Compare commits

..

3 Commits

Author SHA1 Message Date
Jack Ye
01c6b9dcb8 feat: add mem_wal flag to merge insert for MemWAL write path
Add support for enabling MemWAL (Memory Write-Ahead Log) mode on merge insert
operations. This allows streaming writes to route through memory nodes for
high-performance buffered writes.

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

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

Co-Authored-By: Claude <noreply@anthropic.com>
Co-Authored-By: Happy <yesreply@happy.engineering>
2026-03-16 01:04:04 -07:00
Will Jones
33a13f0738 fixes for breaking changes 2026-03-04 15:27:32 -08:00
Will Jones
cabc75f167 feat: upgrade Lance to 3.0.0-rc.3 2026-03-04 14:57:17 -08:00
81 changed files with 5562 additions and 6877 deletions

View File

@@ -1,5 +1,5 @@
[tool.bumpversion]
current_version = "0.27.2-beta.0"
current_version = "0.27.0-beta.3"
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@v1
- uses: srvaroa/labeler@master
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@v4
- uses: actions/setup-node@v3
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@v7
uses: actions/github-script@v6
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@v4
uses: actions/setup-node@v3
with:
node-version: 20
cache: 'npm'
@@ -68,7 +68,7 @@ jobs:
run: |
PYTHONPATH=. mkdocs build
- name: Setup Pages
uses: actions/configure-pages@v5
uses: actions/configure-pages@v2
- name: Upload artifact
uses: actions/upload-pages-artifact@v3
with:

View File

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

View File

@@ -19,7 +19,6 @@ on:
paths:
- .github/workflows/npm-publish.yml
- Cargo.toml # Change in dependency frequently breaks builds
- Cargo.lock
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
@@ -125,12 +124,7 @@ jobs:
pre_build: |-
set -e &&
apt-get update &&
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++
apt-get install -y protobuf-compiler pkg-config
- target: x86_64-unknown-linux-musl
# This one seems to need some extra memory
host: ubuntu-2404-8x-x64
@@ -150,10 +144,9 @@ jobs:
set -e &&
apt-get update &&
apt-get install -y protobuf-compiler pkg-config &&
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" &&
# 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 &&
rustup target add aarch64-unknown-linux-gnu
- target: aarch64-unknown-linux-musl
host: ubuntu-2404-8x-x64
@@ -273,7 +266,7 @@ jobs:
- target: x86_64-unknown-linux-gnu
host: ubuntu-latest
- target: aarch64-unknown-linux-gnu
host: ubuntu-2404-8x-arm64
host: buildjet-16vcpu-ubuntu-2204-arm
node:
- '20'
runs-on: ${{ matrix.settings.host }}

View File

@@ -9,7 +9,6 @@ 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

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

View File

@@ -7,7 +7,6 @@ on:
pull_request:
paths:
- Cargo.toml
- Cargo.lock
- rust/**
- .github/workflows/rust.yml
@@ -207,14 +206,14 @@ jobs:
- name: Downgrade dependencies
# These packages have newer requirements for MSRV
run: |
cargo update -p aws-sdk-bedrockruntime --precise 1.77.0
cargo update -p aws-sdk-dynamodb --precise 1.68.0
cargo update -p aws-config --precise 1.6.0
cargo update -p aws-sdk-kms --precise 1.63.0
cargo update -p aws-sdk-s3 --precise 1.79.0
cargo update -p aws-sdk-sso --precise 1.62.0
cargo update -p aws-sdk-ssooidc --precise 1.63.0
cargo update -p aws-sdk-sts --precise 1.63.0
cargo update -p aws-sdk-bedrockruntime --precise 1.64.0
cargo update -p aws-sdk-dynamodb --precise 1.55.0
cargo update -p aws-config --precise 1.5.10
cargo update -p aws-sdk-kms --precise 1.51.0
cargo update -p aws-sdk-s3 --precise 1.65.0
cargo update -p aws-sdk-sso --precise 1.50.0
cargo update -p aws-sdk-ssooidc --precise 1.51.0
cargo update -p aws-sdk-sts --precise 1.51.0
cargo update -p home --precise 0.5.9
- name: cargo +${{ matrix.msrv }} check
env:

2393
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" = "=4.0.0-rc.3", default-features = false, "tag" = "v4.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-core = { "version" = "=4.0.0-rc.3", "tag" = "v4.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-datagen = { "version" = "=4.0.0-rc.3", "tag" = "v4.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-file = { "version" = "=4.0.0-rc.3", "tag" = "v4.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-io = { "version" = "=4.0.0-rc.3", default-features = false, "tag" = "v4.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-index = { "version" = "=4.0.0-rc.3", "tag" = "v4.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-linalg = { "version" = "=4.0.0-rc.3", "tag" = "v4.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace = { "version" = "=4.0.0-rc.3", "tag" = "v4.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace-impls = { "version" = "=4.0.0-rc.3", default-features = false, "tag" = "v4.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-table = { "version" = "=4.0.0-rc.3", "tag" = "v4.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-testing = { "version" = "=4.0.0-rc.3", "tag" = "v4.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-datafusion = { "version" = "=4.0.0-rc.3", "tag" = "v4.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-encoding = { "version" = "=4.0.0-rc.3", "tag" = "v4.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-arrow = { "version" = "=4.0.0-rc.3", "tag" = "v4.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance = { "version" = "=3.0.0-rc.3", default-features = false, "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-core = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-datagen = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-file = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-io = { "version" = "=3.0.0-rc.3", default-features = false, "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-index = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-linalg = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace-impls = { "version" = "=3.0.0-rc.3", default-features = false, "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-table = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-testing = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-datafusion = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-encoding = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
lance-arrow = { "version" = "=3.0.0-rc.3", "tag" = "v3.0.0-rc.3", "git" = "https://github.com/lance-format/lance.git" }
ahash = "0.8"
# Note that this one does not include pyarrow
arrow = { version = "57.2", optional = false }

View File

@@ -3,7 +3,6 @@
from __future__ import annotations
import argparse
import functools
import json
import os
import re
@@ -27,7 +26,6 @@ SEMVER_RE = re.compile(
)
@functools.total_ordering
@dataclass(frozen=True)
class SemVer:
major: int
@@ -158,9 +156,7 @@ def read_current_version(repo_root: Path) -> str:
def determine_latest_tag(tags: Iterable[TagInfo]) -> TagInfo:
# Stable releases (no prerelease) are always preferred over pre-releases.
# Within each group, standard semver ordering applies.
return max(tags, key=lambda tag: (not tag.semver.prerelease, tag.semver))
return max(tags, key=lambda tag: tag.semver)
def write_outputs(args: argparse.Namespace, payload: dict) -> None:

View File

@@ -1,7 +1,7 @@
version: "3.9"
services:
localstack:
image: localstack/localstack:4.0
image: localstack/localstack:3.3
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:3.12-slim-bookworm
#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
# 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/*
# 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
# 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 && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN apt-get -y update &&\
apt-get -y upgrade && \
apt-get -y install git
# Verify installations
RUN python --version && \
rustc --version && \
protoc --version
RUN pip install --no-cache-dir tantivy lancedb
RUN pip install tantivy lancedb

View File

@@ -52,21 +52,14 @@ 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
@@ -120,7 +113,7 @@ markdown_extensions:
emoji_index: !!python/name:material.extensions.emoji.twemoji
emoji_generator: !!python/name:material.extensions.emoji.to_svg
- markdown.extensions.toc:
toc_depth: 4
toc_depth: 3
permalink: true
permalink_title: Anchor link to this section

View File

@@ -1,9 +1,9 @@
mkdocs==1.6.1
mkdocs==1.5.3
mkdocs-jupyter==0.24.1
mkdocs-material==9.6.23
mkdocs-autorefs>=0.5,<=1.0
mkdocstrings[python]>=0.24,<1.0
griffe>=0.40,<1.0
mkdocs-render-swagger-plugin>=0.1.0
pydantic>=2.0,<3.0
mkdocs-redirects>=1.2.0
mkdocs-material==9.5.3
mkdocs-autorefs<=1.0
mkdocstrings[python]==0.25.2
griffe
mkdocs-render-swagger-plugin
pydantic
mkdocs-redirects

View File

@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
<dependency>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-core</artifactId>
<version>0.27.2-beta.0</version>
<version>0.27.0-beta.3</version>
</dependency>
```

View File

@@ -71,12 +71,11 @@ Add new columns with defined values.
#### Parameters
* **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)
* **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.
#### Returns
@@ -485,7 +484,19 @@ Modeled after ``VACUUM`` in PostgreSQL.
- Prune: Removes old versions of the dataset
- Index: Optimizes the indices, adding new data to existing indices
The frequency an application should call optimize is based on the frequency of
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
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

@@ -37,12 +37,3 @@ 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 Enterprise Client
# LanceDB Java SDK
## Configuration and Initialization

View File

@@ -8,7 +8,7 @@
<parent>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.27.2-beta.0</version>
<version>0.27.0-beta.3</version>
<relativePath>../pom.xml</relativePath>
</parent>
@@ -56,21 +56,21 @@
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-slf4j2-impl</artifactId>
<version>2.25.3</version>
<version>2.24.3</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-core</artifactId>
<version>2.25.3</version>
<version>2.24.3</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-api</artifactId>
<version>2.25.3</version>
<version>2.24.3</version>
<scope>test</scope>
</dependency>
</dependencies>

View File

@@ -6,7 +6,7 @@
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.27.2-beta.0</version>
<version>0.27.0-beta.3</version>
<packaging>pom</packaging>
<name>${project.artifactId}</name>
<description>LanceDB Java SDK Parent POM</description>
@@ -28,7 +28,7 @@
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<arrow.version>15.0.0</arrow.version>
<lance-core.version>3.0.1</lance-core.version>
<lance-core.version>3.1.0-beta.2</lance-core.version>
<spotless.skip>false</spotless.skip>
<spotless.version>2.30.0</spotless.version>
<spotless.java.googlejavaformat.version>1.7</spotless.java.googlejavaformat.version>
@@ -111,7 +111,7 @@
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-source-plugin</artifactId>
<version>3.3.1</version>
<version>2.2.1</version>
<executions>
<execution>
<id>attach-sources</id>
@@ -124,7 +124,7 @@
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-javadoc-plugin</artifactId>
<version>3.11.2</version>
<version>2.9.1</version>
<executions>
<execution>
<id>attach-javadocs</id>
@@ -178,15 +178,15 @@
<plugins>
<plugin>
<artifactId>maven-clean-plugin</artifactId>
<version>3.4.1</version>
<version>3.1.0</version>
</plugin>
<plugin>
<artifactId>maven-resources-plugin</artifactId>
<version>3.3.1</version>
<version>3.0.2</version>
</plugin>
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.14.0</version>
<version>3.8.1</version>
<configuration>
<compilerArgs>
<arg>-h</arg>
@@ -205,11 +205,11 @@
</plugin>
<plugin>
<artifactId>maven-jar-plugin</artifactId>
<version>3.4.2</version>
<version>3.0.2</version>
</plugin>
<plugin>
<artifactId>maven-install-plugin</artifactId>
<version>3.1.3</version>
<version>2.5.2</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>3.2.7</version>
<version>1.5</version>
<executions>
<execution>
<id>sign-artifacts</id>

View File

@@ -1,7 +1,7 @@
[package]
name = "lancedb-nodejs"
edition.workspace = true
version = "0.27.2-beta.0"
version = "0.27.0-beta.3"
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 = "0.1", features = ["static"] }
lzma-sys = { version = "*", features = ["static"] }
log.workspace = true
# Pin to resolve build failures; update periodically for security patches.
aws-lc-sys = "=0.38.0"
aws-lc-rs = "=1.16.1"
# Workaround for build failure until we can fix it.
aws-lc-sys = "=0.28.0"
aws-lc-rs = "=1.13.0"
[build-dependencies]
napi-build = "2.3.1"

View File

@@ -63,7 +63,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
tableFromIPC,
DataType,
Dictionary,
Uint8: ArrowUint8,
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
} = <any>arrow;
type Schema = ApacheArrow["Schema"];
@@ -363,38 +362,6 @@ 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

@@ -1259,98 +1259,6 @@ 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([
@@ -2296,36 +2204,3 @@ 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

@@ -30,15 +30,12 @@
"x64",
"arm64"
],
"dev": true,
"license": "Apache-2.0",
"optional": true,
"os": [
"darwin",
"linux",
"win32"
],
"peer": true,
"dependencies": {
"reflect-metadata": "^0.2.2"
},
@@ -94,15 +91,14 @@
}
},
"node_modules/@babel/code-frame": {
"version": "7.29.0",
"resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.29.0.tgz",
"integrity": "sha512-9NhCeYjq9+3uxgdtp20LSiJXJvN0FeCtNGpJxuMFZ1Kv3cWUNb6DOhJwUvcVCzKGR66cw4njwM6hrJLqgOwbcw==",
"version": "7.26.2",
"resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.26.2.tgz",
"integrity": "sha512-RJlIHRueQgwWitWgF8OdFYGZX328Ax5BCemNGlqHfplnRT9ESi8JkFlvaVYbS+UubVY6dpv87Fs2u5M29iNFVQ==",
"dev": true,
"license": "MIT",
"dependencies": {
"@babel/helper-validator-identifier": "^7.28.5",
"@babel/helper-validator-identifier": "^7.25.9",
"js-tokens": "^4.0.0",
"picocolors": "^1.1.1"
"picocolors": "^1.0.0"
},
"engines": {
"node": ">=6.9.0"
@@ -237,21 +233,19 @@
}
},
"node_modules/@babel/helper-string-parser": {
"version": "7.27.1",
"resolved": "https://registry.npmjs.org/@babel/helper-string-parser/-/helper-string-parser-7.27.1.tgz",
"integrity": "sha512-qMlSxKbpRlAridDExk92nSobyDdpPijUq2DW6oDnUqd0iOGxmQjyqhMIihI9+zv4LPyZdRje2cavWPbCbWm3eA==",
"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==",
"dev": true,
"license": "MIT",
"engines": {
"node": ">=6.9.0"
}
},
"node_modules/@babel/helper-validator-identifier": {
"version": "7.28.5",
"resolved": "https://registry.npmjs.org/@babel/helper-validator-identifier/-/helper-validator-identifier-7.28.5.tgz",
"integrity": "sha512-qSs4ifwzKJSV39ucNjsvc6WVHs6b7S03sOh2OcHF9UHfVPqWWALUsNUVzhSBiItjRZoLHx7nIarVjqKVusUZ1Q==",
"version": "7.25.9",
"resolved": "https://registry.npmjs.org/@babel/helper-validator-identifier/-/helper-validator-identifier-7.25.9.tgz",
"integrity": "sha512-Ed61U6XJc3CVRfkERJWDz4dJwKe7iLmmJsbOGu9wSloNSFttHV0I8g6UAgb7qnK5ly5bGLPd4oXZlxCdANBOWQ==",
"dev": true,
"license": "MIT",
"engines": {
"node": ">=6.9.0"
}
@@ -266,27 +260,25 @@
}
},
"node_modules/@babel/helpers": {
"version": "7.28.6",
"resolved": "https://registry.npmjs.org/@babel/helpers/-/helpers-7.28.6.tgz",
"integrity": "sha512-xOBvwq86HHdB7WUDTfKfT/Vuxh7gElQ+Sfti2Cy6yIWNW05P8iUslOVcZ4/sKbE+/jQaukQAdz/gf3724kYdqw==",
"version": "7.26.0",
"resolved": "https://registry.npmjs.org/@babel/helpers/-/helpers-7.26.0.tgz",
"integrity": "sha512-tbhNuIxNcVb21pInl3ZSjksLCvgdZy9KwJ8brv993QtIVKJBBkYXz4q4ZbAv31GdnC+R90np23L5FbEBlthAEw==",
"dev": true,
"license": "MIT",
"dependencies": {
"@babel/template": "^7.28.6",
"@babel/types": "^7.28.6"
"@babel/template": "^7.25.9",
"@babel/types": "^7.26.0"
},
"engines": {
"node": ">=6.9.0"
}
},
"node_modules/@babel/parser": {
"version": "7.29.0",
"resolved": "https://registry.npmjs.org/@babel/parser/-/parser-7.29.0.tgz",
"integrity": "sha512-IyDgFV5GeDUVX4YdF/3CPULtVGSXXMLh1xVIgdCgxApktqnQV0r7/8Nqthg+8YLGaAtdyIlo2qIdZrbCv4+7ww==",
"version": "7.26.2",
"resolved": "https://registry.npmjs.org/@babel/parser/-/parser-7.26.2.tgz",
"integrity": "sha512-DWMCZH9WA4Maitz2q21SRKHo9QXZxkDsbNZoVD62gusNtNBBqDg9i7uOhASfTfIGNzW+O+r7+jAlM8dwphcJKQ==",
"dev": true,
"license": "MIT",
"dependencies": {
"@babel/types": "^7.29.0"
"@babel/types": "^7.26.0"
},
"bin": {
"parser": "bin/babel-parser.js"
@@ -518,15 +510,14 @@
}
},
"node_modules/@babel/template": {
"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==",
"version": "7.25.9",
"resolved": "https://registry.npmjs.org/@babel/template/-/template-7.25.9.tgz",
"integrity": "sha512-9DGttpmPvIxBb/2uwpVo3dqJ+O6RooAFOS+lB+xDqoE2PVCE8nfoHMdZLpfCQRLwvohzXISPZcgxt80xLfsuwg==",
"dev": true,
"license": "MIT",
"dependencies": {
"@babel/code-frame": "^7.28.6",
"@babel/parser": "^7.28.6",
"@babel/types": "^7.28.6"
"@babel/code-frame": "^7.25.9",
"@babel/parser": "^7.25.9",
"@babel/types": "^7.25.9"
},
"engines": {
"node": ">=6.9.0"
@@ -551,14 +542,13 @@
}
},
"node_modules/@babel/types": {
"version": "7.29.0",
"resolved": "https://registry.npmjs.org/@babel/types/-/types-7.29.0.tgz",
"integrity": "sha512-LwdZHpScM4Qz8Xw2iKSzS+cfglZzJGvofQICy7W7v4caru4EaAmyUuO6BGrbyQ2mYV11W0U8j5mBhd14dd3B0A==",
"version": "7.26.0",
"resolved": "https://registry.npmjs.org/@babel/types/-/types-7.26.0.tgz",
"integrity": "sha512-Z/yiTPj+lDVnF7lWeKCIJzaIkI0vYO87dMpZ4bg4TDrFe4XXLFWL1TbXU27gBP3QccxV9mZICCrnjnYlJjXHOA==",
"dev": true,
"license": "MIT",
"dependencies": {
"@babel/helper-string-parser": "^7.27.1",
"@babel/helper-validator-identifier": "^7.28.5"
"@babel/helper-string-parser": "^7.25.9",
"@babel/helper-validator-identifier": "^7.25.9"
},
"engines": {
"node": ">=6.9.0"
@@ -1161,6 +1151,95 @@
"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",
@@ -1527,6 +1606,15 @@
"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",
@@ -1758,7 +1846,6 @@
"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"
}
@@ -1767,7 +1854,6 @@
"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"
},
@@ -1933,15 +2019,13 @@
"node_modules/balanced-match": {
"version": "1.0.2",
"resolved": "https://registry.npmjs.org/balanced-match/-/balanced-match-1.0.2.tgz",
"integrity": "sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw==",
"dev": true
"integrity": "sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw=="
},
"node_modules/brace-expansion": {
"version": "1.1.12",
"resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-1.1.12.tgz",
"integrity": "sha512-9T9UjW3r0UW5c1Q7GTwllptXwhvYmEzFhzMfZ9H7FQWt+uZePjZPjBP/W1ZEyZ1twGWom5/56TF4lPcqjnDHcg==",
"version": "1.1.11",
"resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-1.1.11.tgz",
"integrity": "sha512-iCuPHDFgrHX7H2vEI/5xpz07zSHB00TpugqhmYtVmMO6518mCuRMoOYFldEBl0g187ufozdaHgWKcYFb61qGiA==",
"dev": true,
"license": "MIT",
"dependencies": {
"balanced-match": "^1.0.0",
"concat-map": "0.0.1"
@@ -2018,19 +2102,6 @@
"integrity": "sha512-E+XQCRwSbaaiChtv6k6Dwgc+bx+Bs6vuKJHHl5kox/BaKbhiXzqQOwK4cO22yElGp2OCmjwVhT3HmxgyPGnJfQ==",
"dev": true
},
"node_modules/call-bind-apply-helpers": {
"version": "1.0.2",
"resolved": "https://registry.npmjs.org/call-bind-apply-helpers/-/call-bind-apply-helpers-1.0.2.tgz",
"integrity": "sha512-Sp1ablJ0ivDkSzjcaJdxEunN5/XvksFJ2sMBFfq6x0ryhQV/2b/KwFe21cMpmHtPOSij8K99/wSfoEuTObmuMQ==",
"license": "MIT",
"dependencies": {
"es-errors": "^1.3.0",
"function-bind": "^1.1.2"
},
"engines": {
"node": ">= 0.4"
}
},
"node_modules/callsites": {
"version": "3.1.0",
"resolved": "https://registry.npmjs.org/callsites/-/callsites-3.1.0.tgz",
@@ -2227,11 +2298,9 @@
}
},
"node_modules/cross-spawn": {
"version": "7.0.6",
"resolved": "https://registry.npmjs.org/cross-spawn/-/cross-spawn-7.0.6.tgz",
"integrity": "sha512-uV2QOWP2nWzsy2aMp8aRibhi9dlzF5Hgh5SHaB9OiTGEyDTiJJyx0uy51QXdyWbtAHNua4XJzUKca3OzKUd3vA==",
"dev": true,
"license": "MIT",
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"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",
@@ -4299,7 +4354,6 @@
"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"
},
@@ -4311,7 +4365,6 @@
"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"
}
@@ -4399,7 +4452,20 @@
"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",
"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==",
"dependencies": {
"emoji-regex": "^8.0.0",
"is-fullwidth-code-point": "^3.0.0",
@@ -4413,7 +4479,18 @@
"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"
},
"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==",
"dependencies": {
"ansi-regex": "^5.0.1"
},
@@ -4464,15 +4541,15 @@
}
},
"node_modules/tar": {
"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",
"version": "7.4.3",
"resolved": "https://registry.npmjs.org/tar/-/tar-7.4.3.tgz",
"integrity": "sha512-5S7Va8hKfV7W5U6g3aYxXmlPoZVAwUMy9AOKyF2fVuZa2UD3qZjg578OrLRt8PcNN1PleVaL/5/yYATNL0ICUw==",
"dependencies": {
"@isaacs/fs-minipass": "^4.0.0",
"chownr": "^3.0.0",
"minipass": "^7.1.2",
"minizlib": "^3.1.0",
"minizlib": "^3.0.1",
"mkdirp": "^3.0.1",
"yallist": "^5.0.0"
},
"engines": {
@@ -4705,7 +4782,6 @@
"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"
},
@@ -4733,6 +4809,23 @@
"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

@@ -20,8 +20,6 @@ import {
Float32,
Float64,
Int,
Int8,
Int16,
Int32,
Int64,
LargeBinary,
@@ -37,8 +35,6 @@ import {
Timestamp,
Type,
Uint8,
Uint16,
Uint32,
Utf8,
Vector,
makeVector as arrowMakeVector,
@@ -533,8 +529,7 @@ function isObject(value: unknown): value is Record<string, unknown> {
!(value instanceof Date) &&
!(value instanceof Set) &&
!(value instanceof Map) &&
!(value instanceof Buffer) &&
!ArrayBuffer.isView(value)
!(value instanceof Buffer)
);
}
@@ -593,13 +588,6 @@ 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
@@ -758,32 +746,6 @@ 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[],
@@ -852,16 +814,6 @@ 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

@@ -5,15 +5,12 @@ import {
Table as ArrowTable,
Data,
DataType,
Field,
IntoVector,
MultiVector,
Schema,
dataTypeToJson,
fromDataToBuffer,
fromTableToBuffer,
isMultiVector,
makeEmptyTable,
tableFromIPC,
} from "./arrow";
@@ -87,16 +84,6 @@ 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;
}
@@ -394,16 +381,15 @@ export abstract class Table {
abstract vectorSearch(vector: IntoVector | MultiVector): VectorQuery;
/**
* Add new columns with defined values.
* @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)
* @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.
* @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[] | Field | Field[] | Schema,
newColumnTransforms: AddColumnsSql[],
): Promise<AddColumnsResult>;
/**
@@ -515,7 +501,19 @@ export abstract class Table {
* - Index: Optimizes the indices, adding new data to existing indices
*
*
* The frequency an application should call optimize is based on the frequency of
* 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
* 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
@@ -808,40 +806,9 @@ export class LocalTable extends Table {
// TODO: Support BatchUDF
async addColumns(
newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
newColumnTransforms: AddColumnsSql[],
): Promise<AddColumnsResult> {
// 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");
return await this.inner.addColumns(newColumnTransforms);
}
async alterColumns(

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-darwin-arm64",
"version": "0.27.2-beta.0",
"version": "0.27.0-beta.3",
"os": ["darwin"],
"cpu": ["arm64"],
"main": "lancedb.darwin-arm64.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-arm64-gnu",
"version": "0.27.2-beta.0",
"version": "0.27.0-beta.3",
"os": ["linux"],
"cpu": ["arm64"],
"main": "lancedb.linux-arm64-gnu.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-arm64-musl",
"version": "0.27.2-beta.0",
"version": "0.27.0-beta.3",
"os": ["linux"],
"cpu": ["arm64"],
"main": "lancedb.linux-arm64-musl.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-x64-gnu",
"version": "0.27.2-beta.0",
"version": "0.27.0-beta.3",
"os": ["linux"],
"cpu": ["x64"],
"main": "lancedb.linux-x64-gnu.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-x64-musl",
"version": "0.27.2-beta.0",
"version": "0.27.0-beta.3",
"os": ["linux"],
"cpu": ["x64"],
"main": "lancedb.linux-x64-musl.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-win32-arm64-msvc",
"version": "0.27.2-beta.0",
"version": "0.27.0-beta.3",
"os": [
"win32"
],

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-win32-x64-msvc",
"version": "0.27.2-beta.0",
"version": "0.27.0-beta.3",
"os": ["win32"],
"cpu": ["x64"],
"main": "lancedb.win32-x64-msvc.node",

4599
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": "0.27.2-beta.0",
"version": "0.27.0-beta.3",
"main": "dist/index.js",
"exports": {
".": "./dist/index.js",

View File

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

View File

@@ -3,7 +3,7 @@
use std::collections::HashMap;
use lancedb::ipc::{ipc_file_to_batches, ipc_file_to_schema};
use lancedb::ipc::ipc_file_to_batches;
use lancedb::table::{
AddDataMode, ColumnAlteration as LanceColumnAlteration, Duration, NewColumnTransform,
OptimizeAction, OptimizeOptions, Table as LanceDbTable,
@@ -279,23 +279,6 @@ 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 = "0.30.2-beta.1"
current_version = "0.30.0-beta.3"
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 = "0.30.2-beta.1"
version = "0.30.0-beta.3"
edition.workspace = true
description = "Python bindings for LanceDB"
license.workspace = true
@@ -16,14 +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
log.workspace = true
pyo3 = { version = "0.26", features = ["extension-module", "abi3-py39"] }
pyo3-async-runtimes = { version = "0.26", features = [
"attributes",
@@ -31,8 +28,6 @@ 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 Python SDK
# LanceDB
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>=2.1.0",
"numpy>=1.24.0",
"deprecation",
"numpy",
"overrides>=0.7; python_version<'3.12'",
"packaging>=23.0",
"packaging",
"pyarrow>=16",
"pydantic>=1.10",
"tqdm>=4.27.0",
@@ -45,51 +45,51 @@ repository = "https://github.com/lancedb/lancedb"
[project.optional-dependencies]
pylance = [
"pylance>=4.0.0b7",
"pylance>=1.0.0b14",
]
tests = [
"aiohttp>=3.9.0",
"boto3>=1.28.57",
"aiohttp",
"boto3",
"pandas>=1.4",
"pytest>=7.0",
"pytest-mock>=3.10",
"pytest-asyncio>=0.21",
"duckdb>=0.9.0",
"pytz>=2023.3",
"pytest",
"pytest-mock",
"pytest-asyncio",
"duckdb",
"pytz",
"polars>=0.19, <=1.3.0",
"tantivy>=0.20.0",
"pyarrow-stubs>=16.0",
"pylance>=4.0.0b7",
"requests>=2.31.0",
"datafusion>=52,<53",
"tantivy",
"pyarrow-stubs",
"pylance>=1.0.0b14,<3.0.0",
"requests",
"datafusion<52",
]
dev = [
"ruff>=0.3.0",
"pre-commit>=3.5.0",
"pyright>=1.1.350",
"ruff",
"pre-commit",
"pyright",
'typing-extensions>=4.0.0; python_version < "3.11"',
]
docs = ["mkdocs", "mkdocs-jupyter", "mkdocs-material", "mkdocstrings-python"]
clip = ["torch", "pillow>=12.1.1", "open-clip-torch"]
siglip = ["torch", "pillow>=12.1.1", "transformers>=4.41.0","sentencepiece"]
clip = ["torch", "pillow", "open-clip-torch"]
siglip = ["torch", "pillow", "transformers>=4.41.0","sentencepiece"]
embeddings = [
"requests>=2.31.0",
"openai>=1.6.1",
"sentence-transformers>=2.2.0",
"torch>=2.0.0",
"pillow>=12.1.1",
"open-clip-torch>=2.20.0",
"cohere>=4.0",
"sentence-transformers",
"torch",
"pillow",
"open-clip-torch",
"cohere",
"colpali-engine>=0.3.10",
"huggingface_hub>=0.19.0",
"InstructorEmbedding>=1.0.1",
"google.generativeai>=0.3.0",
"huggingface_hub",
"InstructorEmbedding",
"google.generativeai",
"boto3>=1.28.57",
"awscli>=1.44.38",
"awscli>=1.29.57",
"botocore>=1.31.57",
'ibm-watsonx-ai>=1.1.2; python_version >= "3.10"',
"ollama>=0.3.0",
"sentencepiece>=0.1.99"
"sentencepiece"
]
azure = ["adlfs>=2024.2.0"]

View File

@@ -135,10 +135,7 @@ class Table:
def close(self) -> None: ...
async def schema(self) -> pa.Schema: ...
async def add(
self,
data: pa.RecordBatchReader,
mode: Literal["append", "overwrite"],
progress: Optional[Any] = None,
self, data: pa.RecordBatchReader, mode: Literal["append", "overwrite"]
) -> AddResult: ...
async def update(
self, updates: Dict[str, str], where: Optional[str]
@@ -169,8 +166,6 @@ 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, Any, Dict, Iterable, List, Literal, Optional, Union
from typing import TYPE_CHECKING, Dict, Iterable, List, Literal, Optional, Union
if sys.version_info >= (3, 12):
from typing import override
@@ -1541,8 +1541,6 @@ 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.
@@ -1575,9 +1573,6 @@ 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
-------
@@ -1592,8 +1587,6 @@ 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

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

View File

@@ -12,7 +12,7 @@ from __future__ import annotations
import asyncio
import sys
from typing import Any, Dict, Iterable, List, Optional, Union
from typing import 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._namespace_client = namespace
self._ns = 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._namespace_client.list_tables(request)
response = self._ns.list_tables(request)
return response.tables if response.tables else []
@override
@@ -309,9 +309,7 @@ class LanceNamespaceDBConnection(DBConnection):
# Try to describe the table first to see if it exists
try:
describe_request = DescribeTableRequest(id=table_id)
describe_response = self._namespace_client.describe_table(
describe_request
)
describe_response = self._ns.describe_table(describe_request)
location = describe_response.location
namespace_storage_options = describe_response.storage_options
except Exception:
@@ -325,7 +323,7 @@ class LanceNamespaceDBConnection(DBConnection):
location=None,
properties=self.storage_options if self.storage_options else None,
)
declare_response = self._namespace_client.declare_table(declare_request)
declare_response = self._ns.declare_table(declare_request)
if not declare_response.location:
raise ValueError(
@@ -355,7 +353,7 @@ 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._namespace_client,
namespace=self._ns,
table_id=table_id,
)
@@ -373,7 +371,6 @@ class LanceNamespaceDBConnection(DBConnection):
storage_options=merged_storage_options,
storage_options_provider=storage_options_provider,
location=location,
namespace_client=self._namespace_client,
)
return tbl
@@ -392,7 +389,7 @@ class LanceNamespaceDBConnection(DBConnection):
namespace = []
table_id = namespace + [name]
request = DescribeTableRequest(id=table_id)
response = self._namespace_client.describe_table(request)
response = self._ns.describe_table(request)
# Merge storage options: self.storage_options < user options < namespace options
merged_storage_options = dict(self.storage_options)
@@ -405,14 +402,10 @@ 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._namespace_client,
namespace=self._ns,
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,
@@ -420,8 +413,6 @@ 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
@@ -431,7 +422,7 @@ class LanceNamespaceDBConnection(DBConnection):
namespace = []
table_id = namespace + [name]
request = DropTableRequest(id=table_id)
self._namespace_client.drop_table(request)
self._ns.drop_table(request)
@override
def rename_table(
@@ -493,7 +484,7 @@ class LanceNamespaceDBConnection(DBConnection):
request = ListNamespacesRequest(
id=namespace, page_token=page_token, limit=limit
)
response = self._namespace_client.list_namespaces(request)
response = self._ns.list_namespaces(request)
return ListNamespacesResponse(
namespaces=response.namespaces if response.namespaces else [],
page_token=response.page_token,
@@ -529,7 +520,7 @@ class LanceNamespaceDBConnection(DBConnection):
mode=_normalize_create_namespace_mode(mode),
properties=properties,
)
response = self._namespace_client.create_namespace(request)
response = self._ns.create_namespace(request)
return CreateNamespaceResponse(
properties=response.properties if hasattr(response, "properties") else None
)
@@ -564,7 +555,7 @@ class LanceNamespaceDBConnection(DBConnection):
mode=_normalize_drop_namespace_mode(mode),
behavior=_normalize_drop_namespace_behavior(behavior),
)
response = self._namespace_client.drop_namespace(request)
response = self._ns.drop_namespace(request)
return DropNamespaceResponse(
properties=(
response.properties if hasattr(response, "properties") else None
@@ -590,7 +581,7 @@ class LanceNamespaceDBConnection(DBConnection):
Response containing the namespace properties.
"""
request = DescribeNamespaceRequest(id=namespace)
response = self._namespace_client.describe_namespace(request)
response = self._ns.describe_namespace(request)
return DescribeNamespaceResponse(
properties=response.properties if hasattr(response, "properties") else None
)
@@ -624,7 +615,7 @@ class LanceNamespaceDBConnection(DBConnection):
if namespace is None:
namespace = []
request = ListTablesRequest(id=namespace, page_token=page_token, limit=limit)
response = self._namespace_client.list_tables(request)
response = self._ns.list_tables(request)
return ListTablesResponse(
tables=response.tables if response.tables else [],
page_token=response.page_token,
@@ -639,8 +630,6 @@ 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
@@ -654,8 +643,6 @@ 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,
@@ -664,8 +651,6 @@ 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,
)
@@ -700,7 +685,7 @@ class AsyncLanceNamespaceDBConnection:
session : Optional[Session]
A session to use for this connection
"""
self._namespace_client = namespace
self._ns = namespace
self.read_consistency_interval = read_consistency_interval
self.storage_options = storage_options or {}
self.session = session
@@ -728,7 +713,7 @@ class AsyncLanceNamespaceDBConnection:
if namespace is None:
namespace = []
request = ListTablesRequest(id=namespace, page_token=page_token, limit=limit)
response = self._namespace_client.list_tables(request)
response = self._ns.list_tables(request)
return response.tables if response.tables else []
async def create_table(
@@ -765,9 +750,7 @@ class AsyncLanceNamespaceDBConnection:
# Try to describe the table first to see if it exists
try:
describe_request = DescribeTableRequest(id=table_id)
describe_response = self._namespace_client.describe_table(
describe_request
)
describe_response = self._ns.describe_table(describe_request)
location = describe_response.location
namespace_storage_options = describe_response.storage_options
except Exception:
@@ -781,7 +764,7 @@ class AsyncLanceNamespaceDBConnection:
location=None,
properties=self.storage_options if self.storage_options else None,
)
declare_response = self._namespace_client.declare_table(declare_request)
declare_response = self._ns.declare_table(declare_request)
if not declare_response.location:
raise ValueError(
@@ -814,7 +797,7 @@ class AsyncLanceNamespaceDBConnection:
and namespace_storage_options is not None
):
provider = LanceNamespaceStorageOptionsProvider(
namespace=self._namespace_client,
namespace=self._ns,
table_id=table_id,
)
else:
@@ -834,7 +817,6 @@ 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)
@@ -855,7 +837,7 @@ class AsyncLanceNamespaceDBConnection:
namespace = []
table_id = namespace + [name]
request = DescribeTableRequest(id=table_id)
response = self._namespace_client.describe_table(request)
response = self._ns.describe_table(request)
# Merge storage options: self.storage_options < user options < namespace options
merged_storage_options = dict(self.storage_options)
@@ -867,14 +849,10 @@ 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._namespace_client,
namespace=self._ns,
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(
@@ -892,8 +870,6 @@ 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)
@@ -905,7 +881,7 @@ class AsyncLanceNamespaceDBConnection:
namespace = []
table_id = namespace + [name]
request = DropTableRequest(id=table_id)
self._namespace_client.drop_table(request)
self._ns.drop_table(request)
async def rename_table(
self,
@@ -967,7 +943,7 @@ class AsyncLanceNamespaceDBConnection:
request = ListNamespacesRequest(
id=namespace, page_token=page_token, limit=limit
)
response = self._namespace_client.list_namespaces(request)
response = self._ns.list_namespaces(request)
return ListNamespacesResponse(
namespaces=response.namespaces if response.namespaces else [],
page_token=response.page_token,
@@ -1002,7 +978,7 @@ class AsyncLanceNamespaceDBConnection:
mode=_normalize_create_namespace_mode(mode),
properties=properties,
)
response = self._namespace_client.create_namespace(request)
response = self._ns.create_namespace(request)
return CreateNamespaceResponse(
properties=response.properties if hasattr(response, "properties") else None
)
@@ -1036,7 +1012,7 @@ class AsyncLanceNamespaceDBConnection:
mode=_normalize_drop_namespace_mode(mode),
behavior=_normalize_drop_namespace_behavior(behavior),
)
response = self._namespace_client.drop_namespace(request)
response = self._ns.drop_namespace(request)
return DropNamespaceResponse(
properties=(
response.properties if hasattr(response, "properties") else None
@@ -1063,7 +1039,7 @@ class AsyncLanceNamespaceDBConnection:
Response containing the namespace properties.
"""
request = DescribeNamespaceRequest(id=namespace)
response = self._namespace_client.describe_namespace(request)
response = self._ns.describe_namespace(request)
return DescribeNamespaceResponse(
properties=response.properties if hasattr(response, "properties") else None
)
@@ -1096,7 +1072,7 @@ class AsyncLanceNamespaceDBConnection:
if namespace is None:
namespace = []
request = ListTablesRequest(id=namespace, page_token=page_token, limit=limit)
response = self._namespace_client.list_tables(request)
response = self._ns.list_tables(request)
return ListTablesResponse(
tables=response.tables if response.tables else [],
page_token=response.page_token,

View File

@@ -2205,8 +2205,8 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
self._vector_query.select(self._columns)
self._fts_query.select(self._columns)
if self._where:
self._vector_query.where(self._where, not self._postfilter)
self._fts_query.where(self._where, not self._postfilter)
self._vector_query.where(self._where, self._postfilter)
self._fts_query.where(self._where, self._postfilter)
if self._with_row_id:
self._vector_query.with_row_id(True)
self._fts_query.with_row_id(True)

View File

@@ -4,7 +4,7 @@
from datetime import timedelta
import logging
from functools import cached_property
from typing import Any, Callable, Dict, Iterable, List, Optional, Union, Literal
from typing import Dict, Iterable, List, Optional, Union, Literal
import warnings
from lancedb._lancedb import (
@@ -35,7 +35,6 @@ import pyarrow as pa
from lancedb.common import DATA, VEC, VECTOR_COLUMN_NAME
from lancedb.merge import LanceMergeInsertBuilder
from lancedb.embeddings import EmbeddingFunctionRegistry
from lancedb.table import _normalize_progress
from ..query import LanceVectorQueryBuilder, LanceQueryBuilder, LanceTakeQueryBuilder
from ..table import AsyncTable, IndexStatistics, Query, Table, Tags
@@ -309,7 +308,6 @@ class RemoteTable(Table):
mode: str = "append",
on_bad_vectors: str = "error",
fill_value: float = 0.0,
progress: Optional[Union[bool, Callable, Any]] = None,
) -> AddResult:
"""Add more data to the [Table](Table). It has the same API signature as
the OSS version.
@@ -332,29 +330,17 @@ class RemoteTable(Table):
One of "error", "drop", "fill".
fill_value: float, default 0.
The value to use when filling vectors. Only used if on_bad_vectors="fill".
progress: bool, callable, or tqdm-like, optional
A callback or tqdm-compatible progress bar. See
:meth:`Table.add` for details.
Returns
-------
AddResult
An object containing the new version number of the table after adding data.
"""
progress, owns = _normalize_progress(progress)
try:
return LOOP.run(
self._table.add(
data,
mode=mode,
on_bad_vectors=on_bad_vectors,
fill_value=fill_value,
progress=progress,
)
return LOOP.run(
self._table.add(
data, mode=mode, on_bad_vectors=on_bad_vectors, fill_value=fill_value
)
finally:
if owns:
progress.close()
)
def search(
self,
@@ -654,45 +640,6 @@ 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

@@ -14,7 +14,6 @@ from functools import cached_property
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
Iterable,
List,
@@ -557,21 +556,6 @@ def _table_uri(base: str, table_name: str) -> str:
return join_uri(base, f"{table_name}.lance")
def _normalize_progress(progress):
"""Normalize a ``progress`` parameter for :meth:`Table.add`.
Returns ``(progress_obj, owns)`` where *owns* is True when we created a
tqdm bar that the caller must close.
"""
if progress is True:
from tqdm.auto import tqdm
return tqdm(unit=" rows"), True
if progress is False or progress is None:
return None, False
return progress, False
class Table(ABC):
"""
A Table is a collection of Records in a LanceDB Database.
@@ -990,7 +974,6 @@ class Table(ABC):
mode: AddMode = "append",
on_bad_vectors: OnBadVectorsType = "error",
fill_value: float = 0.0,
progress: Optional[Union[bool, Callable, Any]] = None,
) -> AddResult:
"""Add more data to the [Table](Table).
@@ -1012,29 +995,6 @@ class Table(ABC):
One of "error", "drop", "fill".
fill_value: float, default 0.
The value to use when filling vectors. Only used if on_bad_vectors="fill".
progress: bool, callable, or tqdm-like, optional
Progress reporting during the add operation. Can be:
- ``True`` to automatically create and display a tqdm progress
bar (requires ``tqdm`` to be installed)::
table.add(data, progress=True)
- A **callable** that receives a dict with keys ``output_rows``,
``output_bytes``, ``total_rows``, ``elapsed_seconds``,
``active_tasks``, ``total_tasks``, and ``done``::
def on_progress(p):
print(f"{p['output_rows']}/{p['total_rows']} rows, "
f"{p['active_tasks']}/{p['total_tasks']} workers")
table.add(data, progress=on_progress)
- A **tqdm-compatible** progress bar whose ``total`` and
``update()`` will be called automatically. The postfix shows
write throughput (MB/s) and active worker count::
with tqdm() as pbar:
table.add(data, progress=pbar)
Returns
-------
@@ -1546,17 +1506,22 @@ 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.
The frequency an application should call optimize is based on the frequency of
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
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
@@ -1781,8 +1746,6 @@ 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:
@@ -1790,7 +1753,6 @@ 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:
@@ -1802,8 +1764,6 @@ 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,
)
)
@@ -1846,8 +1806,6 @@ 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 = []
@@ -1859,8 +1817,6 @@ 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
@@ -1892,16 +1848,6 @@ 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,
@@ -2254,18 +2200,12 @@ class LanceTable(Table):
def prewarm_index(self, name: str) -> None:
"""
Prewarm an index in the table.
Prewarms 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 loads the entire index into memory
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.
If the index does not fit into the available cache this call
may be wasteful
Parameters
----------
@@ -2274,29 +2214,6 @@ 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:
@@ -2532,7 +2449,6 @@ class LanceTable(Table):
mode: AddMode = "append",
on_bad_vectors: OnBadVectorsType = "error",
fill_value: float = 0.0,
progress: Optional[Union[bool, Callable, Any]] = None,
) -> AddResult:
"""Add data to the table.
If vector columns are missing and the table
@@ -2551,29 +2467,17 @@ class LanceTable(Table):
One of "error", "drop", "fill", "null".
fill_value: float, default 0.
The value to use when filling vectors. Only used if on_bad_vectors="fill".
progress: bool, callable, or tqdm-like, optional
A callback or tqdm-compatible progress bar. See
:meth:`Table.add` for details.
Returns
-------
int
The number of vectors in the table.
"""
progress, owns = _normalize_progress(progress)
try:
return LOOP.run(
self._table.add(
data,
mode=mode,
on_bad_vectors=on_bad_vectors,
fill_value=fill_value,
progress=progress,
)
return LOOP.run(
self._table.add(
data, mode=mode, on_bad_vectors=on_bad_vectors, fill_value=fill_value
)
finally:
if owns:
progress.close()
)
def merge(
self,
@@ -2809,7 +2713,6 @@ 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.
@@ -2870,7 +2773,6 @@ 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(
@@ -3095,17 +2997,22 @@ 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.
The frequency an application should call optimize is based on the frequency of
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
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
@@ -3706,47 +3613,19 @@ 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:
@@ -3822,7 +3701,6 @@ class AsyncTable:
mode: Optional[Literal["append", "overwrite"]] = "append",
on_bad_vectors: Optional[OnBadVectorsType] = None,
fill_value: Optional[float] = None,
progress: Optional[Union[bool, Callable, Any]] = None,
) -> AddResult:
"""Add more data to the [Table](Table).
@@ -3844,9 +3722,6 @@ class AsyncTable:
One of "error", "drop", "fill", "null".
fill_value: float, default 0.
The value to use when filling vectors. Only used if on_bad_vectors="fill".
progress: callable or tqdm-like, optional
A callback or tqdm-compatible progress bar. See
:meth:`Table.add` for details.
"""
schema = await self.schema()
@@ -3870,9 +3745,8 @@ class AsyncTable:
)
_register_optional_converters()
data = to_scannable(data)
progress, owns = _normalize_progress(progress)
try:
return await self._inner.add(data, mode or "append", progress=progress)
return await self._inner.add(data, mode or "append")
except RuntimeError as e:
if "Cast error" in str(e):
raise ValueError(e)
@@ -3880,9 +3754,6 @@ class AsyncTable:
raise ValueError(e)
else:
raise
finally:
if owns:
progress.close()
def merge_insert(self, on: Union[str, Iterable[str]]) -> LanceMergeInsertBuilder:
"""
@@ -4310,6 +4181,7 @@ class AsyncTable:
when_not_matched_by_source_condition=merge._when_not_matched_by_source_condition,
timeout=merge._timeout,
use_index=merge._use_index,
mem_wal=merge._mem_wal,
),
)
@@ -4681,17 +4553,22 @@ 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.
The frequency an application should call optimize is based on the frequency of
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
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
@@ -4812,16 +4689,7 @@ class IndexStatistics:
num_indexed_rows: int
num_unindexed_rows: int
index_type: Literal[
"IVF_FLAT",
"IVF_SQ",
"IVF_PQ",
"IVF_RQ",
"IVF_HNSW_SQ",
"IVF_HNSW_PQ",
"FTS",
"BTREE",
"BITMAP",
"LABEL_LIST",
"IVF_PQ", "IVF_HNSW_PQ", "IVF_HNSW_SQ", "FTS", "BTREE", "BITMAP", "LABEL_LIST"
]
distance_type: Optional[Literal["l2", "cosine", "dot"]] = None
num_indices: Optional[int] = None

View File

@@ -177,60 +177,6 @@ async def test_analyze_plan(table: AsyncTable):
assert "metrics=" in res
@pytest.fixture
def table_with_id(tmpdir_factory) -> Table:
tmp_path = str(tmpdir_factory.mktemp("data"))
db = lancedb.connect(tmp_path)
data = pa.table(
{
"id": pa.array([1, 2, 3, 4], type=pa.int64()),
"text": pa.array(["a", "b", "cat", "dog"]),
"vector": pa.array(
[[0.1, 0.1], [2, 2], [-0.1, -0.1], [0.5, -0.5]],
type=pa.list_(pa.float32(), list_size=2),
),
}
)
table = db.create_table("test_with_id", data)
table.create_fts_index("text", with_position=False, use_tantivy=False)
return table
def test_hybrid_prefilter_explain_plan(table_with_id: Table):
"""
Verify that the prefilter logic is not inverted in LanceHybridQueryBuilder.
"""
plan_prefilter = (
table_with_id.search(query_type="hybrid")
.vector([0.0, 0.0])
.text("dog")
.where("id = 1", prefilter=True)
.limit(2)
.explain_plan(verbose=True)
)
plan_postfilter = (
table_with_id.search(query_type="hybrid")
.vector([0.0, 0.0])
.text("dog")
.where("id = 1", prefilter=False)
.limit(2)
.explain_plan(verbose=True)
)
# prefilter=True: filter is pushed into the LanceRead scan.
# The FTS sub-plan exposes this as "full_filter=id = Int64(1)" inside LanceRead.
assert "full_filter=id = Int64(1)" in plan_prefilter, (
f"Should push the filter into the scan.\nPlan:\n{plan_prefilter}"
)
# prefilter=False: filter is applied as a separate FilterExec after the search.
# The filter must NOT be embedded in the scan.
assert "full_filter=id = Int64(1)" not in plan_postfilter, (
f"Should NOT push the filter into the scan.\nPlan:\n{plan_postfilter}"
)
def test_normalize_scores():
cases = [
(pa.array([0.1, 0.4]), pa.array([0.0, 1.0])),

View File

@@ -3,7 +3,6 @@
from datetime import timedelta
import random
from typing import get_args, get_type_hints
import pyarrow as pa
import pytest
@@ -23,7 +22,6 @@ from lancedb.index import (
HnswSq,
FTS,
)
from lancedb.table import IndexStatistics
@pytest_asyncio.fixture
@@ -285,23 +283,3 @@ async def test_create_index_with_binary_vectors(binary_table: AsyncTable):
for v in range(256):
res = await binary_table.query().nearest_to([v] * 128).to_arrow()
assert res["id"][0].as_py() == v
def test_index_statistics_index_type_lists_all_supported_values():
expected_index_types = {
"IVF_FLAT",
"IVF_SQ",
"IVF_PQ",
"IVF_RQ",
"IVF_HNSW_SQ",
"IVF_HNSW_PQ",
"FTS",
"BTREE",
"BITMAP",
"LABEL_LIST",
}
assert (
set(get_args(get_type_hints(IndexStatistics)["index_type"]))
== expected_index_types
)

View File

@@ -147,12 +147,7 @@ class TrackingNamespace(LanceNamespace):
This simulates a credential rotation system where each call returns
new credentials that expire after credential_expires_in_seconds.
"""
# 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)
modified = copy.deepcopy(storage_options) if storage_options else {}
# Increment credentials to simulate rotation
modified["aws_access_key_id"] = f"AKID_{count}"

View File

@@ -326,24 +326,6 @@ 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(
@@ -527,102 +509,6 @@ async def test_add_async(mem_db_async: AsyncConnection):
assert await table.count_rows() == 3
def test_add_progress_callback(mem_db: DBConnection):
table = mem_db.create_table(
"test",
data=[{"id": 1}, {"id": 2}],
)
updates = []
table.add([{"id": 3}, {"id": 4}], progress=lambda p: updates.append(dict(p)))
assert len(table) == 4
# The done callback always fires, so we should always get at least one.
assert len(updates) >= 1, "expected at least one progress callback"
for p in updates:
assert "output_rows" in p
assert "output_bytes" in p
assert "total_rows" in p
assert "elapsed_seconds" in p
assert "active_tasks" in p
assert "total_tasks" in p
assert "done" in p
# The last callback should have done=True.
assert updates[-1]["done"] is True
def test_add_progress_tqdm_like(mem_db: DBConnection):
"""Test that a tqdm-like object gets total set and update() called."""
class FakeBar:
def __init__(self):
self.total = None
self.n = 0
self.postfix = None
def update(self, n):
self.n += n
def set_postfix_str(self, s):
self.postfix = s
def refresh(self):
pass
table = mem_db.create_table(
"test",
data=[{"id": 1}, {"id": 2}],
)
bar = FakeBar()
table.add([{"id": 3}, {"id": 4}], progress=bar)
assert len(table) == 4
# Postfix should contain throughput and worker count
if bar.postfix is not None:
assert "MB/s" in bar.postfix
assert "workers" in bar.postfix
def test_add_progress_bool(mem_db: DBConnection):
"""Test that progress=True creates and closes a tqdm bar automatically."""
table = mem_db.create_table(
"test",
data=[{"id": 1}, {"id": 2}],
)
table.add([{"id": 3}, {"id": 4}], progress=True)
assert len(table) == 4
# progress=False should be the same as None
table.add([{"id": 5}], progress=False)
assert len(table) == 5
@pytest.mark.asyncio
async def test_add_progress_callback_async(mem_db_async: AsyncConnection):
"""Progress callbacks work through the async path too."""
table = await mem_db_async.create_table("test", data=[{"id": 1}, {"id": 2}])
updates = []
await table.add([{"id": 3}, {"id": 4}], progress=lambda p: updates.append(dict(p)))
assert await table.count_rows() == 4
assert len(updates) >= 1
assert updates[-1]["done"] is True
def test_add_progress_callback_error(mem_db: DBConnection):
"""A failing callback must not prevent the write from succeeding."""
table = mem_db.create_table("test", data=[{"id": 1}, {"id": 2}])
def bad_callback(p):
raise RuntimeError("boom")
table.add([{"id": 3}, {"id": 4}], progress=bad_callback)
assert len(table) == 4
def test_polars(mem_db: DBConnection):
data = {
"vector": [[3.1, 4.1], [5.9, 26.5]],

View File

@@ -17,8 +17,7 @@ use pyo3::{
use pyo3_async_runtimes::tokio::future_into_py;
use crate::{
error::PythonErrorExt, namespace::extract_namespace_arc,
storage_options::py_object_to_storage_options_provider, table::Table,
error::PythonErrorExt, storage_options::py_object_to_storage_options_provider, table::Table,
};
#[pyclass]
@@ -183,8 +182,7 @@ impl Connection {
})
}
#[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))]
#[pyo3(signature = (name, namespace=vec![], storage_options = None, storage_options_provider=None, index_cache_size = None, location=None))]
pub fn open_table(
self_: PyRef<'_, Self>,
name: String,
@@ -193,13 +191,11 @@ 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.clone());
builder = builder.namespace(namespace);
if let Some(storage_options) = storage_options {
builder = builder.storage_options(storage_options);
}
@@ -213,20 +209,6 @@ 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()?;
@@ -524,6 +506,7 @@ pub struct PyClientConfig {
id_delimiter: Option<String>,
tls_config: Option<PyClientTlsConfig>,
header_provider: Option<Py<PyAny>>,
mem_wal_enabled: Option<bool>,
}
#[derive(FromPyObject)]
@@ -608,6 +591,7 @@ impl From<PyClientConfig> for lancedb::remote::ClientConfig {
id_delimiter: value.id_delimiter,
tls_config: value.tls_config.map(Into::into),
header_provider,
mem_wal_enabled: value.mem_wal_enabled,
}
}
}

View File

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

View File

@@ -1,696 +0,0 @@
// 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

@@ -316,19 +316,6 @@ 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

@@ -19,7 +19,7 @@ use lancedb::table::{
Table as LanceDbTable,
};
use pyo3::{
Bound, FromPyObject, Py, PyAny, PyRef, PyResult, Python,
Bound, FromPyObject, PyAny, PyRef, PyResult, Python,
exceptions::{PyKeyError, PyRuntimeError, PyValueError},
pyclass, pymethods,
types::{IntoPyDict, PyAnyMethods, PyDict, PyDictMethods},
@@ -299,12 +299,10 @@ impl Table {
})
}
#[pyo3(signature = (data, mode, progress=None))]
pub fn add<'a>(
self_: PyRef<'a, Self>,
data: PyScannable,
mode: String,
progress: Option<Py<PyAny>>,
) -> PyResult<Bound<'a, PyAny>> {
let mut op = self_.inner_ref()?.add(data);
if mode == "append" {
@@ -314,81 +312,6 @@ impl Table {
} else {
return Err(PyValueError::new_err(format!("Invalid mode: {}", mode)));
}
if let Some(progress_obj) = progress {
let is_callable = Python::attach(|py| progress_obj.bind(py).is_callable());
if is_callable {
// Callback: call with a dict of progress info.
op = op.progress(move |p| {
Python::attach(|py| {
let dict = PyDict::new(py);
if let Err(e) = dict
.set_item("output_rows", p.output_rows())
.and_then(|_| dict.set_item("output_bytes", p.output_bytes()))
.and_then(|_| dict.set_item("total_rows", p.total_rows()))
.and_then(|_| {
dict.set_item("elapsed_seconds", p.elapsed().as_secs_f64())
})
.and_then(|_| dict.set_item("active_tasks", p.active_tasks()))
.and_then(|_| dict.set_item("total_tasks", p.total_tasks()))
.and_then(|_| dict.set_item("done", p.done()))
{
log::warn!("progress dict error: {e}");
return;
}
if let Err(e) = progress_obj.call1(py, (dict,)) {
log::warn!("progress callback error: {e}");
}
});
});
} else {
// tqdm-like: has update() method.
let mut last_rows: usize = 0;
let mut total_set = false;
op = op.progress(move |p| {
let current = p.output_rows();
let prev = last_rows;
last_rows = current;
Python::attach(|py| {
if let Some(total) = p.total_rows()
&& !total_set
{
if let Err(e) = progress_obj.setattr(py, "total", total) {
log::warn!("progress setattr error: {e}");
}
total_set = true;
}
let delta = current.saturating_sub(prev);
if delta > 0 {
if let Err(e) = progress_obj.call_method1(py, "update", (delta,)) {
log::warn!("progress update error: {e}");
}
// Show throughput and active workers in tqdm postfix.
let elapsed = p.elapsed().as_secs_f64();
if elapsed > 0.0 {
let mb_per_sec = p.output_bytes() as f64 / elapsed / 1_000_000.0;
let postfix = format!(
"{:.1} MB/s | {}/{} workers",
mb_per_sec,
p.active_tasks(),
p.total_tasks()
);
if let Err(e) =
progress_obj.call_method1(py, "set_postfix_str", (postfix,))
{
log::warn!("progress set_postfix_str error: {e}");
}
}
}
if p.done() {
// Force a final refresh so the bar shows completion.
if let Err(e) = progress_obj.call_method0(py, "refresh") {
log::warn!("progress refresh error: {e}");
}
}
});
});
}
}
future_into_py(self_.py(), async move {
let result = op.execute().await.infer_error()?;
@@ -503,17 +426,6 @@ 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 {
@@ -798,6 +710,9 @@ impl Table {
if let Some(use_index) = parameters.use_index {
builder.use_index(use_index);
}
if let Some(mem_wal) = parameters.mem_wal {
builder.mem_wal(mem_wal);
}
future_into_py(self_.py(), async move {
let res = builder.execute(Box::new(batches)).await.infer_error()?;
@@ -958,6 +873,7 @@ pub struct MergeInsertParams {
when_not_matched_by_source_condition: Option<String>,
timeout: Option<std::time::Duration>,
use_index: Option<bool>,
mem_wal: Option<bool>,
}
#[pyclass]

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'", specifier = "<52" },
{ name = "datafusion", marker = "extra == 'tests'" },
{ 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,<3.0.0" },
{ name = "pylance", marker = "extra == 'tests'", specifier = ">=1.0.0b14" },
{ 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 = "0.27.2-beta.0"
version = "0.27.0-beta.3"
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 SDK
# LanceDB Rust
<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

@@ -136,7 +136,6 @@ impl OpenTableBuilder {
lance_read_params: None,
location: None,
namespace_client: None,
managed_versioning: None,
},
embedding_registry,
}
@@ -236,29 +235,6 @@ 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?;
@@ -318,12 +294,6 @@ 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();
@@ -596,8 +566,11 @@ pub struct ConnectBuilder {
}
#[cfg(feature = "remote")]
const ENV_VARS_TO_STORAGE_OPTS: [(&str, &str); 1] =
[("AZURE_STORAGE_ACCOUNT_NAME", "azure_storage_account_name")];
const ENV_VARS_TO_STORAGE_OPTS: [(&str, &str); 3] = [
("AZURE_STORAGE_ACCOUNT_NAME", "azure_storage_account_name"),
("AZURE_CLIENT_ID", "azure_client_id"),
("AZURE_TENANT_ID", "azure_tenant_id"),
];
impl ConnectBuilder {
/// Create a new [`ConnectOptions`] with the given database URI.
@@ -811,13 +784,19 @@ impl ConnectBuilder {
message: "An api_key is required when connecting to LanceDb Cloud".to_string(),
})?;
// Propagate mem_wal_enabled from options to client_config
let mut client_config = self.request.client_config;
if options.mem_wal_enabled.is_some() {
client_config.mem_wal_enabled = options.mem_wal_enabled;
}
let storage_options = StorageOptions(options.storage_options.clone());
let internal = Arc::new(crate::remote::db::RemoteDatabase::try_new(
&self.request.uri,
&api_key,
&region,
options.host_override,
self.request.client_config,
client_config,
storage_options.into(),
)?);
Ok(Connection {

View File

@@ -66,10 +66,6 @@ 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 {
@@ -81,7 +77,6 @@ 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()
}
}
@@ -166,9 +161,6 @@ 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 {
@@ -180,7 +172,6 @@ impl CloneTableRequest {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
}
}
}

View File

@@ -669,7 +669,6 @@ 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?;
@@ -870,7 +869,6 @@ 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
{
@@ -948,9 +946,7 @@ impl Database for ListingDatabase {
self.store_wrapper.clone(),
None,
self.read_consistency_interval,
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
None,
)
.await?;
@@ -1026,8 +1022,6 @@ 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?,
);
@@ -1168,7 +1162,6 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await
.unwrap();
@@ -1229,7 +1222,6 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await
.unwrap();
@@ -1289,7 +1281,6 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await;
@@ -1326,7 +1317,6 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: false, // Request deep clone
namespace_client: None,
})
.await;
@@ -1367,7 +1357,6 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await;
@@ -1408,7 +1397,6 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await;
@@ -1428,7 +1416,6 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await;
@@ -1465,7 +1452,6 @@ mod tests {
source_version: Some(1),
source_tag: Some("v1.0".to_string()),
is_shallow: true,
namespace_client: None,
})
.await;
@@ -1539,7 +1525,6 @@ mod tests {
source_version: Some(initial_version),
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await
.unwrap();
@@ -1618,7 +1603,6 @@ mod tests {
source_version: None,
source_tag: Some("v1.0".to_string()),
is_shallow: true,
namespace_client: None,
})
.await
.unwrap();
@@ -1670,7 +1654,6 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await
.unwrap();
@@ -1763,7 +1746,6 @@ mod tests {
source_version: None,
source_tag: None,
is_shallow: true,
namespace_client: None,
})
.await
.unwrap();

View File

@@ -7,7 +7,6 @@ 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,
@@ -19,8 +18,6 @@ use lance_namespace::{
},
};
use lance_namespace_impls::ConnectBuilder;
use lance_table::io::commit::CommitHandler;
use lance_table::io::commit::external_manifest::ExternalManifestCommitHandler;
use crate::database::ReadConsistency;
use crate::error::{Error, Result};
@@ -208,12 +205,14 @@ 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, managed_versioning) = {
let (location, initial_storage_options) = {
let response = self.namespace.declare_table(declare_request).await?;
let loc = response.location.ok_or_else(|| Error::Runtime {
message: "Table location is missing from declare_table response".to_string(),
@@ -223,33 +222,21 @@ impl Database for LanceNamespaceDatabase {
.storage_options
.or_else(|| Some(self.storage_options.clone()))
.filter(|o| !o.is_empty());
(loc, opts, response.managed_versioning)
(loc, opts)
};
// Build write params with storage options and commit handler
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 write_params = if let Some(storage_opts) = initial_storage_options {
let mut params = request.write_options.lance_write_params.unwrap_or_default();
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),
));
}
// 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);
Some(params)
} else {
request.write_options.lance_write_params
};
let native_table = NativeTable::create_from_namespace(
self.namespace.clone(),

View File

@@ -339,12 +339,6 @@ 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

@@ -47,25 +47,6 @@ 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 {
@@ -88,29 +69,6 @@ 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
@@ -1633,58 +1591,6 @@ 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

@@ -14,6 +14,7 @@ use crate::remote::db::RemoteOptions;
use crate::remote::retry::{ResolvedRetryConfig, RetryCounter};
const REQUEST_ID_HEADER: HeaderName = HeaderName::from_static("x-request-id");
const MEM_WAL_ENABLED_HEADER: HeaderName = HeaderName::from_static("x-lancedb-mem-wal-enabled");
/// Configuration for TLS/mTLS settings.
#[derive(Clone, Debug, Default)]
@@ -52,6 +53,10 @@ pub struct ClientConfig {
pub tls_config: Option<TlsConfig>,
/// Provider for custom headers to be added to each request
pub header_provider: Option<Arc<dyn HeaderProvider>>,
/// Enable MemWAL write path for streaming writes.
/// When true, write operations will use the MemWAL architecture
/// for high-performance streaming writes.
pub mem_wal_enabled: Option<bool>,
}
impl std::fmt::Debug for ClientConfig {
@@ -67,6 +72,7 @@ impl std::fmt::Debug for ClientConfig {
"header_provider",
&self.header_provider.as_ref().map(|_| "Some(...)"),
)
.field("mem_wal_enabled", &self.mem_wal_enabled)
.finish()
}
}
@@ -81,6 +87,7 @@ impl Default for ClientConfig {
id_delimiter: None,
tls_config: None,
header_provider: None,
mem_wal_enabled: None,
}
}
}
@@ -426,11 +433,14 @@ impl<S: HttpSend> RestfulLanceDbClient<S> {
})?,
);
}
if let Some(prefix) = db_prefix {
if db_prefix.is_some() {
headers.insert(
HeaderName::from_static("x-lancedb-database-prefix"),
HeaderValue::from_str(prefix).map_err(|_| Error::InvalidInput {
message: format!("non-ascii database prefix '{}' provided", prefix),
HeaderValue::from_str(db_prefix.unwrap()).map_err(|_| Error::InvalidInput {
message: format!(
"non-ascii database prefix '{}' provided",
db_prefix.unwrap()
),
})?,
);
}
@@ -443,13 +453,23 @@ impl<S: HttpSend> RestfulLanceDbClient<S> {
})?,
);
}
if let Some(v) = options.0.get("azure_storage_account_name") {
headers.insert(
HeaderName::from_static("x-azure-storage-account-name"),
HeaderValue::from_str(v).map_err(|_| Error::InvalidInput {
message: format!("non-ascii storage account name '{}' provided", db_name),
})?,
);
// Map azure storage options to x-azure-* headers.
// The option key uses underscores (e.g. "azure_client_id") while the
// header uses hyphens (e.g. "x-azure-client-id").
let azure_opts: [(&str, &str); 3] = [
("azure_storage_account_name", "x-azure-storage-account-name"),
("azure_client_id", "x-azure-client-id"),
("azure_tenant_id", "x-azure-tenant-id"),
];
for (opt_key, header_name) in azure_opts {
if let Some(v) = options.0.get(opt_key) {
headers.insert(
HeaderName::from_static(header_name),
HeaderValue::from_str(v).map_err(|_| Error::InvalidInput {
message: format!("non-ascii value '{}' for option '{}'", v, opt_key),
})?,
);
}
}
for (key, value) in &config.extra_headers {
@@ -464,6 +484,11 @@ impl<S: HttpSend> RestfulLanceDbClient<S> {
);
}
// Add MemWAL header if enabled
if let Some(true) = config.mem_wal_enabled {
headers.insert(MEM_WAL_ENABLED_HEADER, HeaderValue::from_static("true"));
}
Ok(headers)
}
@@ -1072,4 +1097,34 @@ mod tests {
_ => panic!("Expected Runtime error"),
}
}
#[test]
fn test_default_headers_azure_opts() {
let mut opts = HashMap::new();
opts.insert(
"azure_storage_account_name".to_string(),
"myaccount".to_string(),
);
opts.insert("azure_client_id".to_string(), "my-client-id".to_string());
opts.insert("azure_tenant_id".to_string(), "my-tenant-id".to_string());
let remote_opts = RemoteOptions::new(opts);
let headers = RestfulLanceDbClient::<Sender>::default_headers(
"test-key",
"us-east-1",
"testdb",
false,
&remote_opts,
None,
&ClientConfig::default(),
)
.unwrap();
assert_eq!(
headers.get("x-azure-storage-account-name").unwrap(),
"myaccount"
);
assert_eq!(headers.get("x-azure-client-id").unwrap(), "my-client-id");
assert_eq!(headers.get("x-azure-tenant-id").unwrap(), "my-tenant-id");
}
}

View File

@@ -72,16 +72,13 @@ impl ServerVersion {
pub fn support_structural_fts(&self) -> bool {
self.0 >= semver::Version::new(0, 3, 0)
}
pub fn support_multipart_write(&self) -> bool {
self.0 >= semver::Version::new(0, 4, 0)
}
}
pub const OPT_REMOTE_PREFIX: &str = "remote_database_";
pub const OPT_REMOTE_API_KEY: &str = "remote_database_api_key";
pub const OPT_REMOTE_REGION: &str = "remote_database_region";
pub const OPT_REMOTE_HOST_OVERRIDE: &str = "remote_database_host_override";
pub const OPT_REMOTE_MEM_WAL_ENABLED: &str = "remote_database_mem_wal_enabled";
// TODO: add support for configuring client config via key/value options
#[derive(Clone, Debug, Default)]
@@ -102,6 +99,12 @@ pub struct RemoteDatabaseOptions {
/// These options are only used for LanceDB Enterprise and only a subset of options
/// are supported.
pub storage_options: HashMap<String, String>,
/// Enable MemWAL write path for high-performance streaming writes.
///
/// When enabled, write operations (insert, merge_insert, etc.) will use
/// the MemWAL architecture which buffers writes in memory and Write-Ahead Log
/// before asynchronously merging to the base table.
pub mem_wal_enabled: Option<bool>,
}
impl RemoteDatabaseOptions {
@@ -113,6 +116,9 @@ impl RemoteDatabaseOptions {
let api_key = map.get(OPT_REMOTE_API_KEY).cloned();
let region = map.get(OPT_REMOTE_REGION).cloned();
let host_override = map.get(OPT_REMOTE_HOST_OVERRIDE).cloned();
let mem_wal_enabled = map
.get(OPT_REMOTE_MEM_WAL_ENABLED)
.map(|v| v.to_lowercase() == "true");
let storage_options = map
.iter()
.filter(|(key, _)| !key.starts_with(OPT_REMOTE_PREFIX))
@@ -123,6 +129,7 @@ impl RemoteDatabaseOptions {
region,
host_override,
storage_options,
mem_wal_enabled,
})
}
}
@@ -141,6 +148,12 @@ impl DatabaseOptions for RemoteDatabaseOptions {
if let Some(host_override) = &self.host_override {
map.insert(OPT_REMOTE_HOST_OVERRIDE.to_string(), host_override.clone());
}
if let Some(mem_wal_enabled) = &self.mem_wal_enabled {
map.insert(
OPT_REMOTE_MEM_WAL_ENABLED.to_string(),
mem_wal_enabled.to_string(),
);
}
}
}
@@ -185,6 +198,20 @@ impl RemoteDatabaseOptionsBuilder {
self.options.host_override = Some(host_override);
self
}
/// Enable MemWAL write path for high-performance streaming writes.
///
/// When enabled, write operations will use the MemWAL architecture
/// which buffers writes in memory and Write-Ahead Log before
/// asynchronously merging to the base table.
///
/// # Arguments
///
/// * `enabled` - Whether to enable MemWAL writes
pub fn mem_wal_enabled(mut self, enabled: bool) -> Self {
self.options.mem_wal_enabled = Some(enabled);
self
}
}
#[derive(Debug)]
@@ -468,7 +495,6 @@ 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
@@ -782,7 +808,12 @@ impl RemoteOptions {
impl From<StorageOptions> for RemoteOptions {
fn from(options: StorageOptions) -> Self {
let supported_opts = vec!["account_name", "azure_storage_account_name"];
let supported_opts = vec![
"account_name",
"azure_storage_account_name",
"azure_client_id",
"azure_tenant_id",
];
let mut filtered = HashMap::new();
for opt in supported_opts {
if let Some(v) = options.0.get(opt) {

File diff suppressed because it is too large Load Diff

View File

@@ -11,14 +11,10 @@ use arrow_ipc::CompressionType;
use datafusion_common::{DataFusionError, Result as DataFusionResult};
use datafusion_execution::{SendableRecordBatchStream, TaskContext};
use datafusion_physical_expr::EquivalenceProperties;
use datafusion_physical_plan::metrics::{ExecutionPlanMetricsSet, MetricsSet};
use datafusion_physical_plan::stream::RecordBatchStreamAdapter;
use datafusion_physical_plan::{
DisplayAs, DisplayFormatType, ExecutionPlan, ExecutionPlanProperties, PlanProperties,
};
use datafusion_physical_plan::{DisplayAs, DisplayFormatType, ExecutionPlan, PlanProperties};
use futures::StreamExt;
use http::header::CONTENT_TYPE;
use lance::io::exec::utils::InstrumentedRecordBatchStreamAdapter;
use crate::Error;
use crate::remote::ARROW_STREAM_CONTENT_TYPE;
@@ -26,16 +22,13 @@ use crate::remote::client::{HttpSend, RestfulLanceDbClient, Sender};
use crate::remote::table::RemoteTable;
use crate::table::AddResult;
use crate::table::datafusion::insert::COUNT_SCHEMA;
use crate::table::write_progress::WriteProgressTracker;
/// ExecutionPlan for inserting data into a remote LanceDB table.
///
/// Streams data as Arrow IPC to `/v1/table/{id}/insert/` endpoint.
///
/// When `upload_id` is set, inserts are staged as part of a multipart write
/// session and the plan supports multiple partitions for parallel uploads.
/// Without `upload_id`, the plan requires a single partition and commits
/// immediately.
/// This plan:
/// 1. Requires single partition (no parallel remote inserts yet)
/// 2. Streams data as Arrow IPC to `/v1/table/{id}/insert/` endpoint
/// 3. Stores AddResult for retrieval after execution
#[derive(Debug)]
pub struct RemoteInsertExec<S: HttpSend = Sender> {
table_name: String,
@@ -45,69 +38,21 @@ pub struct RemoteInsertExec<S: HttpSend = Sender> {
overwrite: bool,
properties: PlanProperties,
add_result: Arc<Mutex<Option<AddResult>>>,
metrics: ExecutionPlanMetricsSet,
upload_id: Option<String>,
tracker: Option<Arc<WriteProgressTracker>>,
}
impl<S: HttpSend + 'static> RemoteInsertExec<S> {
/// Create a new single-partition RemoteInsertExec.
/// Create a new RemoteInsertExec.
pub fn new(
table_name: String,
identifier: String,
client: RestfulLanceDbClient<S>,
input: Arc<dyn ExecutionPlan>,
overwrite: bool,
tracker: Option<Arc<WriteProgressTracker>>,
) -> Self {
Self::new_inner(
table_name, identifier, client, input, overwrite, None, tracker,
)
}
/// Create a multi-partition RemoteInsertExec for use with multipart writes.
///
/// Each partition's insert is staged under the given `upload_id` without
/// committing. The caller is responsible for calling the complete (or abort)
/// endpoint after all partitions finish.
pub fn new_multipart(
table_name: String,
identifier: String,
client: RestfulLanceDbClient<S>,
input: Arc<dyn ExecutionPlan>,
overwrite: bool,
upload_id: String,
tracker: Option<Arc<WriteProgressTracker>>,
) -> Self {
Self::new_inner(
table_name,
identifier,
client,
input,
overwrite,
Some(upload_id),
tracker,
)
}
fn new_inner(
table_name: String,
identifier: String,
client: RestfulLanceDbClient<S>,
input: Arc<dyn ExecutionPlan>,
overwrite: bool,
upload_id: Option<String>,
tracker: Option<Arc<WriteProgressTracker>>,
) -> Self {
let num_partitions = if upload_id.is_some() {
input.output_partitioning().partition_count()
} else {
1
};
let schema = COUNT_SCHEMA.clone();
let properties = PlanProperties::new(
EquivalenceProperties::new(schema),
datafusion_physical_plan::Partitioning::UnknownPartitioning(num_partitions),
datafusion_physical_plan::Partitioning::UnknownPartitioning(1),
datafusion_physical_plan::execution_plan::EmissionType::Final,
datafusion_physical_plan::execution_plan::Boundedness::Bounded,
);
@@ -120,9 +65,6 @@ impl<S: HttpSend + 'static> RemoteInsertExec<S> {
overwrite,
properties,
add_result: Arc::new(Mutex::new(None)),
metrics: ExecutionPlanMetricsSet::new(),
upload_id,
tracker,
}
}
@@ -141,7 +83,6 @@ impl<S: HttpSend + 'static> RemoteInsertExec<S> {
fn stream_as_http_body(
data: SendableRecordBatchStream,
error_tx: tokio::sync::oneshot::Sender<DataFusionError>,
tracker: Option<Arc<WriteProgressTracker>>,
) -> DataFusionResult<reqwest::Body> {
let options = arrow_ipc::writer::IpcWriteOptions::default()
.try_with_compression(Some(CompressionType::LZ4_FRAME))?;
@@ -153,46 +94,37 @@ impl<S: HttpSend + 'static> RemoteInsertExec<S> {
let stream = futures::stream::try_unfold(
(data, writer, Some(error_tx), false),
move |(mut data, mut writer, error_tx, finished)| {
let tracker = tracker.clone();
async move {
if finished {
return Ok(None);
move |(mut data, mut writer, error_tx, finished)| async move {
if finished {
return Ok(None);
}
match data.next().await {
Some(Ok(batch)) => {
writer
.write(&batch)
.map_err(|e| std::io::Error::other(e.to_string()))?;
let buffer = std::mem::take(writer.get_mut());
Ok(Some((buffer, (data, writer, error_tx, false))))
}
match data.next().await {
Some(Ok(batch)) => {
writer
.write(&batch)
.map_err(|e| std::io::Error::other(e.to_string()))?;
let buffer = std::mem::take(writer.get_mut());
if let Some(ref t) = tracker {
t.record_bytes(buffer.len());
}
Ok(Some((buffer, (data, writer, error_tx, false))))
Some(Err(e)) => {
// Send the original error through the channel before
// returning a generic error to reqwest.
if let Some(tx) = error_tx {
let _ = tx.send(e);
}
Some(Err(e)) => {
// Send the original error through the channel before
// returning a generic error to reqwest.
if let Some(tx) = error_tx {
let _ = tx.send(e);
}
Err(std::io::Error::other(
"input stream error (see error channel)",
))
}
None => {
writer
.finish()
.map_err(|e| std::io::Error::other(e.to_string()))?;
let buffer = std::mem::take(writer.get_mut());
if buffer.is_empty() {
Ok(None)
} else {
if let Some(ref t) = tracker {
t.record_bytes(buffer.len());
}
Ok(Some((buffer, (data, writer, None, true))))
}
Err(std::io::Error::other(
"input stream error (see error channel)",
))
}
None => {
writer
.finish()
.map_err(|e| std::io::Error::other(e.to_string()))?;
let buffer = std::mem::take(writer.get_mut());
if buffer.is_empty() {
Ok(None)
} else {
Ok(Some((buffer, (data, writer, None, true))))
}
}
}
@@ -242,11 +174,8 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteInsertExec<S> {
}
fn required_input_distribution(&self) -> Vec<datafusion_physical_plan::Distribution> {
if self.upload_id.is_some() {
vec![datafusion_physical_plan::Distribution::UnspecifiedDistribution]
} else {
vec![datafusion_physical_plan::Distribution::SinglePartition]
}
// Until we have a separate commit endpoint, we need to do all inserts in a single partition
vec![datafusion_physical_plan::Distribution::SinglePartition]
}
fn benefits_from_input_partitioning(&self) -> Vec<bool> {
@@ -262,14 +191,12 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteInsertExec<S> {
"RemoteInsertExec requires exactly one child".to_string(),
));
}
Ok(Arc::new(Self::new_inner(
Ok(Arc::new(Self::new(
self.table_name.clone(),
self.identifier.clone(),
self.client.clone(),
children[0].clone(),
self.overwrite,
self.upload_id.clone(),
self.tracker.clone(),
)))
}
@@ -278,29 +205,18 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteInsertExec<S> {
partition: usize,
context: Arc<TaskContext>,
) -> DataFusionResult<SendableRecordBatchStream> {
if self.upload_id.is_none() && partition != 0 {
if partition != 0 {
return Err(DataFusionError::Internal(
"RemoteInsertExec only supports single partition execution without upload_id"
.to_string(),
"RemoteInsertExec only supports single partition execution".to_string(),
));
}
let input_stream = self.input.execute(partition, context)?;
let input_schema = input_stream.schema();
let input_stream: SendableRecordBatchStream =
Box::pin(InstrumentedRecordBatchStreamAdapter::new(
input_schema,
input_stream,
partition,
&self.metrics,
));
let input_stream = self.input.execute(0, context)?;
let client = self.client.clone();
let identifier = self.identifier.clone();
let overwrite = self.overwrite;
let add_result = self.add_result.clone();
let table_name = self.table_name.clone();
let upload_id = self.upload_id.clone();
let tracker = self.tracker.clone();
let stream = futures::stream::once(async move {
let mut request = client
@@ -310,12 +226,9 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteInsertExec<S> {
if overwrite {
request = request.query(&[("mode", "overwrite")]);
}
if let Some(ref uid) = upload_id {
request = request.query(&[("upload_id", uid.as_str())]);
}
let (error_tx, mut error_rx) = tokio::sync::oneshot::channel();
let body = Self::stream_as_http_body(input_stream, error_tx, tracker)?;
let body = Self::stream_as_http_body(input_stream, error_tx)?;
let request = request.body(body);
let result: DataFusionResult<(String, _)> = async {
@@ -349,43 +262,32 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteInsertExec<S> {
let (request_id, response) = result?;
// For multipart writes, the staging response is not the final
// version. Only parse AddResult for non-multipart inserts.
if upload_id.is_none() {
let body_text = response.text().await.map_err(|e| {
let body_text = response.text().await.map_err(|e| {
DataFusionError::External(Box::new(Error::Http {
source: Box::new(e),
request_id: request_id.clone(),
status_code: None,
}))
})?;
let parsed_result = if body_text.trim().is_empty() {
// Backward compatible with old servers
AddResult { version: 0 }
} else {
serde_json::from_str(&body_text).map_err(|e| {
DataFusionError::External(Box::new(Error::Http {
source: Box::new(e),
source: format!("Failed to parse add response: {}", e).into(),
request_id: request_id.clone(),
status_code: None,
}))
})?;
let parsed_result = if body_text.trim().is_empty() {
// Backward compatible with old servers
AddResult { version: 0 }
} else {
serde_json::from_str(&body_text).map_err(|e| {
DataFusionError::External(Box::new(Error::Http {
source: format!("Failed to parse add response: {}", e).into(),
request_id: request_id.clone(),
status_code: None,
}))
})?
};
})?
};
{
let mut res_lock = add_result.lock().map_err(|_| {
DataFusionError::Execution("Failed to acquire lock for add_result".to_string())
})?;
*res_lock = Some(parsed_result);
} else {
// We don't use the body in this case, but we should still consume it.
let _ = response.bytes().await.map_err(|e| {
DataFusionError::External(Box::new(Error::Http {
source: Box::new(e),
request_id: request_id.clone(),
status_code: None,
}))
})?;
}
// Return a single batch with count 0 (actual count is tracked in add_result)
@@ -399,10 +301,6 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteInsertExec<S> {
stream,
)))
}
fn metrics(&self) -> Option<MetricsSet> {
Some(self.metrics.clone_inner())
}
}
#[cfg(test)]

View File

@@ -34,13 +34,9 @@ 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;
@@ -74,10 +70,7 @@ pub mod optimize;
pub mod query;
pub mod schema_evolution;
pub mod update;
pub mod write_progress;
use crate::index::waiter::wait_for_index;
#[cfg(feature = "remote")]
pub(crate) use add_data::PreprocessingOutput;
pub use add_data::{AddDataBuilder, AddDataMode, AddResult, NaNVectorBehavior};
pub use chrono::Duration;
pub use delete::DeleteResult;
@@ -280,13 +273,8 @@ 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.
@@ -443,34 +431,6 @@ mod test_utils {
embedding_registry: Arc::new(MemoryRegistry::new()),
}
}
pub fn new_with_handler_version_and_config<T>(
name: impl Into<String>,
version: semver::Version,
handler: impl Fn(reqwest::Request) -> http::Response<T> + Clone + Send + Sync + 'static,
config: crate::remote::ClientConfig,
) -> Self
where
T: Into<reqwest::Body>,
{
let inner = Arc::new(
crate::remote::table::RemoteTable::new_mock_with_version_and_config(
name.into(),
handler.clone(),
Some(version),
config.clone(),
),
);
let database = Arc::new(crate::remote::db::RemoteDatabase::new_mock_with_config(
handler, config,
));
Self {
inner,
database: Some(database),
// Registry is unused.
embedding_registry: Arc::new(MemoryRegistry::new()),
}
}
}
}
@@ -982,7 +942,17 @@ impl Table {
/// * Prune: Removes old versions of the dataset
/// * Index: Optimizes the indices, adding new data to existing indices
///
/// The frequency an application should call optimize is based on the frequency of
/// <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
/// 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
@@ -1149,45 +1119,22 @@ 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 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.
/// This is a hint to fully load the index into memory. It can be used to
/// avoid cold starts
///
/// 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.
/// available cache.
///
/// Note: This function is not yet supported on all indices, in which case it
/// may do nothing.
///
/// 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(
@@ -1265,13 +1212,10 @@ 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 namespace operations (e.g., managed versioning).
// pub(crate) so query.rs can access the field for server-side query execution.
// 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
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 {
@@ -1283,7 +1227,6 @@ 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()
}
}
@@ -1320,7 +1263,7 @@ 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, false, None).await
Self::open_with_params(uri, &name, vec![], None, None, None, None).await
}
/// Opens an existing Table
@@ -1330,10 +1273,7 @@ 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 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.
/// * `namespace_client` - Optional namespace client for server-side query execution
///
/// # Returns
///
@@ -1347,8 +1287,6 @@ 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
@@ -1357,54 +1295,17 @@ impl NativeTable {
None => params,
};
// 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 = 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(),
})?;
let dataset = DatasetConsistencyWrapper::new_latest(dataset, read_consistency_interval);
let id = Self::build_id(&namespace, name);
@@ -1417,7 +1318,6 @@ impl NativeTable {
dataset,
read_consistency_interval,
namespace_client,
server_side_query_enabled,
})
}
@@ -1521,7 +1421,6 @@ impl NativeTable {
dataset,
read_consistency_interval,
namespace_client: stored_namespace_client,
server_side_query_enabled,
})
}
@@ -1561,8 +1460,7 @@ 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 namespace operations
/// * `server_side_query_enabled` - Whether to enable server-side query execution
/// * `namespace_client` - Optional namespace client for server-side query execution
///
/// # Returns
///
@@ -1577,7 +1475,6 @@ 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 {
@@ -1610,7 +1507,6 @@ impl NativeTable {
dataset: DatasetConsistencyWrapper::new_latest(dataset, read_consistency_interval),
read_consistency_interval,
namespace_client,
server_side_query_enabled,
})
}
@@ -1624,7 +1520,6 @@ 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(
@@ -1636,7 +1531,6 @@ impl NativeTable {
params,
read_consistency_interval,
namespace_client,
server_side_query_enabled,
)
.await
}
@@ -1740,7 +1634,6 @@ impl NativeTable {
dataset: DatasetConsistencyWrapper::new_latest(dataset, read_consistency_interval),
read_consistency_interval,
namespace_client: stored_namespace_client,
server_side_query_enabled,
})
}
@@ -2229,26 +2122,21 @@ impl BaseTable for NativeTable {
let table_schema = Schema::from(&ds.schema().clone());
let num_partitions = if let Some(parallelism) = add.write_parallelism {
parallelism
// Peek at the first batch to estimate a good partition count for
// write parallelism.
let mut peeked = PeekedScannable::new(add.data);
let num_partitions = if let Some(first_batch) = peeked.peek().await {
let max_partitions = lance_core::utils::tokio::get_num_compute_intensive_cpus();
estimate_write_partitions(
first_batch.get_array_memory_size(),
first_batch.num_rows(),
peeked.num_rows(),
max_partitions,
)
} else {
// Peek at the first batch to estimate a good partition count for
// write parallelism.
let mut peeked = PeekedScannable::new(add.data);
let n = if let Some(first_batch) = peeked.peek().await {
let max_partitions = lance_core::utils::tokio::get_num_compute_intensive_cpus();
estimate_write_partitions(
first_batch.get_array_memory_size(),
first_batch.num_rows(),
peeked.num_rows(),
max_partitions,
)
} else {
1
};
add.data = Box::new(peeked);
n
1
};
add.data = Box::new(peeked);
let output = add.into_plan(&table_schema, &table_def)?;
@@ -2277,21 +2165,13 @@ impl BaseTable for NativeTable {
let insert_exec = Arc::new(InsertExec::new(ds_wrapper.clone(), ds, plan, lance_params));
let tracker_for_tasks = output.tracker.clone();
if let Some(ref t) = tracker_for_tasks {
t.set_total_tasks(num_partitions);
}
let _finish = write_progress::FinishOnDrop(output.tracker);
// Execute all partitions in parallel.
let task_ctx = Arc::new(TaskContext::default());
let handles = FuturesUnordered::new();
for partition in 0..num_partitions {
let exec = insert_exec.clone();
let ctx = task_ctx.clone();
let tracker = tracker_for_tasks.clone();
handles.push(tokio::spawn(async move {
let _guard = tracker.as_ref().map(|t| t.track_task());
let mut stream = exec
.execute(partition, ctx)
.map_err(|e| -> Error { e.into() })?;
@@ -2352,12 +2232,6 @@ 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
@@ -2751,7 +2625,7 @@ mod tests {
vec![Ok(batch.clone())],
batch.schema(),
));
let table = NativeTable::create(uri, "test", vec![], reader, None, None, None, None, false)
let table = NativeTable::create(uri, "test", vec![], reader, None, None, None, None)
.await
.unwrap();

View File

@@ -13,9 +13,6 @@ use crate::embeddings::EmbeddingRegistry;
use crate::table::datafusion::cast::cast_to_table_schema;
use crate::table::datafusion::reject_nan::reject_nan_vectors;
use crate::table::datafusion::scannable_exec::ScannableExec;
use crate::table::write_progress::ProgressCallback;
use crate::table::write_progress::WriteProgress;
use crate::table::write_progress::WriteProgressTracker;
use crate::{Error, Result};
use super::{BaseTable, TableDefinition, WriteOptions};
@@ -55,8 +52,6 @@ pub struct AddDataBuilder {
pub(crate) write_options: WriteOptions,
pub(crate) on_nan_vectors: NaNVectorBehavior,
pub(crate) embedding_registry: Option<Arc<dyn EmbeddingRegistry>>,
pub(crate) progress_callback: Option<ProgressCallback>,
pub(crate) write_parallelism: Option<usize>,
}
impl std::fmt::Debug for AddDataBuilder {
@@ -82,8 +77,6 @@ impl AddDataBuilder {
write_options: WriteOptions::default(),
on_nan_vectors: NaNVectorBehavior::default(),
embedding_registry,
progress_callback: None,
write_parallelism: None,
}
}
@@ -108,43 +101,7 @@ impl AddDataBuilder {
self
}
/// Set a callback to receive progress updates during the add operation.
///
/// The callback is invoked once per batch written, and once more with
/// [`WriteProgress::done`] set to `true` when the write completes.
///
/// ```
/// # use lancedb::Table;
/// # async fn example(table: &Table) -> Result<(), Box<dyn std::error::Error>> {
/// let batch = arrow_array::record_batch!(("id", Int32, [1, 2, 3])).unwrap();
/// table.add(batch)
/// .progress(|p| println!("{}/{:?} rows", p.output_rows(), p.total_rows()))
/// .execute()
/// .await?;
/// # Ok(())
/// # }
/// ```
pub fn progress(mut self, callback: impl FnMut(&WriteProgress) + Send + 'static) -> Self {
self.progress_callback = Some(Arc::new(std::sync::Mutex::new(callback)));
self
}
/// Set the number of parallel write streams.
///
/// By default, the number of streams is estimated from the data size.
/// Setting this to `1` disables parallel writes.
pub fn write_parallelism(mut self, parallelism: usize) -> Self {
self.write_parallelism = Some(parallelism);
self
}
pub async fn execute(self) -> Result<AddResult> {
if self.write_parallelism.map(|p| p == 0).unwrap_or(false) {
return Err(Error::InvalidInput {
message: "write_parallelism must be greater than 0".to_string(),
});
}
self.parent.clone().add(self).await
}
@@ -173,11 +130,8 @@ impl AddDataBuilder {
scannable_with_embeddings(self.data, table_def, self.embedding_registry.as_ref())?;
let rescannable = self.data.rescannable();
let tracker = self
.progress_callback
.map(|cb| Arc::new(WriteProgressTracker::new(cb, self.data.num_rows())));
let plan: Arc<dyn datafusion_physical_plan::ExecutionPlan> =
Arc::new(ScannableExec::new(self.data, tracker.clone()));
Arc::new(ScannableExec::new(self.data));
// Skip casting when overwriting — the input schema replaces the table schema.
let plan = if overwrite {
plan
@@ -195,7 +149,6 @@ impl AddDataBuilder {
rescannable,
write_options: self.write_options,
mode: self.mode,
tracker,
})
}
}
@@ -208,7 +161,6 @@ pub struct PreprocessingOutput {
pub rescannable: bool,
pub write_options: WriteOptions,
pub mode: AddDataMode,
pub tracker: Option<Arc<WriteProgressTracker>>,
}
/// Check that the input schema is valid for insert.

View File

@@ -3,13 +3,12 @@
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::{CastExpr, Literal};
use datafusion_physical_expr::expressions::{Literal, cast};
use datafusion_physical_plan::expressions::Column;
use datafusion_physical_plan::projection::ProjectionExec;
use datafusion_physical_plan::{ExecutionPlan, PhysicalExpr};
@@ -26,9 +25,12 @@ 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>
})?;
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: Vec<(Arc<dyn PhysicalExpr>, String)> = exprs
.into_iter()
@@ -49,6 +51,7 @@ 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();
@@ -69,19 +72,24 @@ 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>
})?;
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 output_struct_fields: Fields = sub_exprs
.iter()
@@ -117,21 +125,17 @@ fn build_field_exprs(
// Types match: pass through.
(inp, tbl) if inp == tbl => input_expr,
// Types differ: cast.
// 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 {
_ => cast(input_expr, input_schema, table_field.data_type().clone()).map_err(|e| {
Error::InvalidInput {
message: format!(
"cannot cast field '{}' from {} to {}",
"cannot cast field '{}' from {} to {}: {}",
table_field.name(),
inp,
tbl,
input_field.data_type(),
table_field.data_type(),
e
),
});
}
}
})?,
};
let output_field = Arc::new(Field::new(
@@ -149,12 +153,10 @@ fn build_field_exprs(
mod tests {
use std::sync::Arc;
use arrow::buffer::OffsetBuffer;
use arrow_array::{
Array, Float32Array, Float64Array, Int32Array, Int64Array, ListArray, RecordBatch,
StringArray, StructArray, UInt32Array, UInt64Array,
Float32Array, Float64Array, Int32Array, Int64Array, RecordBatch, StringArray, StructArray,
};
use arrow_schema::{DataType, Field, Fields, Schema};
use arrow_schema::{DataType, Field, Schema};
use datafusion::prelude::SessionContext;
use datafusion_catalog::MemTable;
use futures::TryStreamExt;
@@ -493,129 +495,4 @@ 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

@@ -12,16 +12,13 @@ use datafusion_common::{DataFusionError, Result as DataFusionResult};
use datafusion_execution::{SendableRecordBatchStream, TaskContext};
use datafusion_physical_expr::{EquivalenceProperties, Partitioning};
use datafusion_physical_plan::execution_plan::{Boundedness, EmissionType};
use datafusion_physical_plan::metrics::{ExecutionPlanMetricsSet, MetricBuilder, MetricsSet};
use datafusion_physical_plan::stream::RecordBatchStreamAdapter;
use datafusion_physical_plan::{
DisplayAs, DisplayFormatType, ExecutionPlan, ExecutionPlanProperties, PlanProperties,
};
use futures::TryStreamExt;
use lance::Dataset;
use lance::dataset::transaction::{Operation, Transaction};
use lance::dataset::{CommitBuilder, InsertBuilder, WriteParams};
use lance::io::exec::utils::InstrumentedRecordBatchStreamAdapter;
use lance_table::format::Fragment;
use crate::table::dataset::DatasetConsistencyWrapper;
@@ -83,7 +80,6 @@ pub struct InsertExec {
write_params: WriteParams,
properties: PlanProperties,
partial_transactions: Arc<Mutex<Vec<Transaction>>>,
metrics: ExecutionPlanMetricsSet,
}
impl InsertExec {
@@ -109,7 +105,6 @@ impl InsertExec {
write_params,
properties,
partial_transactions: Arc::new(Mutex::new(Vec::with_capacity(num_partitions))),
metrics: ExecutionPlanMetricsSet::new(),
}
}
}
@@ -181,19 +176,6 @@ impl ExecutionPlan for InsertExec {
let total_partitions = self.input.output_partitioning().partition_count();
let ds_wrapper = self.ds_wrapper.clone();
let output_bytes = MetricBuilder::new(&self.metrics).output_bytes(partition);
let input_schema = input_stream.schema();
let input_stream: SendableRecordBatchStream =
Box::pin(InstrumentedRecordBatchStreamAdapter::new(
input_schema,
input_stream.map_ok(move |batch| {
output_bytes.add(batch.get_array_memory_size());
batch
}),
partition,
&self.metrics,
));
let stream = futures::stream::once(async move {
let transaction = InsertBuilder::new(dataset.clone())
.with_params(&write_params)
@@ -233,10 +215,6 @@ impl ExecutionPlan for InsertExec {
stream,
)))
}
fn metrics(&self) -> Option<MetricsSet> {
Some(self.metrics.clone_inner())
}
}
#[cfg(test)]

View File

@@ -7,21 +7,17 @@ use std::sync::{Arc, Mutex};
use datafusion_common::{DataFusionError, Result as DFResult, Statistics, stats::Precision};
use datafusion_execution::{SendableRecordBatchStream, TaskContext};
use datafusion_physical_expr::{EquivalenceProperties, Partitioning};
use datafusion_physical_plan::stream::RecordBatchStreamAdapter;
use datafusion_physical_plan::{
DisplayAs, DisplayFormatType, ExecutionPlan, PlanProperties, execution_plan::EmissionType,
};
use futures::TryStreamExt;
use crate::table::write_progress::WriteProgressTracker;
use crate::{arrow::SendableRecordBatchStreamExt, data::scannable::Scannable};
pub(crate) struct ScannableExec {
// We don't require Scannable to be Sync, so we wrap it in a Mutex to allow safe concurrent access.
pub struct ScannableExec {
// We don't require Scannable to by Sync, so we wrap it in a Mutex to allow safe concurrent access.
source: Mutex<Box<dyn Scannable>>,
num_rows: Option<usize>,
properties: PlanProperties,
tracker: Option<Arc<WriteProgressTracker>>,
}
impl std::fmt::Debug for ScannableExec {
@@ -34,7 +30,7 @@ impl std::fmt::Debug for ScannableExec {
}
impl ScannableExec {
pub fn new(source: Box<dyn Scannable>, tracker: Option<Arc<WriteProgressTracker>>) -> Self {
pub fn new(source: Box<dyn Scannable>) -> Self {
let schema = source.schema();
let eq_properties = EquivalenceProperties::new(schema);
let properties = PlanProperties::new(
@@ -50,7 +46,6 @@ impl ScannableExec {
source,
num_rows,
properties,
tracker,
}
}
}
@@ -107,18 +102,7 @@ impl ExecutionPlan for ScannableExec {
Err(poison) => poison.into_inner().scan_as_stream(),
};
let tracker = self.tracker.clone();
let stream = stream.into_df_stream().map_ok(move |batch| {
if let Some(ref t) = tracker {
t.record_batch(batch.num_rows(), batch.get_array_memory_size());
}
batch
});
Ok(Box::pin(RecordBatchStreamAdapter::new(
self.schema(),
stream,
)))
Ok(stream.into_df_stream())
}
fn partition_statistics(&self, _partition: Option<usize>) -> DFResult<Statistics> {

View File

@@ -1,4 +1,3 @@
use futures::FutureExt;
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
use serde::{Deserialize, Serialize};
@@ -24,7 +23,7 @@ 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).boxed().await?;
let delete_result = dataset.delete(predicate).await?;
let num_deleted_rows = delete_result.num_deleted_rows;
let version = dataset.version().version;
table.dataset.update(dataset);

View File

@@ -55,6 +55,7 @@ pub struct MergeInsertBuilder {
pub(crate) when_not_matched_by_source_delete_filt: Option<String>,
pub(crate) timeout: Option<Duration>,
pub(crate) use_index: bool,
pub(crate) mem_wal: bool,
}
impl MergeInsertBuilder {
@@ -69,6 +70,7 @@ impl MergeInsertBuilder {
when_not_matched_by_source_delete_filt: None,
timeout: None,
use_index: true,
mem_wal: false,
}
}
@@ -148,13 +150,65 @@ impl MergeInsertBuilder {
self
}
/// Enables MemWAL (Memory Write-Ahead Log) mode for this merge insert operation.
///
/// When enabled, the merge insert will route data through a memory node service
/// that buffers writes before flushing to storage. This is only supported for
/// remote (LanceDB Cloud) tables.
///
/// If not set, defaults to `false`.
pub fn mem_wal(&mut self, enabled: bool) -> &mut Self {
self.mem_wal = enabled;
self
}
/// Executes the merge insert operation
///
/// Returns version and statistics about the merge operation including the number of rows
/// inserted, updated, and deleted.
pub async fn execute(self, new_data: Box<dyn RecordBatchReader + Send>) -> Result<MergeResult> {
// Validate MemWAL constraints before execution
if self.mem_wal {
self.validate_mem_wal_pattern()?;
}
self.table.clone().merge_insert(self, new_data).await
}
/// Validate that the merge insert pattern is supported by MemWAL.
///
/// MemWAL only supports the upsert pattern:
/// - when_matched_update_all (without filter)
/// - when_not_matched_insert_all
/// - NO when_not_matched_by_source_delete
fn validate_mem_wal_pattern(&self) -> Result<()> {
// Must have when_matched_update_all without filter
if !self.when_matched_update_all {
return Err(Error::InvalidInput {
message: "MemWAL requires when_matched_update_all() to be set".to_string(),
});
}
if self.when_matched_update_all_filt.is_some() {
return Err(Error::InvalidInput {
message: "MemWAL does not support conditional when_matched_update_all (no filter allowed)".to_string(),
});
}
// Must have when_not_matched_insert_all
if !self.when_not_matched_insert_all {
return Err(Error::InvalidInput {
message: "MemWAL requires when_not_matched_insert_all() to be set".to_string(),
});
}
// Must NOT have when_not_matched_by_source_delete
if self.when_not_matched_by_source_delete {
return Err(Error::InvalidInput {
message: "MemWAL does not support when_not_matched_by_source_delete()".to_string(),
});
}
Ok(())
}
}
/// Internal implementation of the merge insert logic
@@ -165,6 +219,14 @@ pub(crate) async fn execute_merge_insert(
params: MergeInsertBuilder,
new_data: Box<dyn RecordBatchReader + Send>,
) -> Result<MergeResult> {
if params.mem_wal {
return Err(Error::NotSupported {
message: "MemWAL is not supported for native (local) tables. \
MemWAL is only available for remote (LanceDB Cloud) tables."
.to_string(),
});
}
let dataset = table.dataset.get().await?;
let mut builder = LanceMergeInsertBuilder::try_new(dataset.clone(), params.on)?;
match (
@@ -324,4 +386,139 @@ mod tests {
merge_insert_builder.execute(new_batches).await.unwrap();
assert_eq!(table.count_rows(None).await.unwrap(), 25);
}
#[tokio::test]
async fn test_mem_wal_validation_valid_pattern() {
let conn = connect("memory://").execute().await.unwrap();
let batches = merge_insert_test_batches(0, 0);
let table = conn
.create_table("mem_wal_test", batches)
.execute()
.await
.unwrap();
// Valid MemWAL pattern: when_matched_update_all + when_not_matched_insert_all
let new_batches = merge_insert_test_batches(5, 1);
let mut builder = table.merge_insert(&["i"]);
builder.when_matched_update_all(None);
builder.when_not_matched_insert_all();
builder.mem_wal(true);
// Should fail because native tables don't support MemWAL, but validation passes
let result = builder.execute(new_batches).await;
assert!(result.is_err());
let err = result.unwrap_err().to_string();
assert!(
err.contains("MemWAL is not supported for native"),
"Expected native table error, got: {}",
err
);
}
#[tokio::test]
async fn test_mem_wal_validation_missing_when_matched() {
let conn = connect("memory://").execute().await.unwrap();
let batches = merge_insert_test_batches(0, 0);
let table = conn
.create_table("mem_wal_test2", batches)
.execute()
.await
.unwrap();
// Missing when_matched_update_all
let new_batches = merge_insert_test_batches(5, 1);
let mut builder = table.merge_insert(&["i"]);
builder.when_not_matched_insert_all();
builder.mem_wal(true);
let result = builder.execute(new_batches).await;
assert!(result.is_err());
let err = result.unwrap_err().to_string();
assert!(
err.contains("requires when_matched_update_all"),
"Expected validation error, got: {}",
err
);
}
#[tokio::test]
async fn test_mem_wal_validation_missing_when_not_matched() {
let conn = connect("memory://").execute().await.unwrap();
let batches = merge_insert_test_batches(0, 0);
let table = conn
.create_table("mem_wal_test3", batches)
.execute()
.await
.unwrap();
// Missing when_not_matched_insert_all
let new_batches = merge_insert_test_batches(5, 1);
let mut builder = table.merge_insert(&["i"]);
builder.when_matched_update_all(None);
builder.mem_wal(true);
let result = builder.execute(new_batches).await;
assert!(result.is_err());
let err = result.unwrap_err().to_string();
assert!(
err.contains("requires when_not_matched_insert_all"),
"Expected validation error, got: {}",
err
);
}
#[tokio::test]
async fn test_mem_wal_validation_with_filter() {
let conn = connect("memory://").execute().await.unwrap();
let batches = merge_insert_test_batches(0, 0);
let table = conn
.create_table("mem_wal_test4", batches)
.execute()
.await
.unwrap();
// With conditional filter - not allowed
let new_batches = merge_insert_test_batches(5, 1);
let mut builder = table.merge_insert(&["i"]);
builder.when_matched_update_all(Some("target.age > 0".to_string()));
builder.when_not_matched_insert_all();
builder.mem_wal(true);
let result = builder.execute(new_batches).await;
assert!(result.is_err());
let err = result.unwrap_err().to_string();
assert!(
err.contains("does not support conditional"),
"Expected filter validation error, got: {}",
err
);
}
#[tokio::test]
async fn test_mem_wal_validation_with_delete() {
let conn = connect("memory://").execute().await.unwrap();
let batches = merge_insert_test_batches(0, 0);
let table = conn
.create_table("mem_wal_test5", batches)
.execute()
.await
.unwrap();
// With when_not_matched_by_source_delete - not allowed
let new_batches = merge_insert_test_batches(5, 1);
let mut builder = table.merge_insert(&["i"]);
builder.when_matched_update_all(None);
builder.when_not_matched_insert_all();
builder.when_not_matched_by_source_delete(None);
builder.mem_wal(true);
let result = builder.execute(new_batches).await;
assert!(result.is_err());
let err = result.unwrap_err().to_string();
assert!(
err.contains("does not support when_not_matched_by_source_delete"),
"Expected delete validation error, got: {}",
err
);
}
}

View File

@@ -64,9 +64,6 @@ 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>,
@@ -120,10 +117,6 @@ 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

@@ -40,10 +40,8 @@ pub async fn execute_query(
query: &AnyQuery,
options: QueryExecutionOptions,
) -> Result<DatasetRecordBatchStream> {
// 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
{
// If namespace client is configured, use server-side query execution
if 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
@@ -186,13 +184,6 @@ 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 => {}
}
@@ -347,17 +338,6 @@ 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
@@ -429,17 +409,6 @@ 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

View File

@@ -1,379 +0,0 @@
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
//! Progress monitoring for write operations.
//!
//! You can add a callback to process progress in [`crate::table::AddDataBuilder::progress`].
//! [`WriteProgress`] is the struct passed to the callback.
use std::sync::atomic::{AtomicUsize, Ordering};
use std::sync::{Arc, Mutex};
use std::time::{Duration, Instant};
/// Progress snapshot for a write operation.
#[derive(Debug, Clone)]
pub struct WriteProgress {
// These are private and only accessible via getters, to make it easy to add
// new fields without breaking existing callbacks.
elapsed: Duration,
output_rows: usize,
output_bytes: usize,
total_rows: Option<usize>,
active_tasks: usize,
total_tasks: usize,
done: bool,
}
impl WriteProgress {
/// Wall-clock time since monitoring started.
pub fn elapsed(&self) -> Duration {
self.elapsed
}
/// Number of rows written so far.
pub fn output_rows(&self) -> usize {
self.output_rows
}
/// Number of bytes written so far.
pub fn output_bytes(&self) -> usize {
self.output_bytes
}
/// Total rows expected.
///
/// Populated when the input source reports a row count (e.g. a
/// [`arrow_array::RecordBatch`]). Always `Some` when [`WriteProgress::done`]
/// is `true` — falling back to the actual number of rows written.
pub fn total_rows(&self) -> Option<usize> {
self.total_rows
}
/// Number of parallel write tasks currently in flight.
pub fn active_tasks(&self) -> usize {
self.active_tasks
}
/// Total number of parallel write tasks (i.e. the write parallelism).
pub fn total_tasks(&self) -> usize {
self.total_tasks
}
/// Whether the write operation has completed.
///
/// The final callback always has `done = true`. Callers can use this to
/// finalize progress bars or perform cleanup.
pub fn done(&self) -> bool {
self.done
}
}
/// Callback type for progress updates.
///
/// Callbacks are serialized by the tracker and are never invoked reentrantly,
/// so `FnMut` is safe to use here.
pub type ProgressCallback = Arc<Mutex<dyn FnMut(&WriteProgress) + Send>>;
/// Tracks progress of a write operation and invokes a [`ProgressCallback`].
///
/// Call [`WriteProgressTracker::record_batch`] for each batch written.
/// Call [`WriteProgressTracker::finish`] once after all data is written.
///
/// The callback is never invoked reentrantly: all state updates and callback
/// invocations are serialized behind a single lock.
impl std::fmt::Debug for WriteProgressTracker {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
f.debug_struct("WriteProgressTracker")
.field("total_rows", &self.total_rows)
.finish()
}
}
pub(crate) struct WriteProgressTracker {
rows_and_bytes: std::sync::Mutex<(usize, usize)>,
/// Wire bytes tracked separately by the insert layer. When set (> 0),
/// this takes precedence over the in-memory bytes from `rows_and_bytes`.
wire_bytes: AtomicUsize,
active_tasks: Arc<AtomicUsize>,
total_tasks: AtomicUsize,
start: Instant,
/// Known total rows from the input source, if available.
total_rows: Option<usize>,
callback: ProgressCallback,
}
impl WriteProgressTracker {
pub fn new(callback: ProgressCallback, total_rows: Option<usize>) -> Self {
Self {
rows_and_bytes: std::sync::Mutex::new((0, 0)),
wire_bytes: AtomicUsize::new(0),
active_tasks: Arc::new(AtomicUsize::new(0)),
total_tasks: AtomicUsize::new(1),
start: Instant::now(),
total_rows,
callback,
}
}
/// Set the total number of parallel write tasks (the write parallelism).
pub fn set_total_tasks(&self, n: usize) {
self.total_tasks.store(n, Ordering::Relaxed);
}
/// Increment the active task count. Returns a guard that decrements on drop.
pub fn track_task(&self) -> ActiveTaskGuard {
self.active_tasks.fetch_add(1, Ordering::Relaxed);
ActiveTaskGuard(self.active_tasks.clone())
}
/// Record a batch of rows passing through the scan node.
pub fn record_batch(&self, rows: usize, bytes: usize) {
// Lock order: callback first, then rows_and_bytes. This is the only
// order used anywhere, so deadlocks cannot occur.
let mut cb = self.callback.lock().unwrap();
let mut guard = self.rows_and_bytes.lock().unwrap();
guard.0 += rows;
guard.1 += bytes;
let progress = self.snapshot(guard.0, guard.1, false);
drop(guard);
cb(&progress);
}
/// Record wire bytes from the insert layer (e.g. IPC-encoded bytes for
/// remote writes). When wire bytes are recorded, they take precedence over
/// the in-memory Arrow bytes tracked by [`record_batch`].
pub fn record_bytes(&self, bytes: usize) {
self.wire_bytes.fetch_add(bytes, Ordering::Relaxed);
}
/// Emit the final progress callback indicating the write is complete.
///
/// `total_rows` is always `Some` on the final callback: it uses the known
/// total if available, or falls back to the number of rows actually written.
pub fn finish(&self) {
let mut cb = self.callback.lock().unwrap();
let guard = self.rows_and_bytes.lock().unwrap();
let mut snap = self.snapshot(guard.0, guard.1, true);
snap.total_rows = Some(self.total_rows.unwrap_or(guard.0));
drop(guard);
cb(&snap);
}
fn snapshot(&self, rows: usize, in_memory_bytes: usize, done: bool) -> WriteProgress {
let wire = self.wire_bytes.load(Ordering::Relaxed);
// Prefer wire bytes (actual I/O size) when the insert layer is
// tracking them; fall back to in-memory Arrow size otherwise.
// TODO: for local writes, track actual bytes written by Lance
// instead of using in-memory Arrow size as a proxy.
let output_bytes = if wire > 0 { wire } else { in_memory_bytes };
WriteProgress {
elapsed: self.start.elapsed(),
output_rows: rows,
output_bytes,
total_rows: self.total_rows,
active_tasks: self.active_tasks.load(Ordering::Relaxed),
total_tasks: self.total_tasks.load(Ordering::Relaxed),
done,
}
}
}
/// RAII guard that decrements the active task count when dropped.
pub(crate) struct ActiveTaskGuard(Arc<AtomicUsize>);
impl Drop for ActiveTaskGuard {
fn drop(&mut self) {
self.0.fetch_sub(1, Ordering::Relaxed);
}
}
/// RAII guard that calls [`WriteProgressTracker::finish`] on drop.
///
/// This ensures the final `done=true` callback fires even if the write
/// errors or the future is cancelled.
pub(crate) struct FinishOnDrop(pub Option<Arc<WriteProgressTracker>>);
impl Drop for FinishOnDrop {
fn drop(&mut self) {
if let Some(t) = self.0.take() {
t.finish();
}
}
}
#[cfg(test)]
mod tests {
use std::sync::Arc;
use std::sync::atomic::{AtomicUsize, Ordering};
use arrow_array::record_batch;
use crate::connect;
#[tokio::test]
async fn test_progress_monitor_fires_callback() {
let db = connect("memory://").execute().await.unwrap();
let batch = record_batch!(("id", Int32, [1, 2, 3])).unwrap();
let table = db
.create_table("progress_test", batch)
.execute()
.await
.unwrap();
let callback_count = Arc::new(AtomicUsize::new(0));
let last_rows = Arc::new(AtomicUsize::new(0));
let max_active = Arc::new(AtomicUsize::new(0));
let last_total_tasks = Arc::new(AtomicUsize::new(0));
let cb_count = callback_count.clone();
let cb_rows = last_rows.clone();
let cb_active = max_active.clone();
let cb_total_tasks = last_total_tasks.clone();
let new_data = record_batch!(("id", Int32, [4, 5, 6])).unwrap();
table
.add(new_data)
.progress(move |p| {
cb_count.fetch_add(1, Ordering::SeqCst);
cb_rows.store(p.output_rows(), Ordering::SeqCst);
cb_active.fetch_max(p.active_tasks(), Ordering::SeqCst);
cb_total_tasks.store(p.total_tasks(), Ordering::SeqCst);
})
.execute()
.await
.unwrap();
assert_eq!(table.count_rows(None).await.unwrap(), 6);
assert!(callback_count.load(Ordering::SeqCst) >= 1);
// Progress tracks the newly inserted rows, not the total table size.
assert_eq!(last_rows.load(Ordering::SeqCst), 3);
// At least one callback should have seen an active task.
assert!(max_active.load(Ordering::SeqCst) >= 1);
// total_tasks should reflect the write parallelism.
assert!(last_total_tasks.load(Ordering::SeqCst) >= 1);
}
#[tokio::test]
async fn test_progress_done_fires_at_end() {
let db = connect("memory://").execute().await.unwrap();
let batch = record_batch!(("id", Int32, [1, 2, 3])).unwrap();
let table = db
.create_table("progress_done", batch)
.execute()
.await
.unwrap();
let seen_done = Arc::new(std::sync::Mutex::new(Vec::<bool>::new()));
let seen = seen_done.clone();
let new_data = record_batch!(("id", Int32, [4, 5, 6])).unwrap();
table
.add(new_data)
.progress(move |p| {
seen.lock().unwrap().push(p.done());
})
.execute()
.await
.unwrap();
let done_flags = seen_done.lock().unwrap();
assert!(!done_flags.is_empty(), "at least one callback must fire");
// Only the last callback should have done=true.
let last = *done_flags.last().unwrap();
assert!(last, "last callback must have done=true");
// All earlier callbacks should have done=false.
for &d in done_flags.iter().rev().skip(1) {
assert!(!d, "non-final callbacks must have done=false");
}
}
#[tokio::test]
async fn test_progress_total_rows_known() {
let db = connect("memory://").execute().await.unwrap();
let batch = record_batch!(("id", Int32, [1, 2, 3])).unwrap();
let table = db
.create_table("total_known", batch)
.execute()
.await
.unwrap();
let seen_total = Arc::new(std::sync::Mutex::new(Vec::new()));
let seen = seen_total.clone();
// RecordBatch implements Scannable with num_rows() -> Some(3)
let new_data = record_batch!(("id", Int32, [4, 5, 6])).unwrap();
table
.add(new_data)
.progress(move |p| {
seen.lock().unwrap().push(p.total_rows());
})
.execute()
.await
.unwrap();
let totals = seen_total.lock().unwrap();
// All callbacks (including done) should have total_rows = Some(3)
assert!(
totals.contains(&Some(3)),
"expected total_rows=Some(3) in at least one callback, got: {:?}",
*totals
);
}
#[tokio::test]
async fn test_progress_total_rows_unknown() {
use arrow_array::RecordBatchIterator;
let db = connect("memory://").execute().await.unwrap();
let batch = record_batch!(("id", Int32, [1, 2, 3])).unwrap();
let table = db
.create_table("total_unknown", batch)
.execute()
.await
.unwrap();
let seen_total = Arc::new(std::sync::Mutex::new(Vec::new()));
let seen = seen_total.clone();
// RecordBatchReader does not provide num_rows, so total_rows should be
// None in intermediate callbacks but always Some on the done callback.
let schema = arrow_schema::Schema::new(vec![arrow_schema::Field::new(
"id",
arrow_schema::DataType::Int32,
false,
)]);
let new_data: Box<dyn arrow_array::RecordBatchReader + Send> =
Box::new(RecordBatchIterator::new(
vec![Ok(record_batch!(("id", Int32, [4, 5, 6])).unwrap())],
Arc::new(schema),
));
table
.add(new_data)
.progress(move |p| {
seen.lock().unwrap().push((p.total_rows(), p.done()));
})
.execute()
.await
.unwrap();
let entries = seen_total.lock().unwrap();
assert!(!entries.is_empty(), "at least one callback must fire");
for (total, done) in entries.iter() {
if *done {
assert!(
total.is_some(),
"done callback must have total_rows set, got: {:?}",
total
);
} else {
assert_eq!(
*total, None,
"intermediate callback must have total_rows=None, got: {:?}",
total
);
}
}
}
}