1.10" },
{ name = "pylance", marker = "extra == 'pylance'", specifier = ">=1.0.0b14" },
{ name = "pylance", marker = "extra == 'tests'", specifier = ">=1.0.0b14" },
{ name = "pylance", marker = "extra == 'tests'", specifier = ">=1.0.0b14,<3.0.0" },
{ name = "pyright", marker = "extra == 'dev'" },
{ name = "pytest", marker = "extra == 'tests'" },
{ name = "pytest-asyncio", marker = "extra == 'tests'" },

View File

@@ -1,6 +1,6 @@
[package]
name = "lancedb"
version = "0.27.0-beta.3"
version = "0.27.0-beta.5"
edition.workspace = true
description = "LanceDB: A serverless, low-latency vector database for AI applications"
license.workspace = true

View File

@@ -1,4 +1,4 @@
# LanceDB Rust
# LanceDB Rust SDK
<a href="https://crates.io/crates/vectordb">![img](https://img.shields.io/crates/v/vectordb)</a>
<a href="https://docs.rs/vectordb/latest/vectordb/">![Docs.rs](https://img.shields.io/docsrs/vectordb)</a>

View File

@@ -136,6 +136,7 @@ impl OpenTableBuilder {
lance_read_params: None,
location: None,
namespace_client: None,
managed_versioning: None,
},
embedding_registry,
}
@@ -235,6 +236,29 @@ impl OpenTableBuilder {
self
}
/// Set a namespace client for managed versioning support.
///
/// When a namespace client is provided and the table has `managed_versioning` enabled,
/// the table will use the namespace's commit handler to notify the namespace of
/// version changes. This enables features like event emission for table modifications.
pub fn namespace_client(mut self, client: Arc<dyn lance_namespace::LanceNamespace>) -> Self {
self.request.namespace_client = Some(client);
self
}
/// Set whether managed versioning is enabled for this table.
///
/// When set to `Some(true)`, the table will use namespace-managed commits.
/// When set to `Some(false)`, the table will use local commits even if namespace_client is set.
/// When set to `None` (default), the value will be fetched from the namespace if namespace_client is set.
///
/// This is typically set when the caller has already queried the namespace and knows the
/// managed_versioning status, avoiding a redundant describe_table call.
pub fn managed_versioning(mut self, enabled: bool) -> Self {
self.request.managed_versioning = Some(enabled);
self
}
/// Open the table
pub async fn execute(self) -> Result<Table> {
let table = self.parent.open_table(self.request).await?;
@@ -294,6 +318,12 @@ impl CloneTableBuilder {
self
}
/// Set a namespace client for managed versioning support.
pub fn namespace_client(mut self, client: Arc<dyn lance_namespace::LanceNamespace>) -> Self {
self.request.namespace_client = Some(client);
self
}
/// Execute the clone operation
pub async fn execute(self) -> Result<Table> {
let parent = self.parent.clone();

View File

@@ -66,6 +66,10 @@ pub struct OpenTableRequest {
/// Optional namespace client for server-side query execution.
/// When set, queries will be executed on the namespace server instead of locally.
pub namespace_client: Option<Arc<dyn LanceNamespace>>,
/// Whether managed versioning is enabled for this table.
/// When Some(true), the table will use namespace-managed commits instead of local commits.
/// When None and namespace_client is provided, the value will be fetched from the namespace.
pub managed_versioning: Option<bool>,
}
impl std::fmt::Debug for OpenTableRequest {
@@ -77,6 +81,7 @@ impl std::fmt::Debug for OpenTableRequest {
.field("lance_read_params", &self.lance_read_params)
.field("location", &self.location)
.field("namespace_client", &self.namespace_client)
.field("managed_versioning", &self.managed_versioning)
.finish()
}
}
@@ -161,6 +166,9 @@ pub struct CloneTableRequest {
/// Whether to perform a shallow clone (true) or deep clone (false). Defaults to true.
/// Currently only shallow clone is supported.
pub is_shallow: bool,
/// Optional namespace client for managed versioning support.
/// When set, enables the commit handler to track table versions through the namespace.
pub namespace_client: Option<Arc<dyn LanceNamespace>>,
}
impl CloneTableRequest {
@@ -172,6 +180,7 @@ impl CloneTableRequest {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
}
}
}

View File

@@ -669,6 +669,7 @@ impl ListingDatabase {
lance_read_params: None,
location: None,
namespace_client: None,
managed_versioning: None,
};
let req = (callback)(req);
let table = self.open_table(req).await?;
@@ -869,6 +870,7 @@ impl Database for ListingDatabase {
Some(write_params),
self.read_consistency_interval,
request.namespace_client,
false, // server_side_query_enabled - listing database doesn't support server-side queries
)
.await
{
@@ -946,7 +948,9 @@ impl Database for ListingDatabase {
self.store_wrapper.clone(),
None,
self.read_consistency_interval,
None,
request.namespace_client,
false, // server_side_query_enabled - listing database doesn't support server-side queries
None, // managed_versioning - will be queried if namespace_client is provided
)
.await?;
@@ -1022,6 +1026,8 @@ impl Database for ListingDatabase {
Some(read_params),
self.read_consistency_interval,
request.namespace_client,
false, // server_side_query_enabled - listing database doesn't support server-side queries
request.managed_versioning, // Pass through managed_versioning from request
)
.await?,
);
@@ -1162,6 +1168,7 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await
.unwrap();
@@ -1222,6 +1229,7 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await
.unwrap();
@@ -1281,6 +1289,7 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await;
@@ -1317,6 +1326,7 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: false, // Request deep clone
namespace_client: None,
})
.await;
@@ -1357,6 +1367,7 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await;
@@ -1397,6 +1408,7 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await;
@@ -1416,6 +1428,7 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await;
@@ -1452,6 +1465,7 @@ mod tests {
source_version: Some(1),
source_tag: Some("v1.0".to_string()),
is_shallow: true,
namespace_client: None,
})
.await;
@@ -1525,6 +1539,7 @@ mod tests {
source_version: Some(initial_version),
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await
.unwrap();
@@ -1603,6 +1618,7 @@ mod tests {
source_version: None,
source_tag: Some("v1.0".to_string()),
is_shallow: true,
namespace_client: None,
})
.await
.unwrap();
@@ -1654,6 +1670,7 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await
.unwrap();
@@ -1746,6 +1763,7 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await
.unwrap();

View File

@@ -7,18 +7,20 @@ use std::collections::HashMap;
use std::sync::Arc;
use async_trait::async_trait;
use lance::io::commit::namespace_manifest::LanceNamespaceExternalManifestStore;
use lance_io::object_store::{ObjectStoreParams, StorageOptionsAccessor};
use lance_namespace::{
LanceNamespace,
models::{
CreateEmptyTableRequest, CreateNamespaceRequest, CreateNamespaceResponse,
DeclareTableRequest, DescribeNamespaceRequest, DescribeNamespaceResponse,
DescribeTableRequest, DropNamespaceRequest, DropNamespaceResponse, DropTableRequest,
ListNamespacesRequest, ListNamespacesResponse, ListTablesRequest, ListTablesResponse,
CreateNamespaceRequest, CreateNamespaceResponse, DeclareTableRequest,
DescribeNamespaceRequest, DescribeNamespaceResponse, DescribeTableRequest,
DropNamespaceRequest, DropNamespaceResponse, DropTableRequest, ListNamespacesRequest,
ListNamespacesResponse, ListTablesRequest, ListTablesResponse,
},
};
use lance_namespace_impls::ConnectBuilder;
use log::warn;
use lance_table::io::commit::CommitHandler;
use lance_table::io::commit::external_manifest::ExternalManifestCommitHandler;
use crate::database::ReadConsistency;
use crate::error::{Error, Result};
@@ -206,83 +208,48 @@ impl Database for LanceNamespaceDatabase {
let mut table_id = request.namespace.clone();
table_id.push(request.name.clone());
// Try declare_table first, falling back to create_empty_table for backwards
// compatibility with older namespace clients that don't support declare_table
let declare_request = DeclareTableRequest {
id: Some(table_id.clone()),
..Default::default()
};
let (location, initial_storage_options) =
match self.namespace.declare_table(declare_request).await {
Ok(response) => {
let loc = response.location.ok_or_else(|| Error::Runtime {
message: "Table location is missing from declare_table response"
.to_string(),
})?;
// Use storage options from response, fall back to self.storage_options
let opts = response
.storage_options
.or_else(|| Some(self.storage_options.clone()))
.filter(|o| !o.is_empty());
(loc, opts)
}
Err(e) => {
// Check if the error is "not supported" and try create_empty_table as fallback
let err_str = e.to_string().to_lowercase();
if err_str.contains("not supported") || err_str.contains("not implemented") {
warn!(
"declare_table is not supported by the namespace client, \
falling back to deprecated create_empty_table. \
create_empty_table is deprecated and will be removed in Lance 3.0.0. \
Please upgrade your namespace client to support declare_table."
);
#[allow(deprecated)]
let create_empty_request = CreateEmptyTableRequest {
id: Some(table_id.clone()),
..Default::default()
};
let (location, initial_storage_options, managed_versioning) = {
let response = self.namespace.declare_table(declare_request).await?;
let loc = response.location.ok_or_else(|| Error::Runtime {
message: "Table location is missing from declare_table response".to_string(),
})?;
// Use storage options from response, fall back to self.storage_options
let opts = response
.storage_options
.or_else(|| Some(self.storage_options.clone()))
.filter(|o| !o.is_empty());
(loc, opts, response.managed_versioning)
};
#[allow(deprecated)]
let create_response = self
.namespace
.create_empty_table(create_empty_request)
.await
.map_err(|e| Error::Runtime {
message: format!("Failed to create empty table: {}", e),
})?;
// Build write params with storage options and commit handler
let mut params = request.write_options.lance_write_params.unwrap_or_default();
let loc = create_response.location.ok_or_else(|| Error::Runtime {
message: "Table location is missing from create_empty_table response"
.to_string(),
})?;
// For deprecated path, use self.storage_options
let opts = if self.storage_options.is_empty() {
None
} else {
Some(self.storage_options.clone())
};
(loc, opts)
} else {
return Err(Error::Runtime {
message: format!("Failed to declare table: {}", e),
});
}
}
};
let write_params = if let Some(storage_opts) = initial_storage_options {
let mut params = request.write_options.lance_write_params.unwrap_or_default();
// Set up storage options if provided
if let Some(storage_opts) = initial_storage_options {
let store_params = params
.store_params
.get_or_insert_with(ObjectStoreParams::default);
store_params.storage_options_accessor = Some(Arc::new(
StorageOptionsAccessor::with_static_options(storage_opts),
));
Some(params)
} else {
request.write_options.lance_write_params
};
}
// Set up commit handler when managed_versioning is enabled
if managed_versioning == Some(true) {
let external_store =
LanceNamespaceExternalManifestStore::new(self.namespace.clone(), table_id.clone());
let commit_handler: Arc<dyn CommitHandler> = Arc::new(ExternalManifestCommitHandler {
external_manifest_store: Arc::new(external_store),
});
params.commit_handler = Some(commit_handler);
}
let write_params = Some(params);
let native_table = NativeTable::create_from_namespace(
self.namespace.clone(),

View File

@@ -339,6 +339,12 @@ impl PermutationReader {
}
Ok(false)
}
Select::Expr(columns) => {
// For Expr projections, we check if any alias is _rowid.
// We can't validate the expression itself (it may differ from _rowid)
// but we allow it through; the column will be included.
Ok(columns.iter().any(|(alias, _)| alias == ROW_ID))
}
}
}

View File

@@ -47,6 +47,25 @@ pub enum Select {
///
/// See [`Query::select`] for more details and examples
Dynamic(Vec<(String, String)>),
/// Advanced selection using type-safe DataFusion expressions
///
/// Similar to [`Select::Dynamic`] but uses [`datafusion_expr::Expr`] instead of
/// raw SQL strings. Use [`crate::expr`] helpers to build expressions:
///
/// ```
/// use lancedb::expr::{col, lit};
/// use lancedb::query::Select;
///
/// // SELECT id, id * 2 AS id2 FROM ...
/// let selection = Select::expr_projection(&[
/// ("id", col("id")),
/// ("id2", col("id") * lit(2)),
/// ]);
/// ```
///
/// Note: For remote/server-side queries the expressions are serialized to SQL strings
/// automatically (same as [`Select::Dynamic`]).
Expr(Vec<(String, datafusion_expr::Expr)>),
}
impl Select {
@@ -69,6 +88,29 @@ impl Select {
.collect(),
)
}
/// Create a typed-expression projection.
///
/// This is a convenience method for creating a [`Select::Expr`] variant from
/// a slice of `(name, expr)` pairs where each `expr` is a [`datafusion_expr::Expr`].
///
/// # Example
/// ```
/// use lancedb::expr::{col, lit};
/// use lancedb::query::Select;
///
/// let selection = Select::expr_projection(&[
/// ("id", col("id")),
/// ("id2", col("id") * lit(2)),
/// ]);
/// ```
pub fn expr_projection(columns: &[(impl AsRef<str>, datafusion_expr::Expr)]) -> Self {
Self::Expr(
columns
.iter()
.map(|(name, expr)| (name.as_ref().to_string(), expr.clone()))
.collect(),
)
}
}
/// A trait for converting a type to a query vector
@@ -1591,6 +1633,58 @@ mod tests {
});
}
#[tokio::test]
async fn test_select_with_expr_projection() {
// Mirrors test_select_with_transform but uses Select::Expr instead of Select::Dynamic
let tmp_dir = tempdir().unwrap();
let dataset_path = tmp_dir.path().join("test_expr.lance");
let uri = dataset_path.to_str().unwrap();
let batches = make_non_empty_batches();
let conn = connect(uri).execute().await.unwrap();
let table = conn
.create_table("my_table", batches)
.execute()
.await
.unwrap();
use crate::expr::{col, lit};
let query = table.query().limit(10).select(Select::expr_projection(&[
("id2", col("id") * lit(2i32)),
("id", col("id")),
]));
let schema = query.output_schema().await.unwrap();
assert_eq!(
schema,
Arc::new(ArrowSchema::new(vec![
ArrowField::new("id2", DataType::Int32, true),
ArrowField::new("id", DataType::Int32, true),
]))
);
let result = query.execute().await;
let mut batches = result
.expect("should have result")
.try_collect::<Vec<_>>()
.await
.unwrap();
assert_eq!(batches.len(), 1);
let batch = batches.pop().unwrap();
// id and id2
assert_eq!(batch.num_columns(), 2);
let id: &Int32Array = batch.column_by_name("id").unwrap().as_primitive();
let id2: &Int32Array = batch.column_by_name("id2").unwrap().as_primitive();
id.iter().zip(id2.iter()).for_each(|(id, id2)| {
let id = id.unwrap();
let id2 = id2.unwrap();
assert_eq!(id * 2, id2);
});
}
#[tokio::test]
async fn test_execute_no_vector() {
// TODO: Switch back to memory://foo after https://github.com/lancedb/lancedb/issues/1051

View File

@@ -426,14 +426,11 @@ impl<S: HttpSend> RestfulLanceDbClient<S> {
})?,
);
}
if db_prefix.is_some() {
if let Some(prefix) = db_prefix {
headers.insert(
HeaderName::from_static("x-lancedb-database-prefix"),
HeaderValue::from_str(db_prefix.unwrap()).map_err(|_| Error::InvalidInput {
message: format!(
"non-ascii database prefix '{}' provided",
db_prefix.unwrap()
),
HeaderValue::from_str(prefix).map_err(|_| Error::InvalidInput {
message: format!("non-ascii database prefix '{}' provided", prefix),
})?,
);
}

View File

@@ -464,6 +464,7 @@ impl<S: HttpSend> Database for RemoteDatabase<S> {
lance_read_params: None,
location: None,
namespace_client: None,
managed_versioning: None,
};
let req = (callback)(req);
self.open_table(req).await

View File

@@ -477,6 +477,16 @@ impl<S: HttpSend> RemoteTable<S> {
}));
body["columns"] = alias_map.into();
}
Select::Expr(pairs) => {
let alias_map: Result<serde_json::Map<String, serde_json::Value>> = pairs
.iter()
.map(|(name, expr)| {
expr_to_sql_string(expr)
.map(|sql| (name.clone(), serde_json::Value::String(sql)))
})
.collect();
body["columns"] = alias_map?.into();
}
}
if params.fast_search {
@@ -1645,10 +1655,33 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
Ok(())
}
async fn prewarm_index(&self, _index_name: &str) -> Result<()> {
Err(Error::NotSupported {
message: "prewarm_index is not yet supported on LanceDB cloud.".into(),
})
async fn prewarm_index(&self, index_name: &str) -> Result<()> {
let request = self.client.post(&format!(
"/v1/table/{}/index/{}/prewarm/",
self.identifier, index_name
));
let (request_id, response) = self.send(request, true).await?;
if response.status() == StatusCode::NOT_FOUND {
return Err(Error::IndexNotFound {
name: index_name.to_string(),
});
}
self.check_table_response(&request_id, response).await?;
Ok(())
}
async fn prewarm_data(&self, columns: Option<Vec<String>>) -> Result<()> {
let mut request = self.client.post(&format!(
"/v1/table/{}/page_cache/prewarm/",
self.identifier
));
let body = serde_json::json!({
"columns": columns.unwrap_or_default(),
});
request = request.json(&body);
let (request_id, response) = self.send(request, true).await?;
self.check_table_response(&request_id, response).await?;
Ok(())
}
async fn table_definition(&self) -> Result<TableDefinition> {
@@ -3529,6 +3562,64 @@ mod tests {
assert_eq!(result.version, if old_server { 0 } else { 43 });
}
#[tokio::test]
async fn test_prewarm_index() {
let table = Table::new_with_handler("my_table", |request| {
assert_eq!(request.method(), "POST");
assert_eq!(
request.url().path(),
"/v1/table/my_table/index/my_index/prewarm/"
);
http::Response::builder().status(200).body("{}").unwrap()
});
table.prewarm_index("my_index").await.unwrap();
}
#[tokio::test]
async fn test_prewarm_index_not_found() {
let table = Table::new_with_handler("my_table", |request| {
assert_eq!(
request.url().path(),
"/v1/table/my_table/index/my_index/prewarm/"
);
http::Response::builder().status(404).body("{}").unwrap()
});
let e = table.prewarm_index("my_index").await.unwrap_err();
assert!(matches!(e, Error::IndexNotFound { .. }));
}
#[tokio::test]
async fn test_prewarm_data() {
let table = Table::new_with_handler("my_table", |request| {
assert_eq!(request.method(), "POST");
assert_eq!(
request.url().path(),
"/v1/table/my_table/page_cache/prewarm/"
);
http::Response::builder().status(200).body("{}").unwrap()
});
table.prewarm_data(None).await.unwrap();
}
#[tokio::test]
async fn test_prewarm_data_with_columns() {
let table = Table::new_with_handler("my_table", |request| {
assert_eq!(request.method(), "POST");
assert_eq!(
request.url().path(),
"/v1/table/my_table/page_cache/prewarm/"
);
let body = request.body().unwrap().as_bytes().unwrap();
let body: serde_json::Value = serde_json::from_slice(body).unwrap();
assert_eq!(body["columns"], serde_json::json!(["col_a", "col_b"]));
http::Response::builder().status(200).body("{}").unwrap()
});
table
.prewarm_data(Some(vec!["col_a".into(), "col_b".into()]))
.await
.unwrap();
}
#[tokio::test]
async fn test_drop_index() {
let table = Table::new_with_handler("my_table", |request| {

View File

@@ -34,9 +34,13 @@ use lance_index::vector::sq::builder::SQBuildParams;
use lance_io::object_store::{LanceNamespaceStorageOptionsProvider, StorageOptionsAccessor};
pub use query::AnyQuery;
use lance::io::commit::namespace_manifest::LanceNamespaceExternalManifestStore;
use lance_namespace::LanceNamespace;
use lance_namespace::models::DescribeTableRequest;
use lance_table::format::Manifest;
use lance_table::io::commit::CommitHandler;
use lance_table::io::commit::ManifestNamingScheme;
use lance_table::io::commit::external_manifest::ExternalManifestCommitHandler;
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::format;
@@ -273,8 +277,13 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
async fn list_indices(&self) -> Result<Vec<IndexConfig>>;
/// Drop an index from the table.
async fn drop_index(&self, name: &str) -> Result<()>;
/// Prewarm an index in the table
/// Prewarm an index in the table.
async fn prewarm_index(&self, name: &str) -> Result<()>;
/// Prewarm data for the table.
///
/// Currently only supported on remote tables.
/// If `columns` is `None`, all columns are prewarmed.
async fn prewarm_data(&self, columns: Option<Vec<String>>) -> Result<()>;
/// Get statistics about the index.
async fn index_stats(&self, index_name: &str) -> Result<Option<IndexStatistics>>;
/// Merge insert new records into the table.
@@ -942,17 +951,7 @@ impl Table {
/// * Prune: Removes old versions of the dataset
/// * Index: Optimizes the indices, adding new data to existing indices
///
/// <section class="warning">Experimental API</section>
///
/// The optimization process is undergoing active development and may change.
/// Our goal with these changes is to improve the performance of optimization and
/// reduce the complexity.
///
/// That being said, it is essential today to run optimize if you want the best
/// performance. It should be stable and safe to use in production, but it our
/// hope that the API may be simplified (or not even need to be called) in the future.
///
/// The frequency an application shoudl call optimize is based on the frequency of
/// The frequency an application should call optimize is based on the frequency of
/// data modifications. If data is frequently added, deleted, or updated then
/// optimize should be run frequently. A good rule of thumb is to run optimize if
/// you have added or modified 100,000 or more records or run more than 20 data
@@ -1119,22 +1118,45 @@ impl Table {
self.inner.drop_index(name).await
}
/// Prewarm an index in the table
/// Prewarm an index in the table.
///
/// This is a hint to fully load the index into memory. It can be used to
/// avoid cold starts
/// This is a hint to the database that the index will be accessed in the
/// future and should be loaded into memory if possible. This can reduce
/// cold-start latency for subsequent queries.
///
/// This call initiates prewarming and returns once the request is accepted.
/// It is idempotent and safe to call from multiple clients concurrently.
///
/// It is generally wasteful to call this if the index does not fit into the
/// available cache.
///
/// Note: This function is not yet supported on all indices, in which case it
/// may do nothing.
/// available cache. Not all index types support prewarming; unsupported
/// indices will silently ignore the request.
///
/// Use [`Self::list_indices()`] to find the names of the indices.
pub async fn prewarm_index(&self, name: &str) -> Result<()> {
self.inner.prewarm_index(name).await
}
/// Prewarm data for the table.
///
/// This is a hint to the database that the given columns will be accessed in
/// the future and the database should prefetch the data if possible. This
/// can reduce cold-start latency for subsequent queries. Currently only
/// supported on remote tables.
///
/// This call initiates prewarming and returns once the request is accepted.
/// It is idempotent and safe to call from multiple clients concurrently —
/// calling it on already-prewarmed columns is a no-op on the server.
///
/// This operation has a large upfront cost but can speed up future queries
/// that need to fetch the given columns. Large columns such as embeddings
/// or binary data may not be practical to prewarm. This feature is intended
/// for workloads that issue many queries against the same columns.
///
/// If `columns` is `None`, all columns are prewarmed.
pub async fn prewarm_data(&self, columns: Option<Vec<String>>) -> Result<()> {
self.inner.prewarm_data(columns).await
}
/// Poll until the columns are fully indexed. Will return Error::Timeout if the columns
/// are not fully indexed within the timeout.
pub async fn wait_for_index(
@@ -1212,10 +1234,13 @@ pub struct NativeTable {
// This comes from the connection options. We store here so we can pass down
// to the dataset when we recreate it (for example, in checkout_latest).
read_consistency_interval: Option<std::time::Duration>,
// Optional namespace client for server-side query execution.
// When set, queries will be executed on the namespace server instead of locally.
// pub (crate) namespace_client so query.rs can access the fields
// Optional namespace client for namespace operations (e.g., managed versioning).
// pub(crate) so query.rs can access the field for server-side query execution.
pub(crate) namespace_client: Option<Arc<dyn LanceNamespace>>,
// Whether to enable server-side query execution via the namespace client.
// When true and namespace_client is set, queries will be executed on the
// namespace server instead of locally.
pub(crate) server_side_query_enabled: bool,
}
impl std::fmt::Debug for NativeTable {
@@ -1227,6 +1252,7 @@ impl std::fmt::Debug for NativeTable {
.field("uri", &self.uri)
.field("read_consistency_interval", &self.read_consistency_interval)
.field("namespace_client", &self.namespace_client)
.field("server_side_query_enabled", &self.server_side_query_enabled)
.finish()
}
}
@@ -1263,7 +1289,7 @@ impl NativeTable {
/// * A [NativeTable] object.
pub async fn open(uri: &str) -> Result<Self> {
let name = Self::get_table_name(uri)?;
Self::open_with_params(uri, &name, vec![], None, None, None, None).await
Self::open_with_params(uri, &name, vec![], None, None, None, None, false, None).await
}
/// Opens an existing Table
@@ -1273,7 +1299,10 @@ impl NativeTable {
/// * `base_path` - The base path where the table is located
/// * `name` The Table name
/// * `params` The [ReadParams] to use when opening the table
/// * `namespace_client` - Optional namespace client for server-side query execution
/// * `namespace_client` - Optional namespace client for namespace operations
/// * `server_side_query_enabled` - Whether to enable server-side query execution
/// * `managed_versioning` - Whether managed versioning is enabled. If None and namespace_client
/// is provided, the value will be fetched via describe_table.
///
/// # Returns
///
@@ -1287,6 +1316,8 @@ impl NativeTable {
params: Option<ReadParams>,
read_consistency_interval: Option<std::time::Duration>,
namespace_client: Option<Arc<dyn LanceNamespace>>,
server_side_query_enabled: bool,
managed_versioning: Option<bool>,
) -> Result<Self> {
let params = params.unwrap_or_default();
// patch the params if we have a write store wrapper
@@ -1295,17 +1326,54 @@ impl NativeTable {
None => params,
};
let dataset = DatasetBuilder::from_uri(uri)
.with_read_params(params)
.load()
.await
.map_err(|e| match e {
lance::Error::DatasetNotFound { .. } => Error::TableNotFound {
name: name.to_string(),
source: Box::new(e),
},
e => e.into(),
})?;
// Build table_id from namespace + name
let mut table_id = namespace.clone();
table_id.push(name.to_string());
// Determine if managed_versioning is enabled
// Use the provided value if available, otherwise query the namespace
let managed_versioning = match managed_versioning {
Some(value) => value,
None if namespace_client.is_some() => {
let ns_client = namespace_client.as_ref().unwrap();
let describe_request = DescribeTableRequest {
id: Some(table_id.clone()),
..Default::default()
};
let response = ns_client
.describe_table(describe_request)
.await
.map_err(|e| Error::Runtime {
message: format!(
"Failed to describe table via namespace client: {}. \
If you don't need managed versioning, don't pass namespace_client.",
e
),
})?;
response.managed_versioning == Some(true)
}
None => false,
};
let mut builder = DatasetBuilder::from_uri(uri).with_read_params(params);
// Set up commit handler when managed_versioning is enabled
if managed_versioning && let Some(ref ns_client) = namespace_client {
let external_store =
LanceNamespaceExternalManifestStore::new(ns_client.clone(), table_id.clone());
let commit_handler: Arc<dyn CommitHandler> = Arc::new(ExternalManifestCommitHandler {
external_manifest_store: Arc::new(external_store),
});
builder = builder.with_commit_handler(commit_handler);
}
let dataset = builder.load().await.map_err(|e| match e {
lance::Error::DatasetNotFound { .. } => Error::TableNotFound {
name: name.to_string(),
source: Box::new(e),
},
e => e.into(),
})?;
let dataset = DatasetConsistencyWrapper::new_latest(dataset, read_consistency_interval);
let id = Self::build_id(&namespace, name);
@@ -1318,6 +1386,7 @@ impl NativeTable {
dataset,
read_consistency_interval,
namespace_client,
server_side_query_enabled,
})
}
@@ -1421,6 +1490,7 @@ impl NativeTable {
dataset,
read_consistency_interval,
namespace_client: stored_namespace_client,
server_side_query_enabled,
})
}
@@ -1460,7 +1530,8 @@ impl NativeTable {
/// * `namespace` - The namespace path. When non-empty, an explicit URI must be provided.
/// * `batches` RecordBatch to be saved in the database.
/// * `params` - Write parameters.
/// * `namespace_client` - Optional namespace client for server-side query execution
/// * `namespace_client` - Optional namespace client for namespace operations
/// * `server_side_query_enabled` - Whether to enable server-side query execution
///
/// # Returns
///
@@ -1475,6 +1546,7 @@ impl NativeTable {
params: Option<WriteParams>,
read_consistency_interval: Option<std::time::Duration>,
namespace_client: Option<Arc<dyn LanceNamespace>>,
server_side_query_enabled: bool,
) -> Result<Self> {
// Default params uses format v1.
let params = params.unwrap_or(WriteParams {
@@ -1507,6 +1579,7 @@ impl NativeTable {
dataset: DatasetConsistencyWrapper::new_latest(dataset, read_consistency_interval),
read_consistency_interval,
namespace_client,
server_side_query_enabled,
})
}
@@ -1520,6 +1593,7 @@ impl NativeTable {
params: Option<WriteParams>,
read_consistency_interval: Option<std::time::Duration>,
namespace_client: Option<Arc<dyn LanceNamespace>>,
server_side_query_enabled: bool,
) -> Result<Self> {
let data: Box<dyn Scannable> = Box::new(RecordBatch::new_empty(schema));
Self::create(
@@ -1531,6 +1605,7 @@ impl NativeTable {
params,
read_consistency_interval,
namespace_client,
server_side_query_enabled,
)
.await
}
@@ -1634,6 +1709,7 @@ impl NativeTable {
dataset: DatasetConsistencyWrapper::new_latest(dataset, read_consistency_interval),
read_consistency_interval,
namespace_client: stored_namespace_client,
server_side_query_enabled,
})
}
@@ -2232,6 +2308,12 @@ impl BaseTable for NativeTable {
Ok(dataset.prewarm_index(index_name).await?)
}
async fn prewarm_data(&self, _columns: Option<Vec<String>>) -> Result<()> {
Err(Error::NotSupported {
message: "prewarm_data is currently only supported on remote tables.".into(),
})
}
async fn update(&self, update: UpdateBuilder) -> Result<UpdateResult> {
// Delegate to the submodule implementation
update::execute_update(self, update).await
@@ -2625,7 +2707,7 @@ mod tests {
vec![Ok(batch.clone())],
batch.schema(),
));
let table = NativeTable::create(uri, "test", vec![], reader, None, None, None, None)
let table = NativeTable::create(uri, "test", vec![], reader, None, None, None, None, false)
.await
.unwrap();

View File

@@ -3,12 +3,13 @@
use std::sync::Arc;
use arrow_cast::can_cast_types;
use arrow_schema::{DataType, Field, FieldRef, Fields, Schema};
use datafusion::functions::core::{get_field, named_struct};
use datafusion_common::ScalarValue;
use datafusion_common::config::ConfigOptions;
use datafusion_physical_expr::ScalarFunctionExpr;
use datafusion_physical_expr::expressions::{Literal, cast};
use datafusion_physical_expr::expressions::{CastExpr, Literal};
use datafusion_physical_plan::expressions::Column;
use datafusion_physical_plan::projection::ProjectionExec;
use datafusion_physical_plan::{ExecutionPlan, PhysicalExpr};
@@ -25,12 +26,9 @@ pub fn cast_to_table_schema(
return Ok(input);
}
let exprs = build_field_exprs(
input_schema.fields(),
table_schema.fields(),
&|idx| Arc::new(Column::new(input_schema.field(idx).name(), idx)) as Arc<dyn PhysicalExpr>,
&input_schema,
)?;
let exprs = build_field_exprs(input_schema.fields(), table_schema.fields(), &|idx| {
Arc::new(Column::new(input_schema.field(idx).name(), idx)) as Arc<dyn PhysicalExpr>
})?;
let exprs: Vec<(Arc<dyn PhysicalExpr>, String)> = exprs
.into_iter()
@@ -51,7 +49,6 @@ fn build_field_exprs(
input_fields: &Fields,
table_fields: &Fields,
get_input_expr: &dyn Fn(usize) -> Arc<dyn PhysicalExpr>,
input_schema: &Schema,
) -> Result<Vec<(Arc<dyn PhysicalExpr>, FieldRef)>> {
let config = Arc::new(ConfigOptions::default());
let mut result = Vec::new();
@@ -72,24 +69,19 @@ fn build_field_exprs(
(DataType::Struct(in_children), DataType::Struct(tbl_children))
if in_children != tbl_children =>
{
let sub_exprs = build_field_exprs(
in_children,
tbl_children,
&|child_idx| {
let child_name = in_children[child_idx].name();
Arc::new(ScalarFunctionExpr::new(
&format!("get_field({child_name})"),
get_field(),
vec![
input_expr.clone(),
Arc::new(Literal::new(ScalarValue::from(child_name.as_str()))),
],
Arc::new(in_children[child_idx].as_ref().clone()),
config.clone(),
)) as Arc<dyn PhysicalExpr>
},
input_schema,
)?;
let sub_exprs = build_field_exprs(in_children, tbl_children, &|child_idx| {
let child_name = in_children[child_idx].name();
Arc::new(ScalarFunctionExpr::new(
&format!("get_field({child_name})"),
get_field(),
vec![
input_expr.clone(),
Arc::new(Literal::new(ScalarValue::from(child_name.as_str()))),
],
Arc::new(in_children[child_idx].as_ref().clone()),
config.clone(),
)) as Arc<dyn PhysicalExpr>
})?;
let output_struct_fields: Fields = sub_exprs
.iter()
@@ -125,17 +117,21 @@ fn build_field_exprs(
// Types match: pass through.
(inp, tbl) if inp == tbl => input_expr,
// Types differ: cast.
_ => cast(input_expr, input_schema, table_field.data_type().clone()).map_err(|e| {
Error::InvalidInput {
// safe: false (the default) means overflow/truncation errors surface at execution time.
(_, _) if can_cast_types(input_field.data_type(), table_field.data_type()) => Arc::new(
CastExpr::new(input_expr, table_field.data_type().clone(), None),
)
as Arc<dyn PhysicalExpr>,
(inp, tbl) => {
return Err(Error::InvalidInput {
message: format!(
"cannot cast field '{}' from {} to {}: {}",
"cannot cast field '{}' from {} to {}",
table_field.name(),
input_field.data_type(),
table_field.data_type(),
e
inp,
tbl,
),
}
})?,
});
}
};
let output_field = Arc::new(Field::new(
@@ -153,10 +149,12 @@ fn build_field_exprs(
mod tests {
use std::sync::Arc;
use arrow::buffer::OffsetBuffer;
use arrow_array::{
Float32Array, Float64Array, Int32Array, Int64Array, RecordBatch, StringArray, StructArray,
Array, Float32Array, Float64Array, Int32Array, Int64Array, ListArray, RecordBatch,
StringArray, StructArray, UInt32Array, UInt64Array,
};
use arrow_schema::{DataType, Field, Schema};
use arrow_schema::{DataType, Field, Fields, Schema};
use datafusion::prelude::SessionContext;
use datafusion_catalog::MemTable;
use futures::TryStreamExt;
@@ -495,4 +493,129 @@ mod tests {
assert_eq!(b.value(0), "hello");
assert_eq!(b.value(1), "world");
}
#[tokio::test]
async fn test_narrowing_numeric_cast_success() {
let input_batch = RecordBatch::try_new(
Arc::new(Schema::new(vec![Field::new("a", DataType::UInt64, false)])),
vec![Arc::new(UInt64Array::from(vec![1u64, 2, 3]))],
)
.unwrap();
let table_schema = Schema::new(vec![Field::new("a", DataType::UInt32, false)]);
let plan = plan_from_batch(input_batch).await;
let casted = cast_to_table_schema(plan, &table_schema).unwrap();
let result = collect(casted).await;
assert_eq!(result.schema().field(0).data_type(), &DataType::UInt32);
let a: &UInt32Array = result.column(0).as_any().downcast_ref().unwrap();
assert_eq!(a.values(), &[1u32, 2, 3]);
}
#[tokio::test]
async fn test_narrowing_numeric_cast_overflow_errors() {
let overflow_val = u32::MAX as u64 + 1;
let input_batch = RecordBatch::try_new(
Arc::new(Schema::new(vec![Field::new("a", DataType::UInt64, false)])),
vec![Arc::new(UInt64Array::from(vec![overflow_val]))],
)
.unwrap();
let table_schema = Schema::new(vec![Field::new("a", DataType::UInt32, false)]);
let plan = plan_from_batch(input_batch).await;
// Planning succeeds — the overflow is only detected at execution time.
let casted = cast_to_table_schema(plan, &table_schema).unwrap();
let ctx = SessionContext::new();
let stream = casted.execute(0, ctx.task_ctx()).unwrap();
let result: Result<Vec<RecordBatch>, _> = stream.try_collect().await;
assert!(result.is_err(), "expected overflow error at execution time");
}
#[tokio::test]
async fn test_list_struct_field_reorder() {
// list<struct<a: Int32, b: Int32>> → list<struct<b: Int64, a: Int64>>
// Tests both reordering (a,b → b,a) and element-type widening (Int32 → Int64).
let inner_fields: Fields = vec![
Field::new("a", DataType::Int32, true),
Field::new("b", DataType::Int32, true),
]
.into();
let struct_array = StructArray::from(vec![
(
Arc::new(inner_fields[0].as_ref().clone()),
Arc::new(Int32Array::from(vec![1, 3])) as _,
),
(
Arc::new(inner_fields[1].as_ref().clone()),
Arc::new(Int32Array::from(vec![2, 4])) as _,
),
]);
// Offsets: one list element containing two struct rows (0..2).
let offsets = OffsetBuffer::from_lengths(vec![2]);
let list_array = ListArray::try_new(
Arc::new(Field::new("item", DataType::Struct(inner_fields), true)),
offsets,
Arc::new(struct_array),
None,
)
.unwrap();
let input_batch = RecordBatch::try_new(
Arc::new(Schema::new(vec![Field::new(
"s_list",
list_array.data_type().clone(),
false,
)])),
vec![Arc::new(list_array)],
)
.unwrap();
let table_inner: Fields = vec![
Field::new("b", DataType::Int64, true),
Field::new("a", DataType::Int64, true),
]
.into();
let table_schema = Schema::new(vec![Field::new(
"s_list",
DataType::List(Arc::new(Field::new(
"item",
DataType::Struct(table_inner),
true,
))),
false,
)]);
let plan = plan_from_batch(input_batch).await;
let casted = cast_to_table_schema(plan, &table_schema).unwrap();
let result = collect(casted).await;
let list_col = result
.column(0)
.as_any()
.downcast_ref::<ListArray>()
.unwrap();
let struct_col = list_col
.values()
.as_any()
.downcast_ref::<StructArray>()
.unwrap();
assert_eq!(struct_col.num_columns(), 2);
let b: &Int64Array = struct_col
.column_by_name("b")
.unwrap()
.as_any()
.downcast_ref()
.unwrap();
assert_eq!(b.values(), &[2, 4]);
let a: &Int64Array = struct_col
.column_by_name("a")
.unwrap()
.as_any()
.downcast_ref()
.unwrap();
assert_eq!(a.values(), &[1, 3]);
}
}

View File

@@ -1,3 +1,4 @@
use futures::FutureExt;
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
use serde::{Deserialize, Serialize};
@@ -23,7 +24,7 @@ pub struct DeleteResult {
pub(crate) async fn execute_delete(table: &NativeTable, predicate: &str) -> Result<DeleteResult> {
table.dataset.ensure_mutable()?;
let mut dataset = (*table.dataset.get().await?).clone();
let delete_result = dataset.delete(predicate).await?;
let delete_result = dataset.delete(predicate).boxed().await?;
let num_deleted_rows = delete_result.num_deleted_rows;
let version = dataset.version().version;
table.dataset.update(dataset);

View File

@@ -64,6 +64,9 @@ pub enum OptimizeAction {
older_than: Option<Duration>,
/// Because they may be part of an in-progress transaction, files newer than 7 days old are not deleted by default.
/// If you are sure that there are no in-progress transactions, then you can set this to True to delete all files older than `older_than`.
///
/// **WARNING**: This should only be set to true if you can guarantee that no other process is
/// currently working on this dataset. Otherwise the dataset could be put into a corrupted state.
delete_unverified: Option<bool>,
/// If true, an error will be returned if there are any old versions that are still tagged.
error_if_tagged_old_versions: Option<bool>,
@@ -117,6 +120,10 @@ pub(crate) async fn optimize_indices(table: &NativeTable, options: &OptimizeOpti
/// If you are sure that there are no in-progress transactions, then you
/// can set this to True to delete all files older than `older_than`.
///
/// **WARNING**: This should only be set to true if you can guarantee that
/// no other process is currently working on this dataset. Otherwise the
/// dataset could be put into a corrupted state.
///
/// This calls into [lance::dataset::Dataset::cleanup_old_versions] and
/// returns the result.
pub(crate) async fn cleanup_old_versions(

View File

@@ -40,8 +40,10 @@ pub async fn execute_query(
query: &AnyQuery,
options: QueryExecutionOptions,
) -> Result<DatasetRecordBatchStream> {
// If namespace client is configured, use server-side query execution
if let Some(ref namespace_client) = table.namespace_client {
// If server-side query is enabled and namespace client is configured, use server-side query execution
if table.server_side_query_enabled
&& let Some(ref namespace_client) = table.namespace_client
{
return execute_namespace_query(table, namespace_client.clone(), query, options).await;
}
execute_generic_query(table, query, options).await
@@ -184,6 +186,13 @@ pub async fn create_plan(
Select::Dynamic(ref select_with_transform) => {
scanner.project_with_transform(select_with_transform.as_slice())?;
}
Select::Expr(ref expr_pairs) => {
let sql_pairs: crate::Result<Vec<(String, String)>> = expr_pairs
.iter()
.map(|(name, expr)| expr_to_sql_string(expr).map(|sql| (name.clone(), sql)))
.collect();
scanner.project_with_transform(sql_pairs?.as_slice())?;
}
Select::All => {}
}
@@ -338,6 +347,17 @@ fn convert_to_namespace_query(query: &AnyQuery) -> Result<NsQueryTableRequest> {
.to_string(),
});
}
Select::Expr(pairs) => {
let sql_pairs: crate::Result<Vec<(String, String)>> = pairs
.iter()
.map(|(name, expr)| expr_to_sql_string(expr).map(|sql| (name.clone(), sql)))
.collect();
let sql_pairs = sql_pairs?;
Some(Box::new(QueryTableRequestColumns {
column_names: None,
column_aliases: Some(sql_pairs.into_iter().collect()),
}))
}
};
// Check for unsupported features
@@ -409,6 +429,17 @@ fn convert_to_namespace_query(query: &AnyQuery) -> Result<NsQueryTableRequest> {
.to_string(),
});
}
Select::Expr(pairs) => {
let sql_pairs: crate::Result<Vec<(String, String)>> = pairs
.iter()
.map(|(name, expr)| expr_to_sql_string(expr).map(|sql| (name.clone(), sql)))
.collect();
let sql_pairs = sql_pairs?;
Some(Box::new(QueryTableRequestColumns {
column_names: None,
column_aliases: Some(sql_pairs.into_iter().collect()),
}))
}
};
// Handle full text search if present