mirror of
https://github.com/lancedb/lancedb.git
synced 2026-03-26 02:20:40 +00:00
Compare commits
20 Commits
v0.26.1
...
v0.27.0-be
| Author | SHA1 | Date | |
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9fac56252e |
@@ -1,5 +1,5 @@
|
||||
[tool.bumpversion]
|
||||
current_version = "0.26.1-beta.0"
|
||||
current_version = "0.27.0-beta.0"
|
||||
parse = """(?x)
|
||||
(?P<major>0|[1-9]\\d*)\\.
|
||||
(?P<minor>0|[1-9]\\d*)\\.
|
||||
|
||||
173
.github/workflows/codex-fix-ci.yml
vendored
Normal file
173
.github/workflows/codex-fix-ci.yml
vendored
Normal file
@@ -0,0 +1,173 @@
|
||||
name: Codex Fix CI
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
workflow_run_url:
|
||||
description: "Failing CI workflow run URL (e.g., https://github.com/lancedb/lancedb/actions/runs/12345678)"
|
||||
required: true
|
||||
type: string
|
||||
branch:
|
||||
description: "Branch to fix (e.g., main, release/v2.0, or feature-branch)"
|
||||
required: true
|
||||
type: string
|
||||
guidelines:
|
||||
description: "Additional guidelines for the fix (optional)"
|
||||
required: false
|
||||
type: string
|
||||
|
||||
permissions:
|
||||
contents: write
|
||||
pull-requests: write
|
||||
actions: read
|
||||
|
||||
jobs:
|
||||
fix-ci:
|
||||
runs-on: warp-ubuntu-latest-x64-4x
|
||||
timeout-minutes: 60
|
||||
env:
|
||||
CC: clang
|
||||
CXX: clang++
|
||||
steps:
|
||||
- name: Show inputs
|
||||
run: |
|
||||
echo "workflow_run_url = ${{ inputs.workflow_run_url }}"
|
||||
echo "branch = ${{ inputs.branch }}"
|
||||
echo "guidelines = ${{ inputs.guidelines }}"
|
||||
|
||||
- name: Checkout Repo
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
ref: ${{ inputs.branch }}
|
||||
fetch-depth: 0
|
||||
persist-credentials: true
|
||||
|
||||
- name: Set up Node.js
|
||||
uses: actions/setup-node@v4
|
||||
with:
|
||||
node-version: 20
|
||||
|
||||
- name: Install Codex CLI
|
||||
run: npm install -g @openai/codex
|
||||
|
||||
- name: Install Rust toolchain
|
||||
uses: dtolnay/rust-toolchain@stable
|
||||
with:
|
||||
toolchain: stable
|
||||
components: clippy, rustfmt
|
||||
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
|
||||
- name: Install system dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install -y protobuf-compiler libssl-dev
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.11'
|
||||
|
||||
- name: Install Python dependencies
|
||||
run: |
|
||||
pip install maturin ruff pytest pyarrow pandas polars
|
||||
|
||||
- name: Set up Java
|
||||
uses: actions/setup-java@v4
|
||||
with:
|
||||
distribution: temurin
|
||||
java-version: '11'
|
||||
cache: maven
|
||||
|
||||
- name: Install Node.js dependencies for TypeScript bindings
|
||||
run: |
|
||||
cd nodejs
|
||||
npm ci
|
||||
|
||||
- name: Configure git user
|
||||
run: |
|
||||
git config user.name "lancedb automation"
|
||||
git config user.email "robot@lancedb.com"
|
||||
|
||||
- name: Run Codex to fix CI failure
|
||||
env:
|
||||
WORKFLOW_RUN_URL: ${{ inputs.workflow_run_url }}
|
||||
BRANCH: ${{ inputs.branch }}
|
||||
GUIDELINES: ${{ inputs.guidelines }}
|
||||
GITHUB_TOKEN: ${{ secrets.ROBOT_TOKEN }}
|
||||
GH_TOKEN: ${{ secrets.ROBOT_TOKEN }}
|
||||
OPENAI_API_KEY: ${{ secrets.CODEX_TOKEN }}
|
||||
run: |
|
||||
set -euo pipefail
|
||||
|
||||
cat <<EOF >/tmp/codex-prompt.txt
|
||||
You are running inside the lancedb repository on a GitHub Actions runner. Your task is to fix a CI failure.
|
||||
|
||||
Input parameters:
|
||||
- Failing workflow run URL: ${WORKFLOW_RUN_URL}
|
||||
- Branch to fix: ${BRANCH}
|
||||
- Additional guidelines: ${GUIDELINES:-"None provided"}
|
||||
|
||||
Follow these steps exactly:
|
||||
|
||||
1. Extract the run ID from the workflow URL. The URL format is https://github.com/lancedb/lancedb/actions/runs/<run_id>.
|
||||
|
||||
2. Use "gh run view <run_id> --json jobs,conclusion,name" to get information about the failed run.
|
||||
|
||||
3. Identify which jobs failed. For each failed job, use "gh run view <run_id> --job <job_id> --log-failed" to get the failure logs.
|
||||
|
||||
4. Analyze the failure logs to understand what went wrong. Common failures include:
|
||||
- Compilation errors
|
||||
- Test failures
|
||||
- Clippy warnings treated as errors
|
||||
- Formatting issues
|
||||
- Dependency issues
|
||||
|
||||
5. Based on the analysis, fix the issues in the codebase:
|
||||
- For compilation errors: Fix the code that doesn't compile
|
||||
- For test failures: Fix the failing tests or the code they test
|
||||
- For clippy warnings: Apply the suggested fixes
|
||||
- For formatting issues: Run "cargo fmt --all"
|
||||
- For other issues: Apply appropriate fixes
|
||||
|
||||
6. After making fixes, verify them locally:
|
||||
- Run "cargo fmt --all" to ensure formatting is correct
|
||||
- Run "cargo clippy --workspace --tests --all-features -- -D warnings" to check for issues
|
||||
- Run ONLY the specific failing tests to confirm they pass now:
|
||||
- For Rust test failures: Run the specific test with "cargo test -p <crate> <test_name>"
|
||||
- For Python test failures: Build with "cd python && maturin develop" then run "pytest <specific_test_file>::<test_name>"
|
||||
- For Java test failures: Run "cd java && mvn test -Dtest=<TestClass>#<testMethod>"
|
||||
- For TypeScript test failures: Run "cd nodejs && npm run build && npm test -- --testNamePattern='<test_name>'"
|
||||
- Do NOT run the full test suite - only run the tests that were failing
|
||||
|
||||
7. If the additional guidelines are provided, follow them as well.
|
||||
|
||||
8. Inspect "git status --short" and "git diff" to review your changes.
|
||||
|
||||
9. Create a fix branch: "git checkout -b codex/fix-ci-<run_id>".
|
||||
|
||||
10. Stage all changes with "git add -A" and commit with message "fix: resolve CI failures from run <run_id>".
|
||||
|
||||
11. Push the branch: "git push origin codex/fix-ci-<run_id>". If the remote branch exists, delete it first with "gh api -X DELETE repos/lancedb/lancedb/git/refs/heads/codex/fix-ci-<run_id>" then push. Do NOT use "git push --force" or "git push -f".
|
||||
|
||||
12. Create a pull request targeting "${BRANCH}":
|
||||
- Title: "ci: <short summary describing the fix>" (e.g., "ci: fix clippy warnings in lancedb" or "ci: resolve test flakiness in vector search")
|
||||
- First, write the PR body to /tmp/pr-body.md using a heredoc (cat <<'PREOF' > /tmp/pr-body.md). The body should include:
|
||||
- Link to the failing workflow run
|
||||
- Summary of what failed
|
||||
- Description of the fixes applied
|
||||
- Then run "gh pr create --base ${BRANCH} --body-file /tmp/pr-body.md".
|
||||
|
||||
13. Display the new PR URL, "git status --short", and a summary of what was fixed.
|
||||
|
||||
Constraints:
|
||||
- Use bash commands for all operations.
|
||||
- Do not merge the PR.
|
||||
- Do not modify GitHub workflow files unless they are the cause of the failure.
|
||||
- If any command fails, diagnose and attempt to fix the issue instead of aborting immediately.
|
||||
- If you cannot fix the issue automatically, create the PR anyway with a clear explanation of what you tried and what remains to be fixed.
|
||||
- env "GH_TOKEN" is available, use "gh" tools for GitHub-related operations.
|
||||
EOF
|
||||
|
||||
printenv OPENAI_API_KEY | codex login --with-api-key
|
||||
codex --config shell_environment_policy.ignore_default_excludes=true exec --dangerously-bypass-approvals-and-sandbox "$(cat /tmp/codex-prompt.txt)"
|
||||
74
Cargo.lock
generated
74
Cargo.lock
generated
@@ -3072,9 +3072,9 @@ checksum = "42703706b716c37f96a77aea830392ad231f44c9e9a67872fa5548707e11b11c"
|
||||
|
||||
[[package]]
|
||||
name = "fsst"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "0f03a771ab914e207dd26bd2f12666839555ec8ecc7e1770e1ed6f9900d899a4"
|
||||
checksum = "5f9e5c0b1c67a38cb92b41535d44623483beb9511592ae23a3bf42ddec758690"
|
||||
dependencies = [
|
||||
"arrow-array",
|
||||
"rand 0.9.2",
|
||||
@@ -4405,9 +4405,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "47b685aca3f97ee02997c83ded16f59c747ccb69e74c8abbbae4aa3d22cf1301"
|
||||
checksum = "2b7f07b905df393a5554eba19055c620f9ea25a3e40a013bda4bd8dc4ca66f01"
|
||||
dependencies = [
|
||||
"arrow",
|
||||
"arrow-arith",
|
||||
@@ -4472,9 +4472,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-arrow"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "daf00c7537df524cc518a089f0d156a036d95ca3f5bc2bc1f0a9f9293e9b62ef"
|
||||
checksum = "100e076cb81c8f0c24cd2881c706fc53e037c7d6e81eb320e929e265d157effb"
|
||||
dependencies = [
|
||||
"arrow-array",
|
||||
"arrow-buffer",
|
||||
@@ -4493,9 +4493,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-bitpacking"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "46752e4ac8fc5590a445e780b63a8800adc7a770bd74770a8dc66963778e4e77"
|
||||
checksum = "588318d3d1ba0f97162fab39a323a0a49866bb35b32af42572c6b6a12296fa27"
|
||||
dependencies = [
|
||||
"arrayref",
|
||||
"paste",
|
||||
@@ -4504,9 +4504,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-core"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "3d13d87d07305c6d4b4dc7780fb1107babf782a0e5b1dc7872e17ae1f8fd11ca"
|
||||
checksum = "6fa01d1cf490ccfd3b8eaeee2781415d0419e6be8366040e57e43677abf2644e"
|
||||
dependencies = [
|
||||
"arrow-array",
|
||||
"arrow-buffer",
|
||||
@@ -4543,9 +4543,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-datafusion"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "6451b5af876eaef8bec4b38a39dadac9d44621e1ecf85d0cdf6097a5d0aa8721"
|
||||
checksum = "ef89a39e3284eef76f79e63f23de8881a0583ad6feb20ed39f47eadd847a2b88"
|
||||
dependencies = [
|
||||
"arrow",
|
||||
"arrow-array",
|
||||
@@ -4575,9 +4575,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-datagen"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "e1736708dd7867dfbab8fcc930b21c96717c6c00be73b7d9a240336a4ed80375"
|
||||
checksum = "fc2a60eef5c47e65d91e2ffa8e7e1629c52e7190c8b88a371a1a60601dc49371"
|
||||
dependencies = [
|
||||
"arrow",
|
||||
"arrow-array",
|
||||
@@ -4595,9 +4595,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-encoding"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "d6b6ca4ff94833240d5ba4a94a742cba786d1949b3c3fa7e11d6f0050443432a"
|
||||
checksum = "95ce4a6631308aa681b2671af8f2a845ff781f8d4e755a2a7ccd012379467094"
|
||||
dependencies = [
|
||||
"arrow-arith",
|
||||
"arrow-array",
|
||||
@@ -4634,9 +4634,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-file"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "55fbe959bffe185543aed3cbeb14484f1aa2e55886034fdb1ea3d8cc9b70aad8"
|
||||
checksum = "e2d4d82357cbfaa1a18494226c15b1cb3c8ed0b6c84b91146323c82047ede419"
|
||||
dependencies = [
|
||||
"arrow-arith",
|
||||
"arrow-array",
|
||||
@@ -4668,9 +4668,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-geo"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "a52b0adabc953d457f336a784a3b37353a180e6a79905f544949746e0d4c6483"
|
||||
checksum = "a7183fc870da62826f0f97df8007b634da053eb310157856efe1dc74f446951c"
|
||||
dependencies = [
|
||||
"datafusion",
|
||||
"geo-traits",
|
||||
@@ -4684,9 +4684,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-index"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "6b67654bf86fd942dd2cf08294ee7e91053427cd148225f49c9ff398ff9a40fd"
|
||||
checksum = "20e9c5aa7024a63af9ae89ee8c0f23c8421b7896742e5cd4a271a60f9956cb80"
|
||||
dependencies = [
|
||||
"arrow",
|
||||
"arrow-arith",
|
||||
@@ -4753,9 +4753,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-io"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "8eb0ccc1c414e31687d83992d546af0a0237c8d2f4bf2ae3d347d539fd0fc141"
|
||||
checksum = "c7d2af0b17fb374a8181bcf1a10bce5703ae3ee4373c1587ce4bba23e15e45c8"
|
||||
dependencies = [
|
||||
"arrow",
|
||||
"arrow-arith",
|
||||
@@ -4795,9 +4795,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-linalg"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "083404cf12dcdb1a7df98fb58f9daf626b6e43a2f794b37b6b89b4012a0e1f78"
|
||||
checksum = "5125aa62696e75a7475807564b4921f252d8815be606b84bc00e6def0f5c24bb"
|
||||
dependencies = [
|
||||
"arrow-array",
|
||||
"arrow-buffer",
|
||||
@@ -4813,9 +4813,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-namespace"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "c12778d2aabf9c2bfd16e2509ebe120e562a288d8ae630ec6b6b204868df41b2"
|
||||
checksum = "70545c2676ce954dfd801da5c6a631a70bba967826cd3a8f31b47d1f04bbfed3"
|
||||
dependencies = [
|
||||
"arrow",
|
||||
"async-trait",
|
||||
@@ -4827,9 +4827,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-namespace-impls"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "8863aababdd13a6d2c8d6179dc6981f4f8f49d8b66a00c5dd75115aec4cadc99"
|
||||
checksum = "92519f9f27d62655030aac62ea0db9614b65f086ebe651c1b0a96e351b668022"
|
||||
dependencies = [
|
||||
"arrow",
|
||||
"arrow-ipc",
|
||||
@@ -4872,9 +4872,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-table"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "f0fcc83f197ce2000c4abe4f5e0873490ab1f41788fa76571c4209b87d4daf50"
|
||||
checksum = "b06ad37bd90045de8ef533df170c6098e6ff6ecb427aade47d7db8e2c86f2678"
|
||||
dependencies = [
|
||||
"arrow",
|
||||
"arrow-array",
|
||||
@@ -4913,9 +4913,9 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lance-testing"
|
||||
version = "2.0.0"
|
||||
version = "2.0.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "7fb1f7c7e06f91360e141ecee1cf2110f858c231705f69f2cd2fda9e30c1e9f4"
|
||||
checksum = "cd7f13b0f2b6337af015dcb1519645388dca08c970037aa77aff517687c4019f"
|
||||
dependencies = [
|
||||
"arrow-array",
|
||||
"arrow-schema",
|
||||
@@ -4926,7 +4926,7 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lancedb"
|
||||
version = "0.26.0"
|
||||
version = "0.26.2"
|
||||
dependencies = [
|
||||
"ahash",
|
||||
"anyhow",
|
||||
@@ -5006,7 +5006,7 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lancedb-nodejs"
|
||||
version = "0.26.0"
|
||||
version = "0.26.2"
|
||||
dependencies = [
|
||||
"arrow-array",
|
||||
"arrow-ipc",
|
||||
@@ -5026,7 +5026,7 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "lancedb-python"
|
||||
version = "0.29.0"
|
||||
version = "0.29.2"
|
||||
dependencies = [
|
||||
"arrow",
|
||||
"async-trait",
|
||||
|
||||
28
Cargo.toml
28
Cargo.toml
@@ -15,20 +15,20 @@ categories = ["database-implementations"]
|
||||
rust-version = "1.88.0"
|
||||
|
||||
[workspace.dependencies]
|
||||
lance = { "version" = "=2.0.0", default-features = false }
|
||||
lance-core = "=2.0.0"
|
||||
lance-datagen = "=2.0.0"
|
||||
lance-file = "=2.0.0"
|
||||
lance-io = { "version" = "=2.0.0", default-features = false }
|
||||
lance-index = "=2.0.0"
|
||||
lance-linalg = "=2.0.0"
|
||||
lance-namespace = "=2.0.0"
|
||||
lance-namespace-impls = { "version" = "=2.0.0", default-features = false }
|
||||
lance-table = "=2.0.0"
|
||||
lance-testing = "=2.0.0"
|
||||
lance-datafusion = "=2.0.0"
|
||||
lance-encoding = "=2.0.0"
|
||||
lance-arrow = "=2.0.0"
|
||||
lance = { "version" = "=2.0.1", default-features = false }
|
||||
lance-core = "=2.0.1"
|
||||
lance-datagen = "=2.0.1"
|
||||
lance-file = "=2.0.1"
|
||||
lance-io = { "version" = "=2.0.1", default-features = false }
|
||||
lance-index = "=2.0.1"
|
||||
lance-linalg = "=2.0.1"
|
||||
lance-namespace = "=2.0.1"
|
||||
lance-namespace-impls = { "version" = "=2.0.1", default-features = false }
|
||||
lance-table = "=2.0.1"
|
||||
lance-testing = "=2.0.1"
|
||||
lance-datafusion = "=2.0.1"
|
||||
lance-encoding = "=2.0.1"
|
||||
lance-arrow = "=2.0.1"
|
||||
ahash = "0.8"
|
||||
# Note that this one does not include pyarrow
|
||||
arrow = { version = "57.2", optional = false }
|
||||
|
||||
9
Makefile
Normal file
9
Makefile
Normal file
@@ -0,0 +1,9 @@
|
||||
.PHONY: licenses
|
||||
|
||||
licenses:
|
||||
cargo about generate about.hbs -o RUST_THIRD_PARTY_LICENSES.html -c about.toml
|
||||
cd python && cargo about generate ../about.hbs -o RUST_THIRD_PARTY_LICENSES.html -c ../about.toml
|
||||
cd python && uv sync --all-extras && uv tool run pip-licenses --python .venv/bin/python --format=markdown --with-urls --output-file=PYTHON_THIRD_PARTY_LICENSES.md
|
||||
cd nodejs && cargo about generate ../about.hbs -o RUST_THIRD_PARTY_LICENSES.html -c ../about.toml
|
||||
cd nodejs && npx license-checker --markdown --out NODEJS_THIRD_PARTY_LICENSES.md
|
||||
cd java && ./mvnw license:aggregate-add-third-party -q
|
||||
15276
RUST_THIRD_PARTY_LICENSES.html
Normal file
15276
RUST_THIRD_PARTY_LICENSES.html
Normal file
File diff suppressed because it is too large
Load Diff
70
about.hbs
Normal file
70
about.hbs
Normal file
@@ -0,0 +1,70 @@
|
||||
<html>
|
||||
|
||||
<head>
|
||||
<style>
|
||||
@media (prefers-color-scheme: dark) {
|
||||
body {
|
||||
background: #333;
|
||||
color: white;
|
||||
}
|
||||
a {
|
||||
color: skyblue;
|
||||
}
|
||||
}
|
||||
.container {
|
||||
font-family: sans-serif;
|
||||
max-width: 800px;
|
||||
margin: 0 auto;
|
||||
}
|
||||
.intro {
|
||||
text-align: center;
|
||||
}
|
||||
.licenses-list {
|
||||
list-style-type: none;
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
}
|
||||
.license-used-by {
|
||||
margin-top: -10px;
|
||||
}
|
||||
.license-text {
|
||||
max-height: 200px;
|
||||
overflow-y: scroll;
|
||||
white-space: pre-wrap;
|
||||
}
|
||||
</style>
|
||||
</head>
|
||||
|
||||
<body>
|
||||
<main class="container">
|
||||
<div class="intro">
|
||||
<h1>Third Party Licenses</h1>
|
||||
<p>This page lists the licenses of the projects used in cargo-about.</p>
|
||||
</div>
|
||||
|
||||
<h2>Overview of licenses:</h2>
|
||||
<ul class="licenses-overview">
|
||||
{{#each overview}}
|
||||
<li><a href="#{{id}}">{{name}}</a> ({{count}})</li>
|
||||
{{/each}}
|
||||
</ul>
|
||||
|
||||
<h2>All license text:</h2>
|
||||
<ul class="licenses-list">
|
||||
{{#each licenses}}
|
||||
<li class="license">
|
||||
<h3 id="{{id}}">{{name}}</h3>
|
||||
<h4>Used by:</h4>
|
||||
<ul class="license-used-by">
|
||||
{{#each used_by}}
|
||||
<li><a href="{{#if crate.repository}} {{crate.repository}} {{else}} https://crates.io/crates/{{crate.name}} {{/if}}">{{crate.name}} {{crate.version}}</a></li>
|
||||
{{/each}}
|
||||
</ul>
|
||||
<pre class="license-text">{{text}}</pre>
|
||||
</li>
|
||||
{{/each}}
|
||||
</ul>
|
||||
</main>
|
||||
</body>
|
||||
|
||||
</html>
|
||||
18
about.toml
Normal file
18
about.toml
Normal file
@@ -0,0 +1,18 @@
|
||||
accepted = [
|
||||
"0BSD",
|
||||
"Apache-2.0",
|
||||
"Apache-2.0 WITH LLVM-exception",
|
||||
"BSD-2-Clause",
|
||||
"BSD-3-Clause",
|
||||
"BSL-1.0",
|
||||
"bzip2-1.0.6",
|
||||
"CC0-1.0",
|
||||
"CDDL-1.0",
|
||||
"CDLA-Permissive-2.0",
|
||||
"ISC",
|
||||
"MIT",
|
||||
"MPL-2.0",
|
||||
"OpenSSL",
|
||||
"Unicode-3.0",
|
||||
"Zlib",
|
||||
]
|
||||
@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
|
||||
<dependency>
|
||||
<groupId>com.lancedb</groupId>
|
||||
<artifactId>lancedb-core</artifactId>
|
||||
<version>0.26.1-beta.0</version>
|
||||
<version>0.27.0-beta.0</version>
|
||||
</dependency>
|
||||
```
|
||||
|
||||
|
||||
71
java/JAVA_THIRD_PARTY_LICENSES.md
Normal file
71
java/JAVA_THIRD_PARTY_LICENSES.md
Normal file
@@ -0,0 +1,71 @@
|
||||
|
||||
List of third-party dependencies grouped by their license type.
|
||||
|
||||
Apache 2.0:
|
||||
|
||||
* error-prone annotations (com.google.errorprone:error_prone_annotations:2.28.0 - https://errorprone.info/error_prone_annotations)
|
||||
|
||||
Apache License 2.0:
|
||||
|
||||
* JsonNullable Jackson module (org.openapitools:jackson-databind-nullable:0.2.6 - https://github.com/OpenAPITools/jackson-databind-nullable)
|
||||
|
||||
Apache License V2.0:
|
||||
|
||||
* FlatBuffers Java API (com.google.flatbuffers:flatbuffers-java:23.5.26 - https://github.com/google/flatbuffers)
|
||||
|
||||
Apache License, Version 2.0:
|
||||
|
||||
* Apache Commons Codec (commons-codec:commons-codec:1.15 - https://commons.apache.org/proper/commons-codec/)
|
||||
* Apache HttpClient (org.apache.httpcomponents.client5:httpclient5:5.2.1 - https://hc.apache.org/httpcomponents-client-5.0.x/5.2.1/httpclient5/)
|
||||
* Apache HttpComponents Core HTTP/1.1 (org.apache.httpcomponents.core5:httpcore5:5.2 - https://hc.apache.org/httpcomponents-core-5.2.x/5.2/httpcore5/)
|
||||
* Apache HttpComponents Core HTTP/2 (org.apache.httpcomponents.core5:httpcore5-h2:5.2 - https://hc.apache.org/httpcomponents-core-5.2.x/5.2/httpcore5-h2/)
|
||||
* Arrow Format (org.apache.arrow:arrow-format:15.0.0 - https://arrow.apache.org/arrow-format/)
|
||||
* Arrow Java C Data Interface (org.apache.arrow:arrow-c-data:15.0.0 - https://arrow.apache.org/arrow-c-data/)
|
||||
* Arrow Java Dataset (org.apache.arrow:arrow-dataset:15.0.0 - https://arrow.apache.org/arrow-dataset/)
|
||||
* Arrow Memory - Core (org.apache.arrow:arrow-memory-core:15.0.0 - https://arrow.apache.org/arrow-memory/arrow-memory-core/)
|
||||
* Arrow Memory - Netty (org.apache.arrow:arrow-memory-netty:15.0.0 - https://arrow.apache.org/arrow-memory/arrow-memory-netty/)
|
||||
* Arrow Vectors (org.apache.arrow:arrow-vector:15.0.0 - https://arrow.apache.org/arrow-vector/)
|
||||
* Guava: Google Core Libraries for Java (com.google.guava:guava:33.3.1-jre - https://github.com/google/guava)
|
||||
* J2ObjC Annotations (com.google.j2objc:j2objc-annotations:3.0.0 - https://github.com/google/j2objc/)
|
||||
* Netty/Buffer (io.netty:netty-buffer:4.1.104.Final - https://netty.io/netty-buffer/)
|
||||
* Netty/Common (io.netty:netty-common:4.1.104.Final - https://netty.io/netty-common/)
|
||||
|
||||
Apache-2.0:
|
||||
|
||||
* Apache Commons Lang (org.apache.commons:commons-lang3:3.18.0 - https://commons.apache.org/proper/commons-lang/)
|
||||
* lance-namespace-apache-client (org.lance:lance-namespace-apache-client:0.4.5 - https://github.com/openapitools/openapi-generator)
|
||||
* lance-namespace-core (org.lance:lance-namespace-core:0.4.5 - https://lance.org/format/namespace/lance-namespace-core/)
|
||||
|
||||
EDL 1.0:
|
||||
|
||||
* Jakarta Activation API jar (jakarta.activation:jakarta.activation-api:1.2.2 - https://github.com/eclipse-ee4j/jaf/jakarta.activation-api)
|
||||
|
||||
Eclipse Distribution License - v 1.0:
|
||||
|
||||
* Eclipse Collections API (org.eclipse.collections:eclipse-collections-api:11.1.0 - https://github.com/eclipse/eclipse-collections/eclipse-collections-api)
|
||||
* Eclipse Collections Main Library (org.eclipse.collections:eclipse-collections:11.1.0 - https://github.com/eclipse/eclipse-collections/eclipse-collections)
|
||||
* Jakarta XML Binding API (jakarta.xml.bind:jakarta.xml.bind-api:2.3.3 - https://github.com/eclipse-ee4j/jaxb-api/jakarta.xml.bind-api)
|
||||
|
||||
Eclipse Public License - v 1.0:
|
||||
|
||||
* Eclipse Collections API (org.eclipse.collections:eclipse-collections-api:11.1.0 - https://github.com/eclipse/eclipse-collections/eclipse-collections-api)
|
||||
* Eclipse Collections Main Library (org.eclipse.collections:eclipse-collections:11.1.0 - https://github.com/eclipse/eclipse-collections/eclipse-collections)
|
||||
|
||||
The Apache Software License, Version 2.0:
|
||||
|
||||
* FindBugs-jsr305 (com.google.code.findbugs:jsr305:3.0.2 - http://findbugs.sourceforge.net/)
|
||||
* Guava InternalFutureFailureAccess and InternalFutures (com.google.guava:failureaccess:1.0.2 - https://github.com/google/guava/failureaccess)
|
||||
* Guava ListenableFuture only (com.google.guava:listenablefuture:9999.0-empty-to-avoid-conflict-with-guava - https://github.com/google/guava/listenablefuture)
|
||||
* Jackson datatype: JSR310 (com.fasterxml.jackson.datatype:jackson-datatype-jsr310:2.16.0 - https://github.com/FasterXML/jackson-modules-java8/jackson-datatype-jsr310)
|
||||
* Jackson module: Old JAXB Annotations (javax.xml.bind) (com.fasterxml.jackson.module:jackson-module-jaxb-annotations:2.17.1 - https://github.com/FasterXML/jackson-modules-base)
|
||||
* Jackson-annotations (com.fasterxml.jackson.core:jackson-annotations:2.16.0 - https://github.com/FasterXML/jackson)
|
||||
* Jackson-core (com.fasterxml.jackson.core:jackson-core:2.16.0 - https://github.com/FasterXML/jackson-core)
|
||||
* jackson-databind (com.fasterxml.jackson.core:jackson-databind:2.15.2 - https://github.com/FasterXML/jackson)
|
||||
* Jackson-JAXRS: base (com.fasterxml.jackson.jaxrs:jackson-jaxrs-base:2.17.1 - https://github.com/FasterXML/jackson-jaxrs-providers/jackson-jaxrs-base)
|
||||
* Jackson-JAXRS: JSON (com.fasterxml.jackson.jaxrs:jackson-jaxrs-json-provider:2.17.1 - https://github.com/FasterXML/jackson-jaxrs-providers/jackson-jaxrs-json-provider)
|
||||
* JAR JNI Loader (org.questdb:jar-jni:1.1.1 - https://github.com/questdb/rust-maven-plugin)
|
||||
* Lance Core (org.lance:lance-core:2.0.0 - https://lance.org/)
|
||||
|
||||
The MIT License:
|
||||
|
||||
* Checker Qual (org.checkerframework:checker-qual:3.43.0 - https://checkerframework.org/)
|
||||
71
java/lancedb-core/JAVA_THIRD_PARTY_LICENSES.md
Normal file
71
java/lancedb-core/JAVA_THIRD_PARTY_LICENSES.md
Normal file
@@ -0,0 +1,71 @@
|
||||
|
||||
List of third-party dependencies grouped by their license type.
|
||||
|
||||
Apache 2.0:
|
||||
|
||||
* error-prone annotations (com.google.errorprone:error_prone_annotations:2.28.0 - https://errorprone.info/error_prone_annotations)
|
||||
|
||||
Apache License 2.0:
|
||||
|
||||
* JsonNullable Jackson module (org.openapitools:jackson-databind-nullable:0.2.6 - https://github.com/OpenAPITools/jackson-databind-nullable)
|
||||
|
||||
Apache License V2.0:
|
||||
|
||||
* FlatBuffers Java API (com.google.flatbuffers:flatbuffers-java:23.5.26 - https://github.com/google/flatbuffers)
|
||||
|
||||
Apache License, Version 2.0:
|
||||
|
||||
* Apache Commons Codec (commons-codec:commons-codec:1.15 - https://commons.apache.org/proper/commons-codec/)
|
||||
* Apache HttpClient (org.apache.httpcomponents.client5:httpclient5:5.2.1 - https://hc.apache.org/httpcomponents-client-5.0.x/5.2.1/httpclient5/)
|
||||
* Apache HttpComponents Core HTTP/1.1 (org.apache.httpcomponents.core5:httpcore5:5.2 - https://hc.apache.org/httpcomponents-core-5.2.x/5.2/httpcore5/)
|
||||
* Apache HttpComponents Core HTTP/2 (org.apache.httpcomponents.core5:httpcore5-h2:5.2 - https://hc.apache.org/httpcomponents-core-5.2.x/5.2/httpcore5-h2/)
|
||||
* Arrow Format (org.apache.arrow:arrow-format:15.0.0 - https://arrow.apache.org/arrow-format/)
|
||||
* Arrow Java C Data Interface (org.apache.arrow:arrow-c-data:15.0.0 - https://arrow.apache.org/arrow-c-data/)
|
||||
* Arrow Java Dataset (org.apache.arrow:arrow-dataset:15.0.0 - https://arrow.apache.org/arrow-dataset/)
|
||||
* Arrow Memory - Core (org.apache.arrow:arrow-memory-core:15.0.0 - https://arrow.apache.org/arrow-memory/arrow-memory-core/)
|
||||
* Arrow Memory - Netty (org.apache.arrow:arrow-memory-netty:15.0.0 - https://arrow.apache.org/arrow-memory/arrow-memory-netty/)
|
||||
* Arrow Vectors (org.apache.arrow:arrow-vector:15.0.0 - https://arrow.apache.org/arrow-vector/)
|
||||
* Guava: Google Core Libraries for Java (com.google.guava:guava:33.3.1-jre - https://github.com/google/guava)
|
||||
* J2ObjC Annotations (com.google.j2objc:j2objc-annotations:3.0.0 - https://github.com/google/j2objc/)
|
||||
* Netty/Buffer (io.netty:netty-buffer:4.1.104.Final - https://netty.io/netty-buffer/)
|
||||
* Netty/Common (io.netty:netty-common:4.1.104.Final - https://netty.io/netty-common/)
|
||||
|
||||
Apache-2.0:
|
||||
|
||||
* Apache Commons Lang (org.apache.commons:commons-lang3:3.18.0 - https://commons.apache.org/proper/commons-lang/)
|
||||
* lance-namespace-apache-client (org.lance:lance-namespace-apache-client:0.4.5 - https://github.com/openapitools/openapi-generator)
|
||||
* lance-namespace-core (org.lance:lance-namespace-core:0.4.5 - https://lance.org/format/namespace/lance-namespace-core/)
|
||||
|
||||
EDL 1.0:
|
||||
|
||||
* Jakarta Activation API jar (jakarta.activation:jakarta.activation-api:1.2.2 - https://github.com/eclipse-ee4j/jaf/jakarta.activation-api)
|
||||
|
||||
Eclipse Distribution License - v 1.0:
|
||||
|
||||
* Eclipse Collections API (org.eclipse.collections:eclipse-collections-api:11.1.0 - https://github.com/eclipse/eclipse-collections/eclipse-collections-api)
|
||||
* Eclipse Collections Main Library (org.eclipse.collections:eclipse-collections:11.1.0 - https://github.com/eclipse/eclipse-collections/eclipse-collections)
|
||||
* Jakarta XML Binding API (jakarta.xml.bind:jakarta.xml.bind-api:2.3.3 - https://github.com/eclipse-ee4j/jaxb-api/jakarta.xml.bind-api)
|
||||
|
||||
Eclipse Public License - v 1.0:
|
||||
|
||||
* Eclipse Collections API (org.eclipse.collections:eclipse-collections-api:11.1.0 - https://github.com/eclipse/eclipse-collections/eclipse-collections-api)
|
||||
* Eclipse Collections Main Library (org.eclipse.collections:eclipse-collections:11.1.0 - https://github.com/eclipse/eclipse-collections/eclipse-collections)
|
||||
|
||||
The Apache Software License, Version 2.0:
|
||||
|
||||
* FindBugs-jsr305 (com.google.code.findbugs:jsr305:3.0.2 - http://findbugs.sourceforge.net/)
|
||||
* Guava InternalFutureFailureAccess and InternalFutures (com.google.guava:failureaccess:1.0.2 - https://github.com/google/guava/failureaccess)
|
||||
* Guava ListenableFuture only (com.google.guava:listenablefuture:9999.0-empty-to-avoid-conflict-with-guava - https://github.com/google/guava/listenablefuture)
|
||||
* Jackson datatype: JSR310 (com.fasterxml.jackson.datatype:jackson-datatype-jsr310:2.16.0 - https://github.com/FasterXML/jackson-modules-java8/jackson-datatype-jsr310)
|
||||
* Jackson module: Old JAXB Annotations (javax.xml.bind) (com.fasterxml.jackson.module:jackson-module-jaxb-annotations:2.17.1 - https://github.com/FasterXML/jackson-modules-base)
|
||||
* Jackson-annotations (com.fasterxml.jackson.core:jackson-annotations:2.16.0 - https://github.com/FasterXML/jackson)
|
||||
* Jackson-core (com.fasterxml.jackson.core:jackson-core:2.16.0 - https://github.com/FasterXML/jackson-core)
|
||||
* jackson-databind (com.fasterxml.jackson.core:jackson-databind:2.15.2 - https://github.com/FasterXML/jackson)
|
||||
* Jackson-JAXRS: base (com.fasterxml.jackson.jaxrs:jackson-jaxrs-base:2.17.1 - https://github.com/FasterXML/jackson-jaxrs-providers/jackson-jaxrs-base)
|
||||
* Jackson-JAXRS: JSON (com.fasterxml.jackson.jaxrs:jackson-jaxrs-json-provider:2.17.1 - https://github.com/FasterXML/jackson-jaxrs-providers/jackson-jaxrs-json-provider)
|
||||
* JAR JNI Loader (org.questdb:jar-jni:1.1.1 - https://github.com/questdb/rust-maven-plugin)
|
||||
* Lance Core (org.lance:lance-core:2.0.0 - https://lance.org/)
|
||||
|
||||
The MIT License:
|
||||
|
||||
* Checker Qual (org.checkerframework:checker-qual:3.43.0 - https://checkerframework.org/)
|
||||
@@ -8,7 +8,7 @@
|
||||
<parent>
|
||||
<groupId>com.lancedb</groupId>
|
||||
<artifactId>lancedb-parent</artifactId>
|
||||
<version>0.26.1-beta.0</version>
|
||||
<version>0.27.0-beta.0</version>
|
||||
<relativePath>../pom.xml</relativePath>
|
||||
</parent>
|
||||
|
||||
|
||||
17
java/pom.xml
17
java/pom.xml
@@ -6,7 +6,7 @@
|
||||
|
||||
<groupId>com.lancedb</groupId>
|
||||
<artifactId>lancedb-parent</artifactId>
|
||||
<version>0.26.1-beta.0</version>
|
||||
<version>0.27.0-beta.0</version>
|
||||
<packaging>pom</packaging>
|
||||
<name>${project.artifactId}</name>
|
||||
<description>LanceDB Java SDK Parent POM</description>
|
||||
@@ -28,7 +28,7 @@
|
||||
<properties>
|
||||
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
|
||||
<arrow.version>15.0.0</arrow.version>
|
||||
<lance-core.version>2.0.0</lance-core.version>
|
||||
<lance-core.version>2.0.1</lance-core.version>
|
||||
<spotless.skip>false</spotless.skip>
|
||||
<spotless.version>2.30.0</spotless.version>
|
||||
<spotless.java.googlejavaformat.version>1.7</spotless.java.googlejavaformat.version>
|
||||
@@ -160,6 +160,19 @@
|
||||
<groupId>com.diffplug.spotless</groupId>
|
||||
<artifactId>spotless-maven-plugin</artifactId>
|
||||
</plugin>
|
||||
<plugin>
|
||||
<groupId>org.codehaus.mojo</groupId>
|
||||
<artifactId>license-maven-plugin</artifactId>
|
||||
<version>2.4.0</version>
|
||||
<configuration>
|
||||
<outputDirectory>${project.basedir}</outputDirectory>
|
||||
<thirdPartyFilename>JAVA_THIRD_PARTY_LICENSES.md</thirdPartyFilename>
|
||||
<fileTemplate>/org/codehaus/mojo/license/third-party-file-groupByLicense.ftl</fileTemplate>
|
||||
<includedScopes>compile,runtime</includedScopes>
|
||||
<excludedScopes>test,provided</excludedScopes>
|
||||
<sortArtifactByName>true</sortArtifactByName>
|
||||
</configuration>
|
||||
</plugin>
|
||||
</plugins>
|
||||
<pluginManagement>
|
||||
<plugins>
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
[package]
|
||||
name = "lancedb-nodejs"
|
||||
edition.workspace = true
|
||||
version = "0.26.1-beta.0"
|
||||
version = "0.27.0-beta.0"
|
||||
license.workspace = true
|
||||
description.workspace = true
|
||||
repository.workspace = true
|
||||
|
||||
668
nodejs/NODEJS_THIRD_PARTY_LICENSES.md
Normal file
668
nodejs/NODEJS_THIRD_PARTY_LICENSES.md
Normal file
@@ -0,0 +1,668 @@
|
||||
[@75lb/deep-merge@1.1.2](https://github.com/75lb/deep-merge) - MIT
|
||||
[@aashutoshrathi/word-wrap@1.2.6](https://github.com/aashutoshrathi/word-wrap) - MIT
|
||||
[@ampproject/remapping@2.2.1](https://github.com/ampproject/remapping) - Apache-2.0
|
||||
[@aws-crypto/crc32@3.0.0](https://github.com/aws/aws-sdk-js-crypto-helpers) - Apache-2.0
|
||||
[@aws-crypto/crc32c@3.0.0](https://github.com/aws/aws-sdk-js-crypto-helpers) - Apache-2.0
|
||||
[@aws-crypto/ie11-detection@3.0.0](https://github.com/aws/aws-sdk-js-crypto-helpers) - Apache-2.0
|
||||
[@aws-crypto/sha1-browser@3.0.0](https://github.com/aws/aws-sdk-js-crypto-helpers) - Apache-2.0
|
||||
[@aws-crypto/sha256-browser@3.0.0](https://github.com/aws/aws-sdk-js-crypto-helpers) - Apache-2.0
|
||||
[@aws-crypto/sha256-browser@5.2.0](https://github.com/aws/aws-sdk-js-crypto-helpers) - Apache-2.0
|
||||
[@aws-crypto/sha256-js@3.0.0](https://github.com/aws/aws-sdk-js-crypto-helpers) - Apache-2.0
|
||||
[@aws-crypto/sha256-js@5.2.0](https://github.com/aws/aws-sdk-js-crypto-helpers) - Apache-2.0
|
||||
[@aws-crypto/supports-web-crypto@3.0.0](https://github.com/aws/aws-sdk-js-crypto-helpers) - Apache-2.0
|
||||
[@aws-crypto/supports-web-crypto@5.2.0](https://github.com/aws/aws-sdk-js-crypto-helpers) - Apache-2.0
|
||||
[@aws-crypto/util@3.0.0](https://github.com/aws/aws-sdk-js-crypto-helpers) - Apache-2.0
|
||||
[@aws-crypto/util@5.2.0](https://github.com/aws/aws-sdk-js-crypto-helpers) - Apache-2.0
|
||||
[@aws-sdk/client-dynamodb@3.602.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/client-kms@3.549.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/client-s3@3.550.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/client-sso-oidc@3.549.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/client-sso-oidc@3.600.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/client-sso@3.549.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/client-sso@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/client-sts@3.549.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/client-sts@3.600.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/core@3.549.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/core@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/credential-provider-env@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/credential-provider-env@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/credential-provider-http@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/credential-provider-http@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/credential-provider-ini@3.549.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/credential-provider-ini@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/credential-provider-node@3.549.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/credential-provider-node@3.600.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/credential-provider-process@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/credential-provider-process@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/credential-provider-sso@3.549.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/credential-provider-sso@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/credential-provider-web-identity@3.549.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/credential-provider-web-identity@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/endpoint-cache@3.572.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-bucket-endpoint@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-endpoint-discovery@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-expect-continue@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-flexible-checksums@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-host-header@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-host-header@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-location-constraint@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-logger@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-logger@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-recursion-detection@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-recursion-detection@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-sdk-s3@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-signing@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-ssec@3.537.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-user-agent@3.540.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/middleware-user-agent@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/region-config-resolver@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/region-config-resolver@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/signature-v4-multi-region@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/token-providers@3.549.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/token-providers@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/types@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/types@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/util-arn-parser@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/util-endpoints@3.540.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/util-endpoints@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/util-locate-window@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/util-user-agent-browser@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/util-user-agent-browser@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/util-user-agent-node@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/util-user-agent-node@3.598.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/util-utf8-browser@3.259.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@aws-sdk/xml-builder@3.535.0](https://github.com/aws/aws-sdk-js-v3) - Apache-2.0
|
||||
[@babel/code-frame@7.26.2](https://github.com/babel/babel) - MIT
|
||||
[@babel/compat-data@7.23.5](https://github.com/babel/babel) - MIT
|
||||
[@babel/core@7.23.7](https://github.com/babel/babel) - MIT
|
||||
[@babel/generator@7.23.6](https://github.com/babel/babel) - MIT
|
||||
[@babel/helper-compilation-targets@7.23.6](https://github.com/babel/babel) - MIT
|
||||
[@babel/helper-environment-visitor@7.22.20](https://github.com/babel/babel) - MIT
|
||||
[@babel/helper-function-name@7.23.0](https://github.com/babel/babel) - MIT
|
||||
[@babel/helper-hoist-variables@7.22.5](https://github.com/babel/babel) - MIT
|
||||
[@babel/helper-module-imports@7.22.15](https://github.com/babel/babel) - MIT
|
||||
[@babel/helper-module-transforms@7.23.3](https://github.com/babel/babel) - MIT
|
||||
[@babel/helper-plugin-utils@7.22.5](https://github.com/babel/babel) - MIT
|
||||
[@babel/helper-simple-access@7.22.5](https://github.com/babel/babel) - MIT
|
||||
[@babel/helper-split-export-declaration@7.22.6](https://github.com/babel/babel) - MIT
|
||||
[@babel/helper-string-parser@7.25.9](https://github.com/babel/babel) - MIT
|
||||
[@babel/helper-validator-identifier@7.25.9](https://github.com/babel/babel) - MIT
|
||||
[@babel/helper-validator-option@7.23.5](https://github.com/babel/babel) - MIT
|
||||
[@babel/helpers@7.27.0](https://github.com/babel/babel) - MIT
|
||||
[@babel/parser@7.27.0](https://github.com/babel/babel) - MIT
|
||||
[@babel/plugin-syntax-async-generators@7.8.4](https://github.com/babel/babel/tree/master/packages/babel-plugin-syntax-async-generators) - MIT
|
||||
[@babel/plugin-syntax-bigint@7.8.3](https://github.com/babel/babel/tree/master/packages/babel-plugin-syntax-bigint) - MIT
|
||||
[@babel/plugin-syntax-class-properties@7.12.13](https://github.com/babel/babel) - MIT
|
||||
[@babel/plugin-syntax-import-meta@7.10.4](https://github.com/babel/babel) - MIT
|
||||
[@babel/plugin-syntax-json-strings@7.8.3](https://github.com/babel/babel/tree/master/packages/babel-plugin-syntax-json-strings) - MIT
|
||||
[@babel/plugin-syntax-jsx@7.23.3](https://github.com/babel/babel) - MIT
|
||||
[@babel/plugin-syntax-logical-assignment-operators@7.10.4](https://github.com/babel/babel) - MIT
|
||||
[@babel/plugin-syntax-nullish-coalescing-operator@7.8.3](https://github.com/babel/babel/tree/master/packages/babel-plugin-syntax-nullish-coalescing-operator) - MIT
|
||||
[@babel/plugin-syntax-numeric-separator@7.10.4](https://github.com/babel/babel) - MIT
|
||||
[@babel/plugin-syntax-object-rest-spread@7.8.3](https://github.com/babel/babel/tree/master/packages/babel-plugin-syntax-object-rest-spread) - MIT
|
||||
[@babel/plugin-syntax-optional-catch-binding@7.8.3](https://github.com/babel/babel/tree/master/packages/babel-plugin-syntax-optional-catch-binding) - MIT
|
||||
[@babel/plugin-syntax-optional-chaining@7.8.3](https://github.com/babel/babel/tree/master/packages/babel-plugin-syntax-optional-chaining) - MIT
|
||||
[@babel/plugin-syntax-top-level-await@7.14.5](https://github.com/babel/babel) - MIT
|
||||
[@babel/plugin-syntax-typescript@7.23.3](https://github.com/babel/babel) - MIT
|
||||
[@babel/template@7.27.0](https://github.com/babel/babel) - MIT
|
||||
[@babel/traverse@7.23.7](https://github.com/babel/babel) - MIT
|
||||
[@babel/types@7.27.0](https://github.com/babel/babel) - MIT
|
||||
[@bcoe/v8-coverage@0.2.3](https://github.com/demurgos/v8-coverage) - MIT
|
||||
[@biomejs/biome@1.8.3](https://github.com/biomejs/biome) - MIT OR Apache-2.0
|
||||
[@biomejs/cli-darwin-arm64@1.8.3](https://github.com/biomejs/biome) - MIT OR Apache-2.0
|
||||
[@eslint-community/eslint-utils@4.4.0](https://github.com/eslint-community/eslint-utils) - MIT
|
||||
[@eslint-community/regexpp@4.10.0](https://github.com/eslint-community/regexpp) - MIT
|
||||
[@eslint/eslintrc@2.1.4](https://github.com/eslint/eslintrc) - MIT
|
||||
[@eslint/js@8.57.0](https://github.com/eslint/eslint) - MIT
|
||||
[@huggingface/jinja@0.3.2](https://github.com/huggingface/huggingface.js) - MIT
|
||||
[@huggingface/transformers@3.0.2](https://github.com/huggingface/transformers.js) - Apache-2.0
|
||||
[@humanwhocodes/config-array@0.11.14](https://github.com/humanwhocodes/config-array) - Apache-2.0
|
||||
[@humanwhocodes/module-importer@1.0.1](https://github.com/humanwhocodes/module-importer) - Apache-2.0
|
||||
[@humanwhocodes/object-schema@2.0.2](https://github.com/humanwhocodes/object-schema) - BSD-3-Clause
|
||||
[@img/sharp-darwin-arm64@0.33.5](https://github.com/lovell/sharp) - Apache-2.0
|
||||
[@img/sharp-libvips-darwin-arm64@1.0.4](https://github.com/lovell/sharp-libvips) - LGPL-3.0-or-later
|
||||
[@isaacs/cliui@8.0.2](https://github.com/yargs/cliui) - ISC
|
||||
[@isaacs/fs-minipass@4.0.1](https://github.com/npm/fs-minipass) - ISC
|
||||
[@istanbuljs/load-nyc-config@1.1.0](https://github.com/istanbuljs/load-nyc-config) - ISC
|
||||
[@istanbuljs/schema@0.1.3](https://github.com/istanbuljs/schema) - MIT
|
||||
[@jest/console@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[@jest/core@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[@jest/environment@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[@jest/expect-utils@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[@jest/expect@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[@jest/fake-timers@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[@jest/globals@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[@jest/reporters@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[@jest/schemas@29.6.3](https://github.com/jestjs/jest) - MIT
|
||||
[@jest/source-map@29.6.3](https://github.com/jestjs/jest) - MIT
|
||||
[@jest/test-result@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[@jest/test-sequencer@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[@jest/transform@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[@jest/types@29.6.3](https://github.com/jestjs/jest) - MIT
|
||||
[@jridgewell/gen-mapping@0.3.3](https://github.com/jridgewell/gen-mapping) - MIT
|
||||
[@jridgewell/resolve-uri@3.1.1](https://github.com/jridgewell/resolve-uri) - MIT
|
||||
[@jridgewell/set-array@1.1.2](https://github.com/jridgewell/set-array) - MIT
|
||||
[@jridgewell/sourcemap-codec@1.4.15](https://github.com/jridgewell/sourcemap-codec) - MIT
|
||||
[@jridgewell/trace-mapping@0.3.22](https://github.com/jridgewell/trace-mapping) - MIT
|
||||
[@lancedb/lancedb@0.26.2](https://github.com/lancedb/lancedb) - Apache-2.0
|
||||
[@napi-rs/cli@2.18.3](https://github.com/napi-rs/napi-rs) - MIT
|
||||
[@nodelib/fs.scandir@2.1.5](https://github.com/nodelib/nodelib/tree/master/packages/fs/fs.scandir) - MIT
|
||||
[@nodelib/fs.stat@2.0.5](https://github.com/nodelib/nodelib/tree/master/packages/fs/fs.stat) - MIT
|
||||
[@nodelib/fs.walk@1.2.8](https://github.com/nodelib/nodelib/tree/master/packages/fs/fs.walk) - MIT
|
||||
[@pkgjs/parseargs@0.11.0](https://github.com/pkgjs/parseargs) - MIT
|
||||
[@protobufjs/aspromise@1.1.2](https://github.com/dcodeIO/protobuf.js) - BSD-3-Clause
|
||||
[@protobufjs/base64@1.1.2](https://github.com/dcodeIO/protobuf.js) - BSD-3-Clause
|
||||
[@protobufjs/codegen@2.0.4](https://github.com/dcodeIO/protobuf.js) - BSD-3-Clause
|
||||
[@protobufjs/eventemitter@1.1.0](https://github.com/dcodeIO/protobuf.js) - BSD-3-Clause
|
||||
[@protobufjs/fetch@1.1.0](https://github.com/dcodeIO/protobuf.js) - BSD-3-Clause
|
||||
[@protobufjs/float@1.0.2](https://github.com/dcodeIO/protobuf.js) - BSD-3-Clause
|
||||
[@protobufjs/inquire@1.1.0](https://github.com/dcodeIO/protobuf.js) - BSD-3-Clause
|
||||
[@protobufjs/path@1.1.2](https://github.com/dcodeIO/protobuf.js) - BSD-3-Clause
|
||||
[@protobufjs/pool@1.1.0](https://github.com/dcodeIO/protobuf.js) - BSD-3-Clause
|
||||
[@protobufjs/utf8@1.1.0](https://github.com/dcodeIO/protobuf.js) - BSD-3-Clause
|
||||
[@shikijs/core@1.10.3](https://github.com/shikijs/shiki) - MIT
|
||||
[@sinclair/typebox@0.27.8](https://github.com/sinclairzx81/typebox) - MIT
|
||||
[@sinonjs/commons@3.0.1](https://github.com/sinonjs/commons) - BSD-3-Clause
|
||||
[@sinonjs/fake-timers@10.3.0](https://github.com/sinonjs/fake-timers) - BSD-3-Clause
|
||||
[@smithy/abort-controller@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/abort-controller@3.1.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/chunked-blob-reader-native@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/chunked-blob-reader@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/config-resolver@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/config-resolver@3.0.3](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/core@1.4.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/core@2.2.3](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/credential-provider-imds@2.3.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/credential-provider-imds@3.1.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/eventstream-codec@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/eventstream-serde-browser@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/eventstream-serde-config-resolver@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/eventstream-serde-node@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/eventstream-serde-universal@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/fetch-http-handler@2.5.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/fetch-http-handler@3.1.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/hash-blob-browser@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/hash-node@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/hash-node@3.0.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/hash-stream-node@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/invalid-dependency@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/invalid-dependency@3.0.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/is-array-buffer@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/is-array-buffer@3.0.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/md5-js@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/middleware-content-length@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/middleware-content-length@3.0.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/middleware-endpoint@2.5.1](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/middleware-endpoint@3.0.3](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/middleware-retry@2.3.1](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/middleware-retry@3.0.6](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/middleware-serde@2.3.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/middleware-serde@3.0.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/middleware-stack@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/middleware-stack@3.0.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/node-config-provider@2.3.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/node-config-provider@3.1.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/node-http-handler@2.5.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/node-http-handler@3.1.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/property-provider@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/property-provider@3.1.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/protocol-http@3.3.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/protocol-http@4.0.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/querystring-builder@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/querystring-builder@3.0.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/querystring-parser@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/querystring-parser@3.0.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/service-error-classification@2.1.5](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/service-error-classification@3.0.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/shared-ini-file-loader@2.4.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/shared-ini-file-loader@3.1.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/signature-v4@2.2.1](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/signature-v4@3.1.1](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/smithy-client@2.5.1](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/smithy-client@3.1.4](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/types@2.12.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/types@3.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/url-parser@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/url-parser@3.0.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-base64@2.3.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-base64@3.0.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-body-length-browser@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-body-length-browser@3.0.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-body-length-node@2.3.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-body-length-node@3.0.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-buffer-from@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-buffer-from@3.0.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-config-provider@2.3.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-config-provider@3.0.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-defaults-mode-browser@2.2.1](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-defaults-mode-browser@3.0.6](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-defaults-mode-node@2.3.1](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-defaults-mode-node@3.0.6](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-endpoints@1.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-endpoints@2.0.3](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-hex-encoding@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-hex-encoding@3.0.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-middleware@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-middleware@3.0.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-retry@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-retry@3.0.2](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-stream@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-stream@3.0.4](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-uri-escape@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-uri-escape@3.0.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-utf8@2.3.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-utf8@3.0.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-waiter@2.2.0](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@smithy/util-waiter@3.1.1](https://github.com/awslabs/smithy-typescript) - Apache-2.0
|
||||
[@swc/helpers@0.5.12](https://github.com/swc-project/swc) - Apache-2.0
|
||||
[@types/axios@0.14.0](https://github.com/mzabriskie/axios) - MIT
|
||||
[@types/babel__core@7.20.5](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/babel__generator@7.6.8](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/babel__template@7.4.4](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/babel__traverse@7.20.5](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/command-line-args@5.2.3](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/command-line-usage@5.0.2](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/command-line-usage@5.0.4](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/graceful-fs@4.1.9](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/hast@3.0.4](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/istanbul-lib-coverage@2.0.6](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/istanbul-lib-report@3.0.3](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/istanbul-reports@3.0.4](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/jest@29.5.12](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/json-schema@7.0.15](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/node-fetch@2.6.11](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/node@18.19.26](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/node@20.16.10](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/node@20.17.9](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/node@22.7.4](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/semver@7.5.6](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/stack-utils@2.0.3](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/tmp@0.2.6](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/unist@3.0.2](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/yargs-parser@21.0.3](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@types/yargs@17.0.32](https://github.com/DefinitelyTyped/DefinitelyTyped) - MIT
|
||||
[@typescript-eslint/eslint-plugin@7.1.0](https://github.com/typescript-eslint/typescript-eslint) - MIT
|
||||
[@typescript-eslint/parser@7.1.0](https://github.com/typescript-eslint/typescript-eslint) - BSD-2-Clause
|
||||
[@typescript-eslint/scope-manager@7.1.0](https://github.com/typescript-eslint/typescript-eslint) - MIT
|
||||
[@typescript-eslint/type-utils@7.1.0](https://github.com/typescript-eslint/typescript-eslint) - MIT
|
||||
[@typescript-eslint/types@7.1.0](https://github.com/typescript-eslint/typescript-eslint) - MIT
|
||||
[@typescript-eslint/typescript-estree@7.1.0](https://github.com/typescript-eslint/typescript-eslint) - BSD-2-Clause
|
||||
[@typescript-eslint/utils@7.1.0](https://github.com/typescript-eslint/typescript-eslint) - MIT
|
||||
[@typescript-eslint/visitor-keys@7.1.0](https://github.com/typescript-eslint/typescript-eslint) - MIT
|
||||
[@ungap/structured-clone@1.2.0](https://github.com/ungap/structured-clone) - ISC
|
||||
[abort-controller@3.0.0](https://github.com/mysticatea/abort-controller) - MIT
|
||||
[acorn-jsx@5.3.2](https://github.com/acornjs/acorn-jsx) - MIT
|
||||
[acorn@8.11.3](https://github.com/acornjs/acorn) - MIT
|
||||
[agentkeepalive@4.5.0](https://github.com/node-modules/agentkeepalive) - MIT
|
||||
[ajv@6.12.6](https://github.com/ajv-validator/ajv) - MIT
|
||||
[ansi-escapes@4.3.2](https://github.com/sindresorhus/ansi-escapes) - MIT
|
||||
[ansi-regex@5.0.1](https://github.com/chalk/ansi-regex) - MIT
|
||||
[ansi-regex@6.1.0](https://github.com/chalk/ansi-regex) - MIT
|
||||
[ansi-styles@4.3.0](https://github.com/chalk/ansi-styles) - MIT
|
||||
[ansi-styles@5.2.0](https://github.com/chalk/ansi-styles) - MIT
|
||||
[ansi-styles@6.2.1](https://github.com/chalk/ansi-styles) - MIT
|
||||
[anymatch@3.1.3](https://github.com/micromatch/anymatch) - ISC
|
||||
[apache-arrow@15.0.0](https://github.com/apache/arrow) - Apache-2.0
|
||||
[apache-arrow@16.0.0](https://github.com/apache/arrow) - Apache-2.0
|
||||
[apache-arrow@17.0.0](https://github.com/apache/arrow) - Apache-2.0
|
||||
[apache-arrow@18.0.0](https://github.com/apache/arrow) - Apache-2.0
|
||||
[argparse@1.0.10](https://github.com/nodeca/argparse) - MIT
|
||||
[argparse@2.0.1](https://github.com/nodeca/argparse) - Python-2.0
|
||||
[array-back@3.1.0](https://github.com/75lb/array-back) - MIT
|
||||
[array-back@6.2.2](https://github.com/75lb/array-back) - MIT
|
||||
[array-union@2.1.0](https://github.com/sindresorhus/array-union) - MIT
|
||||
[asynckit@0.4.0](https://github.com/alexindigo/asynckit) - MIT
|
||||
[axios@1.8.4](https://github.com/axios/axios) - MIT
|
||||
[babel-jest@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[babel-plugin-istanbul@6.1.1](https://github.com/istanbuljs/babel-plugin-istanbul) - BSD-3-Clause
|
||||
[babel-plugin-jest-hoist@29.6.3](https://github.com/jestjs/jest) - MIT
|
||||
[babel-preset-current-node-syntax@1.0.1](https://github.com/nicolo-ribaudo/babel-preset-current-node-syntax) - MIT
|
||||
[babel-preset-jest@29.6.3](https://github.com/jestjs/jest) - MIT
|
||||
[balanced-match@1.0.2](https://github.com/juliangruber/balanced-match) - MIT
|
||||
[base-64@0.1.0](https://github.com/mathiasbynens/base64) - MIT
|
||||
[bowser@2.11.0](https://github.com/lancedikson/bowser) - MIT
|
||||
[brace-expansion@1.1.11](https://github.com/juliangruber/brace-expansion) - MIT
|
||||
[brace-expansion@2.0.1](https://github.com/juliangruber/brace-expansion) - MIT
|
||||
[braces@3.0.3](https://github.com/micromatch/braces) - MIT
|
||||
[browserslist@4.22.2](https://github.com/browserslist/browserslist) - MIT
|
||||
[bs-logger@0.2.6](https://github.com/huafu/bs-logger) - MIT
|
||||
[bser@2.1.1](https://github.com/facebook/watchman) - Apache-2.0
|
||||
[buffer-from@1.1.2](https://github.com/LinusU/buffer-from) - MIT
|
||||
[callsites@3.1.0](https://github.com/sindresorhus/callsites) - MIT
|
||||
[camelcase@5.3.1](https://github.com/sindresorhus/camelcase) - MIT
|
||||
[camelcase@6.3.0](https://github.com/sindresorhus/camelcase) - MIT
|
||||
[caniuse-lite@1.0.30001579](https://github.com/browserslist/caniuse-lite) - CC-BY-4.0
|
||||
[chalk-template@0.4.0](https://github.com/chalk/chalk-template) - MIT
|
||||
[chalk@4.1.2](https://github.com/chalk/chalk) - MIT
|
||||
[char-regex@1.0.2](https://github.com/Richienb/char-regex) - MIT
|
||||
[charenc@0.0.2](https://github.com/pvorb/node-charenc) - BSD-3-Clause
|
||||
[chownr@3.0.0](https://github.com/isaacs/chownr) - BlueOak-1.0.0
|
||||
[ci-info@3.9.0](https://github.com/watson/ci-info) - MIT
|
||||
[cjs-module-lexer@1.2.3](https://github.com/nodejs/cjs-module-lexer) - MIT
|
||||
[cliui@8.0.1](https://github.com/yargs/cliui) - ISC
|
||||
[co@4.6.0](https://github.com/tj/co) - MIT
|
||||
[collect-v8-coverage@1.0.2](https://github.com/SimenB/collect-v8-coverage) - MIT
|
||||
[color-convert@2.0.1](https://github.com/Qix-/color-convert) - MIT
|
||||
[color-name@1.1.4](https://github.com/colorjs/color-name) - MIT
|
||||
[color-string@1.9.1](https://github.com/Qix-/color-string) - MIT
|
||||
[color@4.2.3](https://github.com/Qix-/color) - MIT
|
||||
[combined-stream@1.0.8](https://github.com/felixge/node-combined-stream) - MIT
|
||||
[command-line-args@5.2.1](https://github.com/75lb/command-line-args) - MIT
|
||||
[command-line-usage@7.0.1](https://github.com/75lb/command-line-usage) - MIT
|
||||
[concat-map@0.0.1](https://github.com/substack/node-concat-map) - MIT
|
||||
[convert-source-map@2.0.0](https://github.com/thlorenz/convert-source-map) - MIT
|
||||
[create-jest@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[cross-spawn@7.0.6](https://github.com/moxystudio/node-cross-spawn) - MIT
|
||||
[crypt@0.0.2](https://github.com/pvorb/node-crypt) - BSD-3-Clause
|
||||
[debug@4.3.4](https://github.com/debug-js/debug) - MIT
|
||||
[dedent@1.5.1](https://github.com/dmnd/dedent) - MIT
|
||||
[deep-is@0.1.4](https://github.com/thlorenz/deep-is) - MIT
|
||||
[deepmerge@4.3.1](https://github.com/TehShrike/deepmerge) - MIT
|
||||
[delayed-stream@1.0.0](https://github.com/felixge/node-delayed-stream) - MIT
|
||||
[detect-libc@2.0.3](https://github.com/lovell/detect-libc) - Apache-2.0
|
||||
[detect-newline@3.1.0](https://github.com/sindresorhus/detect-newline) - MIT
|
||||
[diff-sequences@29.6.3](https://github.com/jestjs/jest) - MIT
|
||||
[digest-fetch@1.3.0](https://github.com/devfans/digest-fetch) - ISC
|
||||
[dir-glob@3.0.1](https://github.com/kevva/dir-glob) - MIT
|
||||
[doctrine@3.0.0](https://github.com/eslint/doctrine) - Apache-2.0
|
||||
[eastasianwidth@0.2.0](https://github.com/komagata/eastasianwidth) - MIT
|
||||
[electron-to-chromium@1.4.642](https://github.com/kilian/electron-to-chromium) - ISC
|
||||
[emittery@0.13.1](https://github.com/sindresorhus/emittery) - MIT
|
||||
[emoji-regex@8.0.0](https://github.com/mathiasbynens/emoji-regex) - MIT
|
||||
[emoji-regex@9.2.2](https://github.com/mathiasbynens/emoji-regex) - MIT
|
||||
[entities@4.5.0](https://github.com/fb55/entities) - BSD-2-Clause
|
||||
[error-ex@1.3.2](https://github.com/qix-/node-error-ex) - MIT
|
||||
[escalade@3.1.1](https://github.com/lukeed/escalade) - MIT
|
||||
[escape-string-regexp@2.0.0](https://github.com/sindresorhus/escape-string-regexp) - MIT
|
||||
[escape-string-regexp@4.0.0](https://github.com/sindresorhus/escape-string-regexp) - MIT
|
||||
[eslint-scope@7.2.2](https://github.com/eslint/eslint-scope) - BSD-2-Clause
|
||||
[eslint-visitor-keys@3.4.3](https://github.com/eslint/eslint-visitor-keys) - Apache-2.0
|
||||
[eslint@8.57.0](https://github.com/eslint/eslint) - MIT
|
||||
[espree@9.6.1](https://github.com/eslint/espree) - BSD-2-Clause
|
||||
[esprima@4.0.1](https://github.com/jquery/esprima) - BSD-2-Clause
|
||||
[esquery@1.5.0](https://github.com/estools/esquery) - BSD-3-Clause
|
||||
[esrecurse@4.3.0](https://github.com/estools/esrecurse) - BSD-2-Clause
|
||||
[estraverse@5.3.0](https://github.com/estools/estraverse) - BSD-2-Clause
|
||||
[esutils@2.0.3](https://github.com/estools/esutils) - BSD-2-Clause
|
||||
[event-target-shim@5.0.1](https://github.com/mysticatea/event-target-shim) - MIT
|
||||
[execa@5.1.1](https://github.com/sindresorhus/execa) - MIT
|
||||
[exit@0.1.2](https://github.com/cowboy/node-exit) - MIT
|
||||
[expect@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[fast-deep-equal@3.1.3](https://github.com/epoberezkin/fast-deep-equal) - MIT
|
||||
[fast-glob@3.3.2](https://github.com/mrmlnc/fast-glob) - MIT
|
||||
[fast-json-stable-stringify@2.1.0](https://github.com/epoberezkin/fast-json-stable-stringify) - MIT
|
||||
[fast-levenshtein@2.0.6](https://github.com/hiddentao/fast-levenshtein) - MIT
|
||||
[fast-xml-parser@4.2.5](https://github.com/NaturalIntelligence/fast-xml-parser) - MIT
|
||||
[fastq@1.16.0](https://github.com/mcollina/fastq) - ISC
|
||||
[fb-watchman@2.0.2](https://github.com/facebook/watchman) - Apache-2.0
|
||||
[file-entry-cache@6.0.1](https://github.com/royriojas/file-entry-cache) - MIT
|
||||
[fill-range@7.1.1](https://github.com/jonschlinkert/fill-range) - MIT
|
||||
[find-replace@3.0.0](https://github.com/75lb/find-replace) - MIT
|
||||
[find-up@4.1.0](https://github.com/sindresorhus/find-up) - MIT
|
||||
[find-up@5.0.0](https://github.com/sindresorhus/find-up) - MIT
|
||||
[flat-cache@3.2.0](https://github.com/jaredwray/flat-cache) - MIT
|
||||
[flatbuffers@1.12.0](https://github.com/google/flatbuffers) - Apache*
|
||||
[flatbuffers@23.5.26](https://github.com/google/flatbuffers) - Apache*
|
||||
[flatbuffers@24.3.25](https://github.com/google/flatbuffers) - Apache-2.0
|
||||
[flatted@3.2.9](https://github.com/WebReflection/flatted) - ISC
|
||||
[follow-redirects@1.15.6](https://github.com/follow-redirects/follow-redirects) - MIT
|
||||
[foreground-child@3.3.0](https://github.com/tapjs/foreground-child) - ISC
|
||||
[form-data-encoder@1.7.2](https://github.com/octet-stream/form-data-encoder) - MIT
|
||||
[form-data@4.0.0](https://github.com/form-data/form-data) - MIT
|
||||
[formdata-node@4.4.1](https://github.com/octet-stream/form-data) - MIT
|
||||
[fs.realpath@1.0.0](https://github.com/isaacs/fs.realpath) - ISC
|
||||
[fsevents@2.3.3](https://github.com/fsevents/fsevents) - MIT
|
||||
[function-bind@1.1.2](https://github.com/Raynos/function-bind) - MIT
|
||||
[gensync@1.0.0-beta.2](https://github.com/loganfsmyth/gensync) - MIT
|
||||
[get-caller-file@2.0.5](https://github.com/stefanpenner/get-caller-file) - ISC
|
||||
[get-package-type@0.1.0](https://github.com/cfware/get-package-type) - MIT
|
||||
[get-stream@6.0.1](https://github.com/sindresorhus/get-stream) - MIT
|
||||
[glob-parent@5.1.2](https://github.com/gulpjs/glob-parent) - ISC
|
||||
[glob-parent@6.0.2](https://github.com/gulpjs/glob-parent) - ISC
|
||||
[glob@10.4.5](https://github.com/isaacs/node-glob) - ISC
|
||||
[glob@7.2.3](https://github.com/isaacs/node-glob) - ISC
|
||||
[globals@11.12.0](https://github.com/sindresorhus/globals) - MIT
|
||||
[globals@13.24.0](https://github.com/sindresorhus/globals) - MIT
|
||||
[globby@11.1.0](https://github.com/sindresorhus/globby) - MIT
|
||||
[graceful-fs@4.2.11](https://github.com/isaacs/node-graceful-fs) - ISC
|
||||
[graphemer@1.4.0](https://github.com/flmnt/graphemer) - MIT
|
||||
[guid-typescript@1.0.9](https://github.com/NicolasDeveloper/guid-typescript) - ISC
|
||||
[has-flag@4.0.0](https://github.com/sindresorhus/has-flag) - MIT
|
||||
[hasown@2.0.0](https://github.com/inspect-js/hasOwn) - MIT
|
||||
[html-escaper@2.0.2](https://github.com/WebReflection/html-escaper) - MIT
|
||||
[human-signals@2.1.0](https://github.com/ehmicky/human-signals) - Apache-2.0
|
||||
[humanize-ms@1.2.1](https://github.com/node-modules/humanize-ms) - MIT
|
||||
[ignore@5.3.0](https://github.com/kaelzhang/node-ignore) - MIT
|
||||
[import-fresh@3.3.0](https://github.com/sindresorhus/import-fresh) - MIT
|
||||
[import-local@3.1.0](https://github.com/sindresorhus/import-local) - MIT
|
||||
[imurmurhash@0.1.4](https://github.com/jensyt/imurmurhash-js) - MIT
|
||||
[inflight@1.0.6](https://github.com/npm/inflight) - ISC
|
||||
[inherits@2.0.4](https://github.com/isaacs/inherits) - ISC
|
||||
[interpret@1.4.0](https://github.com/gulpjs/interpret) - MIT
|
||||
[is-arrayish@0.2.1](https://github.com/qix-/node-is-arrayish) - MIT
|
||||
[is-arrayish@0.3.2](https://github.com/qix-/node-is-arrayish) - MIT
|
||||
[is-buffer@1.1.6](https://github.com/feross/is-buffer) - MIT
|
||||
[is-core-module@2.13.1](https://github.com/inspect-js/is-core-module) - MIT
|
||||
[is-extglob@2.1.1](https://github.com/jonschlinkert/is-extglob) - MIT
|
||||
[is-fullwidth-code-point@3.0.0](https://github.com/sindresorhus/is-fullwidth-code-point) - MIT
|
||||
[is-generator-fn@2.1.0](https://github.com/sindresorhus/is-generator-fn) - MIT
|
||||
[is-glob@4.0.3](https://github.com/micromatch/is-glob) - MIT
|
||||
[is-number@7.0.0](https://github.com/jonschlinkert/is-number) - MIT
|
||||
[is-path-inside@3.0.3](https://github.com/sindresorhus/is-path-inside) - MIT
|
||||
[is-stream@2.0.1](https://github.com/sindresorhus/is-stream) - MIT
|
||||
[isexe@2.0.0](https://github.com/isaacs/isexe) - ISC
|
||||
[istanbul-lib-coverage@3.2.2](https://github.com/istanbuljs/istanbuljs) - BSD-3-Clause
|
||||
[istanbul-lib-instrument@5.2.1](https://github.com/istanbuljs/istanbuljs) - BSD-3-Clause
|
||||
[istanbul-lib-instrument@6.0.1](https://github.com/istanbuljs/istanbuljs) - BSD-3-Clause
|
||||
[istanbul-lib-report@3.0.1](https://github.com/istanbuljs/istanbuljs) - BSD-3-Clause
|
||||
[istanbul-lib-source-maps@4.0.1](https://github.com/istanbuljs/istanbuljs) - BSD-3-Clause
|
||||
[istanbul-reports@3.1.6](https://github.com/istanbuljs/istanbuljs) - BSD-3-Clause
|
||||
[jackspeak@3.4.3](https://github.com/isaacs/jackspeak) - BlueOak-1.0.0
|
||||
[jest-changed-files@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-circus@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-cli@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-config@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-diff@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-docblock@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-each@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-environment-node@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-get-type@29.6.3](https://github.com/jestjs/jest) - MIT
|
||||
[jest-haste-map@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-leak-detector@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-matcher-utils@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-message-util@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-mock@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-pnp-resolver@1.2.3](https://github.com/arcanis/jest-pnp-resolver) - MIT
|
||||
[jest-regex-util@29.6.3](https://github.com/jestjs/jest) - MIT
|
||||
[jest-resolve-dependencies@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-resolve@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-runner@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-runtime@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-snapshot@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-util@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-validate@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-watcher@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest-worker@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[jest@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[js-tokens@4.0.0](https://github.com/lydell/js-tokens) - MIT
|
||||
[js-yaml@3.14.1](https://github.com/nodeca/js-yaml) - MIT
|
||||
[js-yaml@4.1.0](https://github.com/nodeca/js-yaml) - MIT
|
||||
[jsesc@2.5.2](https://github.com/mathiasbynens/jsesc) - MIT
|
||||
[json-bignum@0.0.3](https://github.com/datalanche/json-bignum) - MIT
|
||||
[json-buffer@3.0.1](https://github.com/dominictarr/json-buffer) - MIT
|
||||
[json-parse-even-better-errors@2.3.1](https://github.com/npm/json-parse-even-better-errors) - MIT
|
||||
[json-schema-traverse@0.4.1](https://github.com/epoberezkin/json-schema-traverse) - MIT
|
||||
[json-stable-stringify-without-jsonify@1.0.1](https://github.com/samn/json-stable-stringify) - MIT
|
||||
[json5@2.2.3](https://github.com/json5/json5) - MIT
|
||||
[keyv@4.5.4](https://github.com/jaredwray/keyv) - MIT
|
||||
[kleur@3.0.3](https://github.com/lukeed/kleur) - MIT
|
||||
[leven@3.1.0](https://github.com/sindresorhus/leven) - MIT
|
||||
[levn@0.4.1](https://github.com/gkz/levn) - MIT
|
||||
[lines-and-columns@1.2.4](https://github.com/eventualbuddha/lines-and-columns) - MIT
|
||||
[linkify-it@5.0.0](https://github.com/markdown-it/linkify-it) - MIT
|
||||
[locate-path@5.0.0](https://github.com/sindresorhus/locate-path) - MIT
|
||||
[locate-path@6.0.0](https://github.com/sindresorhus/locate-path) - MIT
|
||||
[lodash.camelcase@4.3.0](https://github.com/lodash/lodash) - MIT
|
||||
[lodash.memoize@4.1.2](https://github.com/lodash/lodash) - MIT
|
||||
[lodash.merge@4.6.2](https://github.com/lodash/lodash) - MIT
|
||||
[lodash@4.17.21](https://github.com/lodash/lodash) - MIT
|
||||
[long@5.2.3](https://github.com/dcodeIO/long.js) - Apache-2.0
|
||||
[lru-cache@10.4.3](https://github.com/isaacs/node-lru-cache) - ISC
|
||||
[lru-cache@5.1.1](https://github.com/isaacs/node-lru-cache) - ISC
|
||||
[lunr@2.3.9](https://github.com/olivernn/lunr.js) - MIT
|
||||
[make-dir@4.0.0](https://github.com/sindresorhus/make-dir) - MIT
|
||||
[make-error@1.3.6](https://github.com/JsCommunity/make-error) - ISC
|
||||
[makeerror@1.0.12](https://github.com/daaku/nodejs-makeerror) - BSD-3-Clause
|
||||
[markdown-it@14.1.0](https://github.com/markdown-it/markdown-it) - MIT
|
||||
[md5@2.3.0](https://github.com/pvorb/node-md5) - BSD-3-Clause
|
||||
[mdurl@2.0.0](https://github.com/markdown-it/mdurl) - MIT
|
||||
[merge-stream@2.0.0](https://github.com/grncdr/merge-stream) - MIT
|
||||
[merge2@1.4.1](https://github.com/teambition/merge2) - MIT
|
||||
[micromatch@4.0.8](https://github.com/micromatch/micromatch) - MIT
|
||||
[mime-db@1.52.0](https://github.com/jshttp/mime-db) - MIT
|
||||
[mime-types@2.1.35](https://github.com/jshttp/mime-types) - MIT
|
||||
[mimic-fn@2.1.0](https://github.com/sindresorhus/mimic-fn) - MIT
|
||||
[minimatch@3.1.2](https://github.com/isaacs/minimatch) - ISC
|
||||
[minimatch@9.0.3](https://github.com/isaacs/minimatch) - ISC
|
||||
[minimatch@9.0.5](https://github.com/isaacs/minimatch) - ISC
|
||||
[minimist@1.2.8](https://github.com/minimistjs/minimist) - MIT
|
||||
[minipass@7.1.2](https://github.com/isaacs/minipass) - ISC
|
||||
[minizlib@3.0.1](https://github.com/isaacs/minizlib) - MIT
|
||||
[mkdirp@3.0.1](https://github.com/isaacs/node-mkdirp) - MIT
|
||||
[mnemonist@0.38.3](https://github.com/yomguithereal/mnemonist) - MIT
|
||||
[ms@2.1.2](https://github.com/zeit/ms) - MIT
|
||||
[ms@2.1.3](https://github.com/vercel/ms) - MIT
|
||||
[natural-compare@1.4.0](https://github.com/litejs/natural-compare-lite) - MIT
|
||||
[node-domexception@1.0.0](https://github.com/jimmywarting/node-domexception) - MIT
|
||||
[node-fetch@2.7.0](https://github.com/bitinn/node-fetch) - MIT
|
||||
[node-int64@0.4.0](https://github.com/broofa/node-int64) - MIT
|
||||
[node-releases@2.0.14](https://github.com/chicoxyzzy/node-releases) - MIT
|
||||
[normalize-path@3.0.0](https://github.com/jonschlinkert/normalize-path) - MIT
|
||||
[npm-run-path@4.0.1](https://github.com/sindresorhus/npm-run-path) - MIT
|
||||
[obliterator@1.6.1](https://github.com/yomguithereal/obliterator) - MIT
|
||||
[once@1.4.0](https://github.com/isaacs/once) - ISC
|
||||
[onetime@5.1.2](https://github.com/sindresorhus/onetime) - MIT
|
||||
[onnxruntime-common@1.19.2](https://github.com/Microsoft/onnxruntime) - MIT
|
||||
[onnxruntime-common@1.20.0-dev.20241016-2b8fc5529b](https://github.com/Microsoft/onnxruntime) - MIT
|
||||
[onnxruntime-node@1.19.2](https://github.com/Microsoft/onnxruntime) - MIT
|
||||
[onnxruntime-web@1.21.0-dev.20241024-d9ca84ef96](https://github.com/Microsoft/onnxruntime) - MIT
|
||||
[openai@4.29.2](https://github.com/openai/openai-node) - Apache-2.0
|
||||
[optionator@0.9.3](https://github.com/gkz/optionator) - MIT
|
||||
[p-limit@2.3.0](https://github.com/sindresorhus/p-limit) - MIT
|
||||
[p-limit@3.1.0](https://github.com/sindresorhus/p-limit) - MIT
|
||||
[p-locate@4.1.0](https://github.com/sindresorhus/p-locate) - MIT
|
||||
[p-locate@5.0.0](https://github.com/sindresorhus/p-locate) - MIT
|
||||
[p-try@2.2.0](https://github.com/sindresorhus/p-try) - MIT
|
||||
[package-json-from-dist@1.0.1](https://github.com/isaacs/package-json-from-dist) - BlueOak-1.0.0
|
||||
[parent-module@1.0.1](https://github.com/sindresorhus/parent-module) - MIT
|
||||
[parse-json@5.2.0](https://github.com/sindresorhus/parse-json) - MIT
|
||||
[path-exists@4.0.0](https://github.com/sindresorhus/path-exists) - MIT
|
||||
[path-is-absolute@1.0.1](https://github.com/sindresorhus/path-is-absolute) - MIT
|
||||
[path-key@3.1.1](https://github.com/sindresorhus/path-key) - MIT
|
||||
[path-parse@1.0.7](https://github.com/jbgutierrez/path-parse) - MIT
|
||||
[path-scurry@1.11.1](https://github.com/isaacs/path-scurry) - BlueOak-1.0.0
|
||||
[path-type@4.0.0](https://github.com/sindresorhus/path-type) - MIT
|
||||
[picocolors@1.0.0](https://github.com/alexeyraspopov/picocolors) - ISC
|
||||
[picomatch@2.3.1](https://github.com/micromatch/picomatch) - MIT
|
||||
[pirates@4.0.6](https://github.com/danez/pirates) - MIT
|
||||
[pkg-dir@4.2.0](https://github.com/sindresorhus/pkg-dir) - MIT
|
||||
[platform@1.3.6](https://github.com/bestiejs/platform.js) - MIT
|
||||
[prelude-ls@1.2.1](https://github.com/gkz/prelude-ls) - MIT
|
||||
[pretty-format@29.7.0](https://github.com/jestjs/jest) - MIT
|
||||
[prompts@2.4.2](https://github.com/terkelg/prompts) - MIT
|
||||
[protobufjs@7.4.0](https://github.com/protobufjs/protobuf.js) - BSD-3-Clause
|
||||
[proxy-from-env@1.1.0](https://github.com/Rob--W/proxy-from-env) - MIT
|
||||
[punycode.js@2.3.1](https://github.com/mathiasbynens/punycode.js) - MIT
|
||||
[punycode@2.3.1](https://github.com/mathiasbynens/punycode.js) - MIT
|
||||
[pure-rand@6.0.4](https://github.com/dubzzz/pure-rand) - MIT
|
||||
[queue-microtask@1.2.3](https://github.com/feross/queue-microtask) - MIT
|
||||
[react-is@18.2.0](https://github.com/facebook/react) - MIT
|
||||
[rechoir@0.6.2](https://github.com/tkellen/node-rechoir) - MIT
|
||||
[reflect-metadata@0.2.2](https://github.com/rbuckton/reflect-metadata) - Apache-2.0
|
||||
[require-directory@2.1.1](https://github.com/troygoode/node-require-directory) - MIT
|
||||
[resolve-cwd@3.0.0](https://github.com/sindresorhus/resolve-cwd) - MIT
|
||||
[resolve-from@4.0.0](https://github.com/sindresorhus/resolve-from) - MIT
|
||||
[resolve-from@5.0.0](https://github.com/sindresorhus/resolve-from) - MIT
|
||||
[resolve.exports@2.0.2](https://github.com/lukeed/resolve.exports) - MIT
|
||||
[resolve@1.22.8](https://github.com/browserify/resolve) - MIT
|
||||
[reusify@1.0.4](https://github.com/mcollina/reusify) - MIT
|
||||
[rimraf@3.0.2](https://github.com/isaacs/rimraf) - ISC
|
||||
[rimraf@5.0.10](https://github.com/isaacs/rimraf) - ISC
|
||||
[run-parallel@1.2.0](https://github.com/feross/run-parallel) - MIT
|
||||
[semver@6.3.1](https://github.com/npm/node-semver) - ISC
|
||||
[semver@7.6.3](https://github.com/npm/node-semver) - ISC
|
||||
[sharp@0.33.5](https://github.com/lovell/sharp) - Apache-2.0
|
||||
[shebang-command@2.0.0](https://github.com/kevva/shebang-command) - MIT
|
||||
[shebang-regex@3.0.0](https://github.com/sindresorhus/shebang-regex) - MIT
|
||||
[shelljs@0.8.5](https://github.com/shelljs/shelljs) - BSD-3-Clause
|
||||
[shiki@1.10.3](https://github.com/shikijs/shiki) - MIT
|
||||
[shx@0.3.4](https://github.com/shelljs/shx) - MIT
|
||||
[signal-exit@3.0.7](https://github.com/tapjs/signal-exit) - ISC
|
||||
[signal-exit@4.1.0](https://github.com/tapjs/signal-exit) - ISC
|
||||
[simple-swizzle@0.2.2](https://github.com/qix-/node-simple-swizzle) - MIT
|
||||
[sisteransi@1.0.5](https://github.com/terkelg/sisteransi) - MIT
|
||||
[slash@3.0.0](https://github.com/sindresorhus/slash) - MIT
|
||||
[source-map-support@0.5.13](https://github.com/evanw/node-source-map-support) - MIT
|
||||
[source-map@0.6.1](https://github.com/mozilla/source-map) - BSD-3-Clause
|
||||
[sprintf-js@1.0.3](https://github.com/alexei/sprintf.js) - BSD-3-Clause
|
||||
[stack-utils@2.0.6](https://github.com/tapjs/stack-utils) - MIT
|
||||
[stream-read-all@3.0.1](https://github.com/75lb/stream-read-all) - MIT
|
||||
[string-length@4.0.2](https://github.com/sindresorhus/string-length) - MIT
|
||||
[string-width@4.2.3](https://github.com/sindresorhus/string-width) - MIT
|
||||
[string-width@5.1.2](https://github.com/sindresorhus/string-width) - MIT
|
||||
[strip-ansi@6.0.1](https://github.com/chalk/strip-ansi) - MIT
|
||||
[strip-ansi@7.1.0](https://github.com/chalk/strip-ansi) - MIT
|
||||
[strip-bom@4.0.0](https://github.com/sindresorhus/strip-bom) - MIT
|
||||
[strip-final-newline@2.0.0](https://github.com/sindresorhus/strip-final-newline) - MIT
|
||||
[strip-json-comments@3.1.1](https://github.com/sindresorhus/strip-json-comments) - MIT
|
||||
[strnum@1.0.5](https://github.com/NaturalIntelligence/strnum) - MIT
|
||||
[supports-color@7.2.0](https://github.com/chalk/supports-color) - MIT
|
||||
[supports-color@8.1.1](https://github.com/chalk/supports-color) - MIT
|
||||
[supports-preserve-symlinks-flag@1.0.0](https://github.com/inspect-js/node-supports-preserve-symlinks-flag) - MIT
|
||||
[table-layout@3.0.2](https://github.com/75lb/table-layout) - MIT
|
||||
[tar@7.4.3](https://github.com/isaacs/node-tar) - ISC
|
||||
[test-exclude@6.0.0](https://github.com/istanbuljs/test-exclude) - ISC
|
||||
[text-table@0.2.0](https://github.com/substack/text-table) - MIT
|
||||
[tmp@0.2.3](https://github.com/raszi/node-tmp) - MIT
|
||||
[tmpl@1.0.5](https://github.com/daaku/nodejs-tmpl) - BSD-3-Clause
|
||||
[to-regex-range@5.0.1](https://github.com/micromatch/to-regex-range) - MIT
|
||||
[tr46@0.0.3](https://github.com/Sebmaster/tr46.js) - MIT
|
||||
[ts-api-utils@1.0.3](https://github.com/JoshuaKGoldberg/ts-api-utils) - MIT
|
||||
[ts-jest@29.1.2](https://github.com/kulshekhar/ts-jest) - MIT
|
||||
[tslib@1.14.1](https://github.com/Microsoft/tslib) - 0BSD
|
||||
[tslib@2.6.2](https://github.com/Microsoft/tslib) - 0BSD
|
||||
[type-check@0.4.0](https://github.com/gkz/type-check) - MIT
|
||||
[type-detect@4.0.8](https://github.com/chaijs/type-detect) - MIT
|
||||
[type-fest@0.20.2](https://github.com/sindresorhus/type-fest) - (MIT OR CC0-1.0)
|
||||
[type-fest@0.21.3](https://github.com/sindresorhus/type-fest) - (MIT OR CC0-1.0)
|
||||
[typedoc-plugin-markdown@4.2.1](https://github.com/typedoc2md/typedoc-plugin-markdown) - MIT
|
||||
[typedoc@0.26.4](https://github.com/TypeStrong/TypeDoc) - Apache-2.0
|
||||
[typescript-eslint@7.1.0](https://github.com/typescript-eslint/typescript-eslint) - MIT
|
||||
[typescript@5.5.4](https://github.com/Microsoft/TypeScript) - Apache-2.0
|
||||
[typical@4.0.0](https://github.com/75lb/typical) - MIT
|
||||
[typical@7.1.1](https://github.com/75lb/typical) - MIT
|
||||
[uc.micro@2.1.0](https://github.com/markdown-it/uc.micro) - MIT
|
||||
[undici-types@5.26.5](https://github.com/nodejs/undici) - MIT
|
||||
[undici-types@6.19.8](https://github.com/nodejs/undici) - MIT
|
||||
[update-browserslist-db@1.0.13](https://github.com/browserslist/update-db) - MIT
|
||||
[uri-js@4.4.1](https://github.com/garycourt/uri-js) - BSD-2-Clause
|
||||
[uuid@9.0.1](https://github.com/uuidjs/uuid) - MIT
|
||||
[v8-to-istanbul@9.2.0](https://github.com/istanbuljs/v8-to-istanbul) - ISC
|
||||
[walker@1.0.8](https://github.com/daaku/nodejs-walker) - Apache-2.0
|
||||
[web-streams-polyfill@3.3.3](https://github.com/MattiasBuelens/web-streams-polyfill) - MIT
|
||||
[web-streams-polyfill@4.0.0-beta.3](https://github.com/MattiasBuelens/web-streams-polyfill) - MIT
|
||||
[webidl-conversions@3.0.1](https://github.com/jsdom/webidl-conversions) - BSD-2-Clause
|
||||
[whatwg-url@5.0.0](https://github.com/jsdom/whatwg-url) - MIT
|
||||
[which@2.0.2](https://github.com/isaacs/node-which) - ISC
|
||||
[wordwrapjs@5.1.0](https://github.com/75lb/wordwrapjs) - MIT
|
||||
[wrap-ansi@7.0.0](https://github.com/chalk/wrap-ansi) - MIT
|
||||
[wrap-ansi@8.1.0](https://github.com/chalk/wrap-ansi) - MIT
|
||||
[wrappy@1.0.2](https://github.com/npm/wrappy) - ISC
|
||||
[write-file-atomic@4.0.2](https://github.com/npm/write-file-atomic) - ISC
|
||||
[y18n@5.0.8](https://github.com/yargs/y18n) - ISC
|
||||
[yallist@3.1.1](https://github.com/isaacs/yallist) - ISC
|
||||
[yallist@5.0.0](https://github.com/isaacs/yallist) - BlueOak-1.0.0
|
||||
[yaml@2.4.5](https://github.com/eemeli/yaml) - ISC
|
||||
[yargs-parser@21.1.1](https://github.com/yargs/yargs-parser) - ISC
|
||||
[yargs@17.7.2](https://github.com/yargs/yargs) - MIT
|
||||
[yocto-queue@0.1.0](https://github.com/sindresorhus/yocto-queue) - MIT
|
||||
14607
nodejs/RUST_THIRD_PARTY_LICENSES.html
Normal file
14607
nodejs/RUST_THIRD_PARTY_LICENSES.html
Normal file
File diff suppressed because it is too large
Load Diff
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-darwin-arm64",
|
||||
"version": "0.26.1-beta.0",
|
||||
"version": "0.27.0-beta.0",
|
||||
"os": ["darwin"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.darwin-arm64.node",
|
||||
@@ -8,5 +8,9 @@
|
||||
"license": "Apache-2.0",
|
||||
"engines": {
|
||||
"node": ">= 18"
|
||||
},
|
||||
"repository": {
|
||||
"type": "git",
|
||||
"url": "https://github.com/lancedb/lancedb"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-arm64-gnu",
|
||||
"version": "0.26.1-beta.0",
|
||||
"version": "0.27.0-beta.0",
|
||||
"os": ["linux"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.linux-arm64-gnu.node",
|
||||
@@ -9,5 +9,9 @@
|
||||
"engines": {
|
||||
"node": ">= 18"
|
||||
},
|
||||
"libc": ["glibc"]
|
||||
"libc": ["glibc"],
|
||||
"repository": {
|
||||
"type": "git",
|
||||
"url": "https://github.com/lancedb/lancedb"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-arm64-musl",
|
||||
"version": "0.26.1-beta.0",
|
||||
"version": "0.27.0-beta.0",
|
||||
"os": ["linux"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.linux-arm64-musl.node",
|
||||
@@ -9,5 +9,9 @@
|
||||
"engines": {
|
||||
"node": ">= 18"
|
||||
},
|
||||
"libc": ["musl"]
|
||||
"libc": ["musl"],
|
||||
"repository": {
|
||||
"type": "git",
|
||||
"url": "https://github.com/lancedb/lancedb"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-x64-gnu",
|
||||
"version": "0.26.1-beta.0",
|
||||
"version": "0.27.0-beta.0",
|
||||
"os": ["linux"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.linux-x64-gnu.node",
|
||||
@@ -9,5 +9,9 @@
|
||||
"engines": {
|
||||
"node": ">= 18"
|
||||
},
|
||||
"libc": ["glibc"]
|
||||
"libc": ["glibc"],
|
||||
"repository": {
|
||||
"type": "git",
|
||||
"url": "https://github.com/lancedb/lancedb"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-x64-musl",
|
||||
"version": "0.26.1-beta.0",
|
||||
"version": "0.27.0-beta.0",
|
||||
"os": ["linux"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.linux-x64-musl.node",
|
||||
@@ -9,5 +9,9 @@
|
||||
"engines": {
|
||||
"node": ">= 18"
|
||||
},
|
||||
"libc": ["musl"]
|
||||
"libc": ["musl"],
|
||||
"repository": {
|
||||
"type": "git",
|
||||
"url": "https://github.com/lancedb/lancedb"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-win32-arm64-msvc",
|
||||
"version": "0.26.1-beta.0",
|
||||
"version": "0.27.0-beta.0",
|
||||
"os": [
|
||||
"win32"
|
||||
],
|
||||
@@ -14,5 +14,9 @@
|
||||
"license": "Apache-2.0",
|
||||
"engines": {
|
||||
"node": ">= 18"
|
||||
},
|
||||
"repository": {
|
||||
"type": "git",
|
||||
"url": "https://github.com/lancedb/lancedb"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-win32-x64-msvc",
|
||||
"version": "0.26.1-beta.0",
|
||||
"version": "0.27.0-beta.0",
|
||||
"os": ["win32"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.win32-x64-msvc.node",
|
||||
@@ -8,5 +8,9 @@
|
||||
"license": "Apache-2.0",
|
||||
"engines": {
|
||||
"node": ">= 18"
|
||||
},
|
||||
"repository": {
|
||||
"type": "git",
|
||||
"url": "https://github.com/lancedb/lancedb"
|
||||
}
|
||||
}
|
||||
|
||||
4
nodejs/package-lock.json
generated
4
nodejs/package-lock.json
generated
@@ -1,12 +1,12 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb",
|
||||
"version": "0.26.0",
|
||||
"version": "0.26.2",
|
||||
"lockfileVersion": 3,
|
||||
"requires": true,
|
||||
"packages": {
|
||||
"": {
|
||||
"name": "@lancedb/lancedb",
|
||||
"version": "0.26.0",
|
||||
"version": "0.26.2",
|
||||
"cpu": [
|
||||
"x64",
|
||||
"arm64"
|
||||
|
||||
@@ -11,7 +11,7 @@
|
||||
"ann"
|
||||
],
|
||||
"private": false,
|
||||
"version": "0.26.1-beta.0",
|
||||
"version": "0.27.0-beta.0",
|
||||
"main": "dist/index.js",
|
||||
"exports": {
|
||||
".": "./dist/index.js",
|
||||
@@ -36,6 +36,10 @@
|
||||
}
|
||||
},
|
||||
"license": "Apache-2.0",
|
||||
"repository": {
|
||||
"type": "git",
|
||||
"url": "https://github.com/lancedb/lancedb"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@aws-sdk/client-dynamodb": "^3.33.0",
|
||||
"@aws-sdk/client-kms": "^3.33.0",
|
||||
|
||||
@@ -13,6 +13,7 @@ use crate::header::JsHeaderProvider;
|
||||
use crate::table::Table;
|
||||
use crate::ConnectionOptions;
|
||||
use lancedb::connection::{ConnectBuilder, Connection as LanceDBConnection};
|
||||
|
||||
use lancedb::ipc::{ipc_file_to_batches, ipc_file_to_schema};
|
||||
|
||||
#[napi]
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
[tool.bumpversion]
|
||||
current_version = "0.29.1"
|
||||
current_version = "0.30.0-beta.0"
|
||||
parse = """(?x)
|
||||
(?P<major>0|[1-9]\\d*)\\.
|
||||
(?P<minor>0|[1-9]\\d*)\\.
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "lancedb-python"
|
||||
version = "0.29.1"
|
||||
version = "0.30.0-beta.0"
|
||||
edition.workspace = true
|
||||
description = "Python bindings for LanceDB"
|
||||
license.workspace = true
|
||||
|
||||
206
python/PYTHON_THIRD_PARTY_LICENSES.md
Normal file
206
python/PYTHON_THIRD_PARTY_LICENSES.md
Normal file
@@ -0,0 +1,206 @@
|
||||
| Name | Version | License | URL |
|
||||
|--------------------------------|-----------------|--------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------|
|
||||
| InstructorEmbedding | 1.0.1 | Apache License 2.0 | https://github.com/HKUNLP/instructor-embedding |
|
||||
| Jinja2 | 3.1.6 | BSD License | https://github.com/pallets/jinja/ |
|
||||
| Markdown | 3.10.2 | BSD-3-Clause | https://Python-Markdown.github.io/ |
|
||||
| MarkupSafe | 3.0.3 | BSD-3-Clause | https://github.com/pallets/markupsafe/ |
|
||||
| PyJWT | 2.11.0 | MIT | https://github.com/jpadilla/pyjwt |
|
||||
| PyYAML | 6.0.3 | MIT License | https://pyyaml.org/ |
|
||||
| Pygments | 2.19.2 | BSD License | https://pygments.org |
|
||||
| accelerate | 1.12.0 | Apache Software License | https://github.com/huggingface/accelerate |
|
||||
| adlfs | 2026.2.0 | BSD License | UNKNOWN |
|
||||
| aiohappyeyeballs | 2.6.1 | Python Software Foundation License | https://github.com/aio-libs/aiohappyeyeballs |
|
||||
| aiohttp | 3.13.3 | Apache-2.0 AND MIT | https://github.com/aio-libs/aiohttp |
|
||||
| aiosignal | 1.4.0 | Apache Software License | https://github.com/aio-libs/aiosignal |
|
||||
| annotated-types | 0.7.0 | MIT License | https://github.com/annotated-types/annotated-types |
|
||||
| anyio | 4.12.1 | MIT | https://anyio.readthedocs.io/en/stable/versionhistory.html |
|
||||
| appnope | 0.1.4 | BSD License | http://github.com/minrk/appnope |
|
||||
| asttokens | 3.0.1 | Apache 2.0 | https://github.com/gristlabs/asttokens |
|
||||
| attrs | 25.4.0 | MIT | https://www.attrs.org/en/stable/changelog.html |
|
||||
| awscli | 1.44.35 | Apache Software License | http://aws.amazon.com/cli/ |
|
||||
| azure-core | 1.38.0 | MIT License | https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/core/azure-core |
|
||||
| azure-datalake-store | 0.0.53 | MIT License | https://github.com/Azure/azure-data-lake-store-python |
|
||||
| azure-identity | 1.25.1 | MIT | https://github.com/Azure/azure-sdk-for-python |
|
||||
| azure-storage-blob | 12.28.0 | MIT License | https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/storage/azure-storage-blob |
|
||||
| babel | 2.18.0 | BSD License | https://babel.pocoo.org/ |
|
||||
| backrefs | 6.1 | MIT | https://github.com/facelessuser/backrefs |
|
||||
| beautifulsoup4 | 4.14.3 | MIT License | https://www.crummy.com/software/BeautifulSoup/bs4/ |
|
||||
| bleach | 6.3.0 | Apache Software License | https://github.com/mozilla/bleach |
|
||||
| boto3 | 1.42.45 | Apache-2.0 | https://github.com/boto/boto3 |
|
||||
| botocore | 1.42.45 | Apache-2.0 | https://github.com/boto/botocore |
|
||||
| cachetools | 7.0.0 | MIT | https://github.com/tkem/cachetools/ |
|
||||
| certifi | 2026.1.4 | Mozilla Public License 2.0 (MPL 2.0) | https://github.com/certifi/python-certifi |
|
||||
| cffi | 2.0.0 | MIT | https://cffi.readthedocs.io/en/latest/whatsnew.html |
|
||||
| cfgv | 3.5.0 | MIT | https://github.com/asottile/cfgv |
|
||||
| charset-normalizer | 3.4.4 | MIT | https://github.com/jawah/charset_normalizer/blob/master/CHANGELOG.md |
|
||||
| click | 8.3.1 | BSD-3-Clause | https://github.com/pallets/click/ |
|
||||
| cohere | 5.20.4 | MIT License | https://github.com/cohere-ai/cohere-python |
|
||||
| colorama | 0.4.6 | BSD License | https://github.com/tartley/colorama |
|
||||
| colpali_engine | 0.3.13 | MIT License | https://github.com/illuin-tech/colpali |
|
||||
| comm | 0.2.3 | BSD License | https://github.com/ipython/comm |
|
||||
| cryptography | 46.0.4 | Apache-2.0 OR BSD-3-Clause | https://github.com/pyca/cryptography |
|
||||
| datafusion | 51.0.0 | Apache Software License | https://datafusion.apache.org/python |
|
||||
| debugpy | 1.8.20 | MIT License | https://aka.ms/debugpy |
|
||||
| decorator | 5.2.1 | BSD License | UNKNOWN |
|
||||
| defusedxml | 0.7.1 | Python Software Foundation License | https://github.com/tiran/defusedxml |
|
||||
| deprecation | 2.1.0 | Apache Software License | http://deprecation.readthedocs.io/ |
|
||||
| distlib | 0.4.0 | Python Software Foundation License | https://github.com/pypa/distlib |
|
||||
| distro | 1.9.0 | Apache Software License | https://github.com/python-distro/distro |
|
||||
| docutils | 0.19 | BSD License; GNU General Public License (GPL); Public Domain; Python Software Foundation License | https://docutils.sourceforge.io/ |
|
||||
| duckdb | 1.4.4 | MIT License | https://github.com/duckdb/duckdb-python |
|
||||
| executing | 2.2.1 | MIT License | https://github.com/alexmojaki/executing |
|
||||
| fastavro | 1.12.1 | MIT | https://github.com/fastavro/fastavro |
|
||||
| fastjsonschema | 2.21.2 | BSD License | https://github.com/horejsek/python-fastjsonschema |
|
||||
| filelock | 3.20.3 | Unlicense | https://github.com/tox-dev/py-filelock |
|
||||
| frozenlist | 1.8.0 | Apache-2.0 | https://github.com/aio-libs/frozenlist |
|
||||
| fsspec | 2026.2.0 | BSD-3-Clause | https://github.com/fsspec/filesystem_spec |
|
||||
| ftfy | 6.3.1 | Apache-2.0 | https://ftfy.readthedocs.io/en/latest/ |
|
||||
| ghp-import | 2.1.0 | Apache Software License | https://github.com/c-w/ghp-import |
|
||||
| google-ai-generativelanguage | 0.6.15 | Apache Software License | https://github.com/googleapis/google-cloud-python/tree/main/packages/google-ai-generativelanguage |
|
||||
| google-api-core | 2.25.2 | Apache Software License | https://github.com/googleapis/python-api-core |
|
||||
| google-api-python-client | 2.189.0 | Apache Software License | https://github.com/googleapis/google-api-python-client/ |
|
||||
| google-auth | 2.48.0 | Apache Software License | https://github.com/googleapis/google-auth-library-python |
|
||||
| google-auth-httplib2 | 0.3.0 | Apache Software License | https://github.com/GoogleCloudPlatform/google-auth-library-python-httplib2 |
|
||||
| google-generativeai | 0.8.6 | Apache Software License | https://github.com/google/generative-ai-python |
|
||||
| googleapis-common-protos | 1.72.0 | Apache Software License | https://github.com/googleapis/google-cloud-python/tree/main/packages/googleapis-common-protos |
|
||||
| griffe | 2.0.0 | ISC | https://mkdocstrings.github.io/griffe |
|
||||
| griffecli | 2.0.0 | ISC | UNKNOWN |
|
||||
| griffelib | 2.0.0 | ISC | UNKNOWN |
|
||||
| grpcio | 1.78.0 | Apache-2.0 | https://grpc.io |
|
||||
| grpcio-status | 1.71.2 | Apache Software License | https://grpc.io |
|
||||
| h11 | 0.16.0 | MIT License | https://github.com/python-hyper/h11 |
|
||||
| hf-xet | 1.2.0 | Apache-2.0 | https://github.com/huggingface/xet-core |
|
||||
| httpcore | 1.0.9 | BSD-3-Clause | https://www.encode.io/httpcore/ |
|
||||
| httplib2 | 0.31.2 | MIT License | https://github.com/httplib2/httplib2 |
|
||||
| httpx | 0.28.1 | BSD License | https://github.com/encode/httpx |
|
||||
| huggingface_hub | 0.36.2 | Apache Software License | https://github.com/huggingface/huggingface_hub |
|
||||
| ibm-cos-sdk | 2.14.3 | Apache Software License | https://github.com/ibm/ibm-cos-sdk-python |
|
||||
| ibm-cos-sdk-core | 2.14.3 | Apache Software License | https://github.com/ibm/ibm-cos-sdk-python-core |
|
||||
| ibm-cos-sdk-s3transfer | 2.14.3 | Apache Software License | https://github.com/IBM/ibm-cos-sdk-python-s3transfer |
|
||||
| ibm_watsonx_ai | 1.5.1 | BSD License | https://ibm.github.io/watsonx-ai-python-sdk/changelog.html |
|
||||
| identify | 2.6.16 | MIT | https://github.com/pre-commit/identify |
|
||||
| idna | 3.11 | BSD-3-Clause | https://github.com/kjd/idna |
|
||||
| iniconfig | 2.3.0 | MIT | https://github.com/pytest-dev/iniconfig |
|
||||
| ipykernel | 6.31.0 | BSD-3-Clause | https://ipython.org |
|
||||
| ipython | 9.10.0 | BSD-3-Clause | https://ipython.org |
|
||||
| ipython_pygments_lexers | 1.1.1 | BSD License | https://github.com/ipython/ipython-pygments-lexers |
|
||||
| isodate | 0.7.2 | BSD License | https://github.com/gweis/isodate/ |
|
||||
| jedi | 0.19.2 | MIT License | https://github.com/davidhalter/jedi |
|
||||
| jiter | 0.13.0 | MIT License | https://github.com/pydantic/jiter/ |
|
||||
| jmespath | 1.0.1 | MIT License | https://github.com/jmespath/jmespath.py |
|
||||
| joblib | 1.5.3 | BSD-3-Clause | https://joblib.readthedocs.io |
|
||||
| jsonschema | 4.26.0 | MIT | https://github.com/python-jsonschema/jsonschema |
|
||||
| jsonschema-specifications | 2025.9.1 | MIT | https://github.com/python-jsonschema/jsonschema-specifications |
|
||||
| jupyter_client | 8.8.0 | BSD License | https://jupyter.org |
|
||||
| jupyter_core | 5.9.1 | BSD-3-Clause | https://jupyter.org |
|
||||
| jupyterlab_pygments | 0.3.0 | BSD License | https://github.com/jupyterlab/jupyterlab_pygments |
|
||||
| jupytext | 1.19.1 | MIT License | https://github.com/mwouts/jupytext |
|
||||
| lance-namespace | 0.4.5 | Apache-2.0 | https://github.com/lance-format/lance-namespace |
|
||||
| lance-namespace-urllib3-client | 0.4.5 | Apache-2.0 | https://github.com/lance-format/lance-namespace |
|
||||
| lancedb | 0.29.2 | Apache Software License | https://github.com/lancedb/lancedb |
|
||||
| lomond | 0.3.3 | BSD License | https://github.com/wildfoundry/dataplicity-lomond |
|
||||
| markdown-it-py | 4.0.0 | MIT License | https://github.com/executablebooks/markdown-it-py |
|
||||
| matplotlib-inline | 0.2.1 | UNKNOWN | https://github.com/ipython/matplotlib-inline |
|
||||
| mdit-py-plugins | 0.5.0 | MIT License | https://github.com/executablebooks/mdit-py-plugins |
|
||||
| mdurl | 0.1.2 | MIT License | https://github.com/executablebooks/mdurl |
|
||||
| mergedeep | 1.3.4 | MIT License | https://github.com/clarketm/mergedeep |
|
||||
| mistune | 3.2.0 | BSD License | https://github.com/lepture/mistune |
|
||||
| mkdocs | 1.6.1 | BSD-2-Clause | https://github.com/mkdocs/mkdocs |
|
||||
| mkdocs-autorefs | 1.4.3 | ISC | https://mkdocstrings.github.io/autorefs |
|
||||
| mkdocs-get-deps | 0.2.0 | MIT | https://github.com/mkdocs/get-deps |
|
||||
| mkdocs-jupyter | 0.25.1 | Apache-2.0 | https://github.com/danielfrg/mkdocs-jupyter |
|
||||
| mkdocs-material | 9.7.1 | MIT | https://github.com/squidfunk/mkdocs-material |
|
||||
| mkdocs-material-extensions | 1.3.1 | MIT | https://github.com/facelessuser/mkdocs-material-extensions |
|
||||
| mkdocstrings | 1.0.3 | ISC | https://mkdocstrings.github.io |
|
||||
| mkdocstrings-python | 2.0.2 | ISC | https://mkdocstrings.github.io/python |
|
||||
| mpmath | 1.3.0 | BSD License | http://mpmath.org/ |
|
||||
| msal | 1.34.0 | MIT License | https://github.com/AzureAD/microsoft-authentication-library-for-python |
|
||||
| msal-extensions | 1.3.1 | MIT License | https://github.com/AzureAD/microsoft-authentication-extensions-for-python/releases |
|
||||
| multidict | 6.7.1 | Apache License 2.0 | https://github.com/aio-libs/multidict |
|
||||
| nbclient | 0.10.4 | BSD License | https://jupyter.org |
|
||||
| nbconvert | 7.17.0 | BSD License | https://jupyter.org |
|
||||
| nbformat | 5.10.4 | BSD License | https://jupyter.org |
|
||||
| nest-asyncio | 1.6.0 | BSD License | https://github.com/erdewit/nest_asyncio |
|
||||
| networkx | 3.6.1 | BSD-3-Clause | https://networkx.org/ |
|
||||
| nodeenv | 1.10.0 | BSD License | https://github.com/ekalinin/nodeenv |
|
||||
| numpy | 2.4.2 | BSD-3-Clause AND 0BSD AND MIT AND Zlib AND CC0-1.0 | https://numpy.org |
|
||||
| ollama | 0.6.1 | MIT | https://ollama.com |
|
||||
| open_clip_torch | 3.2.0 | MIT License | https://github.com/mlfoundations/open_clip |
|
||||
| openai | 2.18.0 | Apache Software License | https://github.com/openai/openai-python |
|
||||
| packaging | 26.0 | Apache-2.0 OR BSD-2-Clause | https://github.com/pypa/packaging |
|
||||
| paginate | 0.5.7 | MIT License | https://github.com/Signum/paginate |
|
||||
| pandas | 2.3.3 | BSD License | https://pandas.pydata.org |
|
||||
| pandocfilters | 1.5.1 | BSD License | http://github.com/jgm/pandocfilters |
|
||||
| parso | 0.8.6 | MIT License | https://github.com/davidhalter/parso |
|
||||
| pathspec | 1.0.4 | Mozilla Public License 2.0 (MPL 2.0) | UNKNOWN |
|
||||
| peft | 0.17.1 | Apache Software License | https://github.com/huggingface/peft |
|
||||
| pexpect | 4.9.0 | ISC License (ISCL) | https://pexpect.readthedocs.io/ |
|
||||
| pillow | 12.1.0 | MIT-CMU | https://python-pillow.github.io |
|
||||
| platformdirs | 4.5.1 | MIT | https://github.com/tox-dev/platformdirs |
|
||||
| pluggy | 1.6.0 | MIT License | UNKNOWN |
|
||||
| polars | 1.3.0 | MIT License | https://www.pola.rs/ |
|
||||
| pre_commit | 4.5.1 | MIT | https://github.com/pre-commit/pre-commit |
|
||||
| prompt_toolkit | 3.0.52 | BSD License | https://github.com/prompt-toolkit/python-prompt-toolkit |
|
||||
| propcache | 0.4.1 | Apache Software License | https://github.com/aio-libs/propcache |
|
||||
| proto-plus | 1.27.1 | Apache Software License | https://github.com/googleapis/proto-plus-python |
|
||||
| protobuf | 5.29.6 | 3-Clause BSD License | https://developers.google.com/protocol-buffers/ |
|
||||
| psutil | 7.2.2 | BSD-3-Clause | https://github.com/giampaolo/psutil |
|
||||
| ptyprocess | 0.7.0 | ISC License (ISCL) | https://github.com/pexpect/ptyprocess |
|
||||
| pure_eval | 0.2.3 | MIT License | http://github.com/alexmojaki/pure_eval |
|
||||
| pyarrow | 23.0.0 | Apache-2.0 | https://arrow.apache.org/ |
|
||||
| pyarrow-stubs | 20.0.0.20251215 | BSD-2-Clause | https://github.com/zen-xu/pyarrow-stubs |
|
||||
| pyasn1 | 0.6.2 | BSD-2-Clause | https://github.com/pyasn1/pyasn1 |
|
||||
| pyasn1_modules | 0.4.2 | BSD License | https://github.com/pyasn1/pyasn1-modules |
|
||||
| pycparser | 3.0 | BSD-3-Clause | https://github.com/eliben/pycparser |
|
||||
| pydantic | 2.12.5 | MIT | https://github.com/pydantic/pydantic |
|
||||
| pydantic_core | 2.41.5 | MIT | https://github.com/pydantic/pydantic-core |
|
||||
| pylance | 2.0.0 | Apache Software License | UNKNOWN |
|
||||
| pymdown-extensions | 10.20.1 | MIT | https://github.com/facelessuser/pymdown-extensions |
|
||||
| pyparsing | 3.3.2 | MIT | https://github.com/pyparsing/pyparsing/ |
|
||||
| pyright | 1.1.408 | MIT | https://github.com/RobertCraigie/pyright-python |
|
||||
| pytest | 9.0.2 | MIT | https://docs.pytest.org/en/latest/ |
|
||||
| pytest-asyncio | 1.3.0 | Apache-2.0 | https://github.com/pytest-dev/pytest-asyncio |
|
||||
| pytest-mock | 3.15.1 | MIT License | https://github.com/pytest-dev/pytest-mock/ |
|
||||
| python-dateutil | 2.9.0.post0 | Apache Software License; BSD License | https://github.com/dateutil/dateutil |
|
||||
| pytz | 2025.2 | MIT License | http://pythonhosted.org/pytz |
|
||||
| pyyaml_env_tag | 1.1 | MIT | https://github.com/waylan/pyyaml-env-tag |
|
||||
| pyzmq | 27.1.0 | BSD License | https://pyzmq.readthedocs.org |
|
||||
| referencing | 0.37.0 | MIT | https://github.com/python-jsonschema/referencing |
|
||||
| regex | 2026.1.15 | Apache-2.0 AND CNRI-Python | https://github.com/mrabarnett/mrab-regex |
|
||||
| requests | 2.32.5 | Apache Software License | https://requests.readthedocs.io |
|
||||
| rpds-py | 0.30.0 | MIT | https://github.com/crate-py/rpds |
|
||||
| rsa | 4.7.2 | Apache Software License | https://stuvel.eu/rsa |
|
||||
| ruff | 0.15.0 | MIT License | https://docs.astral.sh/ruff |
|
||||
| s3transfer | 0.16.0 | Apache Software License | https://github.com/boto/s3transfer |
|
||||
| safetensors | 0.7.0 | Apache Software License | https://github.com/huggingface/safetensors |
|
||||
| scikit-learn | 1.8.0 | BSD-3-Clause | https://scikit-learn.org |
|
||||
| scipy | 1.17.0 | BSD License | https://scipy.org/ |
|
||||
| sentence-transformers | 5.2.2 | Apache Software License | https://www.SBERT.net |
|
||||
| sentencepiece | 0.2.1 | UNKNOWN | https://github.com/google/sentencepiece |
|
||||
| six | 1.17.0 | MIT License | https://github.com/benjaminp/six |
|
||||
| sniffio | 1.3.1 | Apache Software License; MIT License | https://github.com/python-trio/sniffio |
|
||||
| soupsieve | 2.8.3 | MIT | https://github.com/facelessuser/soupsieve |
|
||||
| stack-data | 0.6.3 | MIT License | http://github.com/alexmojaki/stack_data |
|
||||
| sympy | 1.14.0 | BSD License | https://sympy.org |
|
||||
| tabulate | 0.9.0 | MIT License | https://github.com/astanin/python-tabulate |
|
||||
| tantivy | 0.25.1 | UNKNOWN | UNKNOWN |
|
||||
| threadpoolctl | 3.6.0 | BSD License | https://github.com/joblib/threadpoolctl |
|
||||
| timm | 1.0.24 | Apache Software License | https://github.com/huggingface/pytorch-image-models |
|
||||
| tinycss2 | 1.4.0 | BSD License | https://www.courtbouillon.org/tinycss2 |
|
||||
| tokenizers | 0.22.2 | Apache Software License | https://github.com/huggingface/tokenizers |
|
||||
| torch | 2.8.0 | BSD License | https://pytorch.org/ |
|
||||
| torchvision | 0.23.0 | BSD | https://github.com/pytorch/vision |
|
||||
| tornado | 6.5.4 | Apache Software License | http://www.tornadoweb.org/ |
|
||||
| tqdm | 4.67.3 | MPL-2.0 AND MIT | https://tqdm.github.io |
|
||||
| traitlets | 5.14.3 | BSD License | https://github.com/ipython/traitlets |
|
||||
| transformers | 4.57.6 | Apache Software License | https://github.com/huggingface/transformers |
|
||||
| types-requests | 2.32.4.20260107 | Apache-2.0 | https://github.com/python/typeshed |
|
||||
| typing-inspection | 0.4.2 | MIT | https://github.com/pydantic/typing-inspection |
|
||||
| typing_extensions | 4.15.0 | PSF-2.0 | https://github.com/python/typing_extensions |
|
||||
| tzdata | 2025.3 | Apache-2.0 | https://github.com/python/tzdata |
|
||||
| uritemplate | 4.2.0 | BSD 3-Clause OR Apache-2.0 | https://uritemplate.readthedocs.org |
|
||||
| urllib3 | 2.6.3 | MIT | https://github.com/urllib3/urllib3/blob/main/CHANGES.rst |
|
||||
| virtualenv | 20.36.1 | MIT | https://github.com/pypa/virtualenv |
|
||||
| watchdog | 6.0.0 | Apache Software License | https://github.com/gorakhargosh/watchdog |
|
||||
| webencodings | 0.5.1 | BSD License | https://github.com/SimonSapin/python-webencodings |
|
||||
| yarl | 1.22.0 | Apache Software License | https://github.com/aio-libs/yarl |
|
||||
14687
python/RUST_THIRD_PARTY_LICENSES.html
Normal file
14687
python/RUST_THIRD_PARTY_LICENSES.html
Normal file
File diff suppressed because it is too large
Load Diff
@@ -9,7 +9,7 @@ import json
|
||||
from ._lancedb import async_permutation_builder, PermutationReader
|
||||
from .table import LanceTable
|
||||
from .background_loop import LOOP
|
||||
from .util import batch_to_tensor
|
||||
from .util import batch_to_tensor, batch_to_tensor_rows
|
||||
from typing import Any, Callable, Iterator, Literal, Optional, TYPE_CHECKING, Union
|
||||
|
||||
if TYPE_CHECKING:
|
||||
@@ -333,7 +333,11 @@ class Transforms:
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def arrow2python(batch: pa.RecordBatch) -> dict[str, list[Any]]:
|
||||
def arrow2python(batch: pa.RecordBatch) -> list[dict[str, Any]]:
|
||||
return batch.to_pylist()
|
||||
|
||||
@staticmethod
|
||||
def arrow2pythoncol(batch: pa.RecordBatch) -> dict[str, list[Any]]:
|
||||
return batch.to_pydict()
|
||||
|
||||
@staticmethod
|
||||
@@ -687,7 +691,17 @@ class Permutation:
|
||||
return
|
||||
|
||||
def with_format(
|
||||
self, format: Literal["numpy", "python", "pandas", "arrow", "torch", "polars"]
|
||||
self,
|
||||
format: Literal[
|
||||
"numpy",
|
||||
"python",
|
||||
"python_col",
|
||||
"pandas",
|
||||
"arrow",
|
||||
"torch",
|
||||
"torch_col",
|
||||
"polars",
|
||||
],
|
||||
) -> "Permutation":
|
||||
"""
|
||||
Set the format for batches
|
||||
@@ -696,16 +710,18 @@ class Permutation:
|
||||
|
||||
The format can be one of:
|
||||
- "numpy" - the batch will be a dict of numpy arrays (one per column)
|
||||
- "python" - the batch will be a dict of lists (one per column)
|
||||
- "python" - the batch will be a list of dicts (one per row)
|
||||
- "python_col" - the batch will be a dict of lists (one entry per column)
|
||||
- "pandas" - the batch will be a pandas DataFrame
|
||||
- "arrow" - the batch will be a pyarrow RecordBatch
|
||||
- "torch" - the batch will be a two dimensional torch tensor
|
||||
- "torch" - the batch will be a list of tensors, one per row
|
||||
- "torch_col" - the batch will be a 2D torch tensor (first dim indexes columns)
|
||||
- "polars" - the batch will be a polars DataFrame
|
||||
|
||||
Conversion may or may not involve a data copy. Lance uses Arrow internally
|
||||
and so it is able to zero-copy to the arrow and polars.
|
||||
and so it is able to zero-copy to the arrow and polars formats.
|
||||
|
||||
Conversion to torch will be zero-copy but will only support a subset of data
|
||||
Conversion to torch_col will be zero-copy but will only support a subset of data
|
||||
types (numeric types).
|
||||
|
||||
Conversion to numpy and/or pandas will typically be zero-copy for numeric
|
||||
@@ -718,6 +734,8 @@ class Permutation:
|
||||
assert format is not None, "format is required"
|
||||
if format == "python":
|
||||
return self.with_transform(Transforms.arrow2python)
|
||||
if format == "python_col":
|
||||
return self.with_transform(Transforms.arrow2pythoncol)
|
||||
elif format == "numpy":
|
||||
return self.with_transform(Transforms.arrow2numpy)
|
||||
elif format == "pandas":
|
||||
@@ -725,6 +743,8 @@ class Permutation:
|
||||
elif format == "arrow":
|
||||
return self.with_transform(Transforms.arrow2arrow)
|
||||
elif format == "torch":
|
||||
return self.with_transform(batch_to_tensor_rows)
|
||||
elif format == "torch_col":
|
||||
return self.with_transform(batch_to_tensor)
|
||||
elif format == "polars":
|
||||
return self.with_transform(Transforms.arrow2polars())
|
||||
@@ -746,15 +766,20 @@ class Permutation:
|
||||
|
||||
def __getitem__(self, index: int) -> Any:
|
||||
"""
|
||||
Return a single row from the permutation
|
||||
|
||||
The output will always be a python dictionary regardless of the format.
|
||||
|
||||
This method is mostly useful for debugging and exploration. For actual
|
||||
processing use [iter](#iter) or a torch data loader to perform batched
|
||||
processing.
|
||||
Returns a single row from the permutation by offset
|
||||
"""
|
||||
pass
|
||||
return self.__getitems__([index])
|
||||
|
||||
def __getitems__(self, indices: list[int]) -> Any:
|
||||
"""
|
||||
Returns rows from the permutation by offset
|
||||
"""
|
||||
|
||||
async def do_getitems():
|
||||
return await self.reader.take_offsets(indices, selection=self.selection)
|
||||
|
||||
batch = LOOP.run(do_getitems())
|
||||
return self.transform_fn(batch)
|
||||
|
||||
@deprecated(details="Use with_skip instead")
|
||||
def skip(self, skip: int) -> "Permutation":
|
||||
|
||||
@@ -2118,19 +2118,17 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
|
||||
""" # noqa: E501
|
||||
self._create_query_builders()
|
||||
|
||||
results = ["Vector Search Plan:"]
|
||||
results.append(
|
||||
self._table._explain_plan(
|
||||
self._vector_query.to_query_object(), verbose=verbose
|
||||
)
|
||||
reranker_label = str(self._reranker) if self._reranker else "No reranker"
|
||||
vector_plan = self._table._explain_plan(
|
||||
self._vector_query.to_query_object(), verbose=verbose
|
||||
)
|
||||
results.append("FTS Search Plan:")
|
||||
results.append(
|
||||
self._table._explain_plan(
|
||||
self._fts_query.to_query_object(), verbose=verbose
|
||||
)
|
||||
fts_plan = self._table._explain_plan(
|
||||
self._fts_query.to_query_object(), verbose=verbose
|
||||
)
|
||||
return "\n".join(results)
|
||||
# Indent sub-plans under the reranker
|
||||
indented_vector = "\n".join(" " + line for line in vector_plan.splitlines())
|
||||
indented_fts = "\n".join(" " + line for line in fts_plan.splitlines())
|
||||
return f"{reranker_label}\n {indented_vector}\n {indented_fts}"
|
||||
|
||||
def analyze_plan(self):
|
||||
"""Execute the query and display with runtime metrics.
|
||||
@@ -3164,23 +3162,20 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
|
||||
... plan = await table.query().nearest_to([1.0, 2.0]).nearest_to_text("hello").explain_plan(True)
|
||||
... print(plan)
|
||||
>>> asyncio.run(doctest_example()) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
|
||||
Vector Search Plan:
|
||||
ProjectionExec: expr=[vector@0 as vector, text@3 as text, _distance@2 as _distance]
|
||||
Take: columns="vector, _rowid, _distance, (text)"
|
||||
CoalesceBatchesExec: target_batch_size=1024
|
||||
GlobalLimitExec: skip=0, fetch=10
|
||||
FilterExec: _distance@2 IS NOT NULL
|
||||
SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST, _rowid@1 ASC NULLS LAST], preserve_partitioning=[false]
|
||||
KNNVectorDistance: metric=l2
|
||||
LanceRead: uri=..., projection=[vector], ...
|
||||
<BLANKLINE>
|
||||
FTS Search Plan:
|
||||
ProjectionExec: expr=[vector@2 as vector, text@3 as text, _score@1 as _score]
|
||||
Take: columns="_rowid, _score, (vector), (text)"
|
||||
CoalesceBatchesExec: target_batch_size=1024
|
||||
GlobalLimitExec: skip=0, fetch=10
|
||||
MatchQuery: column=text, query=hello
|
||||
<BLANKLINE>
|
||||
RRFReranker(K=60)
|
||||
ProjectionExec: expr=[vector@0 as vector, text@3 as text, _distance@2 as _distance]
|
||||
Take: columns="vector, _rowid, _distance, (text)"
|
||||
CoalesceBatchesExec: target_batch_size=1024
|
||||
GlobalLimitExec: skip=0, fetch=10
|
||||
FilterExec: _distance@2 IS NOT NULL
|
||||
SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST, _rowid@1 ASC NULLS LAST], preserve_partitioning=[false]
|
||||
KNNVectorDistance: metric=l2
|
||||
LanceRead: uri=..., projection=[vector], ...
|
||||
ProjectionExec: expr=[vector@2 as vector, text@3 as text, _score@1 as _score]
|
||||
Take: columns="_rowid, _score, (vector), (text)"
|
||||
CoalesceBatchesExec: target_batch_size=1024
|
||||
GlobalLimitExec: skip=0, fetch=10
|
||||
MatchQuery: column=text, query=hello
|
||||
|
||||
Parameters
|
||||
----------
|
||||
@@ -3192,12 +3187,12 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
|
||||
plan : str
|
||||
""" # noqa: E501
|
||||
|
||||
results = ["Vector Search Plan:"]
|
||||
results.append(await self._inner.to_vector_query().explain_plan(verbose))
|
||||
results.append("FTS Search Plan:")
|
||||
results.append(await self._inner.to_fts_query().explain_plan(verbose))
|
||||
|
||||
return "\n".join(results)
|
||||
vector_plan = await self._inner.to_vector_query().explain_plan(verbose)
|
||||
fts_plan = await self._inner.to_fts_query().explain_plan(verbose)
|
||||
# Indent sub-plans under the reranker
|
||||
indented_vector = "\n".join(" " + line for line in vector_plan.splitlines())
|
||||
indented_fts = "\n".join(" " + line for line in fts_plan.splitlines())
|
||||
return f"{self._reranker}\n {indented_vector}\n {indented_fts}"
|
||||
|
||||
async def analyze_plan(self):
|
||||
"""
|
||||
|
||||
@@ -42,10 +42,18 @@ class AnswerdotaiRerankers(Reranker):
|
||||
rerankers = attempt_import_or_raise(
|
||||
"rerankers"
|
||||
) # import here for faster ops later
|
||||
self.model_name = model_name
|
||||
self.model_type = model_type
|
||||
self.reranker = rerankers.Reranker(
|
||||
model_name=model_name, model_type=model_type, **kwargs
|
||||
)
|
||||
|
||||
def __str__(self):
|
||||
return (
|
||||
f"AnswerdotaiRerankers(model_type={self.model_type}, "
|
||||
f"model_name={self.model_name})"
|
||||
)
|
||||
|
||||
def _rerank(self, result_set: pa.Table, query: str):
|
||||
result_set = self._handle_empty_results(result_set)
|
||||
if len(result_set) == 0:
|
||||
|
||||
@@ -40,6 +40,9 @@ class Reranker(ABC):
|
||||
if ARROW_VERSION.major <= 13:
|
||||
self._concat_tables_args = {"promote": True}
|
||||
|
||||
def __str__(self):
|
||||
return self.__class__.__name__
|
||||
|
||||
def rerank_vector(
|
||||
self,
|
||||
query: str,
|
||||
|
||||
@@ -44,6 +44,9 @@ class CohereReranker(Reranker):
|
||||
self.top_n = top_n
|
||||
self.api_key = api_key
|
||||
|
||||
def __str__(self):
|
||||
return f"CohereReranker(model_name={self.model_name})"
|
||||
|
||||
@cached_property
|
||||
def _client(self):
|
||||
cohere = attempt_import_or_raise("cohere")
|
||||
|
||||
@@ -50,6 +50,9 @@ class CrossEncoderReranker(Reranker):
|
||||
if self.device is None:
|
||||
self.device = "cuda" if torch.cuda.is_available() else "cpu"
|
||||
|
||||
def __str__(self):
|
||||
return f"CrossEncoderReranker(model_name={self.model_name})"
|
||||
|
||||
@cached_property
|
||||
def model(self):
|
||||
sbert = attempt_import_or_raise("sentence_transformers")
|
||||
|
||||
@@ -45,6 +45,9 @@ class JinaReranker(Reranker):
|
||||
self.top_n = top_n
|
||||
self.api_key = api_key
|
||||
|
||||
def __str__(self):
|
||||
return f"JinaReranker(model_name={self.model_name})"
|
||||
|
||||
@cached_property
|
||||
def _client(self):
|
||||
import requests
|
||||
|
||||
@@ -38,6 +38,9 @@ class LinearCombinationReranker(Reranker):
|
||||
self.weight = weight
|
||||
self.fill = fill
|
||||
|
||||
def __str__(self):
|
||||
return f"LinearCombinationReranker(weight={self.weight}, fill={self.fill})"
|
||||
|
||||
def rerank_hybrid(
|
||||
self,
|
||||
query: str, # noqa: F821
|
||||
|
||||
@@ -54,6 +54,12 @@ class MRRReranker(Reranker):
|
||||
self.weight_vector = weight_vector
|
||||
self.weight_fts = weight_fts
|
||||
|
||||
def __str__(self):
|
||||
return (
|
||||
f"MRRReranker(weight_vector={self.weight_vector}, "
|
||||
f"weight_fts={self.weight_fts})"
|
||||
)
|
||||
|
||||
def rerank_hybrid(
|
||||
self,
|
||||
query: str, # noqa: F821
|
||||
|
||||
@@ -43,6 +43,9 @@ class OpenaiReranker(Reranker):
|
||||
self.column = column
|
||||
self.api_key = api_key
|
||||
|
||||
def __str__(self):
|
||||
return f"OpenaiReranker(model_name={self.model_name})"
|
||||
|
||||
def _rerank(self, result_set: pa.Table, query: str):
|
||||
result_set = self._handle_empty_results(result_set)
|
||||
if len(result_set) == 0:
|
||||
|
||||
@@ -36,6 +36,9 @@ class RRFReranker(Reranker):
|
||||
super().__init__(return_score)
|
||||
self.K = K
|
||||
|
||||
def __str__(self):
|
||||
return f"RRFReranker(K={self.K})"
|
||||
|
||||
def rerank_hybrid(
|
||||
self,
|
||||
query: str, # noqa: F821
|
||||
|
||||
@@ -52,6 +52,9 @@ class VoyageAIReranker(Reranker):
|
||||
self.api_key = api_key
|
||||
self.truncation = truncation
|
||||
|
||||
def __str__(self):
|
||||
return f"VoyageAIReranker(model_name={self.model_name})"
|
||||
|
||||
@cached_property
|
||||
def _client(self):
|
||||
voyageai = attempt_import_or_raise("voyageai")
|
||||
|
||||
@@ -904,7 +904,9 @@ class Table(ABC):
|
||||
----------
|
||||
field_names: str or list of str
|
||||
The name(s) of the field to index.
|
||||
can be only str if use_tantivy=True for now.
|
||||
If ``use_tantivy`` is False (default), only a single field name
|
||||
(str) is supported. To index multiple fields, create a separate
|
||||
FTS index for each field.
|
||||
replace: bool, default False
|
||||
If True, replace the existing index if it exists. Note that this is
|
||||
not yet an atomic operation; the index will be temporarily
|
||||
@@ -2298,7 +2300,11 @@ class LanceTable(Table):
|
||||
):
|
||||
if not use_tantivy:
|
||||
if not isinstance(field_names, str):
|
||||
raise ValueError("field_names must be a string when use_tantivy=False")
|
||||
raise ValueError(
|
||||
"Native FTS indexes can only be created on a single field "
|
||||
"at a time. To search over multiple text fields, create a "
|
||||
"separate FTS index for each field."
|
||||
)
|
||||
|
||||
if tokenizer_name is None:
|
||||
tokenizer_configs = {
|
||||
|
||||
@@ -419,3 +419,22 @@ def batch_to_tensor(batch: pa.RecordBatch):
|
||||
"""
|
||||
torch = attempt_import_or_raise("torch", "torch")
|
||||
return torch.stack([torch.from_dlpack(col) for col in batch.columns])
|
||||
|
||||
|
||||
def batch_to_tensor_rows(batch: pa.RecordBatch):
|
||||
"""
|
||||
Convert a PyArrow RecordBatch to a list of PyTorch Tensor, one per row
|
||||
|
||||
Each column is converted to a tensor (using zero-copy via DLPack)
|
||||
and the columns are then stacked into a single tensor. The 2D tensor
|
||||
is then converted to a list of tensors, one per row
|
||||
|
||||
Fails if torch or numpy is not installed.
|
||||
Fails if a column's data type is not supported by PyTorch.
|
||||
"""
|
||||
torch = attempt_import_or_raise("torch", "torch")
|
||||
numpy = attempt_import_or_raise("numpy", "numpy")
|
||||
columns = [col.to_numpy(zero_copy_only=False) for col in batch.columns]
|
||||
stacked = torch.tensor(numpy.column_stack(columns))
|
||||
rows = list(stacked.unbind(dim=0))
|
||||
return rows
|
||||
|
||||
@@ -163,9 +163,7 @@ async def test_explain_plan(table: AsyncTable):
|
||||
table.query().nearest_to_text("dog").nearest_to([0.1, 0.1]).explain_plan(True)
|
||||
)
|
||||
|
||||
assert "Vector Search Plan" in plan
|
||||
assert "KNNVectorDistance" in plan
|
||||
assert "FTS Search Plan" in plan
|
||||
assert "LanceRead" in plan
|
||||
|
||||
|
||||
|
||||
@@ -664,23 +664,20 @@ def test_iter_basic(some_permutation: Permutation):
|
||||
expected_batches = (950 + batch_size - 1) // batch_size # ceiling division
|
||||
assert len(batches) == expected_batches
|
||||
|
||||
# Check that all batches are dicts (default python format)
|
||||
assert all(isinstance(batch, dict) for batch in batches)
|
||||
# Check that all batches are lists of dicts (default python format)
|
||||
assert all(isinstance(batch, list) for batch in batches)
|
||||
|
||||
# Check that batches have the correct structure
|
||||
for batch in batches:
|
||||
assert "id" in batch
|
||||
assert "value" in batch
|
||||
assert isinstance(batch["id"], list)
|
||||
assert isinstance(batch["value"], list)
|
||||
assert "id" in batch[0]
|
||||
assert "value" in batch[0]
|
||||
|
||||
# Check that all batches except the last have the correct size
|
||||
for batch in batches[:-1]:
|
||||
assert len(batch["id"]) == batch_size
|
||||
assert len(batch["value"]) == batch_size
|
||||
assert len(batch) == batch_size
|
||||
|
||||
# Last batch might be smaller
|
||||
assert len(batches[-1]["id"]) <= batch_size
|
||||
assert len(batches[-1]) <= batch_size
|
||||
|
||||
|
||||
def test_iter_skip_last_batch(some_permutation: Permutation):
|
||||
@@ -699,11 +696,11 @@ def test_iter_skip_last_batch(some_permutation: Permutation):
|
||||
if 950 % batch_size != 0:
|
||||
assert len(batches_without_skip) == num_full_batches + 1
|
||||
# Last batch should be smaller
|
||||
assert len(batches_without_skip[-1]["id"]) == 950 % batch_size
|
||||
assert len(batches_without_skip[-1]) == 950 % batch_size
|
||||
|
||||
# All batches with skip_last_batch should be full size
|
||||
for batch in batches_with_skip:
|
||||
assert len(batch["id"]) == batch_size
|
||||
assert len(batch) == batch_size
|
||||
|
||||
|
||||
def test_iter_different_batch_sizes(some_permutation: Permutation):
|
||||
@@ -720,12 +717,12 @@ def test_iter_different_batch_sizes(some_permutation: Permutation):
|
||||
# Test with batch size equal to total rows
|
||||
single_batch = list(some_permutation.iter(950, skip_last_batch=False))
|
||||
assert len(single_batch) == 1
|
||||
assert len(single_batch[0]["id"]) == 950
|
||||
assert len(single_batch[0]) == 950
|
||||
|
||||
# Test with batch size larger than total rows
|
||||
oversized_batch = list(some_permutation.iter(10000, skip_last_batch=False))
|
||||
assert len(oversized_batch) == 1
|
||||
assert len(oversized_batch[0]["id"]) == 950
|
||||
assert len(oversized_batch[0]) == 950
|
||||
|
||||
|
||||
def test_dunder_iter(some_permutation: Permutation):
|
||||
@@ -738,15 +735,13 @@ def test_dunder_iter(some_permutation: Permutation):
|
||||
|
||||
# All batches should be full size
|
||||
for batch in batches:
|
||||
assert len(batch["id"]) == 100
|
||||
assert len(batch["value"]) == 100
|
||||
assert len(batch) == 100
|
||||
|
||||
some_permutation = some_permutation.with_batch_size(400)
|
||||
batches = list(some_permutation)
|
||||
assert len(batches) == 2 # floor(950 / 400) since skip_last_batch=True
|
||||
for batch in batches:
|
||||
assert len(batch["id"]) == 400
|
||||
assert len(batch["value"]) == 400
|
||||
assert len(batch) == 400
|
||||
|
||||
|
||||
def test_iter_with_different_formats(some_permutation: Permutation):
|
||||
@@ -761,7 +756,7 @@ def test_iter_with_different_formats(some_permutation: Permutation):
|
||||
# Test with python format (default)
|
||||
python_perm = some_permutation.with_format("python")
|
||||
python_batches = list(python_perm.iter(batch_size, skip_last_batch=False))
|
||||
assert all(isinstance(batch, dict) for batch in python_batches)
|
||||
assert all(isinstance(batch, list) for batch in python_batches)
|
||||
|
||||
# Test with pandas format
|
||||
pandas_perm = some_permutation.with_format("pandas")
|
||||
@@ -780,8 +775,8 @@ def test_iter_with_column_selection(some_permutation: Permutation):
|
||||
|
||||
# Check that batches only contain the id column
|
||||
for batch in batches:
|
||||
assert "id" in batch
|
||||
assert "value" not in batch
|
||||
assert "id" in batch[0]
|
||||
assert "value" not in batch[0]
|
||||
|
||||
|
||||
def test_iter_with_column_rename(some_permutation: Permutation):
|
||||
@@ -791,9 +786,9 @@ def test_iter_with_column_rename(some_permutation: Permutation):
|
||||
|
||||
# Check that batches have the renamed column
|
||||
for batch in batches:
|
||||
assert "id" in batch
|
||||
assert "data" in batch
|
||||
assert "value" not in batch
|
||||
assert "id" in batch[0]
|
||||
assert "data" in batch[0]
|
||||
assert "value" not in batch[0]
|
||||
|
||||
|
||||
def test_iter_with_limit_offset(some_permutation: Permutation):
|
||||
@@ -812,14 +807,14 @@ def test_iter_with_limit_offset(some_permutation: Permutation):
|
||||
assert len(limit_batches) == 5
|
||||
|
||||
no_skip = some_permutation.iter(101, skip_last_batch=False)
|
||||
row_100 = next(no_skip)["id"][100]
|
||||
row_100 = next(no_skip)[100]["id"]
|
||||
|
||||
# Test with both limit and offset
|
||||
limited_perm = some_permutation.with_skip(100).with_take(300)
|
||||
limited_batches = list(limited_perm.iter(100, skip_last_batch=False))
|
||||
# Should have 3 batches (300 / 100)
|
||||
assert len(limited_batches) == 3
|
||||
assert limited_batches[0]["id"][0] == row_100
|
||||
assert limited_batches[0][0]["id"] == row_100
|
||||
|
||||
|
||||
def test_iter_empty_permutation(mem_db):
|
||||
@@ -842,7 +837,7 @@ def test_iter_single_row(mem_db):
|
||||
# With skip_last_batch=False, should get one batch
|
||||
batches = list(perm.iter(10, skip_last_batch=False))
|
||||
assert len(batches) == 1
|
||||
assert len(batches[0]["id"]) == 1
|
||||
assert len(batches[0]) == 1
|
||||
|
||||
# With skip_last_batch=True, should skip the single row (since it's < batch_size)
|
||||
batches_skip = list(perm.iter(10, skip_last_batch=True))
|
||||
@@ -860,8 +855,7 @@ def test_identity_permutation(mem_db):
|
||||
|
||||
batches = list(permutation.iter(10, skip_last_batch=False))
|
||||
assert len(batches) == 1
|
||||
assert len(batches[0]["id"]) == 10
|
||||
assert len(batches[0]["value"]) == 10
|
||||
assert len(batches[0]) == 10
|
||||
|
||||
permutation = permutation.remove_columns(["value"])
|
||||
assert permutation.num_columns == 1
|
||||
@@ -904,10 +898,10 @@ def test_transform_fn(mem_db):
|
||||
py_result = list(permutation.with_format("python").iter(10, skip_last_batch=False))[
|
||||
0
|
||||
]
|
||||
assert len(py_result) == 2
|
||||
assert len(py_result["id"]) == 10
|
||||
assert len(py_result["value"]) == 10
|
||||
assert isinstance(py_result, dict)
|
||||
assert len(py_result) == 10
|
||||
assert "id" in py_result[0]
|
||||
assert "value" in py_result[0]
|
||||
assert isinstance(py_result, list)
|
||||
|
||||
try:
|
||||
import torch
|
||||
@@ -915,9 +909,11 @@ def test_transform_fn(mem_db):
|
||||
torch_result = list(
|
||||
permutation.with_format("torch").iter(10, skip_last_batch=False)
|
||||
)[0]
|
||||
assert torch_result.shape == (2, 10)
|
||||
assert torch_result.dtype == torch.int64
|
||||
assert isinstance(torch_result, torch.Tensor)
|
||||
assert isinstance(torch_result, list)
|
||||
assert len(torch_result) == 10
|
||||
assert isinstance(torch_result[0], torch.Tensor)
|
||||
assert torch_result[0].shape == (2,)
|
||||
assert torch_result[0].dtype == torch.int64
|
||||
except ImportError:
|
||||
# Skip check if torch is not installed
|
||||
pass
|
||||
@@ -945,3 +941,113 @@ def test_custom_transform(mem_db):
|
||||
batch = batches[0]
|
||||
|
||||
assert batch == pa.record_batch([range(10)], ["id"])
|
||||
|
||||
|
||||
def test_getitems_basic(some_permutation: Permutation):
|
||||
"""Test __getitems__ returns correct rows by offset."""
|
||||
result = some_permutation.__getitems__([0, 1, 2])
|
||||
assert isinstance(result, list)
|
||||
assert "id" in result[0]
|
||||
assert "value" in result[0]
|
||||
assert len(result) == 3
|
||||
|
||||
|
||||
def test_getitems_single_index(some_permutation: Permutation):
|
||||
"""Test __getitems__ with a single index."""
|
||||
result = some_permutation.__getitems__([0])
|
||||
assert len(result) == 1
|
||||
|
||||
|
||||
def test_getitems_preserves_order(some_permutation: Permutation):
|
||||
"""Test __getitems__ returns rows in the requested order."""
|
||||
# Get rows in forward order
|
||||
forward = some_permutation.__getitems__([0, 1, 2, 3, 4])
|
||||
# Get the same rows in reverse order
|
||||
reverse = some_permutation.__getitems__([4, 3, 2, 1, 0])
|
||||
|
||||
assert [r["id"] for r in forward] == list(reversed([r["id"] for r in reverse]))
|
||||
assert [r["value"] for r in forward] == list(
|
||||
reversed([r["value"] for r in reverse])
|
||||
)
|
||||
|
||||
|
||||
def test_getitems_non_contiguous(some_permutation: Permutation):
|
||||
"""Test __getitems__ with non-contiguous indices."""
|
||||
result = some_permutation.__getitems__([0, 10, 50, 100, 500])
|
||||
assert len(result) == 5
|
||||
|
||||
# Each id/value pair should match what we'd get individually
|
||||
for i, offset in enumerate([0, 10, 50, 100, 500]):
|
||||
single = some_permutation.__getitems__([offset])
|
||||
assert result[i]["id"] == single[0]["id"]
|
||||
assert result[i]["value"] == single[0]["value"]
|
||||
|
||||
|
||||
def test_getitems_with_column_selection(some_permutation: Permutation):
|
||||
"""Test __getitems__ respects column selection."""
|
||||
id_only = some_permutation.select_columns(["id"])
|
||||
result = id_only.__getitems__([0, 1, 2])
|
||||
assert "id" in result[0]
|
||||
assert "value" not in result[0]
|
||||
assert len(result) == 3
|
||||
|
||||
|
||||
def test_getitems_with_column_rename(some_permutation: Permutation):
|
||||
"""Test __getitems__ respects column renames."""
|
||||
renamed = some_permutation.rename_column("value", "data")
|
||||
result = renamed.__getitems__([0, 1])
|
||||
assert "data" in result[0]
|
||||
assert "value" not in result[0]
|
||||
assert len(result) == 2
|
||||
|
||||
|
||||
def test_getitems_with_format(some_permutation: Permutation):
|
||||
"""Test __getitems__ applies the transform function."""
|
||||
arrow_perm = some_permutation.with_format("arrow")
|
||||
result = arrow_perm.__getitems__([0, 1, 2])
|
||||
assert isinstance(result, pa.RecordBatch)
|
||||
assert result.num_rows == 3
|
||||
|
||||
|
||||
def test_getitems_with_custom_transform(some_permutation: Permutation):
|
||||
"""Test __getitems__ with a custom transform."""
|
||||
|
||||
def transform(batch: pa.RecordBatch) -> list:
|
||||
return batch.column("id").to_pylist()
|
||||
|
||||
custom = some_permutation.with_transform(transform)
|
||||
result = custom.__getitems__([0, 1, 2])
|
||||
assert isinstance(result, list)
|
||||
assert len(result) == 3
|
||||
|
||||
|
||||
def test_getitems_identity_permutation(mem_db):
|
||||
"""Test __getitems__ on an identity permutation."""
|
||||
tbl = mem_db.create_table(
|
||||
"test_table", pa.table({"id": range(10), "value": range(10)})
|
||||
)
|
||||
perm = Permutation.identity(tbl)
|
||||
|
||||
result = perm.__getitems__([0, 5, 9])
|
||||
assert [r["id"] for r in result] == [0, 5, 9]
|
||||
assert [r["value"] for r in result] == [0, 5, 9]
|
||||
|
||||
|
||||
def test_getitems_with_limit_offset(some_permutation: Permutation):
|
||||
"""Test __getitems__ on a permutation with skip/take applied."""
|
||||
limited = some_permutation.with_skip(100).with_take(200)
|
||||
|
||||
# Should be able to access offsets within the limited range
|
||||
result = limited.__getitems__([0, 1, 199])
|
||||
assert len(result) == 3
|
||||
|
||||
# The first item of the limited permutation should match offset 100 of original
|
||||
full_result = some_permutation.__getitems__([100])
|
||||
limited_result = limited.__getitems__([0])
|
||||
assert limited_result[0]["id"] == full_result[0]["id"]
|
||||
|
||||
|
||||
def test_getitems_invalid_offset(some_permutation: Permutation):
|
||||
"""Test __getitems__ with an out-of-range offset raises an error."""
|
||||
with pytest.raises(Exception):
|
||||
some_permutation.__getitems__([999999])
|
||||
|
||||
@@ -4,6 +4,7 @@
|
||||
import pyarrow as pa
|
||||
import pytest
|
||||
from lancedb.util import tbl_to_tensor
|
||||
from lancedb.permutation import Permutation
|
||||
|
||||
torch = pytest.importorskip("torch")
|
||||
|
||||
@@ -16,3 +17,26 @@ def test_table_dataloader(mem_db):
|
||||
for batch in dataloader:
|
||||
assert batch.size(0) == 1
|
||||
assert batch.size(1) == 10
|
||||
|
||||
|
||||
def test_permutation_dataloader(mem_db):
|
||||
table = mem_db.create_table("test_table", pa.table({"a": range(1000)}))
|
||||
|
||||
permutation = Permutation.identity(table)
|
||||
dataloader = torch.utils.data.DataLoader(permutation, batch_size=10, shuffle=True)
|
||||
for batch in dataloader:
|
||||
assert batch["a"].size(0) == 10
|
||||
|
||||
permutation = permutation.with_format("torch")
|
||||
dataloader = torch.utils.data.DataLoader(permutation, batch_size=10, shuffle=True)
|
||||
for batch in dataloader:
|
||||
assert batch.size(0) == 10
|
||||
assert batch.size(1) == 1
|
||||
|
||||
permutation = permutation.with_format("torch_col")
|
||||
dataloader = torch.utils.data.DataLoader(
|
||||
permutation, collate_fn=lambda x: x, batch_size=10, shuffle=True
|
||||
)
|
||||
for batch in dataloader:
|
||||
assert batch.size(0) == 1
|
||||
assert batch.size(1) == 10
|
||||
|
||||
@@ -121,7 +121,8 @@ impl Connection {
|
||||
|
||||
let mode = Self::parse_create_mode_str(mode)?;
|
||||
|
||||
let batches = ArrowArrayStreamReader::from_pyarrow_bound(&data)?;
|
||||
let batches: Box<dyn arrow::array::RecordBatchReader + Send> =
|
||||
Box::new(ArrowArrayStreamReader::from_pyarrow_bound(&data)?);
|
||||
|
||||
let mut builder = inner.create_table(name, batches).mode(mode);
|
||||
|
||||
|
||||
@@ -6,7 +6,7 @@ use std::sync::{Arc, Mutex};
|
||||
use crate::{
|
||||
arrow::RecordBatchStream, connection::Connection, error::PythonErrorExt, table::Table,
|
||||
};
|
||||
use arrow::pyarrow::ToPyArrow;
|
||||
use arrow::pyarrow::{PyArrowType, ToPyArrow};
|
||||
use lancedb::{
|
||||
dataloader::permutation::{
|
||||
builder::{PermutationBuilder as LancePermutationBuilder, ShuffleStrategy},
|
||||
@@ -328,4 +328,21 @@ impl PyPermutationReader {
|
||||
Ok(RecordBatchStream::new(stream))
|
||||
})
|
||||
}
|
||||
|
||||
#[pyo3(signature = (indices, *, selection=None))]
|
||||
pub fn take_offsets<'py>(
|
||||
slf: PyRef<'py, Self>,
|
||||
indices: Vec<u64>,
|
||||
selection: Option<Bound<'py, PyAny>>,
|
||||
) -> PyResult<Bound<'py, PyAny>> {
|
||||
let selection = Self::parse_selection(selection)?;
|
||||
let reader = slf.reader.clone();
|
||||
future_into_py(slf.py(), async move {
|
||||
let batch = reader
|
||||
.take_offsets(&indices, selection)
|
||||
.await
|
||||
.infer_error()?;
|
||||
Ok(PyArrowType(batch))
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
@@ -296,7 +296,8 @@ impl Table {
|
||||
data: Bound<'_, PyAny>,
|
||||
mode: String,
|
||||
) -> PyResult<Bound<'a, PyAny>> {
|
||||
let batches = ArrowArrayStreamReader::from_pyarrow_bound(&data)?;
|
||||
let batches: Box<dyn arrow::array::RecordBatchReader + Send> =
|
||||
Box::new(ArrowArrayStreamReader::from_pyarrow_bound(&data)?);
|
||||
let mut op = self_.inner_ref()?.add(batches);
|
||||
if mode == "append" {
|
||||
op = op.mode(AddDataMode::Append);
|
||||
|
||||
5349
python/uv.lock
generated
Normal file
5349
python/uv.lock
generated
Normal file
File diff suppressed because it is too large
Load Diff
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "lancedb"
|
||||
version = "0.26.1-beta.0"
|
||||
version = "0.27.0-beta.0"
|
||||
edition.workspace = true
|
||||
description = "LanceDB: A serverless, low-latency vector database for AI applications"
|
||||
license.workspace = true
|
||||
|
||||
@@ -3,13 +3,12 @@
|
||||
|
||||
use std::{iter::once, sync::Arc};
|
||||
|
||||
use arrow_array::{Float64Array, Int32Array, RecordBatch, RecordBatchIterator, StringArray};
|
||||
use arrow_array::{Float64Array, Int32Array, RecordBatch, StringArray};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use aws_config::Region;
|
||||
use aws_sdk_bedrockruntime::Client;
|
||||
use futures::StreamExt;
|
||||
use lancedb::{
|
||||
arrow::IntoArrow,
|
||||
connect,
|
||||
embeddings::{bedrock::BedrockEmbeddingFunction, EmbeddingDefinition, EmbeddingFunction},
|
||||
query::{ExecutableQuery, QueryBase},
|
||||
@@ -67,7 +66,7 @@ async fn main() -> Result<()> {
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn make_data() -> impl IntoArrow {
|
||||
fn make_data() -> RecordBatch {
|
||||
let schema = Schema::new(vec![
|
||||
Field::new("id", DataType::Int32, true),
|
||||
Field::new("text", DataType::Utf8, false),
|
||||
@@ -83,10 +82,9 @@ fn make_data() -> impl IntoArrow {
|
||||
]);
|
||||
let price = Float64Array::from(vec![10.0, 50.0, 100.0, 30.0]);
|
||||
let schema = Arc::new(schema);
|
||||
let rb = RecordBatch::try_new(
|
||||
RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(id), Arc::new(text), Arc::new(price)],
|
||||
)
|
||||
.unwrap();
|
||||
Box::new(RecordBatchIterator::new(vec![Ok(rb)], schema))
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
@@ -3,12 +3,13 @@
|
||||
|
||||
use std::sync::Arc;
|
||||
|
||||
use arrow_array::{Int32Array, RecordBatch, RecordBatchIterator, RecordBatchReader, StringArray};
|
||||
use arrow_array::{Int32Array, RecordBatch, RecordBatchIterator, StringArray};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
|
||||
use futures::TryStreamExt;
|
||||
use lance_index::scalar::FullTextSearchQuery;
|
||||
use lancedb::connection::Connection;
|
||||
|
||||
use lancedb::index::scalar::FtsIndexBuilder;
|
||||
use lancedb::index::Index;
|
||||
use lancedb::query::{ExecutableQuery, QueryBase};
|
||||
@@ -29,7 +30,7 @@ async fn main() -> Result<()> {
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn create_some_records() -> Result<Box<dyn RecordBatchReader + Send>> {
|
||||
fn create_some_records() -> Result<Box<dyn arrow_array::RecordBatchReader + Send>> {
|
||||
const TOTAL: usize = 1000;
|
||||
|
||||
let schema = Arc::new(Schema::new(vec![
|
||||
@@ -66,7 +67,7 @@ fn create_some_records() -> Result<Box<dyn RecordBatchReader + Send>> {
|
||||
}
|
||||
|
||||
async fn create_table(db: &Connection) -> Result<Table> {
|
||||
let initial_data: Box<dyn RecordBatchReader + Send> = create_some_records()?;
|
||||
let initial_data = create_some_records()?;
|
||||
let tbl = db.create_table("my_table", initial_data).execute().await?;
|
||||
Ok(tbl)
|
||||
}
|
||||
|
||||
@@ -1,14 +1,13 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
use arrow_array::{RecordBatch, RecordBatchIterator, StringArray};
|
||||
use arrow_array::{RecordBatch, StringArray};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use futures::TryStreamExt;
|
||||
use lance_index::scalar::FullTextSearchQuery;
|
||||
use lancedb::index::scalar::FtsIndexBuilder;
|
||||
use lancedb::index::Index;
|
||||
use lancedb::{
|
||||
arrow::IntoArrow,
|
||||
connect,
|
||||
embeddings::{
|
||||
sentence_transformers::SentenceTransformersEmbeddings, EmbeddingDefinition,
|
||||
@@ -70,7 +69,7 @@ async fn main() -> Result<()> {
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn make_data() -> impl IntoArrow {
|
||||
fn make_data() -> RecordBatch {
|
||||
let schema = Schema::new(vec![Field::new("facts", DataType::Utf8, false)]);
|
||||
|
||||
let facts = StringArray::from_iter_values(vec![
|
||||
@@ -101,8 +100,7 @@ fn make_data() -> impl IntoArrow {
|
||||
"The first chatbot was ELIZA, created in the 1960s.",
|
||||
]);
|
||||
let schema = Arc::new(schema);
|
||||
let rb = RecordBatch::try_new(schema.clone(), vec![Arc::new(facts)]).unwrap();
|
||||
Box::new(RecordBatchIterator::new(vec![Ok(rb)], schema))
|
||||
RecordBatch::try_new(schema.clone(), vec![Arc::new(facts)]).unwrap()
|
||||
}
|
||||
|
||||
async fn create_index(table: &Table) -> Result<()> {
|
||||
|
||||
@@ -8,13 +8,12 @@
|
||||
use std::sync::Arc;
|
||||
|
||||
use arrow_array::types::Float32Type;
|
||||
use arrow_array::{
|
||||
FixedSizeListArray, Int32Array, RecordBatch, RecordBatchIterator, RecordBatchReader,
|
||||
};
|
||||
use arrow_array::{FixedSizeListArray, Int32Array, RecordBatch, RecordBatchIterator};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
|
||||
use futures::TryStreamExt;
|
||||
use lancedb::connection::Connection;
|
||||
|
||||
use lancedb::index::vector::IvfPqIndexBuilder;
|
||||
use lancedb::index::Index;
|
||||
use lancedb::query::{ExecutableQuery, QueryBase};
|
||||
@@ -34,7 +33,7 @@ async fn main() -> Result<()> {
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn create_some_records() -> Result<Box<dyn RecordBatchReader + Send>> {
|
||||
fn create_some_records() -> Result<Box<dyn arrow_array::RecordBatchReader + Send>> {
|
||||
const TOTAL: usize = 1000;
|
||||
const DIM: usize = 128;
|
||||
|
||||
@@ -73,9 +72,9 @@ fn create_some_records() -> Result<Box<dyn RecordBatchReader + Send>> {
|
||||
}
|
||||
|
||||
async fn create_table(db: &Connection) -> Result<Table> {
|
||||
let initial_data: Box<dyn RecordBatchReader + Send> = create_some_records()?;
|
||||
let initial_data = create_some_records()?;
|
||||
let tbl = db
|
||||
.create_table("my_table", Box::new(initial_data))
|
||||
.create_table("my_table", initial_data)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
@@ -5,11 +5,9 @@
|
||||
|
||||
use std::{iter::once, sync::Arc};
|
||||
|
||||
use arrow_array::{Float64Array, Int32Array, RecordBatch, RecordBatchIterator, StringArray};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use arrow_array::{RecordBatch, StringArray};
|
||||
use futures::StreamExt;
|
||||
use lancedb::{
|
||||
arrow::IntoArrow,
|
||||
connect,
|
||||
embeddings::{openai::OpenAIEmbeddingFunction, EmbeddingDefinition, EmbeddingFunction},
|
||||
query::{ExecutableQuery, QueryBase},
|
||||
@@ -64,26 +62,20 @@ async fn main() -> Result<()> {
|
||||
}
|
||||
// --8<-- [end:openai_embeddings]
|
||||
|
||||
fn make_data() -> impl IntoArrow {
|
||||
let schema = Schema::new(vec![
|
||||
Field::new("id", DataType::Int32, true),
|
||||
Field::new("text", DataType::Utf8, false),
|
||||
Field::new("price", DataType::Float64, false),
|
||||
]);
|
||||
|
||||
let id = Int32Array::from(vec![1, 2, 3, 4]);
|
||||
let text = StringArray::from_iter_values(vec![
|
||||
"Black T-Shirt",
|
||||
"Leather Jacket",
|
||||
"Winter Parka",
|
||||
"Hooded Sweatshirt",
|
||||
]);
|
||||
let price = Float64Array::from(vec![10.0, 50.0, 100.0, 30.0]);
|
||||
let schema = Arc::new(schema);
|
||||
let rb = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(id), Arc::new(text), Arc::new(price)],
|
||||
fn make_data() -> RecordBatch {
|
||||
arrow_array::record_batch!(
|
||||
("id", Int32, [1, 2, 3, 4]),
|
||||
(
|
||||
"text",
|
||||
Utf8,
|
||||
[
|
||||
"Black T-Shirt",
|
||||
"Leather Jacket",
|
||||
"Winter Parka",
|
||||
"Hooded Sweatshirt"
|
||||
]
|
||||
),
|
||||
("price", Float64, [10.0, 50.0, 100.0, 30.0])
|
||||
)
|
||||
.unwrap();
|
||||
Box::new(RecordBatchIterator::new(vec![Ok(rb)], schema))
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
@@ -3,11 +3,10 @@
|
||||
|
||||
use std::{iter::once, sync::Arc};
|
||||
|
||||
use arrow_array::{RecordBatch, RecordBatchIterator, StringArray};
|
||||
use arrow_array::{RecordBatch, StringArray};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use futures::StreamExt;
|
||||
use lancedb::{
|
||||
arrow::IntoArrow,
|
||||
connect,
|
||||
embeddings::{
|
||||
sentence_transformers::SentenceTransformersEmbeddings, EmbeddingDefinition,
|
||||
@@ -59,7 +58,7 @@ async fn main() -> Result<()> {
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn make_data() -> impl IntoArrow {
|
||||
fn make_data() -> RecordBatch {
|
||||
let schema = Schema::new(vec![Field::new("facts", DataType::Utf8, false)]);
|
||||
|
||||
let facts = StringArray::from_iter_values(vec![
|
||||
@@ -90,6 +89,5 @@ fn make_data() -> impl IntoArrow {
|
||||
"The first chatbot was ELIZA, created in the 1960s.",
|
||||
]);
|
||||
let schema = Arc::new(schema);
|
||||
let rb = RecordBatch::try_new(schema.clone(), vec![Arc::new(facts)]).unwrap();
|
||||
Box::new(RecordBatchIterator::new(vec![Ok(rb)], schema))
|
||||
RecordBatch::try_new(schema.clone(), vec![Arc::new(facts)]).unwrap()
|
||||
}
|
||||
|
||||
@@ -8,11 +8,9 @@
|
||||
use std::sync::Arc;
|
||||
|
||||
use arrow_array::types::Float32Type;
|
||||
use arrow_array::{FixedSizeListArray, Int32Array, RecordBatch, RecordBatchIterator};
|
||||
use arrow_array::{FixedSizeListArray, Int32Array, RecordBatch};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use futures::TryStreamExt;
|
||||
|
||||
use lancedb::arrow::IntoArrow;
|
||||
use lancedb::connection::Connection;
|
||||
use lancedb::index::Index;
|
||||
use lancedb::query::{ExecutableQuery, QueryBase};
|
||||
@@ -59,7 +57,7 @@ async fn open_with_existing_tbl() -> Result<()> {
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn create_some_records() -> Result<impl IntoArrow> {
|
||||
fn create_some_records() -> Result<RecordBatch> {
|
||||
const TOTAL: usize = 1000;
|
||||
const DIM: usize = 128;
|
||||
|
||||
@@ -76,25 +74,18 @@ fn create_some_records() -> Result<impl IntoArrow> {
|
||||
]));
|
||||
|
||||
// Create a RecordBatch stream.
|
||||
let batches = RecordBatchIterator::new(
|
||||
vec![RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![
|
||||
Arc::new(Int32Array::from_iter_values(0..TOTAL as i32)),
|
||||
Arc::new(
|
||||
FixedSizeListArray::from_iter_primitive::<Float32Type, _, _>(
|
||||
(0..TOTAL).map(|_| Some(vec![Some(1.0); DIM])),
|
||||
DIM as i32,
|
||||
),
|
||||
),
|
||||
],
|
||||
)
|
||||
.unwrap()]
|
||||
.into_iter()
|
||||
.map(Ok),
|
||||
Ok(RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
);
|
||||
Ok(Box::new(batches))
|
||||
vec![
|
||||
Arc::new(Int32Array::from_iter_values(0..TOTAL as i32)),
|
||||
Arc::new(
|
||||
FixedSizeListArray::from_iter_primitive::<Float32Type, _, _>(
|
||||
(0..TOTAL).map(|_| Some(vec![Some(1.0); DIM])),
|
||||
DIM as i32,
|
||||
),
|
||||
),
|
||||
],
|
||||
)?)
|
||||
}
|
||||
|
||||
async fn create_table(db: &Connection) -> Result<LanceDbTable> {
|
||||
|
||||
@@ -6,8 +6,8 @@
|
||||
use std::collections::HashMap;
|
||||
use std::sync::Arc;
|
||||
|
||||
use arrow_array::RecordBatchReader;
|
||||
use arrow_schema::{Field, SchemaRef};
|
||||
use arrow_array::RecordBatch;
|
||||
use arrow_schema::SchemaRef;
|
||||
use lance::dataset::ReadParams;
|
||||
use lance_namespace::models::{
|
||||
CreateNamespaceRequest, CreateNamespaceResponse, DescribeNamespaceRequest,
|
||||
@@ -17,24 +17,20 @@ use lance_namespace::models::{
|
||||
#[cfg(feature = "aws")]
|
||||
use object_store::aws::AwsCredential;
|
||||
|
||||
use crate::arrow::{IntoArrow, IntoArrowStream, SendableRecordBatchStream};
|
||||
use crate::database::listing::{
|
||||
ListingDatabase, OPT_NEW_TABLE_STORAGE_VERSION, OPT_NEW_TABLE_V2_MANIFEST_PATHS,
|
||||
};
|
||||
use crate::connection::create_table::CreateTableBuilder;
|
||||
use crate::data::scannable::Scannable;
|
||||
use crate::database::listing::ListingDatabase;
|
||||
use crate::database::{
|
||||
CloneTableRequest, CreateTableData, CreateTableMode, CreateTableRequest, Database,
|
||||
DatabaseOptions, OpenTableRequest, ReadConsistency, TableNamesRequest,
|
||||
};
|
||||
use crate::embeddings::{
|
||||
EmbeddingDefinition, EmbeddingFunction, EmbeddingRegistry, MemoryRegistry, WithEmbeddings,
|
||||
CloneTableRequest, Database, DatabaseOptions, OpenTableRequest, ReadConsistency,
|
||||
TableNamesRequest,
|
||||
};
|
||||
use crate::embeddings::{EmbeddingRegistry, MemoryRegistry};
|
||||
use crate::error::{Error, Result};
|
||||
#[cfg(feature = "remote")]
|
||||
use crate::remote::{
|
||||
client::ClientConfig,
|
||||
db::{OPT_REMOTE_API_KEY, OPT_REMOTE_HOST_OVERRIDE, OPT_REMOTE_REGION},
|
||||
};
|
||||
use crate::table::{TableDefinition, WriteOptions};
|
||||
use crate::Table;
|
||||
use lance::io::ObjectStoreParams;
|
||||
pub use lance_encoding::version::LanceFileVersion;
|
||||
@@ -42,6 +38,8 @@ pub use lance_encoding::version::LanceFileVersion;
|
||||
use lance_io::object_store::StorageOptions;
|
||||
use lance_io::object_store::{StorageOptionsAccessor, StorageOptionsProvider};
|
||||
|
||||
mod create_table;
|
||||
|
||||
fn merge_storage_options(
|
||||
store_params: &mut ObjectStoreParams,
|
||||
pairs: impl IntoIterator<Item = (String, String)>,
|
||||
@@ -116,337 +114,6 @@ impl TableNamesBuilder {
|
||||
}
|
||||
}
|
||||
|
||||
pub struct NoData {}
|
||||
|
||||
impl IntoArrow for NoData {
|
||||
fn into_arrow(self) -> Result<Box<dyn arrow_array::RecordBatchReader + Send>> {
|
||||
unreachable!("NoData should never be converted to Arrow")
|
||||
}
|
||||
}
|
||||
|
||||
// Stores the value given from the initial CreateTableBuilder::new call
|
||||
// and defers errors until `execute` is called
|
||||
enum CreateTableBuilderInitialData {
|
||||
None,
|
||||
Iterator(Result<Box<dyn RecordBatchReader + Send>>),
|
||||
Stream(Result<SendableRecordBatchStream>),
|
||||
}
|
||||
|
||||
/// A builder for configuring a [`Connection::create_table`] operation
|
||||
pub struct CreateTableBuilder<const HAS_DATA: bool> {
|
||||
parent: Arc<dyn Database>,
|
||||
embeddings: Vec<(EmbeddingDefinition, Arc<dyn EmbeddingFunction>)>,
|
||||
embedding_registry: Arc<dyn EmbeddingRegistry>,
|
||||
request: CreateTableRequest,
|
||||
// This is a bit clumsy but we defer errors until `execute` is called
|
||||
// to maintain backwards compatibility
|
||||
data: CreateTableBuilderInitialData,
|
||||
}
|
||||
|
||||
// Builder methods that only apply when we have initial data
|
||||
impl CreateTableBuilder<true> {
|
||||
fn new<T: IntoArrow>(
|
||||
parent: Arc<dyn Database>,
|
||||
name: String,
|
||||
data: T,
|
||||
embedding_registry: Arc<dyn EmbeddingRegistry>,
|
||||
) -> Self {
|
||||
let dummy_schema = Arc::new(arrow_schema::Schema::new(Vec::<Field>::default()));
|
||||
Self {
|
||||
parent,
|
||||
request: CreateTableRequest::new(
|
||||
name,
|
||||
CreateTableData::Empty(TableDefinition::new_from_schema(dummy_schema)),
|
||||
),
|
||||
embeddings: Vec::new(),
|
||||
embedding_registry,
|
||||
data: CreateTableBuilderInitialData::Iterator(data.into_arrow()),
|
||||
}
|
||||
}
|
||||
|
||||
fn new_streaming<T: IntoArrowStream>(
|
||||
parent: Arc<dyn Database>,
|
||||
name: String,
|
||||
data: T,
|
||||
embedding_registry: Arc<dyn EmbeddingRegistry>,
|
||||
) -> Self {
|
||||
let dummy_schema = Arc::new(arrow_schema::Schema::new(Vec::<Field>::default()));
|
||||
Self {
|
||||
parent,
|
||||
request: CreateTableRequest::new(
|
||||
name,
|
||||
CreateTableData::Empty(TableDefinition::new_from_schema(dummy_schema)),
|
||||
),
|
||||
embeddings: Vec::new(),
|
||||
embedding_registry,
|
||||
data: CreateTableBuilderInitialData::Stream(data.into_arrow()),
|
||||
}
|
||||
}
|
||||
|
||||
/// Execute the create table operation
|
||||
pub async fn execute(self) -> Result<Table> {
|
||||
let embedding_registry = self.embedding_registry.clone();
|
||||
let parent = self.parent.clone();
|
||||
let request = self.into_request()?;
|
||||
Ok(Table::new_with_embedding_registry(
|
||||
parent.create_table(request).await?,
|
||||
parent,
|
||||
embedding_registry,
|
||||
))
|
||||
}
|
||||
|
||||
fn into_request(self) -> Result<CreateTableRequest> {
|
||||
if self.embeddings.is_empty() {
|
||||
match self.data {
|
||||
CreateTableBuilderInitialData::Iterator(maybe_iter) => {
|
||||
let data = maybe_iter?;
|
||||
Ok(CreateTableRequest {
|
||||
data: CreateTableData::Data(data),
|
||||
..self.request
|
||||
})
|
||||
}
|
||||
CreateTableBuilderInitialData::None => {
|
||||
unreachable!("No data provided for CreateTableBuilder<true>")
|
||||
}
|
||||
CreateTableBuilderInitialData::Stream(maybe_stream) => {
|
||||
let data = maybe_stream?;
|
||||
Ok(CreateTableRequest {
|
||||
data: CreateTableData::StreamingData(data),
|
||||
..self.request
|
||||
})
|
||||
}
|
||||
}
|
||||
} else {
|
||||
let CreateTableBuilderInitialData::Iterator(maybe_iter) = self.data else {
|
||||
return Err(Error::NotSupported { message: "Creating a table with embeddings is currently not support when the input is streaming".to_string() });
|
||||
};
|
||||
let data = maybe_iter?;
|
||||
let data = Box::new(WithEmbeddings::new(data, self.embeddings));
|
||||
Ok(CreateTableRequest {
|
||||
data: CreateTableData::Data(data),
|
||||
..self.request
|
||||
})
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Builder methods that only apply when we do not have initial data
|
||||
impl CreateTableBuilder<false> {
|
||||
fn new(
|
||||
parent: Arc<dyn Database>,
|
||||
name: String,
|
||||
schema: SchemaRef,
|
||||
embedding_registry: Arc<dyn EmbeddingRegistry>,
|
||||
) -> Self {
|
||||
let table_definition = TableDefinition::new_from_schema(schema);
|
||||
Self {
|
||||
parent,
|
||||
request: CreateTableRequest::new(name, CreateTableData::Empty(table_definition)),
|
||||
data: CreateTableBuilderInitialData::None,
|
||||
embeddings: Vec::default(),
|
||||
embedding_registry,
|
||||
}
|
||||
}
|
||||
|
||||
/// Execute the create table operation
|
||||
pub async fn execute(self) -> Result<Table> {
|
||||
let parent = self.parent.clone();
|
||||
let embedding_registry = self.embedding_registry.clone();
|
||||
let request = self.into_request()?;
|
||||
Ok(Table::new_with_embedding_registry(
|
||||
parent.create_table(request).await?,
|
||||
parent,
|
||||
embedding_registry,
|
||||
))
|
||||
}
|
||||
|
||||
fn into_request(self) -> Result<CreateTableRequest> {
|
||||
if self.embeddings.is_empty() {
|
||||
return Ok(self.request);
|
||||
}
|
||||
|
||||
let CreateTableData::Empty(table_def) = self.request.data else {
|
||||
unreachable!("CreateTableBuilder<false> should always have Empty data")
|
||||
};
|
||||
|
||||
let schema = table_def.schema.clone();
|
||||
let empty_batch = arrow_array::RecordBatch::new_empty(schema.clone());
|
||||
|
||||
let reader = Box::new(std::iter::once(Ok(empty_batch)).collect::<Vec<_>>());
|
||||
let reader = arrow_array::RecordBatchIterator::new(reader.into_iter(), schema);
|
||||
let with_embeddings = WithEmbeddings::new(reader, self.embeddings);
|
||||
let table_definition = with_embeddings.table_definition()?;
|
||||
|
||||
Ok(CreateTableRequest {
|
||||
data: CreateTableData::Empty(table_definition),
|
||||
..self.request
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
impl<const HAS_DATA: bool> CreateTableBuilder<HAS_DATA> {
|
||||
/// Set the mode for creating the table
|
||||
///
|
||||
/// This controls what happens if a table with the given name already exists
|
||||
pub fn mode(mut self, mode: CreateTableMode) -> Self {
|
||||
self.request.mode = mode;
|
||||
self
|
||||
}
|
||||
|
||||
/// Apply the given write options when writing the initial data
|
||||
pub fn write_options(mut self, write_options: WriteOptions) -> Self {
|
||||
self.request.write_options = write_options;
|
||||
self
|
||||
}
|
||||
|
||||
/// Set an option for the storage layer.
|
||||
///
|
||||
/// Options already set on the connection will be inherited by the table,
|
||||
/// but can be overridden here.
|
||||
///
|
||||
/// See available options at <https://lancedb.com/docs/storage/>
|
||||
pub fn storage_option(mut self, key: impl Into<String>, value: impl Into<String>) -> Self {
|
||||
let store_params = self
|
||||
.request
|
||||
.write_options
|
||||
.lance_write_params
|
||||
.get_or_insert(Default::default())
|
||||
.store_params
|
||||
.get_or_insert(Default::default());
|
||||
merge_storage_options(store_params, [(key.into(), value.into())]);
|
||||
self
|
||||
}
|
||||
|
||||
/// Set multiple options for the storage layer.
|
||||
///
|
||||
/// Options already set on the connection will be inherited by the table,
|
||||
/// but can be overridden here.
|
||||
///
|
||||
/// See available options at <https://lancedb.com/docs/storage/>
|
||||
pub fn storage_options(
|
||||
mut self,
|
||||
pairs: impl IntoIterator<Item = (impl Into<String>, impl Into<String>)>,
|
||||
) -> Self {
|
||||
let store_params = self
|
||||
.request
|
||||
.write_options
|
||||
.lance_write_params
|
||||
.get_or_insert(Default::default())
|
||||
.store_params
|
||||
.get_or_insert(Default::default());
|
||||
let updates = pairs
|
||||
.into_iter()
|
||||
.map(|(key, value)| (key.into(), value.into()));
|
||||
merge_storage_options(store_params, updates);
|
||||
self
|
||||
}
|
||||
|
||||
/// Add an embedding definition to the table.
|
||||
///
|
||||
/// The `embedding_name` must match the name of an embedding function that
|
||||
/// was previously registered with the connection's [`EmbeddingRegistry`].
|
||||
pub fn add_embedding(mut self, definition: EmbeddingDefinition) -> Result<Self> {
|
||||
// Early verification of the embedding name
|
||||
let embedding_func = self
|
||||
.embedding_registry
|
||||
.get(&definition.embedding_name)
|
||||
.ok_or_else(|| Error::EmbeddingFunctionNotFound {
|
||||
name: definition.embedding_name.clone(),
|
||||
reason: "No embedding function found in the connection's embedding_registry"
|
||||
.to_string(),
|
||||
})?;
|
||||
|
||||
self.embeddings.push((definition, embedding_func));
|
||||
Ok(self)
|
||||
}
|
||||
|
||||
/// Set whether to use V2 manifest paths for the table. (default: false)
|
||||
///
|
||||
/// These paths provide more efficient opening of tables with many
|
||||
/// versions on object stores.
|
||||
///
|
||||
/// <div class="warning">Turning this on will make the dataset unreadable
|
||||
/// for older versions of LanceDB (prior to 0.10.0).</div>
|
||||
///
|
||||
/// To migrate an existing dataset, instead use the
|
||||
/// [[NativeTable::migrate_manifest_paths_v2]].
|
||||
///
|
||||
/// This has no effect in LanceDB Cloud.
|
||||
#[deprecated(since = "0.15.1", note = "Use `database_options` instead")]
|
||||
pub fn enable_v2_manifest_paths(mut self, use_v2_manifest_paths: bool) -> Self {
|
||||
let store_params = self
|
||||
.request
|
||||
.write_options
|
||||
.lance_write_params
|
||||
.get_or_insert_with(Default::default)
|
||||
.store_params
|
||||
.get_or_insert_with(Default::default);
|
||||
let value = if use_v2_manifest_paths {
|
||||
"true".to_string()
|
||||
} else {
|
||||
"false".to_string()
|
||||
};
|
||||
merge_storage_options(
|
||||
store_params,
|
||||
[(OPT_NEW_TABLE_V2_MANIFEST_PATHS.to_string(), value)],
|
||||
);
|
||||
self
|
||||
}
|
||||
|
||||
/// Set the data storage version.
|
||||
///
|
||||
/// The default is `LanceFileVersion::Stable`.
|
||||
#[deprecated(since = "0.15.1", note = "Use `database_options` instead")]
|
||||
pub fn data_storage_version(mut self, data_storage_version: LanceFileVersion) -> Self {
|
||||
let store_params = self
|
||||
.request
|
||||
.write_options
|
||||
.lance_write_params
|
||||
.get_or_insert_with(Default::default)
|
||||
.store_params
|
||||
.get_or_insert_with(Default::default);
|
||||
merge_storage_options(
|
||||
store_params,
|
||||
[(
|
||||
OPT_NEW_TABLE_STORAGE_VERSION.to_string(),
|
||||
data_storage_version.to_string(),
|
||||
)],
|
||||
);
|
||||
self
|
||||
}
|
||||
|
||||
/// Set the namespace for the table
|
||||
pub fn namespace(mut self, namespace: Vec<String>) -> Self {
|
||||
self.request.namespace = namespace;
|
||||
self
|
||||
}
|
||||
|
||||
/// Set a custom location for the table.
|
||||
///
|
||||
/// If not set, the database will derive a location from its URI and the table name.
|
||||
/// This is useful when integrating with namespace systems that manage table locations.
|
||||
pub fn location(mut self, location: impl Into<String>) -> Self {
|
||||
self.request.location = Some(location.into());
|
||||
self
|
||||
}
|
||||
|
||||
/// Set a storage options provider for automatic credential refresh.
|
||||
///
|
||||
/// This allows tables to automatically refresh cloud storage credentials
|
||||
/// when they expire, enabling long-running operations on remote storage.
|
||||
pub fn storage_options_provider(mut self, provider: Arc<dyn StorageOptionsProvider>) -> Self {
|
||||
let store_params = self
|
||||
.request
|
||||
.write_options
|
||||
.lance_write_params
|
||||
.get_or_insert(Default::default())
|
||||
.store_params
|
||||
.get_or_insert(Default::default());
|
||||
set_storage_options_provider(store_params, provider);
|
||||
self
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Clone, Debug)]
|
||||
pub struct OpenTableBuilder {
|
||||
parent: Arc<dyn Database>,
|
||||
@@ -684,35 +351,17 @@ impl Connection {
|
||||
///
|
||||
/// * `name` - The name of the table
|
||||
/// * `initial_data` - The initial data to write to the table
|
||||
pub fn create_table<T: IntoArrow>(
|
||||
pub fn create_table<T: Scannable + 'static>(
|
||||
&self,
|
||||
name: impl Into<String>,
|
||||
initial_data: T,
|
||||
) -> CreateTableBuilder<true> {
|
||||
CreateTableBuilder::<true>::new(
|
||||
) -> CreateTableBuilder {
|
||||
let initial_data = Box::new(initial_data);
|
||||
CreateTableBuilder::new(
|
||||
self.internal.clone(),
|
||||
self.embedding_registry.clone(),
|
||||
name.into(),
|
||||
initial_data,
|
||||
self.embedding_registry.clone(),
|
||||
)
|
||||
}
|
||||
|
||||
/// Create a new table from a stream of data
|
||||
///
|
||||
/// # Parameters
|
||||
///
|
||||
/// * `name` - The name of the table
|
||||
/// * `initial_data` - The initial data to write to the table
|
||||
pub fn create_table_streaming<T: IntoArrowStream>(
|
||||
&self,
|
||||
name: impl Into<String>,
|
||||
initial_data: T,
|
||||
) -> CreateTableBuilder<true> {
|
||||
CreateTableBuilder::<true>::new_streaming(
|
||||
self.internal.clone(),
|
||||
name.into(),
|
||||
initial_data,
|
||||
self.embedding_registry.clone(),
|
||||
)
|
||||
}
|
||||
|
||||
@@ -726,13 +375,9 @@ impl Connection {
|
||||
&self,
|
||||
name: impl Into<String>,
|
||||
schema: SchemaRef,
|
||||
) -> CreateTableBuilder<false> {
|
||||
CreateTableBuilder::<false>::new(
|
||||
self.internal.clone(),
|
||||
name.into(),
|
||||
schema,
|
||||
self.embedding_registry.clone(),
|
||||
)
|
||||
) -> CreateTableBuilder {
|
||||
let empty_batch = RecordBatch::new_empty(schema);
|
||||
self.create_table(name, empty_batch)
|
||||
}
|
||||
|
||||
/// Open an existing table in the database
|
||||
@@ -1349,20 +994,11 @@ mod test_utils {
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use crate::database::listing::{ListingDatabaseOptions, NewTableConfig};
|
||||
use crate::query::QueryBase;
|
||||
use crate::query::{ExecutableQuery, QueryExecutionOptions};
|
||||
use crate::test_utils::connection::new_test_connection;
|
||||
use arrow::compute::concat_batches;
|
||||
use arrow_array::RecordBatchReader;
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use datafusion_physical_plan::stream::RecordBatchStreamAdapter;
|
||||
use futures::{stream, TryStreamExt};
|
||||
use lance_core::error::{ArrowResult, DataFusionResult};
|
||||
use lance_testing::datagen::{BatchGenerator, IncrementingInt32};
|
||||
use tempfile::tempdir;
|
||||
|
||||
use crate::arrow::SimpleRecordBatchStream;
|
||||
use crate::test_utils::connection::new_test_connection;
|
||||
|
||||
use super::*;
|
||||
|
||||
@@ -1478,139 +1114,6 @@ mod tests {
|
||||
assert_eq!(tables, vec!["table1".to_owned()]);
|
||||
}
|
||||
|
||||
fn make_data() -> Box<dyn RecordBatchReader + Send + 'static> {
|
||||
let id = Box::new(IncrementingInt32::new().named("id".to_string()));
|
||||
Box::new(BatchGenerator::new().col(id).batches(10, 2000))
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_table_v2() {
|
||||
let tmp_dir = tempdir().unwrap();
|
||||
let uri = tmp_dir.path().to_str().unwrap();
|
||||
let db = connect(uri)
|
||||
.database_options(&ListingDatabaseOptions {
|
||||
new_table_config: NewTableConfig {
|
||||
data_storage_version: Some(LanceFileVersion::Legacy),
|
||||
..Default::default()
|
||||
},
|
||||
..Default::default()
|
||||
})
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let tbl = db
|
||||
.create_table("v1_test", make_data())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// In v1 the row group size will trump max_batch_length
|
||||
let batches = tbl
|
||||
.query()
|
||||
.limit(20000)
|
||||
.execute_with_options(QueryExecutionOptions {
|
||||
max_batch_length: 50000,
|
||||
..Default::default()
|
||||
})
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect::<Vec<_>>()
|
||||
.await
|
||||
.unwrap();
|
||||
assert_eq!(batches.len(), 20);
|
||||
|
||||
let db = connect(uri)
|
||||
.database_options(&ListingDatabaseOptions {
|
||||
new_table_config: NewTableConfig {
|
||||
data_storage_version: Some(LanceFileVersion::Stable),
|
||||
..Default::default()
|
||||
},
|
||||
..Default::default()
|
||||
})
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let tbl = db
|
||||
.create_table("v2_test", make_data())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// In v2 the page size is much bigger than 50k so we should get a single batch
|
||||
let batches = tbl
|
||||
.query()
|
||||
.execute_with_options(QueryExecutionOptions {
|
||||
max_batch_length: 50000,
|
||||
..Default::default()
|
||||
})
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect::<Vec<_>>()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
assert_eq!(batches.len(), 1);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_table_streaming() {
|
||||
let tmp_dir = tempdir().unwrap();
|
||||
|
||||
let uri = tmp_dir.path().to_str().unwrap();
|
||||
let db = connect(uri).execute().await.unwrap();
|
||||
|
||||
let batches = make_data().collect::<ArrowResult<Vec<_>>>().unwrap();
|
||||
|
||||
let schema = batches.first().unwrap().schema();
|
||||
let one_batch = concat_batches(&schema, batches.iter()).unwrap();
|
||||
|
||||
let ldb_stream = stream::iter(batches.clone().into_iter().map(Result::Ok));
|
||||
let ldb_stream: SendableRecordBatchStream =
|
||||
Box::pin(SimpleRecordBatchStream::new(ldb_stream, schema.clone()));
|
||||
|
||||
let tbl1 = db
|
||||
.create_table_streaming("one", ldb_stream)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let df_stream = stream::iter(batches.into_iter().map(DataFusionResult::Ok));
|
||||
let df_stream: datafusion_physical_plan::SendableRecordBatchStream =
|
||||
Box::pin(RecordBatchStreamAdapter::new(schema.clone(), df_stream));
|
||||
|
||||
let tbl2 = db
|
||||
.create_table_streaming("two", df_stream)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let tbl1_data = tbl1
|
||||
.query()
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect::<Vec<_>>()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let tbl1_data = concat_batches(&schema, tbl1_data.iter()).unwrap();
|
||||
assert_eq!(tbl1_data, one_batch);
|
||||
|
||||
let tbl2_data = tbl2
|
||||
.query()
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect::<Vec<_>>()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let tbl2_data = concat_batches(&schema, tbl2_data.iter()).unwrap();
|
||||
assert_eq!(tbl2_data, one_batch);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn drop_table() {
|
||||
let tc = new_test_connection().await.unwrap();
|
||||
@@ -1640,41 +1143,6 @@ mod tests {
|
||||
assert_eq!(tables.len(), 0);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_table_already_exists() {
|
||||
let tmp_dir = tempdir().unwrap();
|
||||
let uri = tmp_dir.path().to_str().unwrap();
|
||||
let db = connect(uri).execute().await.unwrap();
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("x", DataType::Int32, false)]));
|
||||
db.create_empty_table("test", schema.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
// TODO: None of the open table options are "inspectable" right now but once one is we
|
||||
// should assert we are passing these options in correctly
|
||||
db.create_empty_table("test", schema)
|
||||
.mode(CreateTableMode::exist_ok(|mut req| {
|
||||
req.index_cache_size = Some(16);
|
||||
req
|
||||
}))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let other_schema = Arc::new(Schema::new(vec![Field::new("y", DataType::Int32, false)]));
|
||||
assert!(db
|
||||
.create_empty_table("test", other_schema.clone())
|
||||
.execute()
|
||||
.await
|
||||
.is_err());
|
||||
let overwritten = db
|
||||
.create_empty_table("test", other_schema.clone())
|
||||
.mode(CreateTableMode::Overwrite)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
assert_eq!(other_schema, overwritten.schema().await.unwrap());
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_clone_table() {
|
||||
let tmp_dir = tempdir().unwrap();
|
||||
@@ -1685,7 +1153,8 @@ mod tests {
|
||||
let mut batch_gen = BatchGenerator::new()
|
||||
.col(Box::new(IncrementingInt32::new().named("id")))
|
||||
.col(Box::new(IncrementingInt32::new().named("value")));
|
||||
let reader = batch_gen.batches(5, 100);
|
||||
let reader: Box<dyn arrow_array::RecordBatchReader + Send> =
|
||||
Box::new(batch_gen.batches(5, 100));
|
||||
|
||||
let source_table = db
|
||||
.create_table("source_table", reader)
|
||||
@@ -1720,128 +1189,4 @@ mod tests {
|
||||
let cloned_count = cloned_table.count_rows(None).await.unwrap();
|
||||
assert_eq!(source_count, cloned_count);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_empty_table_with_embeddings() {
|
||||
use crate::embeddings::{EmbeddingDefinition, EmbeddingFunction};
|
||||
use arrow_array::{
|
||||
Array, FixedSizeListArray, Float32Array, RecordBatch, RecordBatchIterator, StringArray,
|
||||
};
|
||||
use std::borrow::Cow;
|
||||
|
||||
#[derive(Debug, Clone)]
|
||||
struct MockEmbedding {
|
||||
dim: usize,
|
||||
}
|
||||
|
||||
impl EmbeddingFunction for MockEmbedding {
|
||||
fn name(&self) -> &str {
|
||||
"test_embedding"
|
||||
}
|
||||
|
||||
fn source_type(&self) -> Result<Cow<'_, DataType>> {
|
||||
Ok(Cow::Owned(DataType::Utf8))
|
||||
}
|
||||
|
||||
fn dest_type(&self) -> Result<Cow<'_, DataType>> {
|
||||
Ok(Cow::Owned(DataType::new_fixed_size_list(
|
||||
DataType::Float32,
|
||||
self.dim as i32,
|
||||
true,
|
||||
)))
|
||||
}
|
||||
|
||||
fn compute_source_embeddings(&self, source: Arc<dyn Array>) -> Result<Arc<dyn Array>> {
|
||||
let len = source.len();
|
||||
let values = vec![1.0f32; len * self.dim];
|
||||
let values = Arc::new(Float32Array::from(values));
|
||||
let field = Arc::new(Field::new("item", DataType::Float32, true));
|
||||
Ok(Arc::new(FixedSizeListArray::new(
|
||||
field,
|
||||
self.dim as i32,
|
||||
values,
|
||||
None,
|
||||
)))
|
||||
}
|
||||
|
||||
fn compute_query_embeddings(&self, _input: Arc<dyn Array>) -> Result<Arc<dyn Array>> {
|
||||
unimplemented!()
|
||||
}
|
||||
}
|
||||
|
||||
let tmp_dir = tempdir().unwrap();
|
||||
let uri = tmp_dir.path().to_str().unwrap();
|
||||
let db = connect(uri).execute().await.unwrap();
|
||||
|
||||
let embed_func = Arc::new(MockEmbedding { dim: 128 });
|
||||
db.embedding_registry()
|
||||
.register("test_embedding", embed_func.clone())
|
||||
.unwrap();
|
||||
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("name", DataType::Utf8, true)]));
|
||||
let ed = EmbeddingDefinition {
|
||||
source_column: "name".to_owned(),
|
||||
dest_column: Some("name_embedding".to_owned()),
|
||||
embedding_name: "test_embedding".to_owned(),
|
||||
};
|
||||
|
||||
let table = db
|
||||
.create_empty_table("test", schema)
|
||||
.mode(CreateTableMode::Overwrite)
|
||||
.add_embedding(ed)
|
||||
.unwrap()
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let table_schema = table.schema().await.unwrap();
|
||||
assert!(table_schema.column_with_name("name").is_some());
|
||||
assert!(table_schema.column_with_name("name_embedding").is_some());
|
||||
|
||||
let embedding_field = table_schema.field_with_name("name_embedding").unwrap();
|
||||
assert_eq!(
|
||||
embedding_field.data_type(),
|
||||
&DataType::new_fixed_size_list(DataType::Float32, 128, true)
|
||||
);
|
||||
|
||||
let input_schema = Arc::new(Schema::new(vec![Field::new("name", DataType::Utf8, true)]));
|
||||
let input_batch = RecordBatch::try_new(
|
||||
input_schema.clone(),
|
||||
vec![Arc::new(StringArray::from(vec![
|
||||
Some("Alice"),
|
||||
Some("Bob"),
|
||||
Some("Charlie"),
|
||||
]))],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let input_reader = Box::new(RecordBatchIterator::new(
|
||||
vec![Ok(input_batch)].into_iter(),
|
||||
input_schema,
|
||||
));
|
||||
|
||||
table.add(input_reader).execute().await.unwrap();
|
||||
|
||||
let results = table
|
||||
.query()
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect::<Vec<_>>()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
assert_eq!(results.len(), 1);
|
||||
let batch = &results[0];
|
||||
assert_eq!(batch.num_rows(), 3);
|
||||
assert!(batch.column_by_name("name_embedding").is_some());
|
||||
|
||||
let embedding_col = batch
|
||||
.column_by_name("name_embedding")
|
||||
.unwrap()
|
||||
.as_any()
|
||||
.downcast_ref::<FixedSizeListArray>()
|
||||
.unwrap();
|
||||
assert_eq!(embedding_col.len(), 3);
|
||||
}
|
||||
}
|
||||
|
||||
612
rust/lancedb/src/connection/create_table.rs
Normal file
612
rust/lancedb/src/connection/create_table.rs
Normal file
@@ -0,0 +1,612 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
use std::sync::Arc;
|
||||
|
||||
use lance_io::object_store::StorageOptionsProvider;
|
||||
|
||||
use crate::{
|
||||
connection::{merge_storage_options, set_storage_options_provider},
|
||||
data::scannable::{Scannable, WithEmbeddingsScannable},
|
||||
database::{CreateTableMode, CreateTableRequest, Database},
|
||||
embeddings::{EmbeddingDefinition, EmbeddingFunction, EmbeddingRegistry},
|
||||
table::WriteOptions,
|
||||
Error, Result, Table,
|
||||
};
|
||||
|
||||
pub struct CreateTableBuilder {
|
||||
parent: Arc<dyn Database>,
|
||||
embeddings: Vec<(EmbeddingDefinition, Arc<dyn EmbeddingFunction>)>,
|
||||
embedding_registry: Arc<dyn EmbeddingRegistry>,
|
||||
request: CreateTableRequest,
|
||||
}
|
||||
|
||||
impl CreateTableBuilder {
|
||||
pub(super) fn new(
|
||||
parent: Arc<dyn Database>,
|
||||
embedding_registry: Arc<dyn EmbeddingRegistry>,
|
||||
name: String,
|
||||
data: Box<dyn Scannable>,
|
||||
) -> Self {
|
||||
Self {
|
||||
parent,
|
||||
embeddings: Vec::new(),
|
||||
embedding_registry,
|
||||
request: CreateTableRequest::new(name, data),
|
||||
}
|
||||
}
|
||||
|
||||
/// Set the mode for creating the table
|
||||
///
|
||||
/// This controls what happens if a table with the given name already exists
|
||||
pub fn mode(mut self, mode: CreateTableMode) -> Self {
|
||||
self.request.mode = mode;
|
||||
self
|
||||
}
|
||||
|
||||
/// Apply the given write options when writing the initial data
|
||||
pub fn write_options(mut self, write_options: WriteOptions) -> Self {
|
||||
self.request.write_options = write_options;
|
||||
self
|
||||
}
|
||||
|
||||
/// Set an option for the storage layer.
|
||||
///
|
||||
/// Options already set on the connection will be inherited by the table,
|
||||
/// but can be overridden here.
|
||||
///
|
||||
/// See available options at <https://lancedb.com/docs/storage/>
|
||||
pub fn storage_option(mut self, key: impl Into<String>, value: impl Into<String>) -> Self {
|
||||
let store_params = self
|
||||
.request
|
||||
.write_options
|
||||
.lance_write_params
|
||||
.get_or_insert(Default::default())
|
||||
.store_params
|
||||
.get_or_insert(Default::default());
|
||||
merge_storage_options(store_params, [(key.into(), value.into())]);
|
||||
self
|
||||
}
|
||||
|
||||
/// Set multiple options for the storage layer.
|
||||
///
|
||||
/// Options already set on the connection will be inherited by the table,
|
||||
/// but can be overridden here.
|
||||
///
|
||||
/// See available options at <https://lancedb.com/docs/storage/>
|
||||
pub fn storage_options(
|
||||
mut self,
|
||||
pairs: impl IntoIterator<Item = (impl Into<String>, impl Into<String>)>,
|
||||
) -> Self {
|
||||
let store_params = self
|
||||
.request
|
||||
.write_options
|
||||
.lance_write_params
|
||||
.get_or_insert(Default::default())
|
||||
.store_params
|
||||
.get_or_insert(Default::default());
|
||||
let updates = pairs
|
||||
.into_iter()
|
||||
.map(|(key, value)| (key.into(), value.into()));
|
||||
merge_storage_options(store_params, updates);
|
||||
self
|
||||
}
|
||||
|
||||
/// Add an embedding definition to the table.
|
||||
///
|
||||
/// The `embedding_name` must match the name of an embedding function that
|
||||
/// was previously registered with the connection's [`EmbeddingRegistry`].
|
||||
pub fn add_embedding(mut self, definition: EmbeddingDefinition) -> Result<Self> {
|
||||
// Early verification of the embedding name
|
||||
let embedding_func = self
|
||||
.embedding_registry
|
||||
.get(&definition.embedding_name)
|
||||
.ok_or_else(|| Error::EmbeddingFunctionNotFound {
|
||||
name: definition.embedding_name.clone(),
|
||||
reason: "No embedding function found in the connection's embedding_registry"
|
||||
.to_string(),
|
||||
})?;
|
||||
|
||||
self.embeddings.push((definition, embedding_func));
|
||||
Ok(self)
|
||||
}
|
||||
|
||||
/// Set the namespace for the table
|
||||
pub fn namespace(mut self, namespace: Vec<String>) -> Self {
|
||||
self.request.namespace = namespace;
|
||||
self
|
||||
}
|
||||
|
||||
/// Set a custom location for the table.
|
||||
///
|
||||
/// If not set, the database will derive a location from its URI and the table name.
|
||||
/// This is useful when integrating with namespace systems that manage table locations.
|
||||
pub fn location(mut self, location: impl Into<String>) -> Self {
|
||||
self.request.location = Some(location.into());
|
||||
self
|
||||
}
|
||||
|
||||
/// Set a storage options provider for automatic credential refresh.
|
||||
///
|
||||
/// This allows tables to automatically refresh cloud storage credentials
|
||||
/// when they expire, enabling long-running operations on remote storage.
|
||||
pub fn storage_options_provider(mut self, provider: Arc<dyn StorageOptionsProvider>) -> Self {
|
||||
let store_params = self
|
||||
.request
|
||||
.write_options
|
||||
.lance_write_params
|
||||
.get_or_insert(Default::default())
|
||||
.store_params
|
||||
.get_or_insert(Default::default());
|
||||
set_storage_options_provider(store_params, provider);
|
||||
self
|
||||
}
|
||||
|
||||
/// Execute the create table operation
|
||||
pub async fn execute(mut self) -> Result<Table> {
|
||||
let embedding_registry = self.embedding_registry.clone();
|
||||
let parent = self.parent.clone();
|
||||
|
||||
// If embeddings were configured via add_embedding(), wrap the data
|
||||
if !self.embeddings.is_empty() {
|
||||
let wrapped_data: Box<dyn Scannable> = Box::new(WithEmbeddingsScannable::try_new(
|
||||
self.request.data,
|
||||
self.embeddings,
|
||||
)?);
|
||||
self.request.data = wrapped_data;
|
||||
}
|
||||
|
||||
Ok(Table::new_with_embedding_registry(
|
||||
parent.create_table(self.request).await?,
|
||||
parent,
|
||||
embedding_registry,
|
||||
))
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use arrow_array::{
|
||||
record_batch, Array, FixedSizeListArray, Float32Array, RecordBatch, RecordBatchIterator,
|
||||
};
|
||||
use arrow_schema::{ArrowError, DataType, Field, Schema};
|
||||
use futures::TryStreamExt;
|
||||
use lance_file::version::LanceFileVersion;
|
||||
use tempfile::tempdir;
|
||||
|
||||
use crate::{
|
||||
arrow::{SendableRecordBatchStream, SimpleRecordBatchStream},
|
||||
connect,
|
||||
database::listing::{ListingDatabaseOptions, NewTableConfig},
|
||||
embeddings::{EmbeddingDefinition, EmbeddingFunction, MemoryRegistry},
|
||||
query::{ExecutableQuery, QueryBase, Select},
|
||||
test_utils::embeddings::MockEmbed,
|
||||
};
|
||||
use std::borrow::Cow;
|
||||
|
||||
use super::*;
|
||||
|
||||
#[tokio::test]
|
||||
async fn create_empty_table() {
|
||||
let db = connect("memory://").execute().await.unwrap();
|
||||
let schema = Arc::new(Schema::new(vec![
|
||||
Field::new("id", DataType::Int64, false),
|
||||
Field::new("value", DataType::Float64, false),
|
||||
]));
|
||||
db.create_empty_table("name", schema.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let table = db.open_table("name").execute().await.unwrap();
|
||||
assert_eq!(table.schema().await.unwrap(), schema);
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 0);
|
||||
}
|
||||
|
||||
async fn test_create_table_with_data<T>(data: T)
|
||||
where
|
||||
T: Scannable + 'static,
|
||||
{
|
||||
let db = connect("memory://").execute().await.unwrap();
|
||||
let schema = data.schema();
|
||||
db.create_table("data_table", data).execute().await.unwrap();
|
||||
let table = db.open_table("data_table").execute().await.unwrap();
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 3);
|
||||
assert_eq!(table.schema().await.unwrap(), schema);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn create_table_with_batch() {
|
||||
let batch = record_batch!(("id", Int64, [1, 2, 3])).unwrap();
|
||||
test_create_table_with_data(batch).await;
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_table_with_vec_batch() {
|
||||
let data = vec![
|
||||
record_batch!(("id", Int64, [1, 2])).unwrap(),
|
||||
record_batch!(("id", Int64, [3])).unwrap(),
|
||||
];
|
||||
test_create_table_with_data(data).await;
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_table_with_record_batch_reader() {
|
||||
let data = vec![
|
||||
record_batch!(("id", Int64, [1, 2])).unwrap(),
|
||||
record_batch!(("id", Int64, [3])).unwrap(),
|
||||
];
|
||||
let schema = data[0].schema();
|
||||
let reader: Box<dyn arrow_array::RecordBatchReader + Send> = Box::new(
|
||||
RecordBatchIterator::new(data.into_iter().map(Ok), schema.clone()),
|
||||
);
|
||||
test_create_table_with_data(reader).await;
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_table_with_stream() {
|
||||
let data = vec![
|
||||
record_batch!(("id", Int64, [1, 2])).unwrap(),
|
||||
record_batch!(("id", Int64, [3])).unwrap(),
|
||||
];
|
||||
let schema = data[0].schema();
|
||||
let inner = futures::stream::iter(data.into_iter().map(Ok));
|
||||
let stream: SendableRecordBatchStream = Box::pin(SimpleRecordBatchStream {
|
||||
schema,
|
||||
stream: inner,
|
||||
});
|
||||
test_create_table_with_data(stream).await;
|
||||
}
|
||||
|
||||
#[derive(Debug)]
|
||||
struct MyError;
|
||||
|
||||
impl std::fmt::Display for MyError {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
|
||||
write!(f, "MyError occurred")
|
||||
}
|
||||
}
|
||||
|
||||
impl std::error::Error for MyError {}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_preserves_reader_error() {
|
||||
let first_batch = record_batch!(("id", Int64, [1, 2])).unwrap();
|
||||
let schema = first_batch.schema();
|
||||
let iterator = vec![
|
||||
Ok(first_batch),
|
||||
Err(ArrowError::ExternalError(Box::new(MyError))),
|
||||
];
|
||||
let reader: Box<dyn arrow_array::RecordBatchReader + Send> = Box::new(
|
||||
RecordBatchIterator::new(iterator.into_iter(), schema.clone()),
|
||||
);
|
||||
|
||||
let db = connect("memory://").execute().await.unwrap();
|
||||
let result = db.create_table("failing_table", reader).execute().await;
|
||||
|
||||
assert!(result.is_err());
|
||||
// TODO: when we upgrade to Lance 2.0.0, this should pass
|
||||
// assert!(matches!(result, Err(Error::External { source})
|
||||
// if source.downcast_ref::<MyError>().is_some()
|
||||
// ));
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_preserves_stream_error() {
|
||||
let first_batch = record_batch!(("id", Int64, [1, 2])).unwrap();
|
||||
let schema = first_batch.schema();
|
||||
let iterator = vec![
|
||||
Ok(first_batch),
|
||||
Err(Error::External {
|
||||
source: Box::new(MyError),
|
||||
}),
|
||||
];
|
||||
let stream = futures::stream::iter(iterator);
|
||||
let stream: SendableRecordBatchStream = Box::pin(SimpleRecordBatchStream {
|
||||
schema: schema.clone(),
|
||||
stream,
|
||||
});
|
||||
|
||||
let db = connect("memory://").execute().await.unwrap();
|
||||
let result = db
|
||||
.create_table("failing_stream_table", stream)
|
||||
.execute()
|
||||
.await;
|
||||
|
||||
assert!(result.is_err());
|
||||
// TODO: when we upgrade to Lance 2.0.0, this should pass
|
||||
// assert!(matches!(result, Err(Error::External { source})
|
||||
// if source.downcast_ref::<MyError>().is_some()
|
||||
// ));
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
#[allow(deprecated)]
|
||||
async fn test_create_table_with_storage_options() {
|
||||
let batch = record_batch!(("id", Int64, [1, 2, 3])).unwrap();
|
||||
let db = connect("memory://").execute().await.unwrap();
|
||||
|
||||
let table = db
|
||||
.create_table("options_table", batch)
|
||||
.storage_option("timeout", "30s")
|
||||
.storage_options([("retry_count", "3")])
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let final_options = table.storage_options().await.unwrap();
|
||||
assert_eq!(final_options.get("timeout"), Some(&"30s".to_string()));
|
||||
assert_eq!(final_options.get("retry_count"), Some(&"3".to_string()));
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_table_unregistered_embedding() {
|
||||
let db = connect("memory://").execute().await.unwrap();
|
||||
let batch = record_batch!(("text", Utf8, ["hello", "world"])).unwrap();
|
||||
|
||||
// Try to add an embedding that doesn't exist in the registry
|
||||
let result = db
|
||||
.create_table("embed_table", batch)
|
||||
.add_embedding(EmbeddingDefinition::new(
|
||||
"text",
|
||||
"nonexistent_embedding_function",
|
||||
None::<&str>,
|
||||
));
|
||||
|
||||
match result {
|
||||
Err(Error::EmbeddingFunctionNotFound { name, .. }) => {
|
||||
assert_eq!(name, "nonexistent_embedding_function");
|
||||
}
|
||||
Err(other) => panic!("Expected EmbeddingFunctionNotFound error, got: {:?}", other),
|
||||
Ok(_) => panic!("Expected error, but got Ok"),
|
||||
}
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_table_already_exists() {
|
||||
let tmp_dir = tempdir().unwrap();
|
||||
let uri = tmp_dir.path().to_str().unwrap();
|
||||
let db = connect(uri).execute().await.unwrap();
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("x", DataType::Int32, false)]));
|
||||
db.create_empty_table("test", schema.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
db.create_empty_table("test", schema)
|
||||
.mode(CreateTableMode::exist_ok(|mut req| {
|
||||
req.index_cache_size = Some(16);
|
||||
req
|
||||
}))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let other_schema = Arc::new(Schema::new(vec![Field::new("y", DataType::Int32, false)]));
|
||||
assert!(db
|
||||
.create_empty_table("test", other_schema.clone())
|
||||
.execute()
|
||||
.await
|
||||
.is_err()); // TODO: assert what this error is
|
||||
let overwritten = db
|
||||
.create_empty_table("test", other_schema.clone())
|
||||
.mode(CreateTableMode::Overwrite)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
assert_eq!(other_schema, overwritten.schema().await.unwrap());
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
#[rstest::rstest]
|
||||
#[case(LanceFileVersion::Legacy)]
|
||||
#[case(LanceFileVersion::Stable)]
|
||||
async fn test_create_table_with_storage_version(
|
||||
#[case] data_storage_version: LanceFileVersion,
|
||||
) {
|
||||
let db = connect("memory://")
|
||||
.database_options(&ListingDatabaseOptions {
|
||||
new_table_config: NewTableConfig {
|
||||
data_storage_version: Some(data_storage_version),
|
||||
..Default::default()
|
||||
},
|
||||
..Default::default()
|
||||
})
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let batch = record_batch!(("id", Int64, [1, 2, 3])).unwrap();
|
||||
let table = db
|
||||
.create_table("legacy_table", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let native_table = table.as_native().unwrap();
|
||||
let storage_format = native_table
|
||||
.manifest()
|
||||
.await
|
||||
.unwrap()
|
||||
.data_storage_format
|
||||
.lance_file_version()
|
||||
.unwrap();
|
||||
// Compare resolved versions since Stable/Next are aliases that resolve at storage time
|
||||
assert_eq!(storage_format.resolve(), data_storage_version.resolve());
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_table_with_embedding() {
|
||||
// Register the mock embedding function
|
||||
let registry = Arc::new(MemoryRegistry::new());
|
||||
let mock_embedding: Arc<dyn EmbeddingFunction> = Arc::new(MockEmbed::new("mock", 4));
|
||||
registry.register("mock", mock_embedding).unwrap();
|
||||
|
||||
// Connect with the custom registry
|
||||
let conn = connect("memory://")
|
||||
.embedding_registry(registry)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Create data without the embedding column
|
||||
let batch = record_batch!(("text", Utf8, ["hello", "world", "test"])).unwrap();
|
||||
|
||||
// Create table with add_embedding - embeddings should be computed automatically
|
||||
let table = conn
|
||||
.create_table("embed_test", batch)
|
||||
.add_embedding(EmbeddingDefinition::new(
|
||||
"text",
|
||||
"mock",
|
||||
Some("text_embedding"),
|
||||
))
|
||||
.unwrap()
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Verify row count
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 3);
|
||||
|
||||
// Verify the schema includes the embedding column
|
||||
let result_schema = table.schema().await.unwrap();
|
||||
assert_eq!(result_schema.fields().len(), 2);
|
||||
assert_eq!(result_schema.field(0).name(), "text");
|
||||
assert_eq!(result_schema.field(1).name(), "text_embedding");
|
||||
|
||||
// Verify the embedding column has the correct type
|
||||
assert!(matches!(
|
||||
result_schema.field(1).data_type(),
|
||||
DataType::FixedSizeList(_, 4)
|
||||
));
|
||||
|
||||
// Query to verify the embeddings were computed
|
||||
let results: Vec<RecordBatch> = table
|
||||
.query()
|
||||
.select(Select::columns(&["text", "text_embedding"]))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let total_rows: usize = results.iter().map(|b| b.num_rows()).sum();
|
||||
assert_eq!(total_rows, 3);
|
||||
|
||||
// Check that all rows have embedding values (not null)
|
||||
for batch in &results {
|
||||
let embedding_col = batch.column(1);
|
||||
assert_eq!(embedding_col.null_count(), 0);
|
||||
assert_eq!(embedding_col.len(), batch.num_rows());
|
||||
}
|
||||
|
||||
// Verify the schema metadata contains the column definitions
|
||||
assert!(
|
||||
result_schema
|
||||
.metadata
|
||||
.contains_key("lancedb::column_definitions"),
|
||||
"Schema metadata should contain column definitions"
|
||||
);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_create_empty_table_with_embeddings() {
|
||||
#[derive(Debug, Clone)]
|
||||
struct MockEmbedding {
|
||||
dim: usize,
|
||||
}
|
||||
|
||||
impl EmbeddingFunction for MockEmbedding {
|
||||
fn name(&self) -> &str {
|
||||
"test_embedding"
|
||||
}
|
||||
|
||||
fn source_type(&self) -> Result<Cow<'_, DataType>> {
|
||||
Ok(Cow::Owned(DataType::Utf8))
|
||||
}
|
||||
|
||||
fn dest_type(&self) -> Result<Cow<'_, DataType>> {
|
||||
Ok(Cow::Owned(DataType::new_fixed_size_list(
|
||||
DataType::Float32,
|
||||
self.dim as i32,
|
||||
true,
|
||||
)))
|
||||
}
|
||||
|
||||
fn compute_source_embeddings(&self, source: Arc<dyn Array>) -> Result<Arc<dyn Array>> {
|
||||
let len = source.len();
|
||||
let values = vec![1.0f32; len * self.dim];
|
||||
let values = Arc::new(Float32Array::from(values));
|
||||
let field = Arc::new(Field::new("item", DataType::Float32, true));
|
||||
Ok(Arc::new(FixedSizeListArray::new(
|
||||
field,
|
||||
self.dim as i32,
|
||||
values,
|
||||
None,
|
||||
)))
|
||||
}
|
||||
|
||||
fn compute_query_embeddings(&self, _input: Arc<dyn Array>) -> Result<Arc<dyn Array>> {
|
||||
unimplemented!()
|
||||
}
|
||||
}
|
||||
|
||||
let tmp_dir = tempdir().unwrap();
|
||||
let uri = tmp_dir.path().to_str().unwrap();
|
||||
let db = connect(uri).execute().await.unwrap();
|
||||
|
||||
let embed_func = Arc::new(MockEmbedding { dim: 128 });
|
||||
db.embedding_registry()
|
||||
.register("test_embedding", embed_func.clone())
|
||||
.unwrap();
|
||||
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("name", DataType::Utf8, true)]));
|
||||
let ed = EmbeddingDefinition {
|
||||
source_column: "name".to_owned(),
|
||||
dest_column: Some("name_embedding".to_owned()),
|
||||
embedding_name: "test_embedding".to_owned(),
|
||||
};
|
||||
|
||||
let table = db
|
||||
.create_empty_table("test", schema)
|
||||
.mode(CreateTableMode::Overwrite)
|
||||
.add_embedding(ed)
|
||||
.unwrap()
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let table_schema = table.schema().await.unwrap();
|
||||
assert!(table_schema.column_with_name("name").is_some());
|
||||
assert!(table_schema.column_with_name("name_embedding").is_some());
|
||||
|
||||
let embedding_field = table_schema.field_with_name("name_embedding").unwrap();
|
||||
assert_eq!(
|
||||
embedding_field.data_type(),
|
||||
&DataType::new_fixed_size_list(DataType::Float32, 128, true)
|
||||
);
|
||||
|
||||
let input_batch = record_batch!(("name", Utf8, ["Alice", "Bob", "Charlie"])).unwrap();
|
||||
table.add(input_batch).execute().await.unwrap();
|
||||
|
||||
let results = table
|
||||
.query()
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect::<Vec<_>>()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
assert_eq!(results.len(), 1);
|
||||
let batch = &results[0];
|
||||
assert_eq!(batch.num_rows(), 3);
|
||||
assert!(batch.column_by_name("name_embedding").is_some());
|
||||
|
||||
let embedding_col = batch
|
||||
.column_by_name("name_embedding")
|
||||
.unwrap()
|
||||
.as_any()
|
||||
.downcast_ref::<FixedSizeListArray>()
|
||||
.unwrap();
|
||||
assert_eq!(embedding_col.len(), 3);
|
||||
}
|
||||
}
|
||||
@@ -5,3 +5,4 @@
|
||||
|
||||
pub mod inspect;
|
||||
pub mod sanitize;
|
||||
pub mod scannable;
|
||||
|
||||
580
rust/lancedb/src/data/scannable.rs
Normal file
580
rust/lancedb/src/data/scannable.rs
Normal file
@@ -0,0 +1,580 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
//! Data source abstraction for LanceDB.
|
||||
//!
|
||||
//! This module provides a [`Scannable`] trait that allows input data sources to express
|
||||
//! capabilities (row count, rescannability) so the insert pipeline can make
|
||||
//! better decisions about write parallelism and retry strategies.
|
||||
|
||||
use std::sync::Arc;
|
||||
|
||||
use arrow_array::{RecordBatch, RecordBatchIterator, RecordBatchReader};
|
||||
use arrow_schema::{ArrowError, SchemaRef};
|
||||
use async_trait::async_trait;
|
||||
use futures::stream::once;
|
||||
use futures::StreamExt;
|
||||
use lance_datafusion::utils::StreamingWriteSource;
|
||||
|
||||
use crate::arrow::{
|
||||
SendableRecordBatchStream, SendableRecordBatchStreamExt, SimpleRecordBatchStream,
|
||||
};
|
||||
use crate::embeddings::{
|
||||
compute_embeddings_for_batch, compute_output_schema, EmbeddingDefinition, EmbeddingFunction,
|
||||
EmbeddingRegistry,
|
||||
};
|
||||
use crate::table::{ColumnDefinition, ColumnKind, TableDefinition};
|
||||
use crate::{Error, Result};
|
||||
|
||||
pub trait Scannable: Send {
|
||||
/// Returns the schema of the data.
|
||||
fn schema(&self) -> SchemaRef;
|
||||
|
||||
/// Read data as a stream of record batches.
|
||||
///
|
||||
/// For rescannable sources (in-memory data like RecordBatch, Vec<RecordBatch>),
|
||||
/// this can be called multiple times and returns cloned data each time.
|
||||
///
|
||||
/// For non-rescannable sources (streams, readers), this can only be called once.
|
||||
/// Calling it a second time returns a stream whose first item is an error.
|
||||
fn scan_as_stream(&mut self) -> SendableRecordBatchStream;
|
||||
|
||||
/// Optional hint about the number of rows.
|
||||
///
|
||||
/// When available, this allows the pipeline to estimate total data size
|
||||
/// and choose appropriate partitioning.
|
||||
fn num_rows(&self) -> Option<usize> {
|
||||
None
|
||||
}
|
||||
|
||||
/// Whether the source can be re-read from the beginning.
|
||||
///
|
||||
/// `true` for in-memory data (Tables, DataFrames) and disk-based sources (Datasets).
|
||||
/// `false` for streaming sources (DuckDB results, network streams).
|
||||
///
|
||||
/// When true, the pipeline can retry failed writes by rescanning.
|
||||
fn rescannable(&self) -> bool {
|
||||
false
|
||||
}
|
||||
}
|
||||
|
||||
impl std::fmt::Debug for dyn Scannable {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
|
||||
f.debug_struct("Scannable")
|
||||
.field("schema", &self.schema())
|
||||
.field("num_rows", &self.num_rows())
|
||||
.field("rescannable", &self.rescannable())
|
||||
.finish()
|
||||
}
|
||||
}
|
||||
|
||||
impl Scannable for RecordBatch {
|
||||
fn schema(&self) -> SchemaRef {
|
||||
Self::schema(self)
|
||||
}
|
||||
|
||||
fn scan_as_stream(&mut self) -> SendableRecordBatchStream {
|
||||
let batch = self.clone();
|
||||
let schema = batch.schema();
|
||||
Box::pin(SimpleRecordBatchStream {
|
||||
schema,
|
||||
stream: once(async move { Ok(batch) }),
|
||||
})
|
||||
}
|
||||
|
||||
fn num_rows(&self) -> Option<usize> {
|
||||
Some(Self::num_rows(self))
|
||||
}
|
||||
|
||||
fn rescannable(&self) -> bool {
|
||||
true
|
||||
}
|
||||
}
|
||||
|
||||
impl Scannable for Vec<RecordBatch> {
|
||||
fn schema(&self) -> SchemaRef {
|
||||
if self.is_empty() {
|
||||
Arc::new(arrow_schema::Schema::empty())
|
||||
} else {
|
||||
self[0].schema()
|
||||
}
|
||||
}
|
||||
|
||||
fn scan_as_stream(&mut self) -> SendableRecordBatchStream {
|
||||
if self.is_empty() {
|
||||
let schema = Scannable::schema(self);
|
||||
return Box::pin(SimpleRecordBatchStream {
|
||||
schema,
|
||||
stream: once(async {
|
||||
Err(Error::InvalidInput {
|
||||
message: "Cannot scan an empty Vec<RecordBatch>".to_string(),
|
||||
})
|
||||
}),
|
||||
});
|
||||
}
|
||||
let schema = Scannable::schema(self);
|
||||
let batches = self.clone();
|
||||
let stream = futures::stream::iter(batches.into_iter().map(Ok));
|
||||
Box::pin(SimpleRecordBatchStream { schema, stream })
|
||||
}
|
||||
|
||||
fn num_rows(&self) -> Option<usize> {
|
||||
Some(self.iter().map(|b| b.num_rows()).sum())
|
||||
}
|
||||
|
||||
fn rescannable(&self) -> bool {
|
||||
true
|
||||
}
|
||||
}
|
||||
|
||||
impl Scannable for Box<dyn RecordBatchReader + Send> {
|
||||
fn schema(&self) -> SchemaRef {
|
||||
RecordBatchReader::schema(self.as_ref())
|
||||
}
|
||||
|
||||
fn scan_as_stream(&mut self) -> SendableRecordBatchStream {
|
||||
let schema = Scannable::schema(self);
|
||||
|
||||
// Swap self with a reader that errors on iteration, so a second call
|
||||
// produces a clear error instead of silently returning empty data.
|
||||
let err_reader: Box<dyn RecordBatchReader + Send> = Box::new(RecordBatchIterator::new(
|
||||
vec![Err(ArrowError::InvalidArgumentError(
|
||||
"Reader has already been consumed".into(),
|
||||
))],
|
||||
schema.clone(),
|
||||
));
|
||||
let reader = std::mem::replace(self, err_reader);
|
||||
|
||||
// Bridge the blocking RecordBatchReader to an async stream via a channel.
|
||||
let (tx, rx) = tokio::sync::mpsc::channel::<crate::Result<RecordBatch>>(2);
|
||||
tokio::task::spawn_blocking(move || {
|
||||
for batch_result in reader {
|
||||
let result = batch_result.map_err(Into::into);
|
||||
if tx.blocking_send(result).is_err() {
|
||||
break;
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
let stream = futures::stream::unfold(rx, |mut rx| async move {
|
||||
rx.recv().await.map(|batch| (batch, rx))
|
||||
})
|
||||
.fuse();
|
||||
|
||||
Box::pin(SimpleRecordBatchStream { schema, stream })
|
||||
}
|
||||
}
|
||||
|
||||
impl Scannable for SendableRecordBatchStream {
|
||||
fn schema(&self) -> SchemaRef {
|
||||
self.as_ref().schema()
|
||||
}
|
||||
|
||||
fn scan_as_stream(&mut self) -> SendableRecordBatchStream {
|
||||
let schema = Scannable::schema(self);
|
||||
|
||||
// Swap self with an error stream so a second call produces a clear error.
|
||||
let error_stream = Box::pin(SimpleRecordBatchStream {
|
||||
schema: schema.clone(),
|
||||
stream: once(async {
|
||||
Err(Error::InvalidInput {
|
||||
message: "Stream has already been consumed".to_string(),
|
||||
})
|
||||
}),
|
||||
});
|
||||
std::mem::replace(self, error_stream)
|
||||
}
|
||||
}
|
||||
|
||||
#[async_trait]
|
||||
impl StreamingWriteSource for Box<dyn Scannable> {
|
||||
fn arrow_schema(&self) -> SchemaRef {
|
||||
self.schema()
|
||||
}
|
||||
|
||||
fn into_stream(mut self) -> datafusion_physical_plan::SendableRecordBatchStream {
|
||||
self.scan_as_stream().into_df_stream()
|
||||
}
|
||||
}
|
||||
|
||||
/// A scannable that applies embeddings to the stream.
|
||||
pub struct WithEmbeddingsScannable {
|
||||
inner: Box<dyn Scannable>,
|
||||
embeddings: Vec<(EmbeddingDefinition, Arc<dyn EmbeddingFunction>)>,
|
||||
output_schema: SchemaRef,
|
||||
}
|
||||
|
||||
impl WithEmbeddingsScannable {
|
||||
/// Create a new WithEmbeddingsScannable.
|
||||
///
|
||||
/// The embeddings are applied to the inner scannable's data as new columns.
|
||||
pub fn try_new(
|
||||
inner: Box<dyn Scannable>,
|
||||
embeddings: Vec<(EmbeddingDefinition, Arc<dyn EmbeddingFunction>)>,
|
||||
) -> Result<Self> {
|
||||
let output_schema = compute_output_schema(&inner.schema(), &embeddings)?;
|
||||
|
||||
// Build column definitions: Physical for base columns, Embedding for new ones
|
||||
let base_col_count = inner.schema().fields().len();
|
||||
let column_definitions: Vec<ColumnDefinition> = (0..base_col_count)
|
||||
.map(|_| ColumnDefinition {
|
||||
kind: ColumnKind::Physical,
|
||||
})
|
||||
.chain(embeddings.iter().map(|(ed, _)| ColumnDefinition {
|
||||
kind: ColumnKind::Embedding(ed.clone()),
|
||||
}))
|
||||
.collect();
|
||||
|
||||
let table_definition = TableDefinition::new(output_schema, column_definitions);
|
||||
let output_schema = table_definition.into_rich_schema();
|
||||
|
||||
Ok(Self {
|
||||
inner,
|
||||
embeddings,
|
||||
output_schema,
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
impl Scannable for WithEmbeddingsScannable {
|
||||
fn schema(&self) -> SchemaRef {
|
||||
self.output_schema.clone()
|
||||
}
|
||||
|
||||
fn scan_as_stream(&mut self) -> SendableRecordBatchStream {
|
||||
let inner_stream = self.inner.scan_as_stream();
|
||||
let embeddings = self.embeddings.clone();
|
||||
let output_schema = self.output_schema.clone();
|
||||
|
||||
let mapped_stream = inner_stream.then(move |batch_result| {
|
||||
let embeddings = embeddings.clone();
|
||||
async move {
|
||||
let batch = batch_result?;
|
||||
let result = tokio::task::spawn_blocking(move || {
|
||||
compute_embeddings_for_batch(batch, &embeddings)
|
||||
})
|
||||
.await
|
||||
.map_err(|e| Error::Runtime {
|
||||
message: format!("Task panicked during embedding computation: {}", e),
|
||||
})??;
|
||||
Ok(result)
|
||||
}
|
||||
});
|
||||
|
||||
Box::pin(SimpleRecordBatchStream {
|
||||
schema: output_schema,
|
||||
stream: mapped_stream,
|
||||
})
|
||||
}
|
||||
|
||||
fn num_rows(&self) -> Option<usize> {
|
||||
self.inner.num_rows()
|
||||
}
|
||||
|
||||
fn rescannable(&self) -> bool {
|
||||
self.inner.rescannable()
|
||||
}
|
||||
}
|
||||
|
||||
pub fn scannable_with_embeddings(
|
||||
inner: Box<dyn Scannable>,
|
||||
table_definition: &TableDefinition,
|
||||
registry: Option<&Arc<dyn EmbeddingRegistry>>,
|
||||
) -> Result<Box<dyn Scannable>> {
|
||||
if let Some(registry) = registry {
|
||||
let mut embeddings = Vec::with_capacity(table_definition.column_definitions.len());
|
||||
for cd in table_definition.column_definitions.iter() {
|
||||
if let ColumnKind::Embedding(embedding_def) = &cd.kind {
|
||||
match registry.get(&embedding_def.embedding_name) {
|
||||
Some(func) => {
|
||||
embeddings.push((embedding_def.clone(), func));
|
||||
}
|
||||
None => {
|
||||
return Err(Error::EmbeddingFunctionNotFound {
|
||||
name: embedding_def.embedding_name.clone(),
|
||||
reason: format!(
|
||||
"Table was defined with an embedding column `{}` but no embedding function was found with that name within the registry.",
|
||||
embedding_def.embedding_name
|
||||
),
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if !embeddings.is_empty() {
|
||||
return Ok(Box::new(WithEmbeddingsScannable::try_new(
|
||||
inner, embeddings,
|
||||
)?));
|
||||
}
|
||||
}
|
||||
|
||||
Ok(inner)
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
use arrow_array::record_batch;
|
||||
use futures::TryStreamExt;
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_record_batch_rescannable() {
|
||||
let mut batch = record_batch!(("id", Int64, [0, 1, 2])).unwrap();
|
||||
|
||||
let stream1 = batch.scan_as_stream();
|
||||
let batches1: Vec<RecordBatch> = stream1.try_collect().await.unwrap();
|
||||
assert_eq!(batches1.len(), 1);
|
||||
assert_eq!(batches1[0], batch);
|
||||
|
||||
assert!(batch.rescannable());
|
||||
let stream2 = batch.scan_as_stream();
|
||||
let batches2: Vec<RecordBatch> = stream2.try_collect().await.unwrap();
|
||||
assert_eq!(batches2.len(), 1);
|
||||
assert_eq!(batches2[0], batch);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_vec_batch_rescannable() {
|
||||
let mut batches = vec![
|
||||
record_batch!(("id", Int64, [0, 1])).unwrap(),
|
||||
record_batch!(("id", Int64, [2, 3, 4])).unwrap(),
|
||||
];
|
||||
|
||||
let stream1 = batches.scan_as_stream();
|
||||
let result1: Vec<RecordBatch> = stream1.try_collect().await.unwrap();
|
||||
assert_eq!(result1.len(), 2);
|
||||
assert_eq!(result1[0], batches[0]);
|
||||
assert_eq!(result1[1], batches[1]);
|
||||
|
||||
assert!(batches.rescannable());
|
||||
let stream2 = batches.scan_as_stream();
|
||||
let result2: Vec<RecordBatch> = stream2.try_collect().await.unwrap();
|
||||
assert_eq!(result2.len(), 2);
|
||||
assert_eq!(result2[0], batches[0]);
|
||||
assert_eq!(result2[1], batches[1]);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_vec_batch_empty_errors() {
|
||||
let mut empty: Vec<RecordBatch> = vec![];
|
||||
let mut stream = empty.scan_as_stream();
|
||||
let result = stream.next().await;
|
||||
assert!(result.is_some());
|
||||
assert!(result.unwrap().is_err());
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_reader_not_rescannable() {
|
||||
let batch = record_batch!(("id", Int64, [0, 1, 2])).unwrap();
|
||||
let schema = batch.schema();
|
||||
let mut reader: Box<dyn arrow_array::RecordBatchReader + Send> = Box::new(
|
||||
RecordBatchIterator::new(vec![Ok(batch.clone())], schema.clone()),
|
||||
);
|
||||
|
||||
let stream1 = reader.scan_as_stream();
|
||||
let result1: Vec<RecordBatch> = stream1.try_collect().await.unwrap();
|
||||
assert_eq!(result1.len(), 1);
|
||||
assert_eq!(result1[0], batch);
|
||||
|
||||
assert!(!reader.rescannable());
|
||||
// Second call returns a stream whose first item is an error
|
||||
let mut stream2 = reader.scan_as_stream();
|
||||
let result2 = stream2.next().await;
|
||||
assert!(result2.is_some());
|
||||
assert!(result2.unwrap().is_err());
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_stream_not_rescannable() {
|
||||
let batch = record_batch!(("id", Int64, [0, 1, 2])).unwrap();
|
||||
let schema = batch.schema();
|
||||
let inner_stream = futures::stream::iter(vec![Ok(batch.clone())]);
|
||||
let mut stream: SendableRecordBatchStream = Box::pin(SimpleRecordBatchStream {
|
||||
schema: schema.clone(),
|
||||
stream: inner_stream,
|
||||
});
|
||||
|
||||
let stream1 = stream.scan_as_stream();
|
||||
let result1: Vec<RecordBatch> = stream1.try_collect().await.unwrap();
|
||||
assert_eq!(result1.len(), 1);
|
||||
assert_eq!(result1[0], batch);
|
||||
|
||||
assert!(!stream.rescannable());
|
||||
// Second call returns a stream whose first item is an error
|
||||
let mut stream2 = stream.scan_as_stream();
|
||||
let result2 = stream2.next().await;
|
||||
assert!(result2.is_some());
|
||||
assert!(result2.unwrap().is_err());
|
||||
}
|
||||
|
||||
mod embedding_tests {
|
||||
use super::*;
|
||||
use crate::embeddings::MemoryRegistry;
|
||||
use crate::table::{ColumnDefinition, ColumnKind};
|
||||
use crate::test_utils::embeddings::MockEmbed;
|
||||
use arrow_array::Array as _;
|
||||
use arrow_array::{ArrayRef, StringArray};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_with_embeddings_scannable() {
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("text", DataType::Utf8, false)]));
|
||||
let text_array = StringArray::from(vec!["hello", "world", "test"]);
|
||||
let batch =
|
||||
RecordBatch::try_new(schema.clone(), vec![Arc::new(text_array) as ArrayRef])
|
||||
.unwrap();
|
||||
|
||||
let mock_embedding: Arc<dyn EmbeddingFunction> = Arc::new(MockEmbed::new("mock", 4));
|
||||
let embedding_def = EmbeddingDefinition::new("text", "mock", Some("text_embedding"));
|
||||
|
||||
let mut scannable = WithEmbeddingsScannable::try_new(
|
||||
Box::new(batch.clone()),
|
||||
vec![(embedding_def, mock_embedding)],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
// Check that schema has the embedding column
|
||||
let output_schema = scannable.schema();
|
||||
assert_eq!(output_schema.fields().len(), 2);
|
||||
assert_eq!(output_schema.field(0).name(), "text");
|
||||
assert_eq!(output_schema.field(1).name(), "text_embedding");
|
||||
|
||||
// Check num_rows and rescannable are preserved
|
||||
assert_eq!(scannable.num_rows(), Some(3));
|
||||
assert!(scannable.rescannable());
|
||||
|
||||
// Read the data
|
||||
let stream = scannable.scan_as_stream();
|
||||
let results: Vec<RecordBatch> = stream.try_collect().await.unwrap();
|
||||
assert_eq!(results.len(), 1);
|
||||
|
||||
let result_batch = &results[0];
|
||||
assert_eq!(result_batch.num_rows(), 3);
|
||||
assert_eq!(result_batch.num_columns(), 2);
|
||||
|
||||
// Verify the embedding column is present and has the right shape
|
||||
let embedding_col = result_batch.column(1);
|
||||
assert_eq!(embedding_col.len(), 3);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_maybe_embedded_scannable_no_embeddings() {
|
||||
let batch = record_batch!(("id", Int64, [1, 2, 3])).unwrap();
|
||||
|
||||
// Create a table definition with no embedding columns
|
||||
let table_def = TableDefinition::new_from_schema(batch.schema());
|
||||
|
||||
// Even with a registry, if there are no embedding columns, it's a passthrough
|
||||
let registry: Arc<dyn EmbeddingRegistry> = Arc::new(MemoryRegistry::new());
|
||||
let mut scannable =
|
||||
scannable_with_embeddings(Box::new(batch.clone()), &table_def, Some(®istry))
|
||||
.unwrap();
|
||||
|
||||
// Check that data passes through unchanged
|
||||
let stream = scannable.scan_as_stream();
|
||||
let results: Vec<RecordBatch> = stream.try_collect().await.unwrap();
|
||||
assert_eq!(results.len(), 1);
|
||||
assert_eq!(results[0], batch);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_maybe_embedded_scannable_with_embeddings() {
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("text", DataType::Utf8, false)]));
|
||||
let text_array = StringArray::from(vec!["hello", "world"]);
|
||||
let batch =
|
||||
RecordBatch::try_new(schema.clone(), vec![Arc::new(text_array) as ArrayRef])
|
||||
.unwrap();
|
||||
|
||||
// Create a table definition with an embedding column
|
||||
let embedding_def = EmbeddingDefinition::new("text", "mock", Some("text_embedding"));
|
||||
let embedding_schema = Arc::new(Schema::new(vec![
|
||||
Field::new("text", DataType::Utf8, false),
|
||||
Field::new(
|
||||
"text_embedding",
|
||||
DataType::FixedSizeList(
|
||||
Arc::new(Field::new("item", DataType::Float32, true)),
|
||||
4,
|
||||
),
|
||||
false,
|
||||
),
|
||||
]));
|
||||
let table_def = TableDefinition::new(
|
||||
embedding_schema,
|
||||
vec![
|
||||
ColumnDefinition {
|
||||
kind: ColumnKind::Physical,
|
||||
},
|
||||
ColumnDefinition {
|
||||
kind: ColumnKind::Embedding(embedding_def.clone()),
|
||||
},
|
||||
],
|
||||
);
|
||||
|
||||
// Register the mock embedding function
|
||||
let registry: Arc<dyn EmbeddingRegistry> = Arc::new(MemoryRegistry::new());
|
||||
let mock_embedding: Arc<dyn EmbeddingFunction> = Arc::new(MockEmbed::new("mock", 4));
|
||||
registry.register("mock", mock_embedding).unwrap();
|
||||
|
||||
let mut scannable =
|
||||
scannable_with_embeddings(Box::new(batch), &table_def, Some(®istry)).unwrap();
|
||||
|
||||
// Read and verify the data has embeddings
|
||||
let stream = scannable.scan_as_stream();
|
||||
let results: Vec<RecordBatch> = stream.try_collect().await.unwrap();
|
||||
assert_eq!(results.len(), 1);
|
||||
|
||||
let result_batch = &results[0];
|
||||
assert_eq!(result_batch.num_columns(), 2);
|
||||
assert_eq!(result_batch.schema().field(1).name(), "text_embedding");
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_maybe_embedded_scannable_missing_function() {
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("text", DataType::Utf8, false)]));
|
||||
let text_array = StringArray::from(vec!["hello"]);
|
||||
let batch =
|
||||
RecordBatch::try_new(schema.clone(), vec![Arc::new(text_array) as ArrayRef])
|
||||
.unwrap();
|
||||
|
||||
// Create a table definition with an embedding column
|
||||
let embedding_def =
|
||||
EmbeddingDefinition::new("text", "nonexistent", Some("text_embedding"));
|
||||
let embedding_schema = Arc::new(Schema::new(vec![
|
||||
Field::new("text", DataType::Utf8, false),
|
||||
Field::new(
|
||||
"text_embedding",
|
||||
DataType::FixedSizeList(
|
||||
Arc::new(Field::new("item", DataType::Float32, true)),
|
||||
4,
|
||||
),
|
||||
false,
|
||||
),
|
||||
]));
|
||||
let table_def = TableDefinition::new(
|
||||
embedding_schema,
|
||||
vec![
|
||||
ColumnDefinition {
|
||||
kind: ColumnKind::Physical,
|
||||
},
|
||||
ColumnDefinition {
|
||||
kind: ColumnKind::Embedding(embedding_def),
|
||||
},
|
||||
],
|
||||
);
|
||||
|
||||
// Registry has no embedding functions registered
|
||||
let registry: Arc<dyn EmbeddingRegistry> = Arc::new(MemoryRegistry::new());
|
||||
|
||||
let result = scannable_with_embeddings(Box::new(batch), &table_def, Some(®istry));
|
||||
|
||||
// Should fail because the embedding function is not found
|
||||
assert!(result.is_err());
|
||||
let err = result.err().unwrap();
|
||||
assert!(
|
||||
matches!(err, Error::EmbeddingFunctionNotFound { .. }),
|
||||
"Expected EmbeddingFunctionNotFound"
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -18,12 +18,7 @@ use std::collections::HashMap;
|
||||
use std::sync::Arc;
|
||||
use std::time::Duration;
|
||||
|
||||
use arrow_array::RecordBatchReader;
|
||||
use async_trait::async_trait;
|
||||
use datafusion_physical_plan::stream::RecordBatchStreamAdapter;
|
||||
use futures::stream;
|
||||
use lance::dataset::ReadParams;
|
||||
use lance_datafusion::utils::StreamingWriteSource;
|
||||
use lance_namespace::models::{
|
||||
CreateNamespaceRequest, CreateNamespaceResponse, DescribeNamespaceRequest,
|
||||
DescribeNamespaceResponse, DropNamespaceRequest, DropNamespaceResponse, ListNamespacesRequest,
|
||||
@@ -31,9 +26,9 @@ use lance_namespace::models::{
|
||||
};
|
||||
use lance_namespace::LanceNamespace;
|
||||
|
||||
use crate::arrow::{SendableRecordBatchStream, SendableRecordBatchStreamExt};
|
||||
use crate::data::scannable::Scannable;
|
||||
use crate::error::Result;
|
||||
use crate::table::{BaseTable, TableDefinition, WriteOptions};
|
||||
use crate::table::{BaseTable, WriteOptions};
|
||||
|
||||
pub mod listing;
|
||||
pub mod namespace;
|
||||
@@ -115,51 +110,14 @@ impl Default for CreateTableMode {
|
||||
}
|
||||
}
|
||||
|
||||
/// The data to start a table or a schema to create an empty table
|
||||
pub enum CreateTableData {
|
||||
/// Creates a table using an iterator of data, the schema will be obtained from the data
|
||||
Data(Box<dyn RecordBatchReader + Send>),
|
||||
/// Creates a table using a stream of data, the schema will be obtained from the data
|
||||
StreamingData(SendableRecordBatchStream),
|
||||
/// Creates an empty table, the definition / schema must be provided separately
|
||||
Empty(TableDefinition),
|
||||
}
|
||||
|
||||
impl CreateTableData {
|
||||
pub fn schema(&self) -> Arc<arrow_schema::Schema> {
|
||||
match self {
|
||||
Self::Data(reader) => reader.schema(),
|
||||
Self::StreamingData(stream) => stream.schema(),
|
||||
Self::Empty(definition) => definition.schema.clone(),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[async_trait]
|
||||
impl StreamingWriteSource for CreateTableData {
|
||||
fn arrow_schema(&self) -> Arc<arrow_schema::Schema> {
|
||||
self.schema()
|
||||
}
|
||||
fn into_stream(self) -> datafusion_physical_plan::SendableRecordBatchStream {
|
||||
match self {
|
||||
Self::Data(reader) => reader.into_stream(),
|
||||
Self::StreamingData(stream) => stream.into_df_stream(),
|
||||
Self::Empty(table_definition) => {
|
||||
let schema = table_definition.schema.clone();
|
||||
Box::pin(RecordBatchStreamAdapter::new(schema, stream::empty()))
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// A request to create a table
|
||||
pub struct CreateTableRequest {
|
||||
/// The name of the new table
|
||||
pub name: String,
|
||||
/// The namespace to create the table in. Empty list represents root namespace.
|
||||
pub namespace: Vec<String>,
|
||||
/// Initial data to write to the table, can be None to create an empty table
|
||||
pub data: CreateTableData,
|
||||
/// Initial data to write to the table, can be empty.
|
||||
pub data: Box<dyn Scannable>,
|
||||
/// The mode to use when creating the table
|
||||
pub mode: CreateTableMode,
|
||||
/// Options to use when writing data (only used if `data` is not None)
|
||||
@@ -173,7 +131,7 @@ pub struct CreateTableRequest {
|
||||
}
|
||||
|
||||
impl CreateTableRequest {
|
||||
pub fn new(name: String, data: CreateTableData) -> Self {
|
||||
pub fn new(name: String, data: Box<dyn Scannable>) -> Self {
|
||||
Self {
|
||||
name,
|
||||
namespace: vec![],
|
||||
|
||||
@@ -922,7 +922,7 @@ impl Database for ListingDatabase {
|
||||
.with_read_params(read_params.clone())
|
||||
.load()
|
||||
.await
|
||||
.map_err(|e| Error::Lance { source: e })?;
|
||||
.map_err(|e| -> Error { e.into() })?;
|
||||
|
||||
let version_ref = match (request.source_version, request.source_tag) {
|
||||
(Some(v), None) => Ok(Ref::Version(None, Some(v))),
|
||||
@@ -937,7 +937,7 @@ impl Database for ListingDatabase {
|
||||
source_dataset
|
||||
.shallow_clone(&target_uri, version_ref, Some(storage_params))
|
||||
.await
|
||||
.map_err(|e| Error::Lance { source: e })?;
|
||||
.map_err(|e| -> Error { e.into() })?;
|
||||
|
||||
let cloned_table = NativeTable::open_with_params(
|
||||
&target_uri,
|
||||
@@ -1098,8 +1098,10 @@ impl Database for ListingDatabase {
|
||||
mod tests {
|
||||
use super::*;
|
||||
use crate::connection::ConnectRequest;
|
||||
use crate::database::{CreateTableData, CreateTableMode, CreateTableRequest, WriteOptions};
|
||||
use crate::table::{Table, TableDefinition};
|
||||
use crate::data::scannable::Scannable;
|
||||
use crate::database::{CreateTableMode, CreateTableRequest};
|
||||
use crate::table::WriteOptions;
|
||||
use crate::Table;
|
||||
use arrow_array::{Int32Array, RecordBatch, StringArray};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use std::path::PathBuf;
|
||||
@@ -1139,7 +1141,7 @@ mod tests {
|
||||
.create_table(CreateTableRequest {
|
||||
name: "source_table".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Empty(TableDefinition::new_from_schema(schema.clone())),
|
||||
data: Box::new(RecordBatch::new_empty(schema.clone())) as Box<dyn Scannable>,
|
||||
mode: CreateTableMode::Create,
|
||||
write_options: Default::default(),
|
||||
location: None,
|
||||
@@ -1196,16 +1198,11 @@ mod tests {
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let reader = Box::new(arrow_array::RecordBatchIterator::new(
|
||||
vec![Ok(batch)],
|
||||
schema.clone(),
|
||||
));
|
||||
|
||||
let source_table = db
|
||||
.create_table(CreateTableRequest {
|
||||
name: "source_with_data".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Data(reader),
|
||||
data: Box::new(batch) as Box<dyn Scannable>,
|
||||
mode: CreateTableMode::Create,
|
||||
write_options: Default::default(),
|
||||
location: None,
|
||||
@@ -1264,7 +1261,7 @@ mod tests {
|
||||
db.create_table(CreateTableRequest {
|
||||
name: "source".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Empty(TableDefinition::new_from_schema(schema)),
|
||||
data: Box::new(RecordBatch::new_empty(schema)) as Box<dyn Scannable>,
|
||||
mode: CreateTableMode::Create,
|
||||
write_options: Default::default(),
|
||||
location: None,
|
||||
@@ -1300,7 +1297,7 @@ mod tests {
|
||||
db.create_table(CreateTableRequest {
|
||||
name: "source".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Empty(TableDefinition::new_from_schema(schema)),
|
||||
data: Box::new(RecordBatch::new_empty(schema)) as Box<dyn Scannable>,
|
||||
mode: CreateTableMode::Create,
|
||||
write_options: Default::default(),
|
||||
location: None,
|
||||
@@ -1340,7 +1337,7 @@ mod tests {
|
||||
db.create_table(CreateTableRequest {
|
||||
name: "source".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Empty(TableDefinition::new_from_schema(schema)),
|
||||
data: Box::new(RecordBatch::new_empty(schema)) as Box<dyn Scannable>,
|
||||
mode: CreateTableMode::Create,
|
||||
write_options: Default::default(),
|
||||
location: None,
|
||||
@@ -1380,7 +1377,7 @@ mod tests {
|
||||
db.create_table(CreateTableRequest {
|
||||
name: "source".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Empty(TableDefinition::new_from_schema(schema)),
|
||||
data: Box::new(RecordBatch::new_empty(schema)) as Box<dyn Scannable>,
|
||||
mode: CreateTableMode::Create,
|
||||
write_options: Default::default(),
|
||||
location: None,
|
||||
@@ -1435,7 +1432,7 @@ mod tests {
|
||||
db.create_table(CreateTableRequest {
|
||||
name: "source".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Empty(TableDefinition::new_from_schema(schema)),
|
||||
data: Box::new(RecordBatch::new_empty(schema)) as Box<dyn Scannable>,
|
||||
mode: CreateTableMode::Create,
|
||||
write_options: Default::default(),
|
||||
location: None,
|
||||
@@ -1484,16 +1481,11 @@ mod tests {
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let reader = Box::new(arrow_array::RecordBatchIterator::new(
|
||||
vec![Ok(batch1)],
|
||||
schema.clone(),
|
||||
));
|
||||
|
||||
let source_table = db
|
||||
.create_table(CreateTableRequest {
|
||||
name: "versioned_source".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Data(reader),
|
||||
data: Box::new(batch1) as Box<dyn Scannable>,
|
||||
mode: CreateTableMode::Create,
|
||||
write_options: Default::default(),
|
||||
location: None,
|
||||
@@ -1517,14 +1509,7 @@ mod tests {
|
||||
|
||||
let db = Arc::new(db);
|
||||
let source_table_obj = Table::new(source_table.clone(), db.clone());
|
||||
source_table_obj
|
||||
.add(Box::new(arrow_array::RecordBatchIterator::new(
|
||||
vec![Ok(batch2)],
|
||||
schema.clone(),
|
||||
)))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
source_table_obj.add(batch2).execute().await.unwrap();
|
||||
|
||||
// Verify source table now has 4 rows
|
||||
assert_eq!(source_table.count_rows(None).await.unwrap(), 4);
|
||||
@@ -1570,16 +1555,11 @@ mod tests {
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let reader = Box::new(arrow_array::RecordBatchIterator::new(
|
||||
vec![Ok(batch1)],
|
||||
schema.clone(),
|
||||
));
|
||||
|
||||
let source_table = db
|
||||
.create_table(CreateTableRequest {
|
||||
name: "tagged_source".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Data(reader),
|
||||
data: Box::new(batch1),
|
||||
mode: CreateTableMode::Create,
|
||||
write_options: Default::default(),
|
||||
location: None,
|
||||
@@ -1607,14 +1587,7 @@ mod tests {
|
||||
.unwrap();
|
||||
|
||||
let source_table_obj = Table::new(source_table.clone(), db.clone());
|
||||
source_table_obj
|
||||
.add(Box::new(arrow_array::RecordBatchIterator::new(
|
||||
vec![Ok(batch2)],
|
||||
schema.clone(),
|
||||
)))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
source_table_obj.add(batch2).execute().await.unwrap();
|
||||
|
||||
// Source table should have 4 rows
|
||||
assert_eq!(source_table.count_rows(None).await.unwrap(), 4);
|
||||
@@ -1657,16 +1630,11 @@ mod tests {
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let reader = Box::new(arrow_array::RecordBatchIterator::new(
|
||||
vec![Ok(batch1)],
|
||||
schema.clone(),
|
||||
));
|
||||
|
||||
let source_table = db
|
||||
.create_table(CreateTableRequest {
|
||||
name: "independent_source".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Data(reader),
|
||||
data: Box::new(batch1),
|
||||
mode: CreateTableMode::Create,
|
||||
write_options: Default::default(),
|
||||
location: None,
|
||||
@@ -1706,14 +1674,7 @@ mod tests {
|
||||
|
||||
let db = Arc::new(db);
|
||||
let cloned_table_obj = Table::new(cloned_table.clone(), db.clone());
|
||||
cloned_table_obj
|
||||
.add(Box::new(arrow_array::RecordBatchIterator::new(
|
||||
vec![Ok(batch_clone)],
|
||||
schema.clone(),
|
||||
)))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
cloned_table_obj.add(batch_clone).execute().await.unwrap();
|
||||
|
||||
// Add different data to the source table
|
||||
let batch_source = RecordBatch::try_new(
|
||||
@@ -1726,14 +1687,7 @@ mod tests {
|
||||
.unwrap();
|
||||
|
||||
let source_table_obj = Table::new(source_table.clone(), db);
|
||||
source_table_obj
|
||||
.add(Box::new(arrow_array::RecordBatchIterator::new(
|
||||
vec![Ok(batch_source)],
|
||||
schema.clone(),
|
||||
)))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
source_table_obj.add(batch_source).execute().await.unwrap();
|
||||
|
||||
// Verify they have evolved independently
|
||||
assert_eq!(source_table.count_rows(None).await.unwrap(), 4); // 2 + 2
|
||||
@@ -1751,16 +1705,11 @@ mod tests {
|
||||
RecordBatch::try_new(schema.clone(), vec![Arc::new(Int32Array::from(vec![1, 2]))])
|
||||
.unwrap();
|
||||
|
||||
let reader = Box::new(arrow_array::RecordBatchIterator::new(
|
||||
vec![Ok(batch1)],
|
||||
schema.clone(),
|
||||
));
|
||||
|
||||
let source_table = db
|
||||
.create_table(CreateTableRequest {
|
||||
name: "latest_version_source".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Data(reader),
|
||||
data: Box::new(batch1),
|
||||
mode: CreateTableMode::Create,
|
||||
write_options: Default::default(),
|
||||
location: None,
|
||||
@@ -1779,14 +1728,7 @@ mod tests {
|
||||
.unwrap();
|
||||
|
||||
let source_table_obj = Table::new(source_table.clone(), db.clone());
|
||||
source_table_obj
|
||||
.add(Box::new(arrow_array::RecordBatchIterator::new(
|
||||
vec![Ok(batch)],
|
||||
schema.clone(),
|
||||
)))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
source_table_obj.add(batch).execute().await.unwrap();
|
||||
}
|
||||
|
||||
// Source should have 8 rows total (2 + 2 + 2 + 2)
|
||||
@@ -1849,16 +1791,11 @@ mod tests {
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let reader = Box::new(arrow_array::RecordBatchIterator::new(
|
||||
vec![Ok(batch)],
|
||||
schema.clone(),
|
||||
));
|
||||
|
||||
let table = db
|
||||
.create_table(CreateTableRequest {
|
||||
name: "test_stable".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Data(reader),
|
||||
data: Box::new(batch),
|
||||
mode: CreateTableMode::Create,
|
||||
write_options: Default::default(),
|
||||
location: None,
|
||||
@@ -1887,11 +1824,6 @@ mod tests {
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let reader = Box::new(arrow_array::RecordBatchIterator::new(
|
||||
vec![Ok(batch)],
|
||||
schema.clone(),
|
||||
));
|
||||
|
||||
let mut storage_options = HashMap::new();
|
||||
storage_options.insert(
|
||||
OPT_NEW_TABLE_ENABLE_STABLE_ROW_IDS.to_string(),
|
||||
@@ -1914,7 +1846,7 @@ mod tests {
|
||||
.create_table(CreateTableRequest {
|
||||
name: "test_stable_table_level".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Data(reader),
|
||||
data: Box::new(batch),
|
||||
mode: CreateTableMode::Create,
|
||||
write_options,
|
||||
location: None,
|
||||
@@ -1963,11 +1895,6 @@ mod tests {
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let reader = Box::new(arrow_array::RecordBatchIterator::new(
|
||||
vec![Ok(batch)],
|
||||
schema.clone(),
|
||||
));
|
||||
|
||||
let mut storage_options = HashMap::new();
|
||||
storage_options.insert(
|
||||
OPT_NEW_TABLE_ENABLE_STABLE_ROW_IDS.to_string(),
|
||||
@@ -1990,7 +1917,7 @@ mod tests {
|
||||
.create_table(CreateTableRequest {
|
||||
name: "test_override".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Data(reader),
|
||||
data: Box::new(batch),
|
||||
mode: CreateTableMode::Create,
|
||||
write_options,
|
||||
location: None,
|
||||
@@ -2108,7 +2035,7 @@ mod tests {
|
||||
db.create_table(CreateTableRequest {
|
||||
name: "table1".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Empty(TableDefinition::new_from_schema(schema.clone())),
|
||||
data: Box::new(RecordBatch::new_empty(schema.clone())) as Box<dyn Scannable>,
|
||||
mode: CreateTableMode::Create,
|
||||
write_options: Default::default(),
|
||||
location: None,
|
||||
@@ -2120,7 +2047,7 @@ mod tests {
|
||||
db.create_table(CreateTableRequest {
|
||||
name: "table2".to_string(),
|
||||
namespace: vec![],
|
||||
data: CreateTableData::Empty(TableDefinition::new_from_schema(schema)),
|
||||
data: Box::new(RecordBatch::new_empty(schema)) as Box<dyn Scannable>,
|
||||
mode: CreateTableMode::Create,
|
||||
write_options: Default::default(),
|
||||
location: None,
|
||||
|
||||
@@ -354,15 +354,13 @@ mod tests {
|
||||
use super::*;
|
||||
use crate::connect_namespace;
|
||||
use crate::query::ExecutableQuery;
|
||||
use arrow_array::{Int32Array, RecordBatch, RecordBatchIterator, StringArray};
|
||||
use arrow_array::{Int32Array, RecordBatch, StringArray};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use futures::TryStreamExt;
|
||||
use tempfile::tempdir;
|
||||
|
||||
/// Helper function to create test data
|
||||
fn create_test_data() -> RecordBatchIterator<
|
||||
std::vec::IntoIter<std::result::Result<RecordBatch, arrow_schema::ArrowError>>,
|
||||
> {
|
||||
fn create_test_data() -> RecordBatch {
|
||||
let schema = Arc::new(Schema::new(vec![
|
||||
Field::new("id", DataType::Int32, false),
|
||||
Field::new("name", DataType::Utf8, false),
|
||||
@@ -371,12 +369,7 @@ mod tests {
|
||||
let id_array = Int32Array::from(vec![1, 2, 3, 4, 5]);
|
||||
let name_array = StringArray::from(vec!["Alice", "Bob", "Charlie", "David", "Eve"]);
|
||||
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(id_array), Arc::new(name_array)],
|
||||
)
|
||||
.unwrap();
|
||||
RecordBatchIterator::new(vec![std::result::Result::Ok(batch)].into_iter(), schema)
|
||||
RecordBatch::try_new(schema, vec![Arc::new(id_array), Arc::new(name_array)]).unwrap()
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
@@ -618,13 +611,7 @@ mod tests {
|
||||
|
||||
// Test: Overwrite the table
|
||||
let table2 = conn
|
||||
.create_table(
|
||||
"overwrite_test",
|
||||
RecordBatchIterator::new(
|
||||
vec![std::result::Result::Ok(test_data2)].into_iter(),
|
||||
schema,
|
||||
),
|
||||
)
|
||||
.create_table("overwrite_test", test_data2)
|
||||
.namespace(vec!["test_ns".into()])
|
||||
.mode(CreateTableMode::Overwrite)
|
||||
.execute()
|
||||
|
||||
@@ -13,7 +13,7 @@ use lance_datafusion::exec::SessionContextExt;
|
||||
use crate::{
|
||||
arrow::{SendableRecordBatchStream, SendableRecordBatchStreamExt, SimpleRecordBatchStream},
|
||||
connect,
|
||||
database::{CreateTableData, CreateTableRequest, Database},
|
||||
database::{CreateTableRequest, Database},
|
||||
dataloader::permutation::{
|
||||
shuffle::{Shuffler, ShufflerConfig},
|
||||
split::{SplitStrategy, Splitter, SPLIT_ID_COLUMN},
|
||||
@@ -313,10 +313,8 @@ impl PermutationBuilder {
|
||||
}
|
||||
};
|
||||
|
||||
let create_table_request = CreateTableRequest::new(
|
||||
name.to_string(),
|
||||
CreateTableData::StreamingData(streaming_data),
|
||||
);
|
||||
let create_table_request =
|
||||
CreateTableRequest::new(name.to_string(), Box::new(streaming_data));
|
||||
|
||||
let table = database.create_table(create_table_request).await?;
|
||||
|
||||
@@ -347,7 +345,7 @@ mod tests {
|
||||
.col("col_b", lance_datagen::array::step::<Int32Type>())
|
||||
.into_ldb_stream(RowCount::from(100), BatchCount::from(10));
|
||||
let data_table = db
|
||||
.create_table_streaming("base_tbl", initial_data)
|
||||
.create_table("base_tbl", initial_data)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -387,7 +385,7 @@ mod tests {
|
||||
.col("some_value", lance_datagen::array::step::<Int32Type>())
|
||||
.into_ldb_stream(RowCount::from(100), BatchCount::from(10));
|
||||
let data_table = db
|
||||
.create_table_streaming("mytbl", initial_data)
|
||||
.create_table("mytbl", initial_data)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
@@ -39,6 +39,9 @@ pub struct PermutationReader {
|
||||
limit: Option<u64>,
|
||||
available_rows: u64,
|
||||
split: u64,
|
||||
// Cached map of offset to row id for the split
|
||||
#[allow(clippy::type_complexity)]
|
||||
offset_map: Arc<tokio::sync::Mutex<Option<Arc<HashMap<u64, u64>>>>>,
|
||||
}
|
||||
|
||||
impl std::fmt::Debug for PermutationReader {
|
||||
@@ -72,6 +75,7 @@ impl PermutationReader {
|
||||
limit: None,
|
||||
available_rows: 0,
|
||||
split,
|
||||
offset_map: Arc::new(tokio::sync::Mutex::new(None)),
|
||||
};
|
||||
slf.validate().await?;
|
||||
// Calculate the number of available rows
|
||||
@@ -157,6 +161,7 @@ impl PermutationReader {
|
||||
let available_rows = self.verify_limit_offset(self.limit, Some(offset)).await?;
|
||||
self.offset = Some(offset);
|
||||
self.available_rows = available_rows;
|
||||
self.offset_map = Arc::new(tokio::sync::Mutex::new(None));
|
||||
Ok(self)
|
||||
}
|
||||
|
||||
@@ -164,6 +169,7 @@ impl PermutationReader {
|
||||
let available_rows = self.verify_limit_offset(Some(limit), self.offset).await?;
|
||||
self.available_rows = available_rows;
|
||||
self.limit = Some(limit);
|
||||
self.offset_map = Arc::new(tokio::sync::Mutex::new(None));
|
||||
Ok(self)
|
||||
}
|
||||
|
||||
@@ -180,8 +186,9 @@ impl PermutationReader {
|
||||
base_table: &Arc<dyn BaseTable>,
|
||||
row_ids: RecordBatch,
|
||||
selection: Select,
|
||||
has_row_id: bool,
|
||||
) -> Result<RecordBatch> {
|
||||
let has_row_id = Self::has_row_id(&selection)?;
|
||||
|
||||
let num_rows = row_ids.num_rows();
|
||||
let row_ids = row_ids
|
||||
.column(0)
|
||||
@@ -282,14 +289,13 @@ impl PermutationReader {
|
||||
row_ids: DatasetRecordBatchStream,
|
||||
selection: Select,
|
||||
) -> Result<SendableRecordBatchStream> {
|
||||
let has_row_id = Self::has_row_id(&selection)?;
|
||||
let mut stream = row_ids
|
||||
.map_err(Error::from)
|
||||
.try_filter_map(move |batch| {
|
||||
let selection = selection.clone();
|
||||
let base_table = base_table.clone();
|
||||
async move {
|
||||
Self::load_batch(&base_table, batch, selection, has_row_id)
|
||||
Self::load_batch(&base_table, batch, selection)
|
||||
.await
|
||||
.map(Some)
|
||||
}
|
||||
@@ -397,6 +403,82 @@ impl PermutationReader {
|
||||
Self::row_ids_to_batches(self.base_table.clone(), row_ids, selection).await
|
||||
}
|
||||
|
||||
/// If we are going to use `take` then we load the offset -> row id map once for the split and cache it
|
||||
///
|
||||
/// This method fetches the map with find-or-create semantics.
|
||||
async fn get_offset_map(
|
||||
&self,
|
||||
permutation_table: &Arc<dyn BaseTable>,
|
||||
) -> Result<Arc<HashMap<u64, u64>>> {
|
||||
let mut offset_map_ref = self.offset_map.lock().await;
|
||||
if let Some(offset_map) = &*offset_map_ref {
|
||||
return Ok(offset_map.clone());
|
||||
}
|
||||
let mut offset_map = HashMap::new();
|
||||
let mut row_ids_query = Table::from(permutation_table.clone())
|
||||
.query()
|
||||
.select(Select::Columns(vec![SRC_ROW_ID_COL.to_string()]))
|
||||
.only_if(format!("{} = {}", SPLIT_ID_COLUMN, self.split));
|
||||
if let Some(offset) = self.offset {
|
||||
row_ids_query = row_ids_query.offset(offset as usize);
|
||||
}
|
||||
if let Some(limit) = self.limit {
|
||||
row_ids_query = row_ids_query.limit(limit as usize);
|
||||
}
|
||||
let mut row_ids = row_ids_query.execute().await?;
|
||||
while let Some(batch) = row_ids.try_next().await? {
|
||||
let row_ids = batch
|
||||
.column(0)
|
||||
.as_primitive::<UInt64Type>()
|
||||
.values()
|
||||
.to_vec();
|
||||
for (i, row_id) in row_ids.iter().enumerate() {
|
||||
offset_map.insert(i as u64, *row_id);
|
||||
}
|
||||
}
|
||||
let offset_map = Arc::new(offset_map);
|
||||
*offset_map_ref = Some(offset_map.clone());
|
||||
Ok(offset_map)
|
||||
}
|
||||
|
||||
pub async fn take_offsets(&self, offsets: &[u64], selection: Select) -> Result<RecordBatch> {
|
||||
if let Some(permutation_table) = &self.permutation_table {
|
||||
let offset_map = self.get_offset_map(permutation_table).await?;
|
||||
let row_ids = offsets
|
||||
.iter()
|
||||
.map(|o| offset_map.get(o).copied().expect_ok().map_err(Error::from))
|
||||
.collect::<Result<Vec<_>>>()?;
|
||||
let row_ids = RecordBatch::try_new(
|
||||
Arc::new(arrow_schema::Schema::new(vec![arrow_schema::Field::new(
|
||||
"row_id",
|
||||
arrow_schema::DataType::UInt64,
|
||||
false,
|
||||
)])),
|
||||
vec![Arc::new(UInt64Array::from(row_ids))],
|
||||
)?;
|
||||
Self::load_batch(&self.base_table, row_ids, selection).await
|
||||
} else {
|
||||
let table = Table::from(self.base_table.clone());
|
||||
let batches = table
|
||||
.take_offsets(offsets.to_vec())
|
||||
.select(selection.clone())
|
||||
.execute()
|
||||
.await?
|
||||
.try_collect::<Vec<_>>()
|
||||
.await?;
|
||||
if let Some(first_batch) = batches.first() {
|
||||
let schema = first_batch.schema();
|
||||
let batch = arrow::compute::concat_batches(&schema, &batches)?;
|
||||
Ok(batch)
|
||||
} else {
|
||||
Ok(RecordBatch::try_new(
|
||||
self.output_schema(selection).await?,
|
||||
vec![],
|
||||
)?)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub async fn output_schema(&self, selection: Select) -> Result<SchemaRef> {
|
||||
let table = Table::from(self.base_table.clone());
|
||||
table.query().select(selection).output_schema().await
|
||||
@@ -543,4 +625,224 @@ mod tests {
|
||||
check_batch(&mut stream, &row_ids[7..9]).await;
|
||||
assert!(stream.try_next().await.unwrap().is_none());
|
||||
}
|
||||
|
||||
/// Helper to create a base table and permutation table for take_offsets tests.
|
||||
/// Returns (base_table, row_ids_table, shuffled_row_ids).
|
||||
async fn setup_permutation_tables(num_rows: usize) -> (Table, Table, Vec<u64>) {
|
||||
let base_table = lance_datagen::gen_batch()
|
||||
.col("idx", lance_datagen::array::step::<Int32Type>())
|
||||
.col("other_col", lance_datagen::array::step::<UInt64Type>())
|
||||
.into_mem_table("tbl", RowCount::from(num_rows as u64), BatchCount::from(1))
|
||||
.await;
|
||||
|
||||
let mut row_ids = collect_column::<UInt64Type>(&base_table, "_rowid").await;
|
||||
row_ids.shuffle(&mut rand::rng());
|
||||
|
||||
let split_ids = UInt64Array::from_iter_values(std::iter::repeat_n(0u64, row_ids.len()));
|
||||
let permutation_batch = RecordBatch::try_new(
|
||||
Arc::new(Schema::new(vec![
|
||||
Field::new("row_id", DataType::UInt64, false),
|
||||
Field::new(SPLIT_ID_COLUMN, DataType::UInt64, false),
|
||||
])),
|
||||
vec![
|
||||
Arc::new(UInt64Array::from(row_ids.clone())),
|
||||
Arc::new(split_ids),
|
||||
],
|
||||
)
|
||||
.unwrap();
|
||||
let row_ids_table = virtual_table("row_ids", &permutation_batch).await;
|
||||
|
||||
(base_table, row_ids_table, row_ids)
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_take_offsets_with_permutation_table() {
|
||||
let (base_table, row_ids_table, row_ids) = setup_permutation_tables(10).await;
|
||||
|
||||
let reader = PermutationReader::try_from_tables(
|
||||
base_table.base_table().clone(),
|
||||
row_ids_table.base_table().clone(),
|
||||
0,
|
||||
)
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Take specific offsets and verify the returned rows match the permutation order
|
||||
let offsets = vec![0, 2, 4];
|
||||
let batch = reader.take_offsets(&offsets, Select::All).await.unwrap();
|
||||
|
||||
assert_eq!(batch.num_rows(), 3);
|
||||
|
||||
let idx_values = batch
|
||||
.column(0)
|
||||
.as_primitive::<Int32Type>()
|
||||
.values()
|
||||
.to_vec();
|
||||
let expected: Vec<i32> = offsets
|
||||
.iter()
|
||||
.map(|&o| row_ids[o as usize] as i32)
|
||||
.collect();
|
||||
assert_eq!(idx_values, expected);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_take_offsets_preserves_order() {
|
||||
let (base_table, row_ids_table, row_ids) = setup_permutation_tables(10).await;
|
||||
|
||||
let reader = PermutationReader::try_from_tables(
|
||||
base_table.base_table().clone(),
|
||||
row_ids_table.base_table().clone(),
|
||||
0,
|
||||
)
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Take offsets in reverse order and verify returned rows match that order
|
||||
let offsets = vec![5, 3, 1, 0];
|
||||
let batch = reader.take_offsets(&offsets, Select::All).await.unwrap();
|
||||
|
||||
assert_eq!(batch.num_rows(), 4);
|
||||
|
||||
let idx_values = batch
|
||||
.column(0)
|
||||
.as_primitive::<Int32Type>()
|
||||
.values()
|
||||
.to_vec();
|
||||
let expected: Vec<i32> = offsets
|
||||
.iter()
|
||||
.map(|&o| row_ids[o as usize] as i32)
|
||||
.collect();
|
||||
assert_eq!(idx_values, expected);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_take_offsets_with_column_selection() {
|
||||
let (base_table, row_ids_table, row_ids) = setup_permutation_tables(10).await;
|
||||
|
||||
let reader = PermutationReader::try_from_tables(
|
||||
base_table.base_table().clone(),
|
||||
row_ids_table.base_table().clone(),
|
||||
0,
|
||||
)
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let offsets = vec![1, 3];
|
||||
let batch = reader
|
||||
.take_offsets(&offsets, Select::Columns(vec!["idx".to_string()]))
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
assert_eq!(batch.num_rows(), 2);
|
||||
assert_eq!(batch.num_columns(), 1);
|
||||
assert_eq!(batch.schema().field(0).name(), "idx");
|
||||
|
||||
let idx_values = batch
|
||||
.column(0)
|
||||
.as_primitive::<Int32Type>()
|
||||
.values()
|
||||
.to_vec();
|
||||
let expected: Vec<i32> = offsets
|
||||
.iter()
|
||||
.map(|&o| row_ids[o as usize] as i32)
|
||||
.collect();
|
||||
assert_eq!(idx_values, expected);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_take_offsets_invalid_offset() {
|
||||
let (base_table, row_ids_table, _) = setup_permutation_tables(5).await;
|
||||
|
||||
let reader = PermutationReader::try_from_tables(
|
||||
base_table.base_table().clone(),
|
||||
row_ids_table.base_table().clone(),
|
||||
0,
|
||||
)
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Offset 999 doesn't exist in the offset map
|
||||
let result = reader.take_offsets(&[0, 999], Select::All).await;
|
||||
assert!(result.is_err());
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_take_offsets_identity_reader() {
|
||||
let base_table = lance_datagen::gen_batch()
|
||||
.col("idx", lance_datagen::array::step::<Int32Type>())
|
||||
.into_mem_table("tbl", RowCount::from(10), BatchCount::from(1))
|
||||
.await;
|
||||
|
||||
let reader = PermutationReader::identity(base_table.base_table().clone()).await;
|
||||
|
||||
// With no permutation table, take_offsets uses the base table directly
|
||||
let offsets = vec![0, 2, 4, 6];
|
||||
let batch = reader.take_offsets(&offsets, Select::All).await.unwrap();
|
||||
|
||||
assert_eq!(batch.num_rows(), 4);
|
||||
|
||||
let idx_values = batch
|
||||
.column(0)
|
||||
.as_primitive::<Int32Type>()
|
||||
.values()
|
||||
.to_vec();
|
||||
assert_eq!(idx_values, vec![0, 2, 4, 6]);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_take_offsets_caches_offset_map() {
|
||||
let (base_table, row_ids_table, row_ids) = setup_permutation_tables(10).await;
|
||||
|
||||
let reader = PermutationReader::try_from_tables(
|
||||
base_table.base_table().clone(),
|
||||
row_ids_table.base_table().clone(),
|
||||
0,
|
||||
)
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// First call populates the cache
|
||||
let batch1 = reader.take_offsets(&[0, 1], Select::All).await.unwrap();
|
||||
|
||||
// Second call should use the cached offset map and produce consistent results
|
||||
let batch2 = reader.take_offsets(&[0, 1], Select::All).await.unwrap();
|
||||
|
||||
let values1 = batch1
|
||||
.column(0)
|
||||
.as_primitive::<Int32Type>()
|
||||
.values()
|
||||
.to_vec();
|
||||
let values2 = batch2
|
||||
.column(0)
|
||||
.as_primitive::<Int32Type>()
|
||||
.values()
|
||||
.to_vec();
|
||||
assert_eq!(values1, values2);
|
||||
|
||||
let expected: Vec<i32> = vec![row_ids[0] as i32, row_ids[1] as i32];
|
||||
assert_eq!(values1, expected);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_take_offsets_single_offset() {
|
||||
let (base_table, row_ids_table, row_ids) = setup_permutation_tables(5).await;
|
||||
|
||||
let reader = PermutationReader::try_from_tables(
|
||||
base_table.base_table().clone(),
|
||||
row_ids_table.base_table().clone(),
|
||||
0,
|
||||
)
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let batch = reader.take_offsets(&[2], Select::All).await.unwrap();
|
||||
|
||||
assert_eq!(batch.num_rows(), 1);
|
||||
let idx_values = batch
|
||||
.column(0)
|
||||
.as_primitive::<Int32Type>()
|
||||
.values()
|
||||
.to_vec();
|
||||
assert_eq!(idx_values, vec![row_ids[2] as i32]);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -18,7 +18,7 @@ use std::{
|
||||
};
|
||||
|
||||
use arrow_array::{Array, RecordBatch, RecordBatchReader};
|
||||
use arrow_schema::{DataType, Field, SchemaBuilder};
|
||||
use arrow_schema::{DataType, Field, SchemaBuilder, SchemaRef};
|
||||
// use async_trait::async_trait;
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
@@ -190,6 +190,112 @@ impl<R: RecordBatchReader> WithEmbeddings<R> {
|
||||
}
|
||||
}
|
||||
|
||||
/// Compute embedding arrays for a batch.
|
||||
///
|
||||
/// When multiple embedding functions are defined, they are computed in parallel using
|
||||
/// scoped threads. For a single embedding function, computation is done inline.
|
||||
fn compute_embedding_arrays(
|
||||
batch: &RecordBatch,
|
||||
embeddings: &[(EmbeddingDefinition, Arc<dyn EmbeddingFunction>)],
|
||||
) -> Result<Vec<Arc<dyn Array>>> {
|
||||
if embeddings.len() == 1 {
|
||||
let (fld, func) = &embeddings[0];
|
||||
let src_column =
|
||||
batch
|
||||
.column_by_name(&fld.source_column)
|
||||
.ok_or_else(|| Error::InvalidInput {
|
||||
message: format!("Source column '{}' not found", fld.source_column),
|
||||
})?;
|
||||
return Ok(vec![func.compute_source_embeddings(src_column.clone())?]);
|
||||
}
|
||||
|
||||
// Parallel path: multiple embeddings
|
||||
std::thread::scope(|s| {
|
||||
let handles: Vec<_> = embeddings
|
||||
.iter()
|
||||
.map(|(fld, func)| {
|
||||
let src_column = batch.column_by_name(&fld.source_column).ok_or_else(|| {
|
||||
Error::InvalidInput {
|
||||
message: format!("Source column '{}' not found", fld.source_column),
|
||||
}
|
||||
})?;
|
||||
|
||||
let handle = s.spawn(move || func.compute_source_embeddings(src_column.clone()));
|
||||
|
||||
Ok(handle)
|
||||
})
|
||||
.collect::<Result<_>>()?;
|
||||
|
||||
handles
|
||||
.into_iter()
|
||||
.map(|h| {
|
||||
h.join().map_err(|e| Error::Runtime {
|
||||
message: format!("Thread panicked during embedding computation: {:?}", e),
|
||||
})?
|
||||
})
|
||||
.collect()
|
||||
})
|
||||
}
|
||||
|
||||
/// Compute the output schema when embeddings are applied to a base schema.
|
||||
///
|
||||
/// This returns the schema with embedding columns appended.
|
||||
pub fn compute_output_schema(
|
||||
base_schema: &SchemaRef,
|
||||
embeddings: &[(EmbeddingDefinition, Arc<dyn EmbeddingFunction>)],
|
||||
) -> Result<SchemaRef> {
|
||||
let mut sb: SchemaBuilder = base_schema.as_ref().into();
|
||||
|
||||
for (ed, func) in embeddings {
|
||||
let src_field = base_schema
|
||||
.field_with_name(&ed.source_column)
|
||||
.map_err(|_| Error::InvalidInput {
|
||||
message: format!("Source column '{}' not found in schema", ed.source_column),
|
||||
})?;
|
||||
|
||||
let field_name = ed
|
||||
.dest_column
|
||||
.clone()
|
||||
.unwrap_or_else(|| format!("{}_embedding", &ed.source_column));
|
||||
|
||||
sb.push(Field::new(
|
||||
field_name,
|
||||
func.dest_type()?.into_owned(),
|
||||
src_field.is_nullable(),
|
||||
));
|
||||
}
|
||||
|
||||
Ok(Arc::new(sb.finish()))
|
||||
}
|
||||
|
||||
/// Compute embeddings for a batch and append as new columns.
|
||||
///
|
||||
/// This function computes embeddings using the provided embedding functions and
|
||||
/// appends them as new columns to the batch.
|
||||
pub fn compute_embeddings_for_batch(
|
||||
batch: RecordBatch,
|
||||
embeddings: &[(EmbeddingDefinition, Arc<dyn EmbeddingFunction>)],
|
||||
) -> Result<RecordBatch> {
|
||||
let embedding_arrays = compute_embedding_arrays(&batch, embeddings)?;
|
||||
|
||||
let mut result = batch;
|
||||
for ((fld, _), embedding) in embeddings.iter().zip(embedding_arrays.iter()) {
|
||||
let dst_field_name = fld
|
||||
.dest_column
|
||||
.clone()
|
||||
.unwrap_or_else(|| format!("{}_embedding", &fld.source_column));
|
||||
|
||||
let dst_field = Field::new(
|
||||
dst_field_name,
|
||||
embedding.data_type().clone(),
|
||||
embedding.nulls().is_some(),
|
||||
);
|
||||
|
||||
result = result.try_with_column(dst_field, embedding.clone())?;
|
||||
}
|
||||
Ok(result)
|
||||
}
|
||||
|
||||
impl<R: RecordBatchReader> WithEmbeddings<R> {
|
||||
fn dest_fields(&self) -> Result<Vec<Field>> {
|
||||
let schema = self.inner.schema();
|
||||
@@ -240,48 +346,6 @@ impl<R: RecordBatchReader> WithEmbeddings<R> {
|
||||
column_definitions,
|
||||
})
|
||||
}
|
||||
|
||||
fn compute_embeddings_parallel(&self, batch: &RecordBatch) -> Result<Vec<Arc<dyn Array>>> {
|
||||
if self.embeddings.len() == 1 {
|
||||
let (fld, func) = &self.embeddings[0];
|
||||
let src_column =
|
||||
batch
|
||||
.column_by_name(&fld.source_column)
|
||||
.ok_or_else(|| Error::InvalidInput {
|
||||
message: format!("Source column '{}' not found", fld.source_column),
|
||||
})?;
|
||||
return Ok(vec![func.compute_source_embeddings(src_column.clone())?]);
|
||||
}
|
||||
|
||||
// Parallel path: multiple embeddings
|
||||
std::thread::scope(|s| {
|
||||
let handles: Vec<_> = self
|
||||
.embeddings
|
||||
.iter()
|
||||
.map(|(fld, func)| {
|
||||
let src_column = batch.column_by_name(&fld.source_column).ok_or_else(|| {
|
||||
Error::InvalidInput {
|
||||
message: format!("Source column '{}' not found", fld.source_column),
|
||||
}
|
||||
})?;
|
||||
|
||||
let handle =
|
||||
s.spawn(move || func.compute_source_embeddings(src_column.clone()));
|
||||
|
||||
Ok(handle)
|
||||
})
|
||||
.collect::<Result<_>>()?;
|
||||
|
||||
handles
|
||||
.into_iter()
|
||||
.map(|h| {
|
||||
h.join().map_err(|e| Error::Runtime {
|
||||
message: format!("Thread panicked during embedding computation: {:?}", e),
|
||||
})?
|
||||
})
|
||||
.collect()
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
impl<R: RecordBatchReader> Iterator for MaybeEmbedded<R> {
|
||||
@@ -309,37 +373,13 @@ impl<R: RecordBatchReader> Iterator for WithEmbeddings<R> {
|
||||
fn next(&mut self) -> Option<Self::Item> {
|
||||
let batch = self.inner.next()?;
|
||||
match batch {
|
||||
Ok(batch) => {
|
||||
let embeddings = match self.compute_embeddings_parallel(&batch) {
|
||||
Ok(emb) => emb,
|
||||
Err(e) => {
|
||||
return Some(Err(arrow_schema::ArrowError::ComputeError(format!(
|
||||
"Error computing embedding: {}",
|
||||
e
|
||||
))))
|
||||
}
|
||||
};
|
||||
|
||||
let mut batch = batch;
|
||||
for ((fld, _), embedding) in self.embeddings.iter().zip(embeddings.iter()) {
|
||||
let dst_field_name = fld
|
||||
.dest_column
|
||||
.clone()
|
||||
.unwrap_or_else(|| format!("{}_embedding", &fld.source_column));
|
||||
|
||||
let dst_field = Field::new(
|
||||
dst_field_name,
|
||||
embedding.data_type().clone(),
|
||||
embedding.nulls().is_some(),
|
||||
);
|
||||
|
||||
match batch.try_with_column(dst_field.clone(), embedding.clone()) {
|
||||
Ok(b) => batch = b,
|
||||
Err(e) => return Some(Err(e)),
|
||||
};
|
||||
}
|
||||
Some(Ok(batch))
|
||||
}
|
||||
Ok(batch) => match compute_embeddings_for_batch(batch, &self.embeddings) {
|
||||
Ok(batch_with_embeddings) => Some(Ok(batch_with_embeddings)),
|
||||
Err(e) => Some(Err(arrow_schema::ArrowError::ComputeError(format!(
|
||||
"Error computing embedding: {}",
|
||||
e
|
||||
)))),
|
||||
},
|
||||
Err(e) => Some(Err(e)),
|
||||
}
|
||||
}
|
||||
|
||||
@@ -6,7 +6,7 @@ use std::sync::PoisonError;
|
||||
use arrow_schema::ArrowError;
|
||||
use snafu::Snafu;
|
||||
|
||||
type BoxError = Box<dyn std::error::Error + Send + Sync>;
|
||||
pub(crate) type BoxError = Box<dyn std::error::Error + Send + Sync>;
|
||||
|
||||
#[derive(Debug, Snafu)]
|
||||
#[snafu(visibility(pub(crate)))]
|
||||
@@ -80,6 +80,9 @@ pub enum Error {
|
||||
Arrow { source: ArrowError },
|
||||
#[snafu(display("LanceDBError: not supported: {message}"))]
|
||||
NotSupported { message: String },
|
||||
/// External error pass through from user code.
|
||||
#[snafu(transparent)]
|
||||
External { source: BoxError },
|
||||
#[snafu(whatever, display("{message}"))]
|
||||
Other {
|
||||
message: String,
|
||||
@@ -92,15 +95,26 @@ pub type Result<T> = std::result::Result<T, Error>;
|
||||
|
||||
impl From<ArrowError> for Error {
|
||||
fn from(source: ArrowError) -> Self {
|
||||
Self::Arrow { source }
|
||||
match source {
|
||||
ArrowError::ExternalError(source) => match source.downcast::<Self>() {
|
||||
Ok(e) => *e,
|
||||
Err(source) => Self::External { source },
|
||||
},
|
||||
_ => Self::Arrow { source },
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl From<lance::Error> for Error {
|
||||
fn from(source: lance::Error) -> Self {
|
||||
// TODO: Once Lance is changed to preserve ObjectStore, DataFusion, and Arrow errors, we can
|
||||
// pass those variants through here as well.
|
||||
Self::Lance { source }
|
||||
// Try to unwrap external errors that were wrapped by lance
|
||||
match source {
|
||||
lance::Error::Wrapped { error, .. } => match error.downcast::<Self>() {
|
||||
Ok(e) => *e,
|
||||
Err(source) => Self::External { source },
|
||||
},
|
||||
_ => Self::Lance { source },
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -218,8 +218,9 @@ mod test {
|
||||
datagen = datagen.col(Box::<IncrementingInt32>::default());
|
||||
datagen = datagen.col(Box::new(RandomVector::default().named("vector".into())));
|
||||
|
||||
let data: Box<dyn arrow_array::RecordBatchReader + Send> = Box::new(datagen.batch(100));
|
||||
let res = db
|
||||
.create_table("test", Box::new(datagen.batch(100)))
|
||||
.create_table("test", data)
|
||||
.write_options(WriteOptions {
|
||||
lance_write_params: Some(param),
|
||||
})
|
||||
|
||||
@@ -12,10 +12,10 @@ use arrow_schema::Schema;
|
||||
use crate::{Error, Result};
|
||||
|
||||
/// Convert a Arrow IPC file to a batch reader
|
||||
pub fn ipc_file_to_batches(buf: Vec<u8>) -> Result<impl RecordBatchReader> {
|
||||
pub fn ipc_file_to_batches(buf: Vec<u8>) -> Result<Box<dyn RecordBatchReader + Send>> {
|
||||
let buf_reader = Cursor::new(buf);
|
||||
let reader = FileReader::try_new(buf_reader, None)?;
|
||||
Ok(reader)
|
||||
Ok(Box::new(reader))
|
||||
}
|
||||
|
||||
/// Convert record batches to Arrow IPC file
|
||||
|
||||
@@ -39,7 +39,6 @@
|
||||
//! #### Connect to a database.
|
||||
//!
|
||||
//! ```rust
|
||||
//! # use arrow_schema::{Field, Schema};
|
||||
//! # tokio::runtime::Runtime::new().unwrap().block_on(async {
|
||||
//! let db = lancedb::connect("data/sample-lancedb").execute().await.unwrap();
|
||||
//! # });
|
||||
@@ -74,7 +73,10 @@
|
||||
//!
|
||||
//! #### Create a table
|
||||
//!
|
||||
//! To create a Table, you need to provide a [`arrow_schema::Schema`] and a [`arrow_array::RecordBatch`] stream.
|
||||
//! To create a Table, you need to provide an [`arrow_array::RecordBatch`]. The
|
||||
//! schema of the `RecordBatch` determines the schema of the table.
|
||||
//!
|
||||
//! Vector columns should be represented as `FixedSizeList<Float16/Float32>` data type.
|
||||
//!
|
||||
//! ```rust
|
||||
//! # use std::sync::Arc;
|
||||
@@ -85,34 +87,29 @@
|
||||
//! # tokio::runtime::Runtime::new().unwrap().block_on(async {
|
||||
//! # let tmpdir = tempfile::tempdir().unwrap();
|
||||
//! # let db = lancedb::connect(tmpdir.path().to_str().unwrap()).execute().await.unwrap();
|
||||
//! let ndims = 128;
|
||||
//! let schema = Arc::new(Schema::new(vec![
|
||||
//! Field::new("id", DataType::Int32, false),
|
||||
//! Field::new(
|
||||
//! "vector",
|
||||
//! DataType::FixedSizeList(Arc::new(Field::new("item", DataType::Float32, true)), 128),
|
||||
//! DataType::FixedSizeList(Arc::new(Field::new("item", DataType::Float32, true)), ndims),
|
||||
//! true,
|
||||
//! ),
|
||||
//! ]));
|
||||
//! // Create a RecordBatch stream.
|
||||
//! let batches = RecordBatchIterator::new(
|
||||
//! vec![RecordBatch::try_new(
|
||||
//! let data = RecordBatch::try_new(
|
||||
//! schema.clone(),
|
||||
//! vec![
|
||||
//! Arc::new(Int32Array::from_iter_values(0..256)),
|
||||
//! Arc::new(
|
||||
//! FixedSizeListArray::from_iter_primitive::<Float32Type, _, _>(
|
||||
//! (0..256).map(|_| Some(vec![Some(1.0); 128])),
|
||||
//! 128,
|
||||
//! (0..256).map(|_| Some(vec![Some(1.0); ndims as usize])),
|
||||
//! ndims,
|
||||
//! ),
|
||||
//! ),
|
||||
//! ],
|
||||
//! )
|
||||
//! .unwrap()]
|
||||
//! .into_iter()
|
||||
//! .map(Ok),
|
||||
//! schema.clone(),
|
||||
//! );
|
||||
//! db.create_table("my_table", Box::new(batches))
|
||||
//! .unwrap();
|
||||
//! db.create_table("my_table", data)
|
||||
//! .execute()
|
||||
//! .await
|
||||
//! .unwrap();
|
||||
@@ -151,42 +148,18 @@
|
||||
//! #### Open table and search
|
||||
//!
|
||||
//! ```rust
|
||||
//! # use std::sync::Arc;
|
||||
//! # use futures::TryStreamExt;
|
||||
//! # use arrow_schema::{DataType, Schema, Field};
|
||||
//! # use arrow_array::{RecordBatch, RecordBatchIterator};
|
||||
//! # use arrow_array::{FixedSizeListArray, Float32Array, Int32Array, types::Float32Type};
|
||||
//! # use lancedb::query::{ExecutableQuery, QueryBase};
|
||||
//! # tokio::runtime::Runtime::new().unwrap().block_on(async {
|
||||
//! # let tmpdir = tempfile::tempdir().unwrap();
|
||||
//! # let db = lancedb::connect(tmpdir.path().to_str().unwrap()).execute().await.unwrap();
|
||||
//! # let schema = Arc::new(Schema::new(vec![
|
||||
//! # Field::new("id", DataType::Int32, false),
|
||||
//! # Field::new("vector", DataType::FixedSizeList(
|
||||
//! # Arc::new(Field::new("item", DataType::Float32, true)), 128), true),
|
||||
//! # ]));
|
||||
//! # let batches = RecordBatchIterator::new(vec![
|
||||
//! # RecordBatch::try_new(schema.clone(),
|
||||
//! # vec![
|
||||
//! # Arc::new(Int32Array::from_iter_values(0..10)),
|
||||
//! # Arc::new(FixedSizeListArray::from_iter_primitive::<Float32Type, _, _>(
|
||||
//! # (0..10).map(|_| Some(vec![Some(1.0); 128])), 128)),
|
||||
//! # ]).unwrap()
|
||||
//! # ].into_iter().map(Ok),
|
||||
//! # schema.clone());
|
||||
//! # db.create_table("my_table", Box::new(batches)).execute().await.unwrap();
|
||||
//! # let table = db.open_table("my_table").execute().await.unwrap();
|
||||
//! # async fn example(table: &lancedb::Table) -> lancedb::Result<()> {
|
||||
//! let results = table
|
||||
//! .query()
|
||||
//! .nearest_to(&[1.0; 128])
|
||||
//! .unwrap()
|
||||
//! .nearest_to(&[1.0; 128])?
|
||||
//! .execute()
|
||||
//! .await
|
||||
//! .unwrap()
|
||||
//! .await?
|
||||
//! .try_collect::<Vec<_>>()
|
||||
//! .await
|
||||
//! .unwrap();
|
||||
//! # });
|
||||
//! .await?;
|
||||
//! # Ok(())
|
||||
//! # }
|
||||
//! ```
|
||||
|
||||
pub mod arrow;
|
||||
|
||||
@@ -1381,7 +1381,7 @@ mod tests {
|
||||
use arrow::{array::downcast_array, compute::concat_batches, datatypes::Int32Type};
|
||||
use arrow_array::{
|
||||
cast::AsArray, types::Float32Type, FixedSizeListArray, Float32Array, Int32Array,
|
||||
RecordBatch, RecordBatchIterator, RecordBatchReader, StringArray,
|
||||
RecordBatch, StringArray,
|
||||
};
|
||||
use arrow_schema::{DataType, Field as ArrowField, Schema as ArrowSchema};
|
||||
use futures::{StreamExt, TryStreamExt};
|
||||
@@ -1402,7 +1402,7 @@ mod tests {
|
||||
let batches = make_test_batches();
|
||||
let conn = connect(uri).execute().await.unwrap();
|
||||
let table = conn
|
||||
.create_table("my_table", Box::new(batches))
|
||||
.create_table("my_table", batches)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -1463,7 +1463,7 @@ mod tests {
|
||||
let batches = make_non_empty_batches();
|
||||
let conn = connect(uri).execute().await.unwrap();
|
||||
let table = conn
|
||||
.create_table("my_table", Box::new(batches))
|
||||
.create_table("my_table", batches)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -1525,7 +1525,7 @@ mod tests {
|
||||
let batches = make_non_empty_batches();
|
||||
let conn = connect(uri).execute().await.unwrap();
|
||||
let table = conn
|
||||
.create_table("my_table", Box::new(batches))
|
||||
.create_table("my_table", batches)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -1578,7 +1578,7 @@ mod tests {
|
||||
let batches = make_non_empty_batches();
|
||||
let conn = connect(uri).execute().await.unwrap();
|
||||
let table = conn
|
||||
.create_table("my_table", Box::new(batches))
|
||||
.create_table("my_table", batches)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -1599,13 +1599,13 @@ mod tests {
|
||||
assert!(result.is_err());
|
||||
}
|
||||
|
||||
fn make_non_empty_batches() -> impl RecordBatchReader + Send + 'static {
|
||||
fn make_non_empty_batches() -> Box<dyn arrow_array::RecordBatchReader + Send> {
|
||||
let vec = Box::new(RandomVector::new().named("vector".to_string()));
|
||||
let id = Box::new(IncrementingInt32::new().named("id".to_string()));
|
||||
BatchGenerator::new().col(vec).col(id).batch(512)
|
||||
Box::new(BatchGenerator::new().col(vec).col(id).batch(512))
|
||||
}
|
||||
|
||||
fn make_test_batches() -> impl RecordBatchReader + Send + 'static {
|
||||
fn make_test_batches() -> RecordBatch {
|
||||
let dim: usize = 128;
|
||||
let schema = Arc::new(ArrowSchema::new(vec![
|
||||
ArrowField::new("key", DataType::Int32, false),
|
||||
@@ -1619,12 +1619,7 @@ mod tests {
|
||||
),
|
||||
ArrowField::new("uri", DataType::Utf8, true),
|
||||
]));
|
||||
RecordBatchIterator::new(
|
||||
vec![RecordBatch::new_empty(schema.clone())]
|
||||
.into_iter()
|
||||
.map(Ok),
|
||||
schema,
|
||||
)
|
||||
RecordBatch::new_empty(schema)
|
||||
}
|
||||
|
||||
async fn make_test_table(tmp_dir: &tempfile::TempDir) -> Table {
|
||||
@@ -1633,7 +1628,7 @@ mod tests {
|
||||
|
||||
let batches = make_non_empty_batches();
|
||||
let conn = connect(uri).execute().await.unwrap();
|
||||
conn.create_table("my_table", Box::new(batches))
|
||||
conn.create_table("my_table", batches)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
@@ -1862,10 +1857,8 @@ mod tests {
|
||||
|
||||
let record_batch =
|
||||
RecordBatch::try_new(schema.clone(), vec![Arc::new(text), Arc::new(vector)]).unwrap();
|
||||
let record_batch_iter =
|
||||
RecordBatchIterator::new(vec![record_batch].into_iter().map(Ok), schema.clone());
|
||||
let table = conn
|
||||
.create_table("my_table", record_batch_iter)
|
||||
.create_table("my_table", record_batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -1949,10 +1942,8 @@ mod tests {
|
||||
],
|
||||
)
|
||||
.unwrap();
|
||||
let record_batch_iter =
|
||||
RecordBatchIterator::new(vec![record_batch].into_iter().map(Ok), schema.clone());
|
||||
let table = conn
|
||||
.create_table("my_table", record_batch_iter)
|
||||
.create_table("my_table", record_batch)
|
||||
.mode(CreateTableMode::Overwrite)
|
||||
.execute()
|
||||
.await
|
||||
@@ -2062,8 +2053,6 @@ mod tests {
|
||||
async fn test_pagination_with_fts() {
|
||||
let db = connect("memory://test").execute().await.unwrap();
|
||||
let data = fts_test_data(400);
|
||||
let schema = data.schema();
|
||||
let data = RecordBatchIterator::new(vec![Ok(data)], schema);
|
||||
let table = db.create_table("test_table", data).execute().await.unwrap();
|
||||
|
||||
table
|
||||
|
||||
@@ -491,7 +491,7 @@ impl<S: HttpSend> RestfulLanceDbClient<S> {
|
||||
}
|
||||
|
||||
/// Apply dynamic headers from the header provider if configured
|
||||
async fn apply_dynamic_headers(&self, mut request: Request) -> Result<Request> {
|
||||
pub(crate) async fn apply_dynamic_headers(&self, mut request: Request) -> Result<Request> {
|
||||
if let Some(ref provider) = self.header_provider {
|
||||
let headers = provider.get_headers().await?;
|
||||
let request_headers = request.headers_mut();
|
||||
@@ -555,7 +555,9 @@ impl<S: HttpSend> RestfulLanceDbClient<S> {
|
||||
message: "Attempted to retry a request that cannot be cloned".to_string(),
|
||||
})?;
|
||||
let (_, r) = tmp_req.build_split();
|
||||
let mut r = r.unwrap();
|
||||
let mut r = r.map_err(|e| Error::Runtime {
|
||||
message: format!("Failed to build request: {}", e),
|
||||
})?;
|
||||
let request_id = self.extract_request_id(&mut r);
|
||||
let mut retry_counter = RetryCounter::new(retry_config, request_id.clone());
|
||||
|
||||
@@ -571,7 +573,9 @@ impl<S: HttpSend> RestfulLanceDbClient<S> {
|
||||
}
|
||||
|
||||
let (c, request) = req_builder.build_split();
|
||||
let mut request = request.unwrap();
|
||||
let mut request = request.map_err(|e| Error::Runtime {
|
||||
message: format!("Failed to build request: {}", e),
|
||||
})?;
|
||||
self.set_request_id(&mut request, &request_id.clone());
|
||||
|
||||
// Apply dynamic headers before each retry attempt
|
||||
@@ -621,7 +625,7 @@ impl<S: HttpSend> RestfulLanceDbClient<S> {
|
||||
}
|
||||
}
|
||||
|
||||
fn log_request(&self, request: &Request, request_id: &String) {
|
||||
pub(crate) fn log_request(&self, request: &Request, request_id: &String) {
|
||||
if log::log_enabled!(log::Level::Debug) {
|
||||
let content_type = request
|
||||
.headers()
|
||||
|
||||
@@ -4,13 +4,11 @@
|
||||
use std::collections::HashMap;
|
||||
use std::sync::Arc;
|
||||
|
||||
use arrow_array::RecordBatchIterator;
|
||||
use async_trait::async_trait;
|
||||
use http::StatusCode;
|
||||
use lance_io::object_store::StorageOptions;
|
||||
use moka::future::Cache;
|
||||
use reqwest::header::CONTENT_TYPE;
|
||||
use tokio::task::spawn_blocking;
|
||||
|
||||
use lance_namespace::models::{
|
||||
CreateNamespaceRequest, CreateNamespaceResponse, DescribeNamespaceRequest,
|
||||
@@ -19,16 +17,17 @@ use lance_namespace::models::{
|
||||
};
|
||||
|
||||
use crate::database::{
|
||||
CloneTableRequest, CreateTableData, CreateTableMode, CreateTableRequest, Database,
|
||||
DatabaseOptions, OpenTableRequest, ReadConsistency, TableNamesRequest,
|
||||
CloneTableRequest, CreateTableMode, CreateTableRequest, Database, DatabaseOptions,
|
||||
OpenTableRequest, ReadConsistency, TableNamesRequest,
|
||||
};
|
||||
use crate::error::Result;
|
||||
use crate::remote::util::stream_as_body;
|
||||
use crate::table::BaseTable;
|
||||
use crate::Error;
|
||||
|
||||
use super::client::{ClientConfig, HttpSend, RequestResultExt, RestfulLanceDbClient, Sender};
|
||||
use super::table::RemoteTable;
|
||||
use super::util::{batches_to_ipc_bytes, parse_server_version};
|
||||
use super::util::parse_server_version;
|
||||
use super::ARROW_STREAM_CONTENT_TYPE;
|
||||
|
||||
// Request structure for the remote clone table API
|
||||
@@ -436,26 +435,8 @@ impl<S: HttpSend> Database for RemoteDatabase<S> {
|
||||
Ok(response)
|
||||
}
|
||||
|
||||
async fn create_table(&self, request: CreateTableRequest) -> Result<Arc<dyn BaseTable>> {
|
||||
let data = match request.data {
|
||||
CreateTableData::Data(data) => data,
|
||||
CreateTableData::StreamingData(_) => {
|
||||
return Err(Error::NotSupported {
|
||||
message: "Creating a remote table from a streaming source".to_string(),
|
||||
})
|
||||
}
|
||||
CreateTableData::Empty(table_definition) => {
|
||||
let schema = table_definition.schema.clone();
|
||||
Box::new(RecordBatchIterator::new(vec![], schema))
|
||||
}
|
||||
};
|
||||
|
||||
// TODO: https://github.com/lancedb/lancedb/issues/1026
|
||||
// We should accept data from an async source. In the meantime, spawn this as blocking
|
||||
// to make sure we don't block the tokio runtime if the source is slow.
|
||||
let data_buffer = spawn_blocking(move || batches_to_ipc_bytes(data))
|
||||
.await
|
||||
.unwrap()?;
|
||||
async fn create_table(&self, mut request: CreateTableRequest) -> Result<Arc<dyn BaseTable>> {
|
||||
let body = stream_as_body(request.data.scan_as_stream())?;
|
||||
|
||||
let identifier =
|
||||
build_table_identifier(&request.name, &request.namespace, &self.client.id_delimiter);
|
||||
@@ -463,7 +444,7 @@ impl<S: HttpSend> Database for RemoteDatabase<S> {
|
||||
.client
|
||||
.post(&format!("/v1/table/{}/create/", identifier))
|
||||
.query(&[("mode", Into::<&str>::into(&request.mode))])
|
||||
.body(data_buffer)
|
||||
.body(body)
|
||||
.header(CONTENT_TYPE, ARROW_STREAM_CONTENT_TYPE);
|
||||
|
||||
let (request_id, rsp) = self.client.send(req).await?;
|
||||
@@ -813,7 +794,7 @@ mod tests {
|
||||
use std::collections::HashMap;
|
||||
use std::sync::{Arc, OnceLock};
|
||||
|
||||
use arrow_array::{Int32Array, RecordBatch, RecordBatchIterator};
|
||||
use arrow_array::{Int32Array, RecordBatch};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
|
||||
use crate::connection::ConnectBuilder;
|
||||
@@ -993,8 +974,7 @@ mod tests {
|
||||
vec![Arc::new(Int32Array::from(vec![1, 2, 3]))],
|
||||
)
|
||||
.unwrap();
|
||||
let reader = RecordBatchIterator::new([Ok(data.clone())], data.schema());
|
||||
let table = conn.create_table("table1", reader).execute().await.unwrap();
|
||||
let table = conn.create_table("table1", data).execute().await.unwrap();
|
||||
assert_eq!(table.name(), "table1");
|
||||
}
|
||||
|
||||
@@ -1011,8 +991,7 @@ mod tests {
|
||||
vec![Arc::new(Int32Array::from(vec![1, 2, 3]))],
|
||||
)
|
||||
.unwrap();
|
||||
let reader = RecordBatchIterator::new([Ok(data.clone())], data.schema());
|
||||
let result = conn.create_table("table1", reader).execute().await;
|
||||
let result = conn.create_table("table1", data).execute().await;
|
||||
assert!(result.is_err());
|
||||
assert!(
|
||||
matches!(result, Err(crate::Error::TableAlreadyExists { name }) if name == "table1")
|
||||
@@ -1045,8 +1024,7 @@ mod tests {
|
||||
vec![Arc::new(Int32Array::from(vec![1, 2, 3]))],
|
||||
)
|
||||
.unwrap();
|
||||
let reader = RecordBatchIterator::new([Ok(data.clone())], data.schema());
|
||||
let mut builder = conn.create_table("table1", reader);
|
||||
let mut builder = conn.create_table("table1", data.clone());
|
||||
if let Some(mode) = mode {
|
||||
builder = builder.mode(mode);
|
||||
}
|
||||
@@ -1071,9 +1049,8 @@ mod tests {
|
||||
.unwrap();
|
||||
|
||||
let called: Arc<OnceLock<bool>> = Arc::new(OnceLock::new());
|
||||
let reader = RecordBatchIterator::new([Ok(data.clone())], data.schema());
|
||||
let called_in_cb = called.clone();
|
||||
conn.create_table("table1", reader)
|
||||
conn.create_table("table1", data)
|
||||
.mode(CreateTableMode::ExistOk(Box::new(move |b| {
|
||||
called_in_cb.clone().set(true).unwrap();
|
||||
b
|
||||
@@ -1262,9 +1239,8 @@ mod tests {
|
||||
vec![Arc::new(Int32Array::from(vec![1, 2, 3]))],
|
||||
)
|
||||
.unwrap();
|
||||
let reader = RecordBatchIterator::new([Ok(data.clone())], data.schema());
|
||||
let table = conn
|
||||
.create_table("table1", reader)
|
||||
.create_table("table1", data)
|
||||
.namespace(vec!["ns1".to_string()])
|
||||
.execute()
|
||||
.await
|
||||
@@ -1730,10 +1706,8 @@ mod tests {
|
||||
vec![Arc::new(Int32Array::from(vec![1, 2, 3]))],
|
||||
)
|
||||
.unwrap();
|
||||
let reader = RecordBatchIterator::new([Ok(data.clone())], schema.clone());
|
||||
|
||||
let table = conn
|
||||
.create_table("test_table", reader)
|
||||
.create_table("test_table", data)
|
||||
.namespace(namespace.clone())
|
||||
.execute()
|
||||
.await;
|
||||
@@ -1806,9 +1780,7 @@ mod tests {
|
||||
let data =
|
||||
RecordBatch::try_new(schema.clone(), vec![Arc::new(Int32Array::from(vec![i]))])
|
||||
.unwrap();
|
||||
let reader = RecordBatchIterator::new([Ok(data.clone())], schema.clone());
|
||||
|
||||
conn.create_table(format!("table{}", i), reader)
|
||||
conn.create_table(format!("table{}", i), data)
|
||||
.namespace(namespace.clone())
|
||||
.execute()
|
||||
.await
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,29 +1,50 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
use std::io::Cursor;
|
||||
|
||||
use arrow_array::RecordBatchReader;
|
||||
use arrow_ipc::CompressionType;
|
||||
use futures::{Stream, StreamExt};
|
||||
use reqwest::Response;
|
||||
|
||||
use crate::Result;
|
||||
use crate::{arrow::SendableRecordBatchStream, Result};
|
||||
|
||||
use super::db::ServerVersion;
|
||||
|
||||
pub fn batches_to_ipc_bytes(batches: impl RecordBatchReader) -> Result<Vec<u8>> {
|
||||
pub fn stream_as_ipc(
|
||||
data: SendableRecordBatchStream,
|
||||
) -> Result<impl Stream<Item = Result<bytes::Bytes>>> {
|
||||
let options = arrow_ipc::writer::IpcWriteOptions::default()
|
||||
.try_with_compression(Some(CompressionType::LZ4_FRAME))?;
|
||||
const WRITE_BUF_SIZE: usize = 4096;
|
||||
let buf = Vec::with_capacity(WRITE_BUF_SIZE);
|
||||
let mut buf = Cursor::new(buf);
|
||||
{
|
||||
let mut writer = arrow_ipc::writer::StreamWriter::try_new(&mut buf, &batches.schema())?;
|
||||
let writer =
|
||||
arrow_ipc::writer::StreamWriter::try_new_with_options(buf, &data.schema(), options)?;
|
||||
let stream = futures::stream::try_unfold(
|
||||
(data, writer, false),
|
||||
move |(mut data, mut writer, finished)| async move {
|
||||
if finished {
|
||||
return Ok(None);
|
||||
}
|
||||
match data.next().await {
|
||||
Some(Ok(batch)) => {
|
||||
writer.write(&batch)?;
|
||||
let buffer = std::mem::take(writer.get_mut());
|
||||
Ok(Some((bytes::Bytes::from(buffer), (data, writer, false))))
|
||||
}
|
||||
Some(Err(e)) => Err(e),
|
||||
None => {
|
||||
writer.finish()?;
|
||||
let buffer = std::mem::take(writer.get_mut());
|
||||
Ok(Some((bytes::Bytes::from(buffer), (data, writer, true))))
|
||||
}
|
||||
}
|
||||
},
|
||||
);
|
||||
Ok(stream)
|
||||
}
|
||||
|
||||
for batch in batches {
|
||||
let batch = batch?;
|
||||
writer.write(&batch)?;
|
||||
}
|
||||
writer.finish()?;
|
||||
}
|
||||
Ok(buf.into_inner())
|
||||
pub fn stream_as_body(data: SendableRecordBatchStream) -> Result<reqwest::Body> {
|
||||
let stream = stream_as_ipc(data)?;
|
||||
Ok(reqwest::Body::wrap_stream(stream))
|
||||
}
|
||||
|
||||
pub fn parse_server_version(req_id: &str, rsp: &Response) -> Result<ServerVersion> {
|
||||
|
||||
@@ -5,7 +5,7 @@
|
||||
|
||||
use arrow::array::{AsArray, FixedSizeListBuilder, Float32Builder};
|
||||
use arrow::datatypes::{Float32Type, UInt8Type};
|
||||
use arrow_array::{RecordBatchIterator, RecordBatchReader};
|
||||
use arrow_array::{RecordBatch, RecordBatchReader};
|
||||
use arrow_schema::{DataType, Field, Schema, SchemaRef};
|
||||
use async_trait::async_trait;
|
||||
use datafusion_expr::Expr;
|
||||
@@ -16,8 +16,6 @@ use datafusion_physical_plan::union::UnionExec;
|
||||
use datafusion_physical_plan::ExecutionPlan;
|
||||
use futures::{FutureExt, StreamExt, TryFutureExt};
|
||||
use lance::dataset::builder::DatasetBuilder;
|
||||
use lance::dataset::cleanup::RemovalStats;
|
||||
use lance::dataset::optimize::{compact_files, CompactionMetrics, IndexRemapperOptions};
|
||||
use lance::dataset::scanner::Scanner;
|
||||
pub use lance::dataset::ColumnAlteration;
|
||||
pub use lance::dataset::NewColumnTransform;
|
||||
@@ -46,17 +44,15 @@ use lance_namespace::models::{
|
||||
use lance_namespace::LanceNamespace;
|
||||
use lance_table::format::Manifest;
|
||||
use lance_table::io::commit::ManifestNamingScheme;
|
||||
use log::info;
|
||||
use serde::{Deserialize, Serialize};
|
||||
use std::collections::HashMap;
|
||||
use std::format;
|
||||
use std::path::Path;
|
||||
use std::sync::Arc;
|
||||
|
||||
use crate::arrow::IntoArrow;
|
||||
use crate::connection::NoData;
|
||||
use crate::data::scannable::{scannable_with_embeddings, Scannable};
|
||||
use crate::database::Database;
|
||||
use crate::embeddings::{EmbeddingDefinition, EmbeddingRegistry, MaybeEmbedded, MemoryRegistry};
|
||||
use crate::embeddings::{EmbeddingDefinition, EmbeddingRegistry, MemoryRegistry};
|
||||
use crate::error::{Error, Result};
|
||||
use crate::index::vector::VectorIndex;
|
||||
use crate::index::IndexStatistics;
|
||||
@@ -75,23 +71,27 @@ use crate::utils::{
|
||||
use self::dataset::DatasetConsistencyWrapper;
|
||||
use self::merge::MergeInsertBuilder;
|
||||
|
||||
mod add_data;
|
||||
pub mod datafusion;
|
||||
pub(crate) mod dataset;
|
||||
pub mod delete;
|
||||
pub mod merge;
|
||||
pub mod optimize;
|
||||
pub mod schema_evolution;
|
||||
pub mod update;
|
||||
|
||||
pub use add_data::{AddDataBuilder, AddDataMode, AddResult};
|
||||
|
||||
use crate::index::waiter::wait_for_index;
|
||||
pub use chrono::Duration;
|
||||
pub use delete::DeleteResult;
|
||||
use futures::future::{join_all, Either};
|
||||
pub use lance::dataset::optimize::CompactionOptions;
|
||||
pub use lance::dataset::refs::{TagContents, Tags as LanceTags};
|
||||
pub use lance::dataset::scanner::DatasetRecordBatchStream;
|
||||
use lance::dataset::statistics::DatasetStatisticsExt;
|
||||
use lance_index::frag_reuse::FRAG_REUSE_INDEX_NAME;
|
||||
pub use lance_index::optimize::OptimizeOptions;
|
||||
pub use optimize::{CompactionOptions, OptimizeAction, OptimizeStats};
|
||||
pub use schema_evolution::{AddColumnsResult, AlterColumnsResult, DropColumnsResult};
|
||||
use serde_with::skip_serializing_none;
|
||||
pub use update::{UpdateBuilder, UpdateResult};
|
||||
@@ -169,85 +169,6 @@ impl TableDefinition {
|
||||
}
|
||||
}
|
||||
|
||||
/// Optimize the dataset.
|
||||
///
|
||||
/// Similar to `VACUUM` in PostgreSQL, it offers different options to
|
||||
/// optimize different parts of the table on disk.
|
||||
///
|
||||
/// By default, it optimizes everything, as [`OptimizeAction::All`].
|
||||
pub enum OptimizeAction {
|
||||
/// Run all optimizations with default values
|
||||
All,
|
||||
/// Compacts files in the dataset
|
||||
///
|
||||
/// LanceDb uses a readonly filesystem for performance and safe concurrency. Every time
|
||||
/// new data is added it will be added into new files. Small files
|
||||
/// can hurt both read and write performance. Compaction will merge small files
|
||||
/// into larger ones.
|
||||
///
|
||||
/// All operations that modify data (add, delete, update, merge insert, etc.) will create
|
||||
/// new files. If these operations are run frequently then compaction should run frequently.
|
||||
///
|
||||
/// If these operations are never run (search only) then compaction is not necessary.
|
||||
Compact {
|
||||
options: CompactionOptions,
|
||||
remap_options: Option<Arc<dyn IndexRemapperOptions>>,
|
||||
},
|
||||
/// Prune old version of datasets
|
||||
///
|
||||
/// Every change in LanceDb is additive. When data is removed from a dataset a new version is
|
||||
/// created that doesn't contain the removed data. However, the old version, which does contain
|
||||
/// the removed data, is left in place. This is necessary for consistency and concurrency and
|
||||
/// also enables time travel functionality like the ability to checkout an older version of the
|
||||
/// dataset to undo changes.
|
||||
///
|
||||
/// Over time, these old versions can consume a lot of disk space. The prune operation will
|
||||
/// remove versions of the dataset that are older than a certain age. This will free up the
|
||||
/// space used by that old data.
|
||||
///
|
||||
/// Once a version is pruned it can no longer be checked out.
|
||||
Prune {
|
||||
/// The duration of time to keep versions of the dataset.
|
||||
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`.
|
||||
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>,
|
||||
},
|
||||
/// Optimize the indices
|
||||
///
|
||||
/// This operation optimizes all indices in the table. When new data is added to LanceDb
|
||||
/// it is not added to the indices. However, it can still turn up in searches because the search
|
||||
/// function will scan both the indexed data and the unindexed data in parallel. Over time, the
|
||||
/// unindexed data can become large enough that the search performance is slow. This operation
|
||||
/// will add the unindexed data to the indices without rerunning the full index creation process.
|
||||
///
|
||||
/// Optimizing an index is faster than re-training the index but it does not typically adjust the
|
||||
/// underlying model relied upon by the index. This can eventually lead to poor search accuracy
|
||||
/// and so users may still want to occasionally retrain the index after adding a large amount of
|
||||
/// data.
|
||||
///
|
||||
/// For example, when using IVF, an index will create clusters. Optimizing an index assigns unindexed
|
||||
/// data to the existing clusters, but it does not move the clusters or create new clusters.
|
||||
Index(OptimizeOptions),
|
||||
}
|
||||
|
||||
impl Default for OptimizeAction {
|
||||
fn default() -> Self {
|
||||
Self::All
|
||||
}
|
||||
}
|
||||
|
||||
/// Statistics about the optimization.
|
||||
pub struct OptimizeStats {
|
||||
/// Stats of the file compaction.
|
||||
pub compaction: Option<CompactionMetrics>,
|
||||
|
||||
/// Stats of the version pruning
|
||||
pub prune: Option<RemovalStats>,
|
||||
}
|
||||
|
||||
/// Describes what happens when a vector either contains NaN or
|
||||
/// does not have enough values
|
||||
#[derive(Clone, Debug, Default)]
|
||||
@@ -277,60 +198,6 @@ pub struct WriteOptions {
|
||||
pub lance_write_params: Option<WriteParams>,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Default)]
|
||||
pub enum AddDataMode {
|
||||
/// Rows will be appended to the table (the default)
|
||||
#[default]
|
||||
Append,
|
||||
/// The existing table will be overwritten with the new data
|
||||
Overwrite,
|
||||
}
|
||||
|
||||
/// A builder for configuring a [`crate::connection::Connection::create_table`] or [`Table::add`]
|
||||
/// operation
|
||||
pub struct AddDataBuilder<T: IntoArrow> {
|
||||
parent: Arc<dyn BaseTable>,
|
||||
pub(crate) data: T,
|
||||
pub(crate) mode: AddDataMode,
|
||||
pub(crate) write_options: WriteOptions,
|
||||
embedding_registry: Option<Arc<dyn EmbeddingRegistry>>,
|
||||
}
|
||||
|
||||
impl<T: IntoArrow> std::fmt::Debug for AddDataBuilder<T> {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
|
||||
f.debug_struct("AddDataBuilder")
|
||||
.field("parent", &self.parent)
|
||||
.field("mode", &self.mode)
|
||||
.field("write_options", &self.write_options)
|
||||
.finish()
|
||||
}
|
||||
}
|
||||
|
||||
impl<T: IntoArrow> AddDataBuilder<T> {
|
||||
pub fn mode(mut self, mode: AddDataMode) -> Self {
|
||||
self.mode = mode;
|
||||
self
|
||||
}
|
||||
|
||||
pub fn write_options(mut self, options: WriteOptions) -> Self {
|
||||
self.write_options = options;
|
||||
self
|
||||
}
|
||||
|
||||
pub async fn execute(self) -> Result<AddResult> {
|
||||
let parent = self.parent.clone();
|
||||
let data = self.data.into_arrow()?;
|
||||
let without_data = AddDataBuilder::<NoData> {
|
||||
data: NoData {},
|
||||
mode: self.mode,
|
||||
parent: self.parent,
|
||||
write_options: self.write_options,
|
||||
embedding_registry: self.embedding_registry,
|
||||
};
|
||||
parent.add(without_data, data).await
|
||||
}
|
||||
}
|
||||
|
||||
/// Filters that can be used to limit the rows returned by a query
|
||||
pub enum Filter {
|
||||
/// A SQL filter string
|
||||
@@ -364,15 +231,6 @@ pub trait Tags: Send + Sync {
|
||||
async fn update(&mut self, tag: &str, version: u64) -> Result<()>;
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize, Default)]
|
||||
pub struct AddResult {
|
||||
// The commit version associated with the operation.
|
||||
// A version of `0` indicates compatibility with legacy servers that do not return
|
||||
/// a commit version.
|
||||
#[serde(default)]
|
||||
pub version: u64,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize, Default)]
|
||||
pub struct MergeResult {
|
||||
// The commit version associated with the operation.
|
||||
@@ -445,11 +303,7 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
|
||||
) -> Result<String>;
|
||||
|
||||
/// Add new records to the table.
|
||||
async fn add(
|
||||
&self,
|
||||
add: AddDataBuilder<NoData>,
|
||||
data: Box<dyn arrow_array::RecordBatchReader + Send>,
|
||||
) -> Result<AddResult>;
|
||||
async fn add(&self, add: AddDataBuilder) -> Result<AddResult>;
|
||||
/// Delete rows from the table.
|
||||
async fn delete(&self, predicate: &str) -> Result<DeleteResult>;
|
||||
/// Update rows in the table.
|
||||
@@ -594,6 +448,30 @@ mod test_utils {
|
||||
embedding_registry: Arc::new(MemoryRegistry::new()),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn new_with_handler_and_config<T>(
|
||||
name: impl Into<String>,
|
||||
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_config(
|
||||
name.into(),
|
||||
handler.clone(),
|
||||
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()),
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -694,16 +572,14 @@ impl Table {
|
||||
///
|
||||
/// # Arguments
|
||||
///
|
||||
/// * `batches` data to be added to the Table
|
||||
/// * `data` data to be added to the Table
|
||||
/// * `options` options to control how data is added
|
||||
pub fn add<T: IntoArrow>(&self, batches: T) -> AddDataBuilder<T> {
|
||||
AddDataBuilder {
|
||||
parent: self.inner.clone(),
|
||||
data: batches,
|
||||
mode: AddDataMode::Append,
|
||||
write_options: WriteOptions::default(),
|
||||
embedding_registry: Some(self.embedding_registry.clone()),
|
||||
}
|
||||
pub fn add<T: Scannable + 'static>(&self, data: T) -> AddDataBuilder {
|
||||
AddDataBuilder::new(
|
||||
self.inner.clone(),
|
||||
Box::new(data),
|
||||
Some(self.embedding_registry.clone()),
|
||||
)
|
||||
}
|
||||
|
||||
/// Update existing records in the Table
|
||||
@@ -742,31 +618,26 @@ impl Table {
|
||||
/// .execute()
|
||||
/// .await
|
||||
/// .unwrap();
|
||||
/// # let schema = Arc::new(Schema::new(vec![
|
||||
/// # Field::new("id", DataType::Int32, false),
|
||||
/// # Field::new("vector", DataType::FixedSizeList(
|
||||
/// # Arc::new(Field::new("item", DataType::Float32, true)), 128), true),
|
||||
/// # ]));
|
||||
/// let batches = RecordBatchIterator::new(
|
||||
/// vec![RecordBatch::try_new(
|
||||
/// schema.clone(),
|
||||
/// vec![
|
||||
/// Arc::new(Int32Array::from_iter_values(0..10)),
|
||||
/// Arc::new(
|
||||
/// FixedSizeListArray::from_iter_primitive::<Float32Type, _, _>(
|
||||
/// (0..10).map(|_| Some(vec![Some(1.0); 128])),
|
||||
/// 128,
|
||||
/// ),
|
||||
/// ),
|
||||
/// ],
|
||||
/// )
|
||||
/// .unwrap()]
|
||||
/// .into_iter()
|
||||
/// .map(Ok),
|
||||
/// let schema = Arc::new(Schema::new(vec![
|
||||
/// Field::new("id", DataType::Int32, false),
|
||||
/// Field::new("vector", DataType::FixedSizeList(
|
||||
/// Arc::new(Field::new("item", DataType::Float32, true)), 128), true),
|
||||
/// ]));
|
||||
/// let data = RecordBatch::try_new(
|
||||
/// schema.clone(),
|
||||
/// );
|
||||
/// vec![
|
||||
/// Arc::new(Int32Array::from_iter_values(0..10)),
|
||||
/// Arc::new(
|
||||
/// FixedSizeListArray::from_iter_primitive::<Float32Type, _, _>(
|
||||
/// (0..10).map(|_| Some(vec![Some(1.0); 128])),
|
||||
/// 128,
|
||||
/// ),
|
||||
/// ),
|
||||
/// ],
|
||||
/// )
|
||||
/// .unwrap();
|
||||
/// let tbl = db
|
||||
/// .create_table("delete_test", Box::new(batches))
|
||||
/// .create_table("delete_test", data)
|
||||
/// .execute()
|
||||
/// .await
|
||||
/// .unwrap();
|
||||
@@ -1526,7 +1397,7 @@ impl NativeTable {
|
||||
name: name.to_string(),
|
||||
source: Box::new(e),
|
||||
},
|
||||
source => Error::Lance { source },
|
||||
e => e.into(),
|
||||
})?;
|
||||
|
||||
let dataset = DatasetConsistencyWrapper::new_latest(dataset, read_consistency_interval);
|
||||
@@ -1610,7 +1481,7 @@ impl NativeTable {
|
||||
lance::Error::Namespace { source, .. } => Error::Runtime {
|
||||
message: format!("Failed to get table info from namespace: {:?}", source),
|
||||
},
|
||||
source => Error::Lance { source },
|
||||
e => e.into(),
|
||||
})?;
|
||||
|
||||
let dataset = builder
|
||||
@@ -1622,7 +1493,7 @@ impl NativeTable {
|
||||
name: name.to_string(),
|
||||
source: Box::new(e),
|
||||
},
|
||||
source => Error::Lance { source },
|
||||
e => e.into(),
|
||||
})?;
|
||||
|
||||
let uri = dataset.uri().to_string();
|
||||
@@ -1716,7 +1587,7 @@ impl NativeTable {
|
||||
lance::Error::DatasetAlreadyExists { .. } => Error::TableAlreadyExists {
|
||||
name: name.to_string(),
|
||||
},
|
||||
source => Error::Lance { source },
|
||||
e => e.into(),
|
||||
})?;
|
||||
|
||||
let id = Self::build_id(&namespace, name);
|
||||
@@ -1743,12 +1614,12 @@ impl NativeTable {
|
||||
read_consistency_interval: Option<std::time::Duration>,
|
||||
namespace_client: Option<Arc<dyn LanceNamespace>>,
|
||||
) -> Result<Self> {
|
||||
let batches = RecordBatchIterator::new(vec![], schema);
|
||||
let data: Box<dyn Scannable> = Box::new(RecordBatch::new_empty(schema));
|
||||
Self::create(
|
||||
uri,
|
||||
name,
|
||||
namespace,
|
||||
batches,
|
||||
data,
|
||||
write_store_wrapper,
|
||||
params,
|
||||
read_consistency_interval,
|
||||
@@ -1837,7 +1708,7 @@ impl NativeTable {
|
||||
lance::Error::DatasetAlreadyExists { .. } => Error::TableAlreadyExists {
|
||||
name: name.to_string(),
|
||||
},
|
||||
source => Error::Lance { source },
|
||||
e => e.into(),
|
||||
})?;
|
||||
|
||||
let id = Self::build_id(&namespace, name);
|
||||
@@ -1859,16 +1730,6 @@ impl NativeTable {
|
||||
})
|
||||
}
|
||||
|
||||
async fn optimize_indices(&self, options: &OptimizeOptions) -> Result<()> {
|
||||
info!("LanceDB: optimizing indices: {:?}", options);
|
||||
self.dataset
|
||||
.get_mut()
|
||||
.await?
|
||||
.optimize_indices(options)
|
||||
.await?;
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// Merge new data into this table.
|
||||
pub async fn merge(
|
||||
&mut self,
|
||||
@@ -1884,47 +1745,6 @@ impl NativeTable {
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// Remove old versions of the dataset from disk.
|
||||
///
|
||||
/// # Arguments
|
||||
/// * `older_than` - The duration of time to keep versions of the dataset.
|
||||
/// * `delete_unverified` - 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`.
|
||||
///
|
||||
/// This calls into [lance::dataset::Dataset::cleanup_old_versions] and
|
||||
/// returns the result.
|
||||
async fn cleanup_old_versions(
|
||||
&self,
|
||||
older_than: Duration,
|
||||
delete_unverified: Option<bool>,
|
||||
error_if_tagged_old_versions: Option<bool>,
|
||||
) -> Result<RemovalStats> {
|
||||
Ok(self
|
||||
.dataset
|
||||
.get_mut()
|
||||
.await?
|
||||
.cleanup_old_versions(older_than, delete_unverified, error_if_tagged_old_versions)
|
||||
.await?)
|
||||
}
|
||||
|
||||
/// Compact files in the dataset.
|
||||
///
|
||||
/// This can be run after making several small appends to optimize the table
|
||||
/// for faster reads.
|
||||
///
|
||||
/// This calls into [lance::dataset::optimize::compact_files].
|
||||
async fn compact_files(
|
||||
&self,
|
||||
options: CompactionOptions,
|
||||
remap_options: Option<Arc<dyn IndexRemapperOptions>>,
|
||||
) -> Result<CompactionMetrics> {
|
||||
let mut dataset_mut = self.dataset.get_mut().await?;
|
||||
let metrics = compact_files(&mut dataset_mut, options, remap_options).await?;
|
||||
Ok(metrics)
|
||||
}
|
||||
|
||||
// TODO: why are these individual methods and not some single "get_stats" method?
|
||||
pub async fn count_fragments(&self) -> Result<usize> {
|
||||
Ok(self.dataset.get().await?.count_fragments())
|
||||
@@ -2670,17 +2490,7 @@ impl BaseTable for NativeTable {
|
||||
}
|
||||
}
|
||||
|
||||
async fn add(
|
||||
&self,
|
||||
add: AddDataBuilder<NoData>,
|
||||
data: Box<dyn RecordBatchReader + Send>,
|
||||
) -> Result<AddResult> {
|
||||
let data = Box::new(MaybeEmbedded::try_new(
|
||||
data,
|
||||
self.table_definition().await?,
|
||||
add.embedding_registry,
|
||||
)?) as Box<dyn RecordBatchReader + Send>;
|
||||
|
||||
async fn add(&self, add: AddDataBuilder) -> Result<AddResult> {
|
||||
let lance_params = add.write_options.lance_write_params.unwrap_or(WriteParams {
|
||||
mode: match add.mode {
|
||||
AddDataMode::Append => WriteMode::Append,
|
||||
@@ -2689,6 +2499,11 @@ impl BaseTable for NativeTable {
|
||||
..Default::default()
|
||||
});
|
||||
|
||||
// Apply embeddings if configured
|
||||
let table_def = self.table_definition().await?;
|
||||
let data =
|
||||
scannable_with_embeddings(add.data, &table_def, add.embedding_registry.as_ref())?;
|
||||
|
||||
let dataset = {
|
||||
// Limited scope for the mutable borrow of self.dataset avoids deadlock.
|
||||
let ds = self.dataset.get_mut().await?;
|
||||
@@ -3010,55 +2825,8 @@ impl BaseTable for NativeTable {
|
||||
}
|
||||
|
||||
async fn optimize(&self, action: OptimizeAction) -> Result<OptimizeStats> {
|
||||
let mut stats = OptimizeStats {
|
||||
compaction: None,
|
||||
prune: None,
|
||||
};
|
||||
match action {
|
||||
OptimizeAction::All => {
|
||||
stats.compaction = self
|
||||
.optimize(OptimizeAction::Compact {
|
||||
options: CompactionOptions::default(),
|
||||
remap_options: None,
|
||||
})
|
||||
.await?
|
||||
.compaction;
|
||||
stats.prune = self
|
||||
.optimize(OptimizeAction::Prune {
|
||||
older_than: None,
|
||||
delete_unverified: None,
|
||||
error_if_tagged_old_versions: None,
|
||||
})
|
||||
.await?
|
||||
.prune;
|
||||
self.optimize(OptimizeAction::Index(OptimizeOptions::default()))
|
||||
.await?;
|
||||
}
|
||||
OptimizeAction::Compact {
|
||||
options,
|
||||
remap_options,
|
||||
} => {
|
||||
stats.compaction = Some(self.compact_files(options, remap_options).await?);
|
||||
}
|
||||
OptimizeAction::Prune {
|
||||
older_than,
|
||||
delete_unverified,
|
||||
error_if_tagged_old_versions,
|
||||
} => {
|
||||
stats.prune = Some(
|
||||
self.cleanup_old_versions(
|
||||
older_than.unwrap_or(Duration::try_days(7).expect("valid delta")),
|
||||
delete_unverified,
|
||||
error_if_tagged_old_versions,
|
||||
)
|
||||
.await?,
|
||||
);
|
||||
}
|
||||
OptimizeAction::Index(options) => {
|
||||
self.optimize_indices(&options).await?;
|
||||
}
|
||||
}
|
||||
Ok(stats)
|
||||
// Delegate to the submodule implementation
|
||||
optimize::execute_optimize(self, action).await
|
||||
}
|
||||
|
||||
async fn add_columns(
|
||||
@@ -3342,7 +3110,7 @@ mod tests {
|
||||
use arrow_array::{BinaryArray, LargeBinaryArray};
|
||||
use arrow_data::ArrayDataBuilder;
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use lance::dataset::WriteMode;
|
||||
use futures::TryStreamExt;
|
||||
use lance::io::{ObjectStoreParams, WrappingObjectStore};
|
||||
use lance::Dataset;
|
||||
use rand::Rng;
|
||||
@@ -3353,14 +3121,17 @@ mod tests {
|
||||
use crate::connection::ConnectBuilder;
|
||||
use crate::index::scalar::{BTreeIndexBuilder, BitmapIndexBuilder};
|
||||
use crate::index::vector::{IvfHnswPqIndexBuilder, IvfHnswSqIndexBuilder};
|
||||
use crate::query::{ExecutableQuery, QueryBase};
|
||||
use crate::test_utils::connection::new_test_connection;
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_open() {
|
||||
let tmp_dir = tempdir().unwrap();
|
||||
let dataset_path = tmp_dir.path().join("test.lance");
|
||||
|
||||
let batches = make_test_batches();
|
||||
Dataset::write(batches, dataset_path.to_str().unwrap(), None)
|
||||
let batch = make_test_batches();
|
||||
let reader = RecordBatchIterator::new(vec![Ok(batch.clone())], batch.schema());
|
||||
Dataset::write(reader, dataset_path.to_str().unwrap(), None)
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
@@ -3393,9 +3164,12 @@ mod tests {
|
||||
let tmp_dir = tempdir().unwrap();
|
||||
let uri = tmp_dir.path().to_str().unwrap();
|
||||
|
||||
let batches = make_test_batches();
|
||||
let batches = Box::new(batches) as Box<dyn RecordBatchReader + Send>;
|
||||
let table = NativeTable::create(uri, "test", vec![], batches, None, None, None, None)
|
||||
let batch = make_test_batches();
|
||||
let reader: Box<dyn RecordBatchReader + Send> = Box::new(RecordBatchIterator::new(
|
||||
vec![Ok(batch.clone())],
|
||||
batch.schema(),
|
||||
));
|
||||
let table = NativeTable::create(uri, "test", vec![], reader, None, None, None, None)
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
@@ -3409,33 +3183,6 @@ mod tests {
|
||||
);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_add() {
|
||||
let tmp_dir = tempdir().unwrap();
|
||||
let uri = tmp_dir.path().to_str().unwrap();
|
||||
let conn = connect(uri).execute().await.unwrap();
|
||||
|
||||
let batches = make_test_batches();
|
||||
let schema = batches.schema().clone();
|
||||
let table = conn.create_table("test", batches).execute().await.unwrap();
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 10);
|
||||
|
||||
let new_batches = RecordBatchIterator::new(
|
||||
vec![RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(100..110))],
|
||||
)
|
||||
.unwrap()]
|
||||
.into_iter()
|
||||
.map(Ok),
|
||||
schema.clone(),
|
||||
);
|
||||
|
||||
table.add(new_batches).execute().await.unwrap();
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 20);
|
||||
assert_eq!(table.name(), "test");
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_merge_insert() {
|
||||
let tmp_dir = tempdir().unwrap();
|
||||
@@ -3452,7 +3199,7 @@ mod tests {
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 10);
|
||||
|
||||
// Create new data with i=5..15
|
||||
let new_batches = Box::new(merge_insert_test_batches(5, 1));
|
||||
let new_batches = merge_insert_test_batches(5, 1);
|
||||
|
||||
// Perform a "insert if not exists"
|
||||
let mut merge_insert_builder = table.merge_insert(&["i"]);
|
||||
@@ -3466,7 +3213,7 @@ mod tests {
|
||||
assert_eq!(result.num_attempts, 1);
|
||||
|
||||
// Create new data with i=15..25 (no id matches)
|
||||
let new_batches = Box::new(merge_insert_test_batches(15, 2));
|
||||
let new_batches = merge_insert_test_batches(15, 2);
|
||||
// Perform a "bulk update" (should not affect anything)
|
||||
let mut merge_insert_builder = table.merge_insert(&["i"]);
|
||||
merge_insert_builder.when_matched_update_all(None);
|
||||
@@ -3479,7 +3226,7 @@ mod tests {
|
||||
);
|
||||
|
||||
// Conditional update that only replaces the age=0 data
|
||||
let new_batches = Box::new(merge_insert_test_batches(5, 3));
|
||||
let new_batches = merge_insert_test_batches(5, 3);
|
||||
let mut merge_insert_builder = table.merge_insert(&["i"]);
|
||||
merge_insert_builder.when_matched_update_all(Some("target.age = 0".to_string()));
|
||||
merge_insert_builder.execute(new_batches).await.unwrap();
|
||||
@@ -3505,7 +3252,7 @@ mod tests {
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 10);
|
||||
|
||||
// Test use_index=true (default behavior)
|
||||
let new_batches = Box::new(merge_insert_test_batches(5, 1));
|
||||
let new_batches = merge_insert_test_batches(5, 1);
|
||||
let mut merge_insert_builder = table.merge_insert(&["i"]);
|
||||
merge_insert_builder.when_not_matched_insert_all();
|
||||
merge_insert_builder.use_index(true);
|
||||
@@ -3513,7 +3260,7 @@ mod tests {
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 15);
|
||||
|
||||
// Test use_index=false (force table scan)
|
||||
let new_batches = Box::new(merge_insert_test_batches(15, 2));
|
||||
let new_batches = merge_insert_test_batches(15, 2);
|
||||
let mut merge_insert_builder = table.merge_insert(&["i"]);
|
||||
merge_insert_builder.when_not_matched_insert_all();
|
||||
merge_insert_builder.use_index(false);
|
||||
@@ -3521,59 +3268,6 @@ mod tests {
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 25);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_add_overwrite() {
|
||||
let tmp_dir = tempdir().unwrap();
|
||||
let uri = tmp_dir.path().to_str().unwrap();
|
||||
let conn = connect(uri).execute().await.unwrap();
|
||||
|
||||
let batches = make_test_batches();
|
||||
let schema = batches.schema().clone();
|
||||
let table = conn.create_table("test", batches).execute().await.unwrap();
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 10);
|
||||
|
||||
let batches = vec![RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(100..110))],
|
||||
)
|
||||
.unwrap()]
|
||||
.into_iter()
|
||||
.map(Ok);
|
||||
|
||||
let new_batches = RecordBatchIterator::new(batches.clone(), schema.clone());
|
||||
|
||||
// Can overwrite using AddDataOptions::mode
|
||||
table
|
||||
.add(new_batches)
|
||||
.mode(AddDataMode::Overwrite)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 10);
|
||||
assert_eq!(table.name(), "test");
|
||||
|
||||
// Can overwrite using underlying WriteParams (which
|
||||
// take precedence over AddDataOptions::mode)
|
||||
|
||||
let param: WriteParams = WriteParams {
|
||||
mode: WriteMode::Overwrite,
|
||||
..Default::default()
|
||||
};
|
||||
|
||||
let new_batches = RecordBatchIterator::new(batches.clone(), schema.clone());
|
||||
table
|
||||
.add(new_batches)
|
||||
.write_options(WriteOptions {
|
||||
lance_write_params: Some(param),
|
||||
})
|
||||
.mode(AddDataMode::Append)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 10);
|
||||
assert_eq!(table.name(), "test");
|
||||
}
|
||||
|
||||
#[derive(Default, Debug)]
|
||||
struct NoOpCacheWrapper {
|
||||
called: AtomicBool,
|
||||
@@ -3629,35 +3323,25 @@ mod tests {
|
||||
assert!(wrapper.called());
|
||||
}
|
||||
|
||||
fn merge_insert_test_batches(
|
||||
offset: i32,
|
||||
age: i32,
|
||||
) -> impl RecordBatchReader + Send + Sync + 'static {
|
||||
fn merge_insert_test_batches(offset: i32, age: i32) -> Box<dyn RecordBatchReader + Send> {
|
||||
let schema = Arc::new(Schema::new(vec![
|
||||
Field::new("i", DataType::Int32, false),
|
||||
Field::new("age", DataType::Int32, false),
|
||||
]));
|
||||
RecordBatchIterator::new(
|
||||
vec![RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![
|
||||
Arc::new(Int32Array::from_iter_values(offset..(offset + 10))),
|
||||
Arc::new(Int32Array::from_iter_values(std::iter::repeat_n(age, 10))),
|
||||
],
|
||||
)],
|
||||
schema,
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![
|
||||
Arc::new(Int32Array::from_iter_values(offset..(offset + 10))),
|
||||
Arc::new(Int32Array::from_iter_values(std::iter::repeat_n(age, 10))),
|
||||
],
|
||||
)
|
||||
.unwrap();
|
||||
Box::new(RecordBatchIterator::new(vec![Ok(batch)], schema))
|
||||
}
|
||||
|
||||
fn make_test_batches() -> impl RecordBatchReader + Send + Sync + 'static {
|
||||
fn make_test_batches() -> RecordBatch {
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("i", DataType::Int32, false)]));
|
||||
RecordBatchIterator::new(
|
||||
vec![RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(0..10))],
|
||||
)],
|
||||
schema,
|
||||
)
|
||||
RecordBatch::try_new(schema, vec![Arc::new(Int32Array::from_iter_values(0..10))]).unwrap()
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
@@ -3745,14 +3429,9 @@ mod tests {
|
||||
);
|
||||
|
||||
let vectors = Arc::new(create_fixed_size_list(float_arr, dimension).unwrap());
|
||||
let batches = RecordBatchIterator::new(
|
||||
vec![RecordBatch::try_new(schema.clone(), vec![vectors.clone()]).unwrap()]
|
||||
.into_iter()
|
||||
.map(Ok),
|
||||
schema,
|
||||
);
|
||||
let batch = RecordBatch::try_new(schema.clone(), vec![vectors.clone()]).unwrap();
|
||||
|
||||
let table = conn.create_table("test", batches).execute().await.unwrap();
|
||||
let table = conn.create_table("test", batch).execute().await.unwrap();
|
||||
|
||||
assert_eq!(table.index_stats("my_index").await.unwrap(), None);
|
||||
|
||||
@@ -3783,6 +3462,31 @@ mod tests {
|
||||
assert_eq!(table.list_indices().await.unwrap().len(), 0);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_dynamic_select() {
|
||||
let tc = new_test_connection().await.unwrap();
|
||||
let db = tc.connection;
|
||||
|
||||
let table = db
|
||||
.create_table("test", some_sample_data())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let query = table.query().select(Select::dynamic(&[("i_alias", "i")]));
|
||||
|
||||
let result = query.execute().await;
|
||||
let batches = result
|
||||
.expect("should have result")
|
||||
.try_collect::<Vec<_>>()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
for batch in batches {
|
||||
assert!(batch.column_by_name("i_alias").is_some());
|
||||
}
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_ivf_pq_uses_default_partition_size_for_num_partitions() {
|
||||
use arrow_array::{Float32Array, RecordBatch};
|
||||
@@ -3809,14 +3513,9 @@ mod tests {
|
||||
let float_arr =
|
||||
Float32Array::from_iter_values((0..(num_rows * dimension)).map(|v| v as f32));
|
||||
let vectors = Arc::new(create_fixed_size_list(float_arr, dimension as i32).unwrap());
|
||||
let batches = RecordBatchIterator::new(
|
||||
vec![RecordBatch::try_new(schema.clone(), vec![vectors]).unwrap()]
|
||||
.into_iter()
|
||||
.map(Ok),
|
||||
schema,
|
||||
);
|
||||
let batch = RecordBatch::try_new(schema.clone(), vec![vectors]).unwrap();
|
||||
|
||||
let table = conn.create_table("test", batches).execute().await.unwrap();
|
||||
let table = conn.create_table("test", batch).execute().await.unwrap();
|
||||
let native_table = table.as_native().unwrap();
|
||||
let builder = IvfPqIndexBuilder::default();
|
||||
table
|
||||
@@ -3886,14 +3585,9 @@ mod tests {
|
||||
);
|
||||
|
||||
let vectors = Arc::new(create_fixed_size_list(float_arr, dimension).unwrap());
|
||||
let batches = RecordBatchIterator::new(
|
||||
vec![RecordBatch::try_new(schema.clone(), vec![vectors.clone()]).unwrap()]
|
||||
.into_iter()
|
||||
.map(Ok),
|
||||
schema,
|
||||
);
|
||||
let batch = RecordBatch::try_new(schema.clone(), vec![vectors.clone()]).unwrap();
|
||||
|
||||
let table = conn.create_table("test", batches).execute().await.unwrap();
|
||||
let table = conn.create_table("test", batch).execute().await.unwrap();
|
||||
|
||||
let stats = table.index_stats("my_index").await.unwrap();
|
||||
assert!(stats.is_none());
|
||||
@@ -3951,14 +3645,9 @@ mod tests {
|
||||
);
|
||||
|
||||
let vectors = Arc::new(create_fixed_size_list(float_arr, dimension).unwrap());
|
||||
let batches = RecordBatchIterator::new(
|
||||
vec![RecordBatch::try_new(schema.clone(), vec![vectors.clone()]).unwrap()]
|
||||
.into_iter()
|
||||
.map(Ok),
|
||||
schema,
|
||||
);
|
||||
let batch = RecordBatch::try_new(schema.clone(), vec![vectors.clone()]).unwrap();
|
||||
|
||||
let table = conn.create_table("test", batches).execute().await.unwrap();
|
||||
let table = conn.create_table("test", batch).execute().await.unwrap();
|
||||
let stats = table.index_stats("my_index").await.unwrap();
|
||||
assert!(stats.is_none());
|
||||
|
||||
@@ -4001,7 +3690,7 @@ mod tests {
|
||||
Ok(FixedSizeListArray::from(data))
|
||||
}
|
||||
|
||||
fn some_sample_data() -> Box<dyn RecordBatchReader + Send> {
|
||||
fn some_sample_data() -> Box<dyn arrow_array::RecordBatchReader + Send> {
|
||||
let batch = RecordBatch::try_new(
|
||||
Arc::new(Schema::new(vec![Field::new("i", DataType::Int32, false)])),
|
||||
vec![Arc::new(Int32Array::from(vec![1]))],
|
||||
@@ -4025,10 +3714,7 @@ mod tests {
|
||||
.unwrap();
|
||||
let conn = ConnectBuilder::new(uri).execute().await.unwrap();
|
||||
let table = conn
|
||||
.create_table(
|
||||
"my_table",
|
||||
RecordBatchIterator::new(vec![Ok(batch.clone())], batch.schema()),
|
||||
)
|
||||
.create_table("my_table", batch.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -4107,10 +3793,7 @@ mod tests {
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_bitmap",
|
||||
RecordBatchIterator::new(vec![Ok(batch.clone())], batch.schema()),
|
||||
)
|
||||
.create_table("test_bitmap", batch.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -4211,10 +3894,7 @@ mod tests {
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_bitmap",
|
||||
RecordBatchIterator::new(vec![Ok(batch.clone())], batch.schema()),
|
||||
)
|
||||
.create_table("test_bitmap", batch.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -4274,10 +3954,7 @@ mod tests {
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_bitmap",
|
||||
RecordBatchIterator::new(vec![Ok(batch.clone())], batch.schema()),
|
||||
)
|
||||
.create_table("test_bitmap", batch.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -4322,7 +3999,7 @@ mod tests {
|
||||
|
||||
let conn1 = ConnectBuilder::new(uri).execute().await.unwrap();
|
||||
let table1 = conn1
|
||||
.create_empty_table("my_table", data.schema())
|
||||
.create_empty_table("my_table", RecordBatchReader::schema(&data))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -4592,10 +4269,7 @@ mod tests {
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_stats",
|
||||
RecordBatchIterator::new(vec![Ok(batch.clone())], batch.schema()),
|
||||
)
|
||||
.create_table("test_stats", batch.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -4608,21 +4282,11 @@ mod tests {
|
||||
],
|
||||
)
|
||||
.unwrap();
|
||||
table
|
||||
.add(RecordBatchIterator::new(
|
||||
vec![Ok(batch.clone())],
|
||||
batch.schema(),
|
||||
))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
table.add(batch.clone()).execute().await.unwrap();
|
||||
}
|
||||
|
||||
let empty_table = conn
|
||||
.create_table(
|
||||
"test_stats_empty",
|
||||
RecordBatchIterator::new(vec![], batch.schema()),
|
||||
)
|
||||
.create_table("test_stats_empty", RecordBatch::new_empty(batch.schema()))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -4696,22 +4360,12 @@ mod tests {
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_list_indices_skip_frag_reuse",
|
||||
RecordBatchIterator::new(vec![Ok(batch.clone())], batch.schema()),
|
||||
)
|
||||
.create_table("test_list_indices_skip_frag_reuse", batch.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
table
|
||||
.add(RecordBatchIterator::new(
|
||||
vec![Ok(batch.clone())],
|
||||
batch.schema(),
|
||||
))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
table.add(batch.clone()).execute().await.unwrap();
|
||||
|
||||
table
|
||||
.create_index(&["id"], Index::Bitmap(BitmapIndexBuilder {}))
|
||||
@@ -4741,8 +4395,9 @@ mod tests {
|
||||
let tmp_dir = tempdir().unwrap();
|
||||
let dataset_path = tmp_dir.path().join("test_ns_query.lance");
|
||||
|
||||
let batches = make_test_batches();
|
||||
Dataset::write(batches, dataset_path.to_str().unwrap(), None)
|
||||
let batch = make_test_batches();
|
||||
let reader = RecordBatchIterator::new(vec![Ok(batch.clone())], batch.schema());
|
||||
Dataset::write(reader, dataset_path.to_str().unwrap(), None)
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
@@ -4794,8 +4449,9 @@ mod tests {
|
||||
let tmp_dir = tempdir().unwrap();
|
||||
let dataset_path = tmp_dir.path().join("test_ns_plain.lance");
|
||||
|
||||
let batches = make_test_batches();
|
||||
Dataset::write(batches, dataset_path.to_str().unwrap(), None)
|
||||
let batch = make_test_batches();
|
||||
let reader = RecordBatchIterator::new(vec![Ok(batch.clone())], batch.schema());
|
||||
Dataset::write(reader, dataset_path.to_str().unwrap(), None)
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
|
||||
343
rust/lancedb/src/table/add_data.rs
Normal file
343
rust/lancedb/src/table/add_data.rs
Normal file
@@ -0,0 +1,343 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
use std::sync::Arc;
|
||||
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
use crate::data::scannable::Scannable;
|
||||
use crate::embeddings::EmbeddingRegistry;
|
||||
use crate::Result;
|
||||
|
||||
use super::{BaseTable, WriteOptions};
|
||||
|
||||
#[derive(Debug, Clone, Default)]
|
||||
pub enum AddDataMode {
|
||||
/// Rows will be appended to the table (the default)
|
||||
#[default]
|
||||
Append,
|
||||
/// The existing table will be overwritten with the new data
|
||||
Overwrite,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize, Default)]
|
||||
pub struct AddResult {
|
||||
// The commit version associated with the operation.
|
||||
// A version of `0` indicates compatibility with legacy servers that do not return
|
||||
/// a commit version.
|
||||
#[serde(default)]
|
||||
pub version: u64,
|
||||
}
|
||||
|
||||
/// A builder for configuring a [`crate::table::Table::add`] operation
|
||||
pub struct AddDataBuilder {
|
||||
pub(crate) parent: Arc<dyn BaseTable>,
|
||||
pub(crate) data: Box<dyn Scannable>,
|
||||
pub(crate) mode: AddDataMode,
|
||||
pub(crate) write_options: WriteOptions,
|
||||
pub(crate) embedding_registry: Option<Arc<dyn EmbeddingRegistry>>,
|
||||
}
|
||||
|
||||
impl std::fmt::Debug for AddDataBuilder {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
|
||||
f.debug_struct("AddDataBuilder")
|
||||
.field("parent", &self.parent)
|
||||
.field("mode", &self.mode)
|
||||
.field("write_options", &self.write_options)
|
||||
.finish()
|
||||
}
|
||||
}
|
||||
|
||||
impl AddDataBuilder {
|
||||
pub(crate) fn new(
|
||||
parent: Arc<dyn BaseTable>,
|
||||
data: Box<dyn Scannable>,
|
||||
embedding_registry: Option<Arc<dyn EmbeddingRegistry>>,
|
||||
) -> Self {
|
||||
Self {
|
||||
parent,
|
||||
data,
|
||||
mode: AddDataMode::Append,
|
||||
write_options: WriteOptions::default(),
|
||||
embedding_registry,
|
||||
}
|
||||
}
|
||||
|
||||
pub fn mode(mut self, mode: AddDataMode) -> Self {
|
||||
self.mode = mode;
|
||||
self
|
||||
}
|
||||
|
||||
pub fn write_options(mut self, options: WriteOptions) -> Self {
|
||||
self.write_options = options;
|
||||
self
|
||||
}
|
||||
|
||||
pub async fn execute(self) -> Result<AddResult> {
|
||||
self.parent.clone().add(self).await
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use std::sync::Arc;
|
||||
|
||||
use arrow_array::{record_batch, RecordBatch, RecordBatchIterator};
|
||||
use arrow_schema::{ArrowError, DataType, Field, Schema};
|
||||
use futures::TryStreamExt;
|
||||
use lance::dataset::{WriteMode, WriteParams};
|
||||
|
||||
use crate::arrow::{SendableRecordBatchStream, SimpleRecordBatchStream};
|
||||
use crate::connect;
|
||||
use crate::data::scannable::Scannable;
|
||||
use crate::embeddings::{
|
||||
EmbeddingDefinition, EmbeddingFunction, EmbeddingRegistry, MemoryRegistry,
|
||||
};
|
||||
use crate::query::{ExecutableQuery, QueryBase, Select};
|
||||
use crate::table::{ColumnDefinition, ColumnKind, Table, TableDefinition, WriteOptions};
|
||||
use crate::test_utils::embeddings::MockEmbed;
|
||||
use crate::Error;
|
||||
|
||||
use super::AddDataMode;
|
||||
|
||||
async fn create_test_table() -> Table {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
let batch = record_batch!(("id", Int64, [1, 2, 3])).unwrap();
|
||||
conn.create_table("test", batch).execute().await.unwrap()
|
||||
}
|
||||
|
||||
async fn test_add_with_data<T>(data: T)
|
||||
where
|
||||
T: Scannable + 'static,
|
||||
{
|
||||
let table = create_test_table().await;
|
||||
let schema = data.schema();
|
||||
table.add(data).execute().await.unwrap();
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 5); // 3 initial + 2 added
|
||||
assert_eq!(table.schema().await.unwrap(), schema);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_add_with_batch() {
|
||||
let batch = record_batch!(("id", Int64, [4, 5])).unwrap();
|
||||
test_add_with_data(batch).await;
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_add_with_vec_batch() {
|
||||
let data = vec![
|
||||
record_batch!(("id", Int64, [4])).unwrap(),
|
||||
record_batch!(("id", Int64, [5])).unwrap(),
|
||||
];
|
||||
test_add_with_data(data).await;
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_add_with_record_batch_reader() {
|
||||
let data = vec![
|
||||
record_batch!(("id", Int64, [4])).unwrap(),
|
||||
record_batch!(("id", Int64, [5])).unwrap(),
|
||||
];
|
||||
let schema = data[0].schema();
|
||||
let reader: Box<dyn arrow_array::RecordBatchReader + Send> = Box::new(
|
||||
RecordBatchIterator::new(data.into_iter().map(Ok), schema.clone()),
|
||||
);
|
||||
test_add_with_data(reader).await;
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_add_with_stream() {
|
||||
let data = vec![
|
||||
record_batch!(("id", Int64, [4])).unwrap(),
|
||||
record_batch!(("id", Int64, [5])).unwrap(),
|
||||
];
|
||||
let schema = data[0].schema();
|
||||
let inner = futures::stream::iter(data.into_iter().map(Ok));
|
||||
let stream: SendableRecordBatchStream = Box::pin(SimpleRecordBatchStream {
|
||||
schema,
|
||||
stream: inner,
|
||||
});
|
||||
test_add_with_data(stream).await;
|
||||
}
|
||||
|
||||
#[derive(Debug)]
|
||||
struct MyError;
|
||||
|
||||
impl std::fmt::Display for MyError {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
|
||||
write!(f, "MyError occurred")
|
||||
}
|
||||
}
|
||||
|
||||
impl std::error::Error for MyError {}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_add_preserves_reader_error() {
|
||||
let table = create_test_table().await;
|
||||
let first_batch = record_batch!(("id", Int64, [4])).unwrap();
|
||||
let schema = first_batch.schema();
|
||||
let iterator = vec![
|
||||
Ok(first_batch),
|
||||
Err(ArrowError::ExternalError(Box::new(MyError))),
|
||||
];
|
||||
let reader: Box<dyn arrow_array::RecordBatchReader + Send> = Box::new(
|
||||
RecordBatchIterator::new(iterator.into_iter(), schema.clone()),
|
||||
);
|
||||
|
||||
let result = table.add(reader).execute().await;
|
||||
|
||||
assert!(result.is_err());
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_add_preserves_stream_error() {
|
||||
let table = create_test_table().await;
|
||||
let first_batch = record_batch!(("id", Int64, [4])).unwrap();
|
||||
let schema = first_batch.schema();
|
||||
let iterator = vec![
|
||||
Ok(first_batch),
|
||||
Err(Error::External {
|
||||
source: Box::new(MyError),
|
||||
}),
|
||||
];
|
||||
let stream = futures::stream::iter(iterator);
|
||||
let stream: SendableRecordBatchStream = Box::pin(SimpleRecordBatchStream {
|
||||
schema: schema.clone(),
|
||||
stream,
|
||||
});
|
||||
|
||||
let result = table.add(stream).execute().await;
|
||||
|
||||
assert!(result.is_err());
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_add() {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
let batch = record_batch!(("i", Int32, [0, 1, 2])).unwrap();
|
||||
let table = conn
|
||||
.create_table("test", batch.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 3);
|
||||
|
||||
let new_batch = record_batch!(("i", Int32, [3])).unwrap();
|
||||
table.add(new_batch).execute().await.unwrap();
|
||||
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 4);
|
||||
assert_eq!(table.schema().await.unwrap(), batch.schema());
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_add_overwrite() {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
let batch = record_batch!(("i", Int32, [0, 1, 2])).unwrap();
|
||||
let table = conn
|
||||
.create_table("test", batch.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), batch.num_rows());
|
||||
|
||||
let new_batch = record_batch!(("x", Float32, [0.0, 1.0])).unwrap();
|
||||
let res = table
|
||||
.add(new_batch.clone())
|
||||
.mode(AddDataMode::Overwrite)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
assert_eq!(res.version, table.version().await.unwrap());
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), new_batch.num_rows());
|
||||
assert_eq!(table.schema().await.unwrap(), new_batch.schema());
|
||||
|
||||
// Can overwrite using underlying WriteParams (which
|
||||
// take precedence over AddDataMode)
|
||||
let param: WriteParams = WriteParams {
|
||||
mode: WriteMode::Overwrite,
|
||||
..Default::default()
|
||||
};
|
||||
|
||||
table
|
||||
.add(new_batch.clone())
|
||||
.write_options(WriteOptions {
|
||||
lance_write_params: Some(param),
|
||||
})
|
||||
.mode(AddDataMode::Append)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), new_batch.num_rows());
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_add_with_embeddings() {
|
||||
let registry = Arc::new(MemoryRegistry::new());
|
||||
let mock_embedding: Arc<dyn EmbeddingFunction> = Arc::new(MockEmbed::new("mock", 4));
|
||||
registry.register("mock", mock_embedding).unwrap();
|
||||
|
||||
let conn = connect("memory://")
|
||||
.embedding_registry(registry)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let schema = Arc::new(Schema::new(vec![
|
||||
Field::new("text", DataType::Utf8, false),
|
||||
Field::new(
|
||||
"text_embedding",
|
||||
DataType::FixedSizeList(Arc::new(Field::new("item", DataType::Float32, true)), 4),
|
||||
false,
|
||||
),
|
||||
]));
|
||||
|
||||
// Add embedding metadata to the schema
|
||||
let embedding_def = EmbeddingDefinition::new("text", "mock", Some("text_embedding"));
|
||||
let table_def = TableDefinition::new(
|
||||
schema.clone(),
|
||||
vec![
|
||||
ColumnDefinition {
|
||||
kind: ColumnKind::Physical,
|
||||
},
|
||||
ColumnDefinition {
|
||||
kind: ColumnKind::Embedding(embedding_def),
|
||||
},
|
||||
],
|
||||
);
|
||||
let rich_schema = table_def.into_rich_schema();
|
||||
|
||||
let table = conn
|
||||
.create_empty_table("embed_test", rich_schema)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Now add new data WITHOUT the embedding column - it should be computed automatically
|
||||
let new_batch = record_batch!(("text", Utf8, ["hello", "world"])).unwrap();
|
||||
table.add(new_batch).execute().await.unwrap();
|
||||
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 2);
|
||||
|
||||
// Query to verify the embeddings were computed for the new rows
|
||||
let results: Vec<RecordBatch> = table
|
||||
.query()
|
||||
.select(Select::columns(&["text", "text_embedding"]))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let total_rows: usize = results.iter().map(|b| b.num_rows()).sum();
|
||||
assert_eq!(total_rows, 2);
|
||||
|
||||
// Check that all rows have embedding values (not null)
|
||||
for batch in &results {
|
||||
let embedding_col = batch.column(1);
|
||||
assert_eq!(embedding_col.null_count(), 0);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -287,8 +287,7 @@ pub mod tests {
|
||||
|
||||
use arrow::array::AsArray;
|
||||
use arrow_array::{
|
||||
BinaryArray, Float64Array, Int32Array, Int64Array, RecordBatch, RecordBatchIterator,
|
||||
RecordBatchReader, StringArray, UInt32Array,
|
||||
BinaryArray, Float64Array, Int32Array, Int64Array, RecordBatch, StringArray, UInt32Array,
|
||||
};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use datafusion::{
|
||||
@@ -308,7 +307,7 @@ pub mod tests {
|
||||
table::datafusion::BaseTableAdapter,
|
||||
};
|
||||
|
||||
fn make_test_batches() -> impl RecordBatchReader + Send + Sync + 'static {
|
||||
fn make_test_batches() -> RecordBatch {
|
||||
let metadata = HashMap::from_iter(vec![("foo".to_string(), "bar".to_string())]);
|
||||
let schema = Arc::new(
|
||||
Schema::new(vec![
|
||||
@@ -317,19 +316,17 @@ pub mod tests {
|
||||
])
|
||||
.with_metadata(metadata),
|
||||
);
|
||||
RecordBatchIterator::new(
|
||||
vec![RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![
|
||||
Arc::new(Int32Array::from_iter_values(0..10)),
|
||||
Arc::new(UInt32Array::from_iter_values(0..10)),
|
||||
],
|
||||
)],
|
||||
RecordBatch::try_new(
|
||||
schema,
|
||||
vec![
|
||||
Arc::new(Int32Array::from_iter_values(0..10)),
|
||||
Arc::new(UInt32Array::from_iter_values(0..10)),
|
||||
],
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
fn make_tbl_two_test_batches() -> impl RecordBatchReader + Send + Sync + 'static {
|
||||
fn make_tbl_two_test_batches() -> RecordBatch {
|
||||
let metadata = HashMap::from_iter(vec![("foo".to_string(), "bar".to_string())]);
|
||||
let schema = Arc::new(
|
||||
Schema::new(vec![
|
||||
@@ -342,28 +339,26 @@ pub mod tests {
|
||||
])
|
||||
.with_metadata(metadata),
|
||||
);
|
||||
RecordBatchIterator::new(
|
||||
vec![RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![
|
||||
Arc::new(Int64Array::from_iter_values(0..1000)),
|
||||
Arc::new(StringArray::from_iter_values(
|
||||
(0..1000).map(|i| i.to_string()),
|
||||
)),
|
||||
Arc::new(Float64Array::from_iter_values((0..1000).map(|i| i as f64))),
|
||||
Arc::new(StringArray::from_iter_values(
|
||||
(0..1000).map(|i| format!("{{\"i\":{}}}", i)),
|
||||
)),
|
||||
Arc::new(BinaryArray::from_iter_values(
|
||||
(0..1000).map(|i| (i as u32).to_be_bytes().to_vec()),
|
||||
)),
|
||||
Arc::new(StringArray::from_iter_values(
|
||||
(0..1000).map(|i| i.to_string()),
|
||||
)),
|
||||
],
|
||||
)],
|
||||
RecordBatch::try_new(
|
||||
schema,
|
||||
vec![
|
||||
Arc::new(Int64Array::from_iter_values(0..1000)),
|
||||
Arc::new(StringArray::from_iter_values(
|
||||
(0..1000).map(|i| i.to_string()),
|
||||
)),
|
||||
Arc::new(Float64Array::from_iter_values((0..1000).map(|i| i as f64))),
|
||||
Arc::new(StringArray::from_iter_values(
|
||||
(0..1000).map(|i| format!("{{\"i\":{}}}", i)),
|
||||
)),
|
||||
Arc::new(BinaryArray::from_iter_values(
|
||||
(0..1000).map(|i| (i as u32).to_be_bytes().to_vec()),
|
||||
)),
|
||||
Arc::new(StringArray::from_iter_values(
|
||||
(0..1000).map(|i| i.to_string()),
|
||||
)),
|
||||
],
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
struct TestFixture {
|
||||
|
||||
@@ -222,7 +222,7 @@ mod tests {
|
||||
use std::vec;
|
||||
|
||||
use super::*;
|
||||
use arrow_array::{record_batch, Int32Array, RecordBatchIterator};
|
||||
use arrow_array::{record_batch, RecordBatchIterator};
|
||||
use datafusion::prelude::SessionContext;
|
||||
use datafusion_catalog::MemTable;
|
||||
use tempfile::tempdir;
|
||||
@@ -238,11 +238,8 @@ mod tests {
|
||||
|
||||
// Create initial table
|
||||
let batch = record_batch!(("id", Int32, [1, 2, 3])).unwrap();
|
||||
let schema = batch.schema();
|
||||
let reader = RecordBatchIterator::new(vec![Ok(batch)], schema);
|
||||
|
||||
let table = db
|
||||
.create_table("test_insert", Box::new(reader))
|
||||
.create_table("test_insert", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -279,11 +276,8 @@ mod tests {
|
||||
|
||||
// Create initial table with 3 rows
|
||||
let batch = record_batch!(("id", Int32, [1, 2, 3])).unwrap();
|
||||
let schema = batch.schema();
|
||||
let reader = RecordBatchIterator::new(vec![Ok(batch)], schema);
|
||||
|
||||
let table = db
|
||||
.create_table("test_overwrite", Box::new(reader))
|
||||
.create_table("test_overwrite", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -318,20 +312,9 @@ mod tests {
|
||||
let db = connect(uri).execute().await.unwrap();
|
||||
|
||||
// Create initial table
|
||||
let schema = Arc::new(ArrowSchema::new(vec![Field::new(
|
||||
"id",
|
||||
DataType::Int32,
|
||||
false,
|
||||
)]));
|
||||
let batches = vec![RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from(vec![1, 2, 3]))],
|
||||
)
|
||||
.unwrap()];
|
||||
let reader = RecordBatchIterator::new(batches.into_iter().map(Ok), schema.clone());
|
||||
|
||||
let batch = record_batch!(("id", Int32, [1, 2, 3])).unwrap();
|
||||
let table = db
|
||||
.create_table("test_empty", Box::new(reader))
|
||||
.create_table("test_empty", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -352,12 +335,13 @@ mod tests {
|
||||
false,
|
||||
)]));
|
||||
// Empty batches
|
||||
let source_reader = RecordBatchIterator::new(
|
||||
std::iter::empty::<Result<RecordBatch, arrow_schema::ArrowError>>(),
|
||||
source_schema,
|
||||
);
|
||||
let source_reader: Box<dyn arrow_array::RecordBatchReader + Send> =
|
||||
Box::new(RecordBatchIterator::new(
|
||||
std::iter::empty::<Result<RecordBatch, arrow_schema::ArrowError>>(),
|
||||
source_schema,
|
||||
));
|
||||
let source_table = db
|
||||
.create_table("empty_source", Box::new(source_reader))
|
||||
.create_table("empty_source", source_reader)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -389,20 +373,10 @@ mod tests {
|
||||
let db = connect(uri).execute().await.unwrap();
|
||||
|
||||
// Create initial table
|
||||
let schema = Arc::new(ArrowSchema::new(vec![Field::new(
|
||||
"id",
|
||||
DataType::Int32,
|
||||
true,
|
||||
)]));
|
||||
let batches =
|
||||
vec![
|
||||
RecordBatch::try_new(schema.clone(), vec![Arc::new(Int32Array::from(vec![1]))])
|
||||
.unwrap(),
|
||||
];
|
||||
let reader = RecordBatchIterator::new(batches.into_iter().map(Ok), schema.clone());
|
||||
|
||||
let batch = record_batch!(("id", Int32, [1])).unwrap();
|
||||
let schema = batch.schema();
|
||||
let table = db
|
||||
.create_table("test_multi_batch", Box::new(reader))
|
||||
.create_table("test_multi_batch", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
@@ -97,7 +97,7 @@ mod tests {
|
||||
table::datafusion::BaseTableAdapter,
|
||||
Connection, Table,
|
||||
};
|
||||
use arrow_array::{Int32Array, RecordBatch, RecordBatchIterator, StringArray};
|
||||
use arrow_array::{Int32Array, RecordBatch, StringArray};
|
||||
use arrow_schema::{DataType, Field, Schema as ArrowSchema};
|
||||
use datafusion::prelude::SessionContext;
|
||||
|
||||
@@ -173,14 +173,7 @@ mod tests {
|
||||
|
||||
// Create LanceDB database and table
|
||||
let db = crate::connect("memory://test").execute().await.unwrap();
|
||||
let table = db
|
||||
.create_table(
|
||||
"foo",
|
||||
RecordBatchIterator::new(vec![Ok(batch)].into_iter(), schema),
|
||||
)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let table = db.create_table("foo", batch).execute().await.unwrap();
|
||||
|
||||
// Create FTS index
|
||||
table
|
||||
@@ -323,13 +316,7 @@ mod tests {
|
||||
RecordBatch::try_new(metadata_schema.clone(), vec![metadata_col, extra_col]).unwrap();
|
||||
|
||||
let _metadata_table = db
|
||||
.create_table(
|
||||
"metadata",
|
||||
RecordBatchIterator::new(
|
||||
vec![Ok(metadata_batch.clone())].into_iter(),
|
||||
metadata_schema.clone(),
|
||||
),
|
||||
)
|
||||
.create_table("metadata", metadata_batch.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -393,14 +380,7 @@ mod tests {
|
||||
let batch =
|
||||
RecordBatch::try_new(schema.clone(), vec![id_col, text_col, category_col]).unwrap();
|
||||
|
||||
let table = db
|
||||
.create_table(
|
||||
table_name,
|
||||
RecordBatchIterator::new(vec![Ok(batch)].into_iter(), schema),
|
||||
)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let table = db.create_table(table_name, batch).execute().await.unwrap();
|
||||
|
||||
// Create FTS index
|
||||
table
|
||||
@@ -546,14 +526,7 @@ mod tests {
|
||||
]));
|
||||
let batch = RecordBatch::try_new(schema.clone(), vec![id_col, text_col]).unwrap();
|
||||
|
||||
let table = db
|
||||
.create_table(
|
||||
"docs",
|
||||
RecordBatchIterator::new(vec![Ok(batch)].into_iter(), schema),
|
||||
)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let table = db.create_table("docs", batch).execute().await.unwrap();
|
||||
|
||||
// Create FTS index with position information for phrase queries
|
||||
table
|
||||
@@ -691,14 +664,7 @@ mod tests {
|
||||
let batch =
|
||||
RecordBatch::try_new(schema.clone(), vec![id_col, title_col, content_col]).unwrap();
|
||||
|
||||
let table = db
|
||||
.create_table(
|
||||
"multi_col",
|
||||
RecordBatchIterator::new(vec![Ok(batch)].into_iter(), schema),
|
||||
)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let table = db.create_table("multi_col", batch).execute().await.unwrap();
|
||||
|
||||
// Create FTS indices on both columns
|
||||
table
|
||||
@@ -963,13 +929,7 @@ mod tests {
|
||||
let metadata_batch =
|
||||
RecordBatch::try_new(metadata_schema.clone(), vec![metadata_id, extra_info]).unwrap();
|
||||
let _metadata_table = db
|
||||
.create_table(
|
||||
"metadata",
|
||||
RecordBatchIterator::new(
|
||||
vec![Ok(metadata_batch.clone())].into_iter(),
|
||||
metadata_schema,
|
||||
),
|
||||
)
|
||||
.create_table("metadata", metadata_batch.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -1358,14 +1318,7 @@ mod tests {
|
||||
]));
|
||||
let batch = RecordBatch::try_new(schema.clone(), vec![id_col, text_col]).unwrap();
|
||||
|
||||
let table = db
|
||||
.create_table(
|
||||
"docs",
|
||||
RecordBatchIterator::new(vec![Ok(batch)].into_iter(), schema),
|
||||
)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let table = db.create_table("docs", batch).execute().await.unwrap();
|
||||
|
||||
// Create FTS index with position information
|
||||
table
|
||||
@@ -1510,14 +1463,7 @@ mod tests {
|
||||
let batch =
|
||||
RecordBatch::try_new(schema.clone(), vec![id_col, title_col, content_col]).unwrap();
|
||||
|
||||
let table = db
|
||||
.create_table(
|
||||
"docs",
|
||||
RecordBatchIterator::new(vec![Ok(batch)].into_iter(), schema),
|
||||
)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let table = db.create_table("docs", batch).execute().await.unwrap();
|
||||
|
||||
// Create FTS indices on both columns
|
||||
table
|
||||
@@ -1591,14 +1537,7 @@ mod tests {
|
||||
let batch =
|
||||
RecordBatch::try_new(schema.clone(), vec![id_col, title_col, content_col]).unwrap();
|
||||
|
||||
let table = db
|
||||
.create_table(
|
||||
"docs",
|
||||
RecordBatchIterator::new(vec![Ok(batch)].into_iter(), schema),
|
||||
)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let table = db.create_table("docs", batch).execute().await.unwrap();
|
||||
|
||||
// Create FTS indices
|
||||
table
|
||||
@@ -1724,36 +1663,23 @@ mod tests {
|
||||
.unwrap();
|
||||
|
||||
// Create table with simple text for n-gram testing
|
||||
let data = RecordBatchIterator::new(
|
||||
vec![RecordBatch::try_new(
|
||||
Arc::new(ArrowSchema::new(vec![
|
||||
Field::new("id", DataType::Int32, false),
|
||||
Field::new("text", DataType::Utf8, false),
|
||||
])),
|
||||
vec![
|
||||
Arc::new(Int32Array::from(vec![1, 2, 3])),
|
||||
Arc::new(StringArray::from(vec![
|
||||
"hello world",
|
||||
"lance database",
|
||||
"lance is cool",
|
||||
])),
|
||||
],
|
||||
)
|
||||
.unwrap()]
|
||||
.into_iter()
|
||||
.map(Ok),
|
||||
let data = RecordBatch::try_new(
|
||||
Arc::new(ArrowSchema::new(vec![
|
||||
Field::new("id", DataType::Int32, false),
|
||||
Field::new("text", DataType::Utf8, false),
|
||||
])),
|
||||
);
|
||||
vec![
|
||||
Arc::new(Int32Array::from(vec![1, 2, 3])),
|
||||
Arc::new(StringArray::from(vec![
|
||||
"hello world",
|
||||
"lance database",
|
||||
"lance is cool",
|
||||
])),
|
||||
],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let table = Arc::new(
|
||||
db.create_table("docs", Box::new(data))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap(),
|
||||
);
|
||||
let table = Arc::new(db.create_table("docs", data).execute().await.unwrap());
|
||||
|
||||
// Create FTS index with n-gram tokenizer (default min_ngram_length=3)
|
||||
table
|
||||
@@ -1876,43 +1802,29 @@ mod tests {
|
||||
.unwrap();
|
||||
|
||||
// Create table with two text columns
|
||||
let data = RecordBatchIterator::new(
|
||||
vec![RecordBatch::try_new(
|
||||
Arc::new(ArrowSchema::new(vec![
|
||||
Field::new("id", DataType::Int32, false),
|
||||
Field::new("title", DataType::Utf8, false),
|
||||
Field::new("content", DataType::Utf8, false),
|
||||
])),
|
||||
vec![
|
||||
Arc::new(Int32Array::from(vec![1, 2, 3])),
|
||||
Arc::new(StringArray::from(vec![
|
||||
"Important Document",
|
||||
"Another Document",
|
||||
"Random Text",
|
||||
])),
|
||||
Arc::new(StringArray::from(vec![
|
||||
"This is important information",
|
||||
"This has details",
|
||||
"Nothing special here",
|
||||
])),
|
||||
],
|
||||
)
|
||||
.unwrap()]
|
||||
.into_iter()
|
||||
.map(Ok),
|
||||
let data = RecordBatch::try_new(
|
||||
Arc::new(ArrowSchema::new(vec![
|
||||
Field::new("id", DataType::Int32, false),
|
||||
Field::new("title", DataType::Utf8, false),
|
||||
Field::new("content", DataType::Utf8, false),
|
||||
])),
|
||||
);
|
||||
vec![
|
||||
Arc::new(Int32Array::from(vec![1, 2, 3])),
|
||||
Arc::new(StringArray::from(vec![
|
||||
"Important Document",
|
||||
"Another Document",
|
||||
"Random Text",
|
||||
])),
|
||||
Arc::new(StringArray::from(vec![
|
||||
"This is important information",
|
||||
"This has details",
|
||||
"Nothing special here",
|
||||
])),
|
||||
],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let table = Arc::new(
|
||||
db.create_table("docs", Box::new(data))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap(),
|
||||
);
|
||||
let table = Arc::new(db.create_table("docs", data).execute().await.unwrap());
|
||||
|
||||
// Create FTS indices on both columns
|
||||
table
|
||||
|
||||
@@ -57,15 +57,6 @@ impl DatasetRef {
|
||||
matches!(self, Self::Latest { .. })
|
||||
}
|
||||
|
||||
async fn need_reload(&self) -> Result<bool> {
|
||||
Ok(match self {
|
||||
Self::Latest { dataset, .. } => {
|
||||
dataset.latest_version_id().await? != dataset.version().version
|
||||
}
|
||||
Self::TimeTravel { dataset, version } => dataset.version().version != *version,
|
||||
})
|
||||
}
|
||||
|
||||
async fn as_latest(&mut self, read_consistency_interval: Option<Duration>) -> Result<()> {
|
||||
match self {
|
||||
Self::Latest { .. } => Ok(()),
|
||||
@@ -118,6 +109,21 @@ impl DatasetRef {
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn is_up_to_date(&self) -> bool {
|
||||
match self {
|
||||
Self::Latest {
|
||||
read_consistency_interval,
|
||||
last_consistency_check,
|
||||
..
|
||||
} => match (read_consistency_interval, last_consistency_check) {
|
||||
(None, _) => true,
|
||||
(Some(_), None) => false,
|
||||
(Some(interval), Some(last_check)) => last_check.elapsed() < *interval,
|
||||
},
|
||||
Self::TimeTravel { dataset, version } => dataset.version().version == *version,
|
||||
}
|
||||
}
|
||||
|
||||
fn time_travel_version(&self) -> Option<u64> {
|
||||
match self {
|
||||
Self::Latest { .. } => None,
|
||||
@@ -205,18 +211,7 @@ impl DatasetConsistencyWrapper {
|
||||
}
|
||||
|
||||
pub async fn reload(&self) -> Result<()> {
|
||||
if !self.0.read().await.need_reload().await? {
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
let mut write_guard = self.0.write().await;
|
||||
// on lock escalation -- check if someone else has already reloaded
|
||||
if !write_guard.need_reload().await? {
|
||||
return Ok(());
|
||||
}
|
||||
|
||||
// actually need reloading
|
||||
write_guard.reload().await
|
||||
self.0.write().await.reload().await
|
||||
}
|
||||
|
||||
/// Returns the version, if in time travel mode, or None otherwise
|
||||
@@ -235,35 +230,20 @@ impl DatasetConsistencyWrapper {
|
||||
}
|
||||
}
|
||||
|
||||
async fn is_up_to_date(&self) -> Result<bool> {
|
||||
let dataset_ref = self.0.read().await;
|
||||
match &*dataset_ref {
|
||||
DatasetRef::Latest {
|
||||
read_consistency_interval,
|
||||
last_consistency_check,
|
||||
..
|
||||
} => match (read_consistency_interval, last_consistency_check) {
|
||||
(None, _) => Ok(true),
|
||||
(Some(_), None) => Ok(false),
|
||||
(Some(read_consistency_interval), Some(last_consistency_check)) => {
|
||||
if &last_consistency_check.elapsed() < read_consistency_interval {
|
||||
Ok(true)
|
||||
} else {
|
||||
Ok(false)
|
||||
}
|
||||
}
|
||||
},
|
||||
DatasetRef::TimeTravel { dataset, version } => {
|
||||
Ok(dataset.version().version == *version)
|
||||
}
|
||||
}
|
||||
async fn is_up_to_date(&self) -> bool {
|
||||
self.0.read().await.is_up_to_date()
|
||||
}
|
||||
|
||||
/// Ensures that the dataset is loaded and up-to-date with consistency and
|
||||
/// version parameters.
|
||||
async fn ensure_up_to_date(&self) -> Result<()> {
|
||||
if !self.is_up_to_date().await? {
|
||||
self.reload().await?;
|
||||
if !self.is_up_to_date().await {
|
||||
// Re-check under write lock — another task may have reloaded
|
||||
// while we waited for the lock.
|
||||
let mut write_guard = self.0.write().await;
|
||||
if !write_guard.is_up_to_date() {
|
||||
write_guard.reload().await?;
|
||||
}
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
@@ -351,4 +331,60 @@ mod tests {
|
||||
let stats = io_stats.incremental_stats();
|
||||
assert_eq!(stats.read_iops, 1);
|
||||
}
|
||||
|
||||
/// Regression test: before the fix, the reload fast-path (no version change)
|
||||
/// did not reset `last_consistency_check`, causing a list call on every
|
||||
/// subsequent query once the interval expired.
|
||||
#[tokio::test]
|
||||
async fn test_reload_resets_consistency_timer() {
|
||||
let db = connect("memory://")
|
||||
.read_consistency_interval(Duration::from_secs(1))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let io_stats = IoStatsHolder::default();
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
|
||||
let table = db
|
||||
.create_empty_table("test", schema)
|
||||
.write_options(WriteOptions {
|
||||
lance_write_params: Some(WriteParams {
|
||||
store_params: Some(ObjectStoreParams {
|
||||
object_store_wrapper: Some(Arc::new(io_stats.clone())),
|
||||
..Default::default()
|
||||
}),
|
||||
..Default::default()
|
||||
}),
|
||||
})
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let start = Instant::now();
|
||||
io_stats.incremental_stats(); // reset
|
||||
|
||||
// Step 1: within interval — no list
|
||||
table.schema().await.unwrap();
|
||||
let s = io_stats.incremental_stats();
|
||||
assert_eq!(s.read_iops, 0, "step 1, elapsed={:?}", start.elapsed());
|
||||
|
||||
// Step 2: still within interval — no list
|
||||
table.schema().await.unwrap();
|
||||
let s = io_stats.incremental_stats();
|
||||
assert_eq!(s.read_iops, 0, "step 2, elapsed={:?}", start.elapsed());
|
||||
|
||||
// Step 3: sleep past the 1s boundary
|
||||
tokio::time::sleep(Duration::from_secs(1)).await;
|
||||
|
||||
// Step 4: interval expired — exactly 1 list, timer resets
|
||||
table.schema().await.unwrap();
|
||||
let s = io_stats.incremental_stats();
|
||||
assert_eq!(s.read_iops, 1, "step 4, elapsed={:?}", start.elapsed());
|
||||
|
||||
// Step 5: 10 more calls — timer just reset, no lists (THIS is the regression test).
|
||||
for _ in 0..10 {
|
||||
table.schema().await.unwrap();
|
||||
}
|
||||
let s = io_stats.incremental_stats();
|
||||
assert_eq!(s.read_iops, 0, "step 5, elapsed={:?}", start.elapsed());
|
||||
}
|
||||
}
|
||||
|
||||
@@ -34,7 +34,7 @@ pub(crate) async fn execute_delete(table: &NativeTable, predicate: &str) -> Resu
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use crate::connect;
|
||||
use arrow_array::{record_batch, Int32Array, RecordBatch, RecordBatchIterator};
|
||||
use arrow_array::{record_batch, Int32Array, RecordBatch};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use std::sync::Arc;
|
||||
|
||||
@@ -53,10 +53,7 @@ mod tests {
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_delete",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_delete", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -102,10 +99,7 @@ mod tests {
|
||||
let original_schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_delete_all",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], original_schema.clone()),
|
||||
)
|
||||
.create_table("test_delete_all", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -126,13 +120,8 @@ mod tests {
|
||||
// Create a table with 5 rows
|
||||
let batch = record_batch!(("id", Int32, [1, 2, 3, 4, 5])).unwrap();
|
||||
|
||||
let schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_delete_noop",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_delete_noop", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
729
rust/lancedb/src/table/optimize.rs
Normal file
729
rust/lancedb/src/table/optimize.rs
Normal file
@@ -0,0 +1,729 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
//! Table optimization operations for compaction, pruning, and index optimization.
|
||||
//!
|
||||
//! This module contains the implementation of optimization operations that help
|
||||
//! maintain good performance for LanceDB tables.
|
||||
|
||||
use std::sync::Arc;
|
||||
|
||||
use lance::dataset::cleanup::RemovalStats;
|
||||
use lance::dataset::optimize::{compact_files, CompactionMetrics, IndexRemapperOptions};
|
||||
use lance_index::optimize::OptimizeOptions;
|
||||
use lance_index::DatasetIndexExt;
|
||||
use log::info;
|
||||
|
||||
pub use chrono::Duration;
|
||||
pub use lance::dataset::optimize::CompactionOptions;
|
||||
|
||||
use super::NativeTable;
|
||||
use crate::error::Result;
|
||||
|
||||
/// Optimize the dataset.
|
||||
///
|
||||
/// Similar to `VACUUM` in PostgreSQL, it offers different options to
|
||||
/// optimize different parts of the table on disk.
|
||||
///
|
||||
/// By default, it optimizes everything, as [`OptimizeAction::All`].
|
||||
pub enum OptimizeAction {
|
||||
/// Run all optimizations with default values
|
||||
All,
|
||||
/// Compacts files in the dataset
|
||||
///
|
||||
/// LanceDb uses a readonly filesystem for performance and safe concurrency. Every time
|
||||
/// new data is added it will be added into new files. Small files
|
||||
/// can hurt both read and write performance. Compaction will merge small files
|
||||
/// into larger ones.
|
||||
///
|
||||
/// All operations that modify data (add, delete, update, merge insert, etc.) will create
|
||||
/// new files. If these operations are run frequently then compaction should run frequently.
|
||||
///
|
||||
/// If these operations are never run (search only) then compaction is not necessary.
|
||||
Compact {
|
||||
options: CompactionOptions,
|
||||
remap_options: Option<Arc<dyn IndexRemapperOptions>>,
|
||||
},
|
||||
/// Prune old version of datasets
|
||||
///
|
||||
/// Every change in LanceDb is additive. When data is removed from a dataset a new version is
|
||||
/// created that doesn't contain the removed data. However, the old version, which does contain
|
||||
/// the removed data, is left in place. This is necessary for consistency and concurrency and
|
||||
/// also enables time travel functionality like the ability to checkout an older version of the
|
||||
/// dataset to undo changes.
|
||||
///
|
||||
/// Over time, these old versions can consume a lot of disk space. The prune operation will
|
||||
/// remove versions of the dataset that are older than a certain age. This will free up the
|
||||
/// space used by that old data.
|
||||
///
|
||||
/// Once a version is pruned it can no longer be checked out.
|
||||
Prune {
|
||||
/// The duration of time to keep versions of the dataset.
|
||||
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`.
|
||||
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>,
|
||||
},
|
||||
/// Optimize the indices
|
||||
///
|
||||
/// This operation optimizes all indices in the table. When new data is added to LanceDb
|
||||
/// it is not added to the indices. However, it can still turn up in searches because the search
|
||||
/// function will scan both the indexed data and the unindexed data in parallel. Over time, the
|
||||
/// unindexed data can become large enough that the search performance is slow. This operation
|
||||
/// will add the unindexed data to the indices without rerunning the full index creation process.
|
||||
///
|
||||
/// Optimizing an index is faster than re-training the index but it does not typically adjust the
|
||||
/// underlying model relied upon by the index. This can eventually lead to poor search accuracy
|
||||
/// and so users may still want to occasionally retrain the index after adding a large amount of
|
||||
/// data.
|
||||
///
|
||||
/// For example, when using IVF, an index will create clusters. Optimizing an index assigns unindexed
|
||||
/// data to the existing clusters, but it does not move the clusters or create new clusters.
|
||||
Index(OptimizeOptions),
|
||||
}
|
||||
|
||||
impl Default for OptimizeAction {
|
||||
fn default() -> Self {
|
||||
Self::All
|
||||
}
|
||||
}
|
||||
|
||||
/// Statistics about the optimization.
|
||||
#[derive(Debug, Default)]
|
||||
pub struct OptimizeStats {
|
||||
/// Stats of the file compaction.
|
||||
pub compaction: Option<CompactionMetrics>,
|
||||
|
||||
/// Stats of the version pruning
|
||||
pub prune: Option<RemovalStats>,
|
||||
}
|
||||
|
||||
/// Internal implementation of optimize_indices
|
||||
///
|
||||
/// This logic was moved from NativeTable to keep table.rs clean.
|
||||
pub(crate) async fn optimize_indices(table: &NativeTable, options: &OptimizeOptions) -> Result<()> {
|
||||
info!("LanceDB: optimizing indices: {:?}", options);
|
||||
table
|
||||
.dataset
|
||||
.get_mut()
|
||||
.await?
|
||||
.optimize_indices(options)
|
||||
.await?;
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// Remove old versions of the dataset from disk.
|
||||
///
|
||||
/// # Arguments
|
||||
/// * `older_than` - The duration of time to keep versions of the dataset.
|
||||
/// * `delete_unverified` - 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`.
|
||||
///
|
||||
/// This calls into [lance::dataset::Dataset::cleanup_old_versions] and
|
||||
/// returns the result.
|
||||
pub(crate) async fn cleanup_old_versions(
|
||||
table: &NativeTable,
|
||||
older_than: Duration,
|
||||
delete_unverified: Option<bool>,
|
||||
error_if_tagged_old_versions: Option<bool>,
|
||||
) -> Result<RemovalStats> {
|
||||
Ok(table
|
||||
.dataset
|
||||
.get_mut()
|
||||
.await?
|
||||
.cleanup_old_versions(older_than, delete_unverified, error_if_tagged_old_versions)
|
||||
.await?)
|
||||
}
|
||||
|
||||
/// Compact files in the dataset.
|
||||
///
|
||||
/// This can be run after making several small appends to optimize the table
|
||||
/// for faster reads.
|
||||
///
|
||||
/// This calls into [lance::dataset::optimize::compact_files].
|
||||
pub(crate) async fn compact_files_impl(
|
||||
table: &NativeTable,
|
||||
options: CompactionOptions,
|
||||
remap_options: Option<Arc<dyn IndexRemapperOptions>>,
|
||||
) -> Result<CompactionMetrics> {
|
||||
let mut dataset_mut = table.dataset.get_mut().await?;
|
||||
let metrics = compact_files(&mut dataset_mut, options, remap_options).await?;
|
||||
Ok(metrics)
|
||||
}
|
||||
|
||||
/// Execute the optimize operation on the table.
|
||||
///
|
||||
/// This is the main entry point for all optimization operations.
|
||||
pub(crate) async fn execute_optimize(
|
||||
table: &NativeTable,
|
||||
action: OptimizeAction,
|
||||
) -> Result<OptimizeStats> {
|
||||
let mut stats = OptimizeStats {
|
||||
compaction: None,
|
||||
prune: None,
|
||||
};
|
||||
match action {
|
||||
OptimizeAction::All => {
|
||||
// Call helper functions directly to avoid async recursion issues
|
||||
stats.compaction =
|
||||
Some(compact_files_impl(table, CompactionOptions::default(), None).await?);
|
||||
stats.prune = Some(
|
||||
cleanup_old_versions(
|
||||
table,
|
||||
Duration::try_days(7).expect("valid delta"),
|
||||
None,
|
||||
None,
|
||||
)
|
||||
.await?,
|
||||
);
|
||||
optimize_indices(table, &OptimizeOptions::default()).await?;
|
||||
}
|
||||
OptimizeAction::Compact {
|
||||
options,
|
||||
remap_options,
|
||||
} => {
|
||||
stats.compaction = Some(compact_files_impl(table, options, remap_options).await?);
|
||||
}
|
||||
OptimizeAction::Prune {
|
||||
older_than,
|
||||
delete_unverified,
|
||||
error_if_tagged_old_versions,
|
||||
} => {
|
||||
stats.prune = Some(
|
||||
cleanup_old_versions(
|
||||
table,
|
||||
older_than.unwrap_or(Duration::try_days(7).expect("valid delta")),
|
||||
delete_unverified,
|
||||
error_if_tagged_old_versions,
|
||||
)
|
||||
.await?,
|
||||
);
|
||||
}
|
||||
OptimizeAction::Index(options) => {
|
||||
optimize_indices(table, &options).await?;
|
||||
}
|
||||
}
|
||||
Ok(stats)
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use arrow_array::{Int32Array, RecordBatch, StringArray};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use rstest::rstest;
|
||||
use std::sync::Arc;
|
||||
|
||||
use crate::connect;
|
||||
use crate::index::{scalar::BTreeIndexBuilder, Index};
|
||||
use crate::query::ExecutableQuery;
|
||||
use crate::table::{CompactionOptions, OptimizeAction, OptimizeStats};
|
||||
use futures::TryStreamExt;
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_optimize_compact_simple() {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
// Create a table with initial data
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("i", DataType::Int32, false)]));
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(0..100))],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table("test_compact", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Add more data to create multiple fragments
|
||||
for i in 0..5 {
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(
|
||||
(i * 100 + 100)..((i + 1) * 100 + 100),
|
||||
))],
|
||||
)
|
||||
.unwrap();
|
||||
table.add(batch).execute().await.unwrap();
|
||||
}
|
||||
|
||||
// Verify we have multiple fragments before compaction
|
||||
let initial_row_count = table.count_rows(None).await.unwrap();
|
||||
assert_eq!(initial_row_count, 600);
|
||||
|
||||
// Run compaction
|
||||
let stats = table
|
||||
.optimize(OptimizeAction::Compact {
|
||||
options: CompactionOptions {
|
||||
target_rows_per_fragment: 1000,
|
||||
..Default::default()
|
||||
},
|
||||
remap_options: None,
|
||||
})
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Verify compaction occurred
|
||||
assert!(stats.compaction.is_some());
|
||||
let compaction_metrics = stats.compaction.unwrap();
|
||||
assert!(compaction_metrics.fragments_removed > 0);
|
||||
|
||||
// Verify data integrity after compaction
|
||||
let final_row_count = table.count_rows(None).await.unwrap();
|
||||
assert_eq!(final_row_count, 600);
|
||||
|
||||
// Verify data content is correct
|
||||
let batches = table
|
||||
.query()
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect::<Vec<_>>()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let total_rows: usize = batches.iter().map(|b| b.num_rows()).sum();
|
||||
assert_eq!(total_rows, 600);
|
||||
|
||||
// Verify the values are as expected
|
||||
let mut all_values: Vec<i32> = Vec::new();
|
||||
for batch in &batches {
|
||||
let array = batch["i"].as_any().downcast_ref::<Int32Array>().unwrap();
|
||||
all_values.extend(array.values().iter().copied());
|
||||
}
|
||||
all_values.sort();
|
||||
let expected: Vec<i32> = (0..600).collect();
|
||||
assert_eq!(all_values, expected);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_optimize_prune_versions() {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
// Create a table
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("i", DataType::Int32, false)]));
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(0..10))],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table("test_prune", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Make several modifications to create versions
|
||||
for i in 0..5 {
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(
|
||||
(i * 10 + 10)..((i + 1) * 10 + 10),
|
||||
))],
|
||||
)
|
||||
.unwrap();
|
||||
table.add(batch).execute().await.unwrap();
|
||||
}
|
||||
|
||||
// Verify multiple versions exist
|
||||
let versions = table.list_versions().await.unwrap();
|
||||
assert!(versions.len() > 1);
|
||||
|
||||
// Run prune with a very old cutoff (won't delete recent versions)
|
||||
let stats = table
|
||||
.optimize(OptimizeAction::Prune {
|
||||
older_than: Some(chrono::Duration::try_days(0).unwrap()),
|
||||
delete_unverified: Some(true),
|
||||
error_if_tagged_old_versions: None,
|
||||
})
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Prune-only operation should not have compaction stats
|
||||
assert!(stats.compaction.is_none());
|
||||
|
||||
// Verify prune stats
|
||||
let prune_stats = stats.prune.unwrap();
|
||||
assert!(prune_stats.bytes_removed > 0);
|
||||
assert_eq!(prune_stats.old_versions, 5);
|
||||
|
||||
// Verify data is still intact
|
||||
let final_row_count = table.count_rows(None).await.unwrap();
|
||||
assert_eq!(final_row_count, 60);
|
||||
|
||||
// Verify data content is correct
|
||||
let batches = table
|
||||
.query()
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect::<Vec<_>>()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let mut all_values: Vec<i32> = Vec::new();
|
||||
for batch in &batches {
|
||||
let array = batch["i"].as_any().downcast_ref::<Int32Array>().unwrap();
|
||||
all_values.extend(array.values().iter().copied());
|
||||
}
|
||||
all_values.sort();
|
||||
let expected: Vec<i32> = (0..60).collect();
|
||||
assert_eq!(all_values, expected);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_optimize_index() {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
// Create a table with data
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("i", DataType::Int32, false)]));
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(0..100))],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table("test_index_optimize", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Create an index
|
||||
table
|
||||
.create_index(&["i"], Index::BTree(BTreeIndexBuilder::default()))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Add more data (unindexed)
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(100..200))],
|
||||
)
|
||||
.unwrap();
|
||||
table.add(batch).execute().await.unwrap();
|
||||
|
||||
// Verify index stats before optimization
|
||||
let indices = table.list_indices().await.unwrap();
|
||||
assert_eq!(indices.len(), 1);
|
||||
let index_name = indices[0].name.clone();
|
||||
let stats_before = table.index_stats(&index_name).await.unwrap().unwrap();
|
||||
assert_eq!(stats_before.num_indexed_rows, 100);
|
||||
assert_eq!(stats_before.num_unindexed_rows, 100);
|
||||
|
||||
// Run index optimization
|
||||
let stats = table
|
||||
.optimize(OptimizeAction::Index(Default::default()))
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// For index optimization, compaction and prune stats should be None
|
||||
assert!(stats.compaction.is_none());
|
||||
assert!(stats.prune.is_none());
|
||||
|
||||
// Verify index stats after optimization
|
||||
let stats_after = table.index_stats(&index_name).await.unwrap().unwrap();
|
||||
assert_eq!(stats_after.num_indexed_rows, 200);
|
||||
assert_eq!(stats_after.num_unindexed_rows, 0);
|
||||
assert!(stats_after.num_indices.is_some());
|
||||
|
||||
// Verify data integrity
|
||||
let final_row_count = table.count_rows(None).await.unwrap();
|
||||
assert_eq!(final_row_count, 200);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_optimize_all() {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
// Create a table with data
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("i", DataType::Int32, false)]));
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(0..100))],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table("test_optimize_all", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Add more data
|
||||
for i in 0..3 {
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(
|
||||
(i * 100 + 100)..((i + 1) * 100 + 100),
|
||||
))],
|
||||
)
|
||||
.unwrap();
|
||||
table.add(batch).execute().await.unwrap();
|
||||
}
|
||||
|
||||
// Run all optimizations
|
||||
let stats = table.optimize(OptimizeAction::All).await.unwrap();
|
||||
|
||||
// Verify stats from both compaction and prune
|
||||
assert!(stats.compaction.is_some());
|
||||
assert!(stats.prune.is_some());
|
||||
|
||||
// Verify data integrity
|
||||
let final_row_count = table.count_rows(None).await.unwrap();
|
||||
assert_eq!(final_row_count, 400);
|
||||
|
||||
// Verify data content
|
||||
let batches = table
|
||||
.query()
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect::<Vec<_>>()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let mut all_values: Vec<i32> = Vec::new();
|
||||
for batch in &batches {
|
||||
let array = batch["i"].as_any().downcast_ref::<Int32Array>().unwrap();
|
||||
all_values.extend(array.values().iter().copied());
|
||||
}
|
||||
all_values.sort();
|
||||
let expected: Vec<i32> = (0..400).collect();
|
||||
assert_eq!(all_values, expected);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_optimize_default_action() {
|
||||
// Verify that default action is All
|
||||
let action: OptimizeAction = Default::default();
|
||||
assert!(matches!(action, OptimizeAction::All));
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_optimize_stats_default() {
|
||||
// Verify OptimizeStats default values
|
||||
let stats: OptimizeStats = Default::default();
|
||||
assert!(stats.compaction.is_none());
|
||||
assert!(stats.prune.is_none());
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_compact_with_deferred_index_remap() {
|
||||
// Smoke test: verifies compaction with deferred index remap doesn't error.
|
||||
// We don't currently assert that remap is actually deferred.
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
// Create a table with data
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(0..100))],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table("test_deferred_remap", batch.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Add more data
|
||||
table.add(batch).execute().await.unwrap();
|
||||
|
||||
// Create an index
|
||||
table
|
||||
.create_index(&["id"], Index::BTree(BTreeIndexBuilder::default()))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Run compaction with deferred index remap
|
||||
let stats = table
|
||||
.optimize(OptimizeAction::Compact {
|
||||
options: CompactionOptions {
|
||||
target_rows_per_fragment: 2000,
|
||||
defer_index_remap: true,
|
||||
..Default::default()
|
||||
},
|
||||
remap_options: None,
|
||||
})
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
assert!(stats.compaction.is_some());
|
||||
|
||||
// Verify data integrity after compaction
|
||||
let final_row_count = table.count_rows(None).await.unwrap();
|
||||
assert_eq!(final_row_count, 200);
|
||||
|
||||
// Verify data content is correct
|
||||
let batches = table
|
||||
.query()
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect::<Vec<_>>()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let mut all_values: Vec<i32> = Vec::new();
|
||||
for batch in &batches {
|
||||
let array = batch["id"].as_any().downcast_ref::<Int32Array>().unwrap();
|
||||
all_values.extend(array.values().iter().copied());
|
||||
}
|
||||
all_values.sort();
|
||||
|
||||
// Since we added the same data twice (0..100 twice), we expect 200 values
|
||||
// with values 0-99 appearing twice
|
||||
let mut expected: Vec<i32> = (0..100).chain(0..100).collect();
|
||||
expected.sort();
|
||||
assert_eq!(all_values, expected);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_compaction_preserves_schema() {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
// Create a table with multiple columns
|
||||
let schema = Arc::new(Schema::new(vec![
|
||||
Field::new("id", DataType::Int32, false),
|
||||
Field::new("name", DataType::Utf8, true),
|
||||
]));
|
||||
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![
|
||||
Arc::new(Int32Array::from_iter_values(0..10)),
|
||||
Arc::new(StringArray::from(
|
||||
(0..10).map(|i| format!("name_{}", i)).collect::<Vec<_>>(),
|
||||
)),
|
||||
],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let original_schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table("test_schema_preserved", batch.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Add more data
|
||||
table.add(batch).execute().await.unwrap();
|
||||
|
||||
// Run compaction
|
||||
table
|
||||
.optimize(OptimizeAction::Compact {
|
||||
options: CompactionOptions::default(),
|
||||
remap_options: None,
|
||||
})
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Verify schema is preserved
|
||||
let current_schema = table.schema().await.unwrap();
|
||||
assert_eq!(current_schema, original_schema);
|
||||
|
||||
// Verify data is intact and correct
|
||||
let batches = table
|
||||
.query()
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect::<Vec<_>>()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let total_rows: usize = batches.iter().map(|b| b.num_rows()).sum();
|
||||
assert_eq!(total_rows, 20);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_optimize_empty_table() {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
// Create a table and delete all data
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("i", DataType::Int32, false)]));
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(0..10))],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table("test_empty_optimize", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Delete all rows
|
||||
table.delete("true").await.unwrap();
|
||||
|
||||
// Verify table is empty
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 0);
|
||||
|
||||
// Optimize should work on empty table
|
||||
let stats = table.optimize(OptimizeAction::All).await.unwrap();
|
||||
assert!(stats.compaction.is_some());
|
||||
assert!(stats.prune.is_some());
|
||||
|
||||
// Verify table is still empty but schema is preserved
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 0);
|
||||
let current_schema = table.schema().await.unwrap();
|
||||
assert_eq!(current_schema, schema);
|
||||
}
|
||||
|
||||
#[rstest]
|
||||
#[case::all(OptimizeAction::All)]
|
||||
#[case::compact(OptimizeAction::Compact {
|
||||
options: CompactionOptions::default(),
|
||||
remap_options: None,
|
||||
})]
|
||||
#[case::prune(OptimizeAction::Prune {
|
||||
older_than: Some(chrono::Duration::try_days(0).unwrap()),
|
||||
delete_unverified: Some(true),
|
||||
error_if_tagged_old_versions: None,
|
||||
})]
|
||||
#[case::index(OptimizeAction::Index(Default::default()))]
|
||||
#[tokio::test]
|
||||
async fn test_optimize_fails_on_checked_out_table(#[case] action: OptimizeAction) {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("i", DataType::Int32, false)]));
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(0..10))],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table("test_checkout_optimize", batch.clone())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
table.add(batch).execute().await.unwrap();
|
||||
|
||||
table.checkout(1).await.unwrap();
|
||||
|
||||
let result = table.optimize(action).await;
|
||||
assert!(result.is_err());
|
||||
|
||||
let err_msg = result.unwrap_err().to_string();
|
||||
assert!(
|
||||
err_msg.contains("cannot be modified when a specific version is checked out"),
|
||||
"Expected error message about checked out table, got: {}",
|
||||
err_msg
|
||||
);
|
||||
}
|
||||
}
|
||||
@@ -89,7 +89,7 @@ pub(crate) async fn execute_drop_columns(
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use arrow_array::{record_batch, Int32Array, RecordBatchIterator, StringArray};
|
||||
use arrow_array::{record_batch, Int32Array, StringArray};
|
||||
use arrow_schema::DataType;
|
||||
use futures::TryStreamExt;
|
||||
use lance::dataset::ColumnAlteration;
|
||||
@@ -105,13 +105,9 @@ mod tests {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
let batch = record_batch!(("id", Int32, [1, 2, 3, 4, 5])).unwrap();
|
||||
let schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_add_columns",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_add_columns", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -169,13 +165,9 @@ mod tests {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
let batch = record_batch!(("x", Int32, [10, 20, 30])).unwrap();
|
||||
let schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_add_multi_columns",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_add_multi_columns", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -205,13 +197,9 @@ mod tests {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
let batch = record_batch!(("id", Int32, [1, 2, 3])).unwrap();
|
||||
let schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_add_const_column",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_add_const_column", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -255,13 +243,9 @@ mod tests {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
let batch = record_batch!(("old_name", Int32, [1, 2, 3])).unwrap();
|
||||
let schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_alter_rename",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_alter_rename", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -304,10 +288,7 @@ mod tests {
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_alter_nullable",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_alter_nullable", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -332,13 +313,9 @@ mod tests {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
let batch = record_batch!(("num", Int32, [1, 2, 3])).unwrap();
|
||||
let schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_cast_type",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_cast_type", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -379,13 +356,9 @@ mod tests {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
let batch = record_batch!(("num", Int32, [1, 2, 3])).unwrap();
|
||||
let schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_invalid_cast",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_invalid_cast", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -407,13 +380,9 @@ mod tests {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
let batch = record_batch!(("a", Int32, [1, 2, 3]), ("b", Int32, [4, 5, 6])).unwrap();
|
||||
let schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_alter_multi",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_alter_multi", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -441,13 +410,9 @@ mod tests {
|
||||
|
||||
let batch =
|
||||
record_batch!(("keep", Int32, [1, 2, 3]), ("remove", Int32, [4, 5, 6])).unwrap();
|
||||
let schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_drop_single",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_drop_single", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -478,13 +443,9 @@ mod tests {
|
||||
("d", Int32, [7, 8])
|
||||
)
|
||||
.unwrap();
|
||||
let schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_drop_multi",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_drop_multi", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -511,13 +472,9 @@ mod tests {
|
||||
("extra", Int32, [10, 20, 30])
|
||||
)
|
||||
.unwrap();
|
||||
let schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_drop_preserves",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_drop_preserves", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -567,13 +524,9 @@ mod tests {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
let batch = record_batch!(("existing", Int32, [1, 2, 3])).unwrap();
|
||||
let schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_drop_nonexistent",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_drop_nonexistent", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -593,13 +546,9 @@ mod tests {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
let batch = record_batch!(("existing", Int32, [1, 2, 3])).unwrap();
|
||||
let schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_alter_nonexistent",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_alter_nonexistent", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -623,13 +572,8 @@ mod tests {
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
let batch = record_batch!(("a", Int32, [1, 2, 3]), ("b", Int32, [4, 5, 6])).unwrap();
|
||||
let schema = batch.schema();
|
||||
|
||||
let table = conn
|
||||
.create_table(
|
||||
"test_version_increment",
|
||||
RecordBatchIterator::new(vec![Ok(batch)], schema),
|
||||
)
|
||||
.create_table("test_version_increment", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
@@ -117,9 +117,8 @@ mod tests {
|
||||
use crate::query::{ExecutableQuery, Select};
|
||||
use arrow_array::{
|
||||
record_batch, Array, BooleanArray, Date32Array, FixedSizeListArray, Float32Array,
|
||||
Float64Array, Int32Array, Int64Array, LargeStringArray, RecordBatch, RecordBatchIterator,
|
||||
RecordBatchReader, StringArray, TimestampMillisecondArray, TimestampNanosecondArray,
|
||||
UInt32Array,
|
||||
Float64Array, Int32Array, Int64Array, LargeStringArray, RecordBatch, StringArray,
|
||||
TimestampMillisecondArray, TimestampNanosecondArray, UInt32Array,
|
||||
};
|
||||
use arrow_data::ArrayDataBuilder;
|
||||
use arrow_schema::{ArrowError, DataType, Field, Schema, TimeUnit};
|
||||
@@ -167,51 +166,46 @@ mod tests {
|
||||
),
|
||||
]));
|
||||
|
||||
let record_batch_iter = RecordBatchIterator::new(
|
||||
vec![RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![
|
||||
Arc::new(Int32Array::from_iter_values(0..10)),
|
||||
Arc::new(Int64Array::from_iter_values(0..10)),
|
||||
Arc::new(UInt32Array::from_iter_values(0..10)),
|
||||
Arc::new(StringArray::from_iter_values(vec![
|
||||
"a", "b", "c", "d", "e", "f", "g", "h", "i", "j",
|
||||
])),
|
||||
Arc::new(LargeStringArray::from_iter_values(vec![
|
||||
"a", "b", "c", "d", "e", "f", "g", "h", "i", "j",
|
||||
])),
|
||||
Arc::new(Float32Array::from_iter_values((0..10).map(|i| i as f32))),
|
||||
Arc::new(Float64Array::from_iter_values((0..10).map(|i| i as f64))),
|
||||
Arc::new(Into::<BooleanArray>::into(vec![
|
||||
true, false, true, false, true, false, true, false, true, false,
|
||||
])),
|
||||
Arc::new(Date32Array::from_iter_values(0..10)),
|
||||
Arc::new(TimestampNanosecondArray::from_iter_values(0..10)),
|
||||
Arc::new(TimestampMillisecondArray::from_iter_values(0..10)),
|
||||
Arc::new(
|
||||
create_fixed_size_list(
|
||||
Float32Array::from_iter_values((0..20).map(|i| i as f32)),
|
||||
2,
|
||||
)
|
||||
.unwrap(),
|
||||
),
|
||||
Arc::new(
|
||||
create_fixed_size_list(
|
||||
Float64Array::from_iter_values((0..20).map(|i| i as f64)),
|
||||
2,
|
||||
)
|
||||
.unwrap(),
|
||||
),
|
||||
],
|
||||
)
|
||||
.unwrap()]
|
||||
.into_iter()
|
||||
.map(Ok),
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
);
|
||||
vec![
|
||||
Arc::new(Int32Array::from_iter_values(0..10)),
|
||||
Arc::new(Int64Array::from_iter_values(0..10)),
|
||||
Arc::new(UInt32Array::from_iter_values(0..10)),
|
||||
Arc::new(StringArray::from_iter_values(vec![
|
||||
"a", "b", "c", "d", "e", "f", "g", "h", "i", "j",
|
||||
])),
|
||||
Arc::new(LargeStringArray::from_iter_values(vec![
|
||||
"a", "b", "c", "d", "e", "f", "g", "h", "i", "j",
|
||||
])),
|
||||
Arc::new(Float32Array::from_iter_values((0..10).map(|i| i as f32))),
|
||||
Arc::new(Float64Array::from_iter_values((0..10).map(|i| i as f64))),
|
||||
Arc::new(Into::<BooleanArray>::into(vec![
|
||||
true, false, true, false, true, false, true, false, true, false,
|
||||
])),
|
||||
Arc::new(Date32Array::from_iter_values(0..10)),
|
||||
Arc::new(TimestampNanosecondArray::from_iter_values(0..10)),
|
||||
Arc::new(TimestampMillisecondArray::from_iter_values(0..10)),
|
||||
Arc::new(
|
||||
create_fixed_size_list(
|
||||
Float32Array::from_iter_values((0..20).map(|i| i as f32)),
|
||||
2,
|
||||
)
|
||||
.unwrap(),
|
||||
),
|
||||
Arc::new(
|
||||
create_fixed_size_list(
|
||||
Float64Array::from_iter_values((0..20).map(|i| i as f64)),
|
||||
2,
|
||||
)
|
||||
.unwrap(),
|
||||
),
|
||||
],
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table("my_table", record_batch_iter)
|
||||
.create_table("my_table", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -338,15 +332,13 @@ mod tests {
|
||||
Ok(FixedSizeListArray::from(data))
|
||||
}
|
||||
|
||||
fn make_test_batches() -> impl RecordBatchReader + Send + Sync + 'static {
|
||||
fn make_test_batch() -> RecordBatch {
|
||||
let schema = Arc::new(Schema::new(vec![Field::new("i", DataType::Int32, false)]));
|
||||
RecordBatchIterator::new(
|
||||
vec![RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(0..10))],
|
||||
)],
|
||||
schema,
|
||||
RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![Arc::new(Int32Array::from_iter_values(0..10))],
|
||||
)
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
@@ -367,12 +359,8 @@ mod tests {
|
||||
)
|
||||
.unwrap();
|
||||
|
||||
let schema = batch.schema();
|
||||
// need the iterator for create table
|
||||
let record_batch_iter = RecordBatchIterator::new(vec![Ok(batch)], schema);
|
||||
|
||||
let table = conn
|
||||
.create_table("my_table", record_batch_iter)
|
||||
.create_table("my_table", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
@@ -430,7 +418,7 @@ mod tests {
|
||||
.await
|
||||
.unwrap();
|
||||
let tbl = conn
|
||||
.create_table("my_table", make_test_batches())
|
||||
.create_table("my_table", make_test_batch())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
@@ -3,3 +3,4 @@
|
||||
|
||||
pub mod connection;
|
||||
pub mod datagen;
|
||||
pub mod embeddings;
|
||||
|
||||
@@ -34,10 +34,7 @@ impl LanceDbDatagenExt for BatchGeneratorBuilder {
|
||||
schema,
|
||||
));
|
||||
let db = connect("memory:///").execute().await.unwrap();
|
||||
db.create_table_streaming(table_name, stream)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
db.create_table(table_name, stream).execute().await.unwrap()
|
||||
}
|
||||
}
|
||||
|
||||
@@ -48,8 +45,5 @@ pub async fn virtual_table(name: &str, values: &RecordBatch) -> Table {
|
||||
schema,
|
||||
));
|
||||
let db = connect("memory:///").execute().await.unwrap();
|
||||
db.create_table_streaming(name, stream)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
db.create_table(name, stream).execute().await.unwrap()
|
||||
}
|
||||
|
||||
59
rust/lancedb/src/test_utils/embeddings.rs
Normal file
59
rust/lancedb/src/test_utils/embeddings.rs
Normal file
@@ -0,0 +1,59 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
use std::{borrow::Cow, sync::Arc};
|
||||
|
||||
use arrow_array::{Array, FixedSizeListArray, Float32Array};
|
||||
use arrow_schema::{DataType, Field};
|
||||
|
||||
use crate::embeddings::EmbeddingFunction;
|
||||
use crate::Result;
|
||||
|
||||
#[derive(Debug, Clone)]
|
||||
pub struct MockEmbed {
|
||||
name: String,
|
||||
dim: usize,
|
||||
}
|
||||
|
||||
impl MockEmbed {
|
||||
pub fn new(name: impl Into<String>, dim: usize) -> Self {
|
||||
Self {
|
||||
name: name.into(),
|
||||
dim,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl EmbeddingFunction for MockEmbed {
|
||||
fn name(&self) -> &str {
|
||||
&self.name
|
||||
}
|
||||
|
||||
fn source_type(&self) -> Result<Cow<'_, DataType>> {
|
||||
Ok(Cow::Borrowed(&DataType::Utf8))
|
||||
}
|
||||
|
||||
fn dest_type(&self) -> Result<Cow<'_, DataType>> {
|
||||
Ok(Cow::Owned(DataType::new_fixed_size_list(
|
||||
DataType::Float32,
|
||||
self.dim as _,
|
||||
true,
|
||||
)))
|
||||
}
|
||||
|
||||
fn compute_source_embeddings(&self, source: Arc<dyn Array>) -> Result<Arc<dyn Array>> {
|
||||
// We can't use the FixedSizeListBuilder here because it always adds a null bitmap
|
||||
// and we want to explicitly work with non-nullable arrays.
|
||||
let len = source.len();
|
||||
let inner = Arc::new(Float32Array::from(vec![Some(1.0); len * self.dim]));
|
||||
let field = Field::new("item", inner.data_type().clone(), false);
|
||||
let arr = FixedSizeListArray::new(Arc::new(field), self.dim as _, inner, None);
|
||||
|
||||
Ok(Arc::new(arr))
|
||||
}
|
||||
|
||||
#[allow(unused_variables)]
|
||||
fn compute_query_embeddings(&self, input: Arc<dyn Array>) -> Result<Arc<dyn Array>> {
|
||||
todo!()
|
||||
}
|
||||
}
|
||||
@@ -15,7 +15,6 @@ use arrow_array::{
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use futures::StreamExt;
|
||||
use lancedb::{
|
||||
arrow::IntoArrow,
|
||||
connect,
|
||||
embeddings::{EmbeddingDefinition, EmbeddingFunction, EmbeddingRegistry},
|
||||
query::ExecutableQuery,
|
||||
@@ -253,7 +252,7 @@ async fn test_no_func_in_registry_on_add() -> Result<()> {
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn create_some_records() -> Result<impl IntoArrow> {
|
||||
fn create_some_records() -> Result<Box<dyn arrow_array::RecordBatchReader + Send>> {
|
||||
const TOTAL: usize = 2;
|
||||
|
||||
let schema = Arc::new(Schema::new(vec![
|
||||
|
||||
@@ -4,7 +4,7 @@
|
||||
#![cfg(feature = "s3-test")]
|
||||
use std::sync::Arc;
|
||||
|
||||
use arrow_array::{Int32Array, RecordBatch, RecordBatchIterator, StringArray};
|
||||
use arrow_array::{Int32Array, RecordBatch, StringArray};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
|
||||
use aws_config::{BehaviorVersion, ConfigLoader, Region, SdkConfig};
|
||||
@@ -111,7 +111,6 @@ async fn test_minio_lifecycle() -> Result<()> {
|
||||
.await?;
|
||||
|
||||
let data = test_data();
|
||||
let data = RecordBatchIterator::new(vec![Ok(data.clone())], data.schema());
|
||||
|
||||
let table = db.create_table("test_table", data).execute().await?;
|
||||
|
||||
@@ -127,7 +126,6 @@ async fn test_minio_lifecycle() -> Result<()> {
|
||||
assert_eq!(row_count, 3);
|
||||
|
||||
let data = test_data();
|
||||
let data = RecordBatchIterator::new(vec![Ok(data.clone())], data.schema());
|
||||
table.add(data).execute().await?;
|
||||
|
||||
db.drop_table("test_table", &[]).await?;
|
||||
@@ -247,7 +245,6 @@ async fn test_encryption() -> Result<()> {
|
||||
|
||||
// Create a table with encryption
|
||||
let data = test_data();
|
||||
let data = RecordBatchIterator::new(vec![Ok(data.clone())], data.schema());
|
||||
|
||||
let mut builder = db.create_table("test_table", data);
|
||||
for (key, value) in CONFIG {
|
||||
@@ -274,7 +271,6 @@ async fn test_encryption() -> Result<()> {
|
||||
let table = db.open_table("test_table").execute().await?;
|
||||
|
||||
let data = test_data();
|
||||
let data = RecordBatchIterator::new(vec![Ok(data.clone())], data.schema());
|
||||
table.add(data).execute().await?;
|
||||
validate_objects_encrypted(&bucket.0, "test_table", &key.0).await;
|
||||
|
||||
@@ -300,7 +296,6 @@ async fn test_table_storage_options_override() -> Result<()> {
|
||||
|
||||
// Create table overriding with key2 encryption
|
||||
let data = test_data();
|
||||
let data = RecordBatchIterator::new(vec![Ok(data.clone())], data.schema());
|
||||
let _table = db
|
||||
.create_table("test_override", data)
|
||||
.storage_option("aws_sse_kms_key_id", &key2.0)
|
||||
@@ -312,7 +307,6 @@ async fn test_table_storage_options_override() -> Result<()> {
|
||||
|
||||
// Also test that a table created without override uses connection settings
|
||||
let data = test_data();
|
||||
let data = RecordBatchIterator::new(vec![Ok(data.clone())], data.schema());
|
||||
let _table2 = db.create_table("test_inherit", data).execute().await?;
|
||||
|
||||
// Verify this table uses key1 from connection
|
||||
@@ -419,7 +413,6 @@ async fn test_concurrent_dynamodb_commit() {
|
||||
.unwrap();
|
||||
|
||||
let data = test_data();
|
||||
let data = RecordBatchIterator::new(vec![Ok(data.clone())], data.schema());
|
||||
|
||||
let table = db.create_table("test_table", data).execute().await.unwrap();
|
||||
|
||||
@@ -430,7 +423,6 @@ async fn test_concurrent_dynamodb_commit() {
|
||||
let table = db.open_table("test_table").execute().await.unwrap();
|
||||
let data = data.clone();
|
||||
tasks.push(tokio::spawn(async move {
|
||||
let data = RecordBatchIterator::new(vec![Ok(data.clone())], data.schema());
|
||||
table.add(data).execute().await.unwrap();
|
||||
}));
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user