mirror of
https://github.com/lancedb/lancedb.git
synced 2026-06-02 20:00:46 +00:00
Compare commits
1 Commits
xuanwo/tab
...
v0.30.0-be
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
71afca2559 |
@@ -1,5 +1,5 @@
|
||||
[tool.bumpversion]
|
||||
current_version = "0.30.1-beta.0"
|
||||
current_version = "0.30.0-beta.0"
|
||||
parse = """(?x)
|
||||
(?P<major>0|[1-9]\\d*)\\.
|
||||
(?P<minor>0|[1-9]\\d*)\\.
|
||||
|
||||
@@ -29,3 +29,7 @@ runs:
|
||||
args: ${{ inputs.args }}
|
||||
docker-options: "-e PIP_EXTRA_INDEX_URL='https://pypi.fury.io/lance-format/ https://pypi.fury.io/lancedb/'"
|
||||
working-directory: python
|
||||
- uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: windows-wheels
|
||||
path: python\target\wheels
|
||||
|
||||
110
.github/workflows/pypi-publish.yml
vendored
110
.github/workflows/pypi-publish.yml
vendored
@@ -8,9 +8,6 @@ on:
|
||||
# This should trigger a dry run (we skip the final publish step)
|
||||
paths:
|
||||
- .github/workflows/pypi-publish.yml
|
||||
- .github/workflows/build_linux_wheel/action.yml
|
||||
- .github/workflows/build_mac_wheel/action.yml
|
||||
- .github/workflows/build_windows_wheel/action.yml
|
||||
- Cargo.toml # Change in dependency frequently breaks builds
|
||||
- Cargo.lock
|
||||
|
||||
@@ -24,21 +21,32 @@ jobs:
|
||||
linux:
|
||||
name: Python ${{ matrix.config.platform }} manylinux${{ matrix.config.manylinux }}
|
||||
timeout-minutes: 60
|
||||
permissions:
|
||||
id-token: write
|
||||
contents: read
|
||||
strategy:
|
||||
matrix:
|
||||
config:
|
||||
- platform: x86_64
|
||||
manylinux: "2_17"
|
||||
extra_args: ""
|
||||
runner: ubuntu-22.04
|
||||
- platform: x86_64
|
||||
manylinux: "2_28"
|
||||
extra_args: "--features fp16kernels"
|
||||
runner: ubuntu-22.04
|
||||
# For successful fat LTO builds, we need a large runner to avoid OOM errors.
|
||||
- platform: aarch64
|
||||
manylinux: "2_17"
|
||||
extra_args: ""
|
||||
# For successful fat LTO builds, we need a large runner to avoid OOM errors.
|
||||
runner: ubuntu-2404-8x-arm64
|
||||
- platform: aarch64
|
||||
manylinux: "2_28"
|
||||
extra_args: "--features fp16kernels"
|
||||
runner: ubuntu-2404-8x-arm64
|
||||
runs-on: ${{ matrix.config.runner }}
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
@@ -52,14 +60,15 @@ jobs:
|
||||
args: "--release --strip ${{ matrix.config.extra_args }}"
|
||||
arm-build: ${{ matrix.config.platform == 'aarch64' }}
|
||||
manylinux: ${{ matrix.config.manylinux }}
|
||||
- uses: actions/upload-artifact@v7
|
||||
- uses: ./.github/workflows/upload_wheel
|
||||
if: startsWith(github.ref, 'refs/tags/python-v')
|
||||
with:
|
||||
name: wheels-linux-${{ matrix.config.platform }}-${{ matrix.config.manylinux }}
|
||||
path: target/wheels/lancedb-*.whl
|
||||
if-no-files-found: error
|
||||
fury_token: ${{ secrets.FURY_TOKEN }}
|
||||
mac:
|
||||
timeout-minutes: 90
|
||||
permissions:
|
||||
id-token: write
|
||||
contents: read
|
||||
runs-on: ${{ matrix.config.runner }}
|
||||
strategy:
|
||||
matrix:
|
||||
@@ -69,7 +78,7 @@ jobs:
|
||||
env:
|
||||
MACOSX_DEPLOYMENT_TARGET: 10.15
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
@@ -81,21 +90,18 @@ jobs:
|
||||
with:
|
||||
python-minor-version: 10
|
||||
args: "--release --strip --target ${{ matrix.config.target }} --features fp16kernels"
|
||||
- uses: actions/upload-artifact@v7
|
||||
- uses: ./.github/workflows/upload_wheel
|
||||
if: startsWith(github.ref, 'refs/tags/python-v')
|
||||
with:
|
||||
name: wheels-mac-${{ matrix.config.target }}
|
||||
path: target/wheels/lancedb-*.whl
|
||||
if-no-files-found: error
|
||||
fury_token: ${{ secrets.FURY_TOKEN }}
|
||||
windows:
|
||||
timeout-minutes: 90
|
||||
timeout-minutes: 60
|
||||
permissions:
|
||||
id-token: write
|
||||
contents: read
|
||||
runs-on: windows-latest
|
||||
env:
|
||||
# link.exe is single-threaded and the long pole on Windows builds. Use
|
||||
# rustc's bundled lld-link instead.
|
||||
CARGO_TARGET_X86_64_PC_WINDOWS_MSVC_LINKER: rust-lld
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
@@ -107,70 +113,18 @@ jobs:
|
||||
with:
|
||||
python-minor-version: 10
|
||||
args: "--release --strip"
|
||||
- uses: actions/upload-artifact@v7
|
||||
vcpkg_token: ${{ secrets.VCPKG_GITHUB_PACKAGES }}
|
||||
- uses: ./.github/workflows/upload_wheel
|
||||
if: startsWith(github.ref, 'refs/tags/python-v')
|
||||
with:
|
||||
name: wheels-windows
|
||||
path: target/wheels/lancedb-*.whl
|
||||
if-no-files-found: error
|
||||
publish:
|
||||
name: Publish wheels
|
||||
if: startsWith(github.ref, 'refs/tags/python-v')
|
||||
needs: [linux, mac, windows]
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
id-token: write
|
||||
contents: read
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- name: Download wheel artifacts
|
||||
uses: actions/download-artifact@v8
|
||||
with:
|
||||
pattern: wheels-*
|
||||
path: target/wheels
|
||||
merge-multiple: true
|
||||
- name: List wheels
|
||||
run: ls -la target/wheels
|
||||
- name: Choose repo
|
||||
id: choose_repo
|
||||
run: |
|
||||
if [[ ${{ github.ref }} == *beta* ]]; then
|
||||
echo "repo=fury" >> $GITHUB_OUTPUT
|
||||
else
|
||||
echo "repo=pypi" >> $GITHUB_OUTPUT
|
||||
fi
|
||||
- name: Publish to Fury
|
||||
if: steps.choose_repo.outputs.repo == 'fury'
|
||||
env:
|
||||
FURY_TOKEN: ${{ secrets.FURY_TOKEN }}
|
||||
run: |
|
||||
shopt -s nullglob
|
||||
WHEELS=(target/wheels/lancedb-*.whl)
|
||||
if [[ ${#WHEELS[@]} -eq 0 ]]; then
|
||||
echo "No wheels found in target/wheels/" >&2
|
||||
exit 1
|
||||
fi
|
||||
for WHEEL in "${WHEELS[@]}"; do
|
||||
echo "Uploading $WHEEL to Fury"
|
||||
curl -f -F package=@"$WHEEL" "https://$FURY_TOKEN@push.fury.io/lancedb/"
|
||||
done
|
||||
# NOTE: pypa/gh-action-pypi-publish must be invoked directly from a
|
||||
# workflow file, not from inside a composite action. When called from a
|
||||
# composite, `github.action_repository` is empty (actions/runner#2473)
|
||||
# and the action falls back to `github.repository`, producing a bogus
|
||||
# `docker://ghcr.io/<repo>:<ref>` image reference that GHA tries to pull.
|
||||
- name: Publish to PyPI
|
||||
if: steps.choose_repo.outputs.repo == 'pypi'
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
with:
|
||||
packages-dir: target/wheels/
|
||||
fury_token: ${{ secrets.FURY_TOKEN }}
|
||||
gh-release:
|
||||
if: startsWith(github.ref, 'refs/tags/python-v')
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
contents: write
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
lfs: true
|
||||
@@ -233,13 +187,13 @@ jobs:
|
||||
report-failure:
|
||||
name: Report Workflow Failure
|
||||
runs-on: ubuntu-latest
|
||||
needs: [linux, mac, windows, publish]
|
||||
needs: [linux, mac, windows]
|
||||
permissions:
|
||||
contents: read
|
||||
issues: write
|
||||
if: always() && failure() && startsWith(github.ref, 'refs/tags/python-v')
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/checkout@v4
|
||||
- uses: ./.github/actions/create-failure-issue
|
||||
with:
|
||||
job-results: ${{ toJSON(needs) }}
|
||||
|
||||
34
.github/workflows/upload_wheel/action.yml
vendored
Normal file
34
.github/workflows/upload_wheel/action.yml
vendored
Normal file
@@ -0,0 +1,34 @@
|
||||
name: upload-wheel
|
||||
|
||||
description: "Upload wheels to Pypi"
|
||||
inputs:
|
||||
fury_token:
|
||||
required: true
|
||||
description: "release token for the fury repo"
|
||||
|
||||
runs:
|
||||
using: "composite"
|
||||
steps:
|
||||
- name: Choose repo
|
||||
shell: bash
|
||||
id: choose_repo
|
||||
run: |
|
||||
if [[ ${{ github.ref }} == *beta* ]]; then
|
||||
echo "repo=fury" >> $GITHUB_OUTPUT
|
||||
else
|
||||
echo "repo=pypi" >> $GITHUB_OUTPUT
|
||||
fi
|
||||
- name: Publish to Fury
|
||||
if: steps.choose_repo.outputs.repo == 'fury'
|
||||
shell: bash
|
||||
env:
|
||||
FURY_TOKEN: ${{ inputs.fury_token }}
|
||||
run: |
|
||||
WHEEL=$(ls target/wheels/lancedb-*.whl 2> /dev/null | head -n 1)
|
||||
echo "Uploading $WHEEL to Fury"
|
||||
curl -f -F package=@$WHEEL https://$FURY_TOKEN@push.fury.io/lancedb/
|
||||
- name: Publish to PyPI
|
||||
if: steps.choose_repo.outputs.repo == 'pypi'
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
with:
|
||||
packages-dir: target/wheels/
|
||||
11
AGENTS.md
11
AGENTS.md
@@ -37,13 +37,10 @@ Before committing changes, run formatting for every language you touched. At min
|
||||
and run targeted tests through `cd python && uv run ...`.
|
||||
* TypeScript changes: run the relevant `npm`/`pnpm` lint, format, build, and docs commands in `nodejs`.
|
||||
|
||||
Before creating a PR, the exact value passed to `gh pr create --title` must follow
|
||||
Conventional Commits, such as `fix: support nested field paths in native index creation`
|
||||
or `feat(python): add dataset multiprocessing support`. Do not use a plain natural
|
||||
language summary like `Support nested field paths in native index creation` as the PR
|
||||
title. The semantic-release check uses the PR title and body as the merge commit message,
|
||||
so a non-conventional PR title will fail CI. After creating a PR, read the remote PR title
|
||||
back and fix it immediately if it is not conventional.
|
||||
Before creating a PR, make sure the PR title follows Conventional Commits, such as
|
||||
`fix: support nested field paths in native index creation` or
|
||||
`feat(python): add dataset multiprocessing support`. The semantic-release check uses the
|
||||
PR title and body as the merge commit message, so a non-conventional PR title will fail CI.
|
||||
|
||||
## Coding tips
|
||||
|
||||
|
||||
506
Cargo.lock
generated
506
Cargo.lock
generated
File diff suppressed because it is too large
Load Diff
28
Cargo.toml
28
Cargo.toml
@@ -13,20 +13,20 @@ categories = ["database-implementations"]
|
||||
rust-version = "1.91.0"
|
||||
|
||||
[workspace.dependencies]
|
||||
lance = { "version" = "=7.2.0-beta.3", default-features = false, "tag" = "v7.2.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-core = { "version" = "=7.2.0-beta.3", "tag" = "v7.2.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-datagen = { "version" = "=7.2.0-beta.3", "tag" = "v7.2.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-file = { "version" = "=7.2.0-beta.3", "tag" = "v7.2.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-io = { "version" = "=7.2.0-beta.3", default-features = false, "tag" = "v7.2.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-index = { "version" = "=7.2.0-beta.3", "tag" = "v7.2.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-linalg = { "version" = "=7.2.0-beta.3", "tag" = "v7.2.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-namespace = { "version" = "=7.2.0-beta.3", "tag" = "v7.2.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-namespace-impls = { "version" = "=7.2.0-beta.3", default-features = false, "tag" = "v7.2.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-table = { "version" = "=7.2.0-beta.3", "tag" = "v7.2.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-testing = { "version" = "=7.2.0-beta.3", "tag" = "v7.2.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-datafusion = { "version" = "=7.2.0-beta.3", "tag" = "v7.2.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-encoding = { "version" = "=7.2.0-beta.3", "tag" = "v7.2.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-arrow = { "version" = "=7.2.0-beta.3", "tag" = "v7.2.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance = { "version" = "=7.0.0-beta.13", default-features = false, "tag" = "v7.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-core = { "version" = "=7.0.0-beta.13", "tag" = "v7.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-datagen = { "version" = "=7.0.0-beta.13", "tag" = "v7.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-file = { "version" = "=7.0.0-beta.13", "tag" = "v7.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-io = { "version" = "=7.0.0-beta.13", default-features = false, "tag" = "v7.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-index = { "version" = "=7.0.0-beta.13", "tag" = "v7.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-linalg = { "version" = "=7.0.0-beta.13", "tag" = "v7.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-namespace = { "version" = "=7.0.0-beta.13", "tag" = "v7.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-namespace-impls = { "version" = "=7.0.0-beta.13", default-features = false, "tag" = "v7.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-table = { "version" = "=7.0.0-beta.13", "tag" = "v7.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-testing = { "version" = "=7.0.0-beta.13", "tag" = "v7.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-datafusion = { "version" = "=7.0.0-beta.13", "tag" = "v7.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-encoding = { "version" = "=7.0.0-beta.13", "tag" = "v7.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
|
||||
lance-arrow = { "version" = "=7.0.0-beta.13", "tag" = "v7.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
|
||||
ahash = "0.8"
|
||||
# Note that this one does not include pyarrow
|
||||
arrow = { version = "58.0.0", optional = false }
|
||||
|
||||
@@ -112,25 +112,25 @@ def fetch_remote_tags() -> List[TagInfo]:
|
||||
"api",
|
||||
"-X",
|
||||
"GET",
|
||||
f"repos/{LANCE_REPO}/releases",
|
||||
f"repos/{LANCE_REPO}/git/refs/tags",
|
||||
"--paginate",
|
||||
"--jq",
|
||||
".[].tag_name",
|
||||
"-F",
|
||||
"per_page=20",
|
||||
".[].ref",
|
||||
]
|
||||
)
|
||||
tags: List[TagInfo] = []
|
||||
for line in output.splitlines():
|
||||
tag = line.strip()
|
||||
if not tag.startswith("v"):
|
||||
ref = line.strip()
|
||||
if not ref.startswith("refs/tags/v"):
|
||||
continue
|
||||
tag = ref.split("refs/tags/")[-1]
|
||||
version = tag.lstrip("v")
|
||||
try:
|
||||
tags.append(TagInfo(tag=tag, version=version, semver=parse_semver(version)))
|
||||
except ValueError:
|
||||
continue
|
||||
if not tags:
|
||||
raise RuntimeError("No Lance releases could be parsed from GitHub API output")
|
||||
raise RuntimeError("No Lance tags could be parsed from GitHub API output")
|
||||
return tags
|
||||
|
||||
|
||||
|
||||
@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
|
||||
<dependency>
|
||||
<groupId>com.lancedb</groupId>
|
||||
<artifactId>lancedb-core</artifactId>
|
||||
<version>0.30.1-beta.0</version>
|
||||
<version>0.30.0-beta.0</version>
|
||||
</dependency>
|
||||
```
|
||||
|
||||
|
||||
@@ -76,57 +76,6 @@ the query optimizer chooses a suboptimal path.
|
||||
|
||||
***
|
||||
|
||||
### useLsmWrite()
|
||||
|
||||
```ts
|
||||
useLsmWrite(useLsmWrite): MergeInsertBuilder
|
||||
```
|
||||
|
||||
Controls whether the merge uses the MemWAL LSM write path.
|
||||
|
||||
By default (unset), a `mergeInsert` on a table with an LSM write spec is
|
||||
routed through Lance's MemWAL shard writer, and a table without one uses
|
||||
the standard path. Pass `false` to force the standard path even when a
|
||||
spec is set. Pass `true` to require a spec — `mergeInsert` rejects if none
|
||||
is installed.
|
||||
|
||||
#### Parameters
|
||||
|
||||
* **useLsmWrite**: `boolean`
|
||||
Whether to use the LSM write path.
|
||||
|
||||
#### Returns
|
||||
|
||||
[`MergeInsertBuilder`](MergeInsertBuilder.md)
|
||||
|
||||
***
|
||||
|
||||
### validateSingleShard()
|
||||
|
||||
```ts
|
||||
validateSingleShard(validateSingleShard): MergeInsertBuilder
|
||||
```
|
||||
|
||||
Controls how an LSM merge checks that its input targets a single shard.
|
||||
|
||||
When a table has an LSM write spec, every row in a `mergeInsert` call must
|
||||
route to the same shard. When `true` (the default), every row is inspected
|
||||
to verify this. When `false`, only the first row is inspected and the
|
||||
shard it routes to is used for the whole input — a faster path for callers
|
||||
that have already pre-sharded their input. Has no effect on tables without
|
||||
an LSM write spec.
|
||||
|
||||
#### Parameters
|
||||
|
||||
* **validateSingleShard**: `boolean`
|
||||
Whether to check every row routes to one shard. Defaults to `true`.
|
||||
|
||||
#### Returns
|
||||
|
||||
[`MergeInsertBuilder`](MergeInsertBuilder.md)
|
||||
|
||||
***
|
||||
|
||||
### whenMatchedUpdateAll()
|
||||
|
||||
```ts
|
||||
|
||||
@@ -187,25 +187,6 @@ Any attempt to use the table after it is closed will result in an error.
|
||||
|
||||
***
|
||||
|
||||
### closeLsmWriters()
|
||||
|
||||
```ts
|
||||
abstract closeLsmWriters(): Promise<void>
|
||||
```
|
||||
|
||||
Drain and close any cached MemWAL shard writers held for this table.
|
||||
|
||||
When an [LsmWriteSpec](../interfaces/LsmWriteSpec.md) is installed, `mergeInsert` opens MemWAL
|
||||
shard writers and caches them for reuse across calls. This closes them,
|
||||
flushing pending data; writers reopen lazily on the next `mergeInsert`.
|
||||
It is a no-op when no writers are cached.
|
||||
|
||||
#### Returns
|
||||
|
||||
`Promise`<`void`>
|
||||
|
||||
***
|
||||
|
||||
### countRows()
|
||||
|
||||
```ts
|
||||
|
||||
@@ -70,20 +70,16 @@ client used by manifest-enabled native connections.
|
||||
optional readConsistencyInterval: number;
|
||||
```
|
||||
|
||||
The interval, in seconds, at which to check for updates to the table
|
||||
from other processes. If None, then consistency is not checked. For
|
||||
performance reasons, this is the default. For strong consistency, set
|
||||
this to zero seconds. Then every read will check for updates from other
|
||||
processes. As a compromise, you can set this to a non-zero value for
|
||||
eventual consistency. If more than that interval has passed since the
|
||||
last check, then the table will be checked for updates. Note: this
|
||||
consistency only applies to read operations. Write operations are
|
||||
(For LanceDB OSS only): The interval, in seconds, at which to check for
|
||||
updates to the table from other processes. If None, then consistency is not
|
||||
checked. For performance reasons, this is the default. For strong
|
||||
consistency, set this to zero seconds. Then every read will check for
|
||||
updates from other processes. As a compromise, you can set this to a
|
||||
non-zero value for eventual consistency. If more than that interval
|
||||
has passed since the last check, then the table will be checked for updates.
|
||||
Note: this consistency only applies to read operations. Write operations are
|
||||
always consistent.
|
||||
|
||||
Stronger consistency is not free. The smaller the interval, the more
|
||||
often each read pays the cost of checking for updates against object
|
||||
storage, raising per-read latency and cost.
|
||||
|
||||
***
|
||||
|
||||
### region?
|
||||
|
||||
@@ -11,10 +11,7 @@ Specification selecting Lance's MemWAL LSM-style write path for
|
||||
|
||||
`specType` is `"bucket"`, `"identity"`, or `"unsharded"`. For `"bucket"`,
|
||||
`column` and `numBuckets` are required; for `"identity"`, `column` is
|
||||
required and must be a deterministic function of the unenforced primary
|
||||
key (every row with a given primary key must always produce the same
|
||||
`column` value, or upserts of that key can land in different shards and a
|
||||
stale version can win).
|
||||
required.
|
||||
|
||||
## Properties
|
||||
|
||||
|
||||
@@ -32,14 +32,6 @@ numInsertedRows: number;
|
||||
|
||||
***
|
||||
|
||||
### numRows
|
||||
|
||||
```ts
|
||||
numRows: number;
|
||||
```
|
||||
|
||||
***
|
||||
|
||||
### numUpdatedRows
|
||||
|
||||
```ts
|
||||
|
||||
@@ -8,7 +8,7 @@
|
||||
<parent>
|
||||
<groupId>com.lancedb</groupId>
|
||||
<artifactId>lancedb-parent</artifactId>
|
||||
<version>0.30.1-beta.0</version>
|
||||
<version>0.30.0-beta.0</version>
|
||||
<relativePath>../pom.xml</relativePath>
|
||||
</parent>
|
||||
|
||||
|
||||
@@ -6,7 +6,7 @@
|
||||
|
||||
<groupId>com.lancedb</groupId>
|
||||
<artifactId>lancedb-parent</artifactId>
|
||||
<version>0.30.1-beta.0</version>
|
||||
<version>0.30.0-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>7.2.0-beta.1</lance-core.version>
|
||||
<lance-core.version>7.0.0-beta.13</lance-core.version>
|
||||
<spotless.skip>false</spotless.skip>
|
||||
<spotless.version>2.30.0</spotless.version>
|
||||
<spotless.java.googlejavaformat.version>1.7</spotless.java.googlejavaformat.version>
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
[package]
|
||||
name = "lancedb-nodejs"
|
||||
edition.workspace = true
|
||||
version = "0.30.1-beta.0"
|
||||
version = "0.30.0-beta.0"
|
||||
publish = false
|
||||
license.workspace = true
|
||||
description.workspace = true
|
||||
|
||||
@@ -171,22 +171,18 @@ describe("given a connection", () => {
|
||||
|
||||
let manifestDir =
|
||||
tmpDir.name + "/test_manifest_paths_v2_empty.lance/_versions";
|
||||
readdirSync(manifestDir)
|
||||
.filter((f) => f.endsWith(".manifest"))
|
||||
.forEach((file) => {
|
||||
expect(file).toMatch(/^\d{20}\.manifest$/);
|
||||
});
|
||||
readdirSync(manifestDir).forEach((file) => {
|
||||
expect(file).toMatch(/^\d{20}\.manifest$/);
|
||||
});
|
||||
|
||||
table = (await db.createTable("test_manifest_paths_v2", [{ id: 1 }], {
|
||||
enableV2ManifestPaths: true,
|
||||
})) as LocalTable;
|
||||
expect(await table.usesV2ManifestPaths()).toBe(true);
|
||||
manifestDir = tmpDir.name + "/test_manifest_paths_v2.lance/_versions";
|
||||
readdirSync(manifestDir)
|
||||
.filter((f) => f.endsWith(".manifest"))
|
||||
.forEach((file) => {
|
||||
expect(file).toMatch(/^\d{20}\.manifest$/);
|
||||
});
|
||||
readdirSync(manifestDir).forEach((file) => {
|
||||
expect(file).toMatch(/^\d{20}\.manifest$/);
|
||||
});
|
||||
});
|
||||
|
||||
it("should be able to migrate tables to the V2 manifest paths", async () => {
|
||||
@@ -203,20 +199,16 @@ describe("given a connection", () => {
|
||||
|
||||
const manifestDir =
|
||||
tmpDir.name + "/test_manifest_path_migration.lance/_versions";
|
||||
readdirSync(manifestDir)
|
||||
.filter((f) => f.endsWith(".manifest"))
|
||||
.forEach((file) => {
|
||||
expect(file).toMatch(/^\d\.manifest$/);
|
||||
});
|
||||
readdirSync(manifestDir).forEach((file) => {
|
||||
expect(file).toMatch(/^\d\.manifest$/);
|
||||
});
|
||||
|
||||
await table.migrateManifestPathsV2();
|
||||
expect(await table.usesV2ManifestPaths()).toBe(true);
|
||||
|
||||
readdirSync(manifestDir)
|
||||
.filter((f) => f.endsWith(".manifest"))
|
||||
.forEach((file) => {
|
||||
expect(file).toMatch(/^\d{20}\.manifest$/);
|
||||
});
|
||||
readdirSync(manifestDir).forEach((file) => {
|
||||
expect(file).toMatch(/^\d{20}\.manifest$/);
|
||||
});
|
||||
});
|
||||
});
|
||||
|
||||
|
||||
@@ -2625,97 +2625,3 @@ describe("setLsmWriteSpec / unsetLsmWriteSpec", () => {
|
||||
).rejects.toThrow();
|
||||
});
|
||||
});
|
||||
|
||||
describe("LSM merge insert", () => {
|
||||
let tmpDir: tmp.DirResult;
|
||||
|
||||
beforeEach(() => {
|
||||
tmpDir = tmp.dirSync({ unsafeCleanup: true });
|
||||
});
|
||||
afterEach(() => tmpDir.removeCallback());
|
||||
|
||||
async function bucketTable(conn: Connection): Promise<Table> {
|
||||
// The primary key column must be non-nullable.
|
||||
const table = await conn.createEmptyTable(
|
||||
"t",
|
||||
new arrow.Schema([
|
||||
new arrow.Field("id", new arrow.Utf8(), false),
|
||||
new arrow.Field("value", new arrow.Float64(), true),
|
||||
]),
|
||||
);
|
||||
await table.add([
|
||||
{ id: "a", value: 1 },
|
||||
{ id: "b", value: 2 },
|
||||
]);
|
||||
await table.setUnenforcedPrimaryKey("id");
|
||||
// numBuckets = 1: every row routes to the single bucket.
|
||||
await table.setLsmWriteSpec({
|
||||
specType: "bucket",
|
||||
column: "id",
|
||||
numBuckets: 1,
|
||||
});
|
||||
return table;
|
||||
}
|
||||
|
||||
it("routes merge_insert through the shard writer", async () => {
|
||||
const conn = await connect(tmpDir.name);
|
||||
const table = await bucketTable(conn);
|
||||
|
||||
const res = await table
|
||||
.mergeInsert("id")
|
||||
.whenMatchedUpdateAll()
|
||||
.whenNotMatchedInsertAll()
|
||||
.execute([
|
||||
{ id: "c", value: 3 },
|
||||
{ id: "d", value: 4 },
|
||||
]);
|
||||
// LSM path: rows go to the MemWAL, so only numRows is populated.
|
||||
expect(res.numRows).toBe(2);
|
||||
expect(res.version).toBe(0);
|
||||
expect(res.numInsertedRows).toBe(0);
|
||||
|
||||
await table.closeLsmWriters();
|
||||
});
|
||||
|
||||
it("falls back to the standard path with useLsmWrite(false)", async () => {
|
||||
const conn = await connect(tmpDir.name);
|
||||
const table = await bucketTable(conn);
|
||||
|
||||
const res = await table
|
||||
.mergeInsert("id")
|
||||
.whenNotMatchedInsertAll()
|
||||
.useLsmWrite(false)
|
||||
.execute([
|
||||
{ id: "b", value: 9 },
|
||||
{ id: "e", value: 5 },
|
||||
]);
|
||||
// Standard path commits: id="e" inserted ("b" already exists).
|
||||
expect(res.numInsertedRows).toBe(1);
|
||||
expect(await table.countRows()).toBe(3);
|
||||
});
|
||||
|
||||
it("supports validateSingleShard(false)", async () => {
|
||||
const conn = await connect(tmpDir.name);
|
||||
const table = await bucketTable(conn);
|
||||
|
||||
const res = await table
|
||||
.mergeInsert("id")
|
||||
.whenMatchedUpdateAll()
|
||||
.whenNotMatchedInsertAll()
|
||||
.validateSingleShard(false)
|
||||
.execute([{ id: "f", value: 6 }]);
|
||||
expect(res.numRows).toBe(1);
|
||||
});
|
||||
|
||||
it("rejects a non-upsert merge under an LSM spec", async () => {
|
||||
const conn = await connect(tmpDir.name);
|
||||
const table = await bucketTable(conn);
|
||||
|
||||
await expect(
|
||||
table
|
||||
.mergeInsert("id")
|
||||
.whenNotMatchedInsertAll()
|
||||
.execute([{ id: "g", value: 7 }]),
|
||||
).rejects.toThrow();
|
||||
});
|
||||
});
|
||||
|
||||
@@ -87,41 +87,6 @@ export class MergeInsertBuilder {
|
||||
this.#schema,
|
||||
);
|
||||
}
|
||||
/**
|
||||
* Controls whether the merge uses the MemWAL LSM write path.
|
||||
*
|
||||
* By default (unset), a `mergeInsert` on a table with an LSM write spec is
|
||||
* routed through Lance's MemWAL shard writer, and a table without one uses
|
||||
* the standard path. Pass `false` to force the standard path even when a
|
||||
* spec is set. Pass `true` to require a spec — `mergeInsert` rejects if none
|
||||
* is installed.
|
||||
*
|
||||
* @param useLsmWrite - Whether to use the LSM write path.
|
||||
*/
|
||||
useLsmWrite(useLsmWrite: boolean): MergeInsertBuilder {
|
||||
return new MergeInsertBuilder(
|
||||
this.#native.useLsmWrite(useLsmWrite),
|
||||
this.#schema,
|
||||
);
|
||||
}
|
||||
/**
|
||||
* Controls how an LSM merge checks that its input targets a single shard.
|
||||
*
|
||||
* When a table has an LSM write spec, every row in a `mergeInsert` call must
|
||||
* route to the same shard. When `true` (the default), every row is inspected
|
||||
* to verify this. When `false`, only the first row is inspected and the
|
||||
* shard it routes to is used for the whole input — a faster path for callers
|
||||
* that have already pre-sharded their input. Has no effect on tables without
|
||||
* an LSM write spec.
|
||||
*
|
||||
* @param validateSingleShard - Whether to check every row routes to one shard. Defaults to `true`.
|
||||
*/
|
||||
validateSingleShard(validateSingleShard: boolean): MergeInsertBuilder {
|
||||
return new MergeInsertBuilder(
|
||||
this.#native.validateSingleShard(validateSingleShard),
|
||||
this.#schema,
|
||||
);
|
||||
}
|
||||
/**
|
||||
* Executes the merge insert operation
|
||||
*
|
||||
|
||||
@@ -161,10 +161,7 @@ export interface Version {
|
||||
*
|
||||
* `specType` is `"bucket"`, `"identity"`, or `"unsharded"`. For `"bucket"`,
|
||||
* `column` and `numBuckets` are required; for `"identity"`, `column` is
|
||||
* required and must be a deterministic function of the unenforced primary
|
||||
* key (every row with a given primary key must always produce the same
|
||||
* `column` value, or upserts of that key can land in different shards and a
|
||||
* stale version can win).
|
||||
* required.
|
||||
*/
|
||||
export interface LsmWriteSpec {
|
||||
/** One of `"bucket"`, `"identity"`, or `"unsharded"`. */
|
||||
@@ -570,16 +567,6 @@ export abstract class Table {
|
||||
* @returns {Promise<void>}
|
||||
*/
|
||||
abstract unsetLsmWriteSpec(): Promise<void>;
|
||||
/**
|
||||
* Drain and close any cached MemWAL shard writers held for this table.
|
||||
*
|
||||
* When an {@link LsmWriteSpec} is installed, `mergeInsert` opens MemWAL
|
||||
* shard writers and caches them for reuse across calls. This closes them,
|
||||
* flushing pending data; writers reopen lazily on the next `mergeInsert`.
|
||||
* It is a no-op when no writers are cached.
|
||||
* @returns {Promise<void>}
|
||||
*/
|
||||
abstract closeLsmWriters(): Promise<void>;
|
||||
/** Retrieve the version of the table */
|
||||
|
||||
abstract version(): Promise<number>;
|
||||
@@ -1054,10 +1041,6 @@ export class LocalTable extends Table {
|
||||
return await this.inner.unsetLsmWriteSpec();
|
||||
}
|
||||
|
||||
async closeLsmWriters(): Promise<void> {
|
||||
return await this.inner.closeLsmWriters();
|
||||
}
|
||||
|
||||
async version(): Promise<number> {
|
||||
return await this.inner.version();
|
||||
}
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-darwin-arm64",
|
||||
"version": "0.30.1-beta.0",
|
||||
"version": "0.30.0-beta.0",
|
||||
"os": ["darwin"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.darwin-arm64.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-arm64-gnu",
|
||||
"version": "0.30.1-beta.0",
|
||||
"version": "0.30.0-beta.0",
|
||||
"os": ["linux"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.linux-arm64-gnu.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-arm64-musl",
|
||||
"version": "0.30.1-beta.0",
|
||||
"version": "0.30.0-beta.0",
|
||||
"os": ["linux"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.linux-arm64-musl.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-x64-gnu",
|
||||
"version": "0.30.1-beta.0",
|
||||
"version": "0.30.0-beta.0",
|
||||
"os": ["linux"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.linux-x64-gnu.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-x64-musl",
|
||||
"version": "0.30.1-beta.0",
|
||||
"version": "0.30.0-beta.0",
|
||||
"os": ["linux"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.linux-x64-musl.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-win32-arm64-msvc",
|
||||
"version": "0.30.1-beta.0",
|
||||
"version": "0.30.0-beta.0",
|
||||
"os": [
|
||||
"win32"
|
||||
],
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-win32-x64-msvc",
|
||||
"version": "0.30.1-beta.0",
|
||||
"version": "0.30.0-beta.0",
|
||||
"os": ["win32"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.win32-x64-msvc.node",
|
||||
|
||||
4
nodejs/package-lock.json
generated
4
nodejs/package-lock.json
generated
@@ -1,12 +1,12 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb",
|
||||
"version": "0.30.1-beta.0",
|
||||
"version": "0.29.1-beta.0",
|
||||
"lockfileVersion": 3,
|
||||
"requires": true,
|
||||
"packages": {
|
||||
"": {
|
||||
"name": "@lancedb/lancedb",
|
||||
"version": "0.30.1-beta.0",
|
||||
"version": "0.29.1-beta.0",
|
||||
"cpu": [
|
||||
"x64",
|
||||
"arm64"
|
||||
|
||||
@@ -11,7 +11,7 @@
|
||||
"ann"
|
||||
],
|
||||
"private": false,
|
||||
"version": "0.30.1-beta.0",
|
||||
"version": "0.30.0-beta.0",
|
||||
"main": "dist/index.js",
|
||||
"exports": {
|
||||
".": "./dist/index.js",
|
||||
|
||||
@@ -24,19 +24,15 @@ mod util;
|
||||
#[napi(object)]
|
||||
#[derive(Debug)]
|
||||
pub struct ConnectionOptions {
|
||||
/// The interval, in seconds, at which to check for updates to the table
|
||||
/// from other processes. If None, then consistency is not checked. For
|
||||
/// performance reasons, this is the default. For strong consistency, set
|
||||
/// this to zero seconds. Then every read will check for updates from other
|
||||
/// processes. As a compromise, you can set this to a non-zero value for
|
||||
/// eventual consistency. If more than that interval has passed since the
|
||||
/// last check, then the table will be checked for updates. Note: this
|
||||
/// consistency only applies to read operations. Write operations are
|
||||
/// (For LanceDB OSS only): The interval, in seconds, at which to check for
|
||||
/// updates to the table from other processes. If None, then consistency is not
|
||||
/// checked. For performance reasons, this is the default. For strong
|
||||
/// consistency, set this to zero seconds. Then every read will check for
|
||||
/// updates from other processes. As a compromise, you can set this to a
|
||||
/// non-zero value for eventual consistency. If more than that interval
|
||||
/// has passed since the last check, then the table will be checked for updates.
|
||||
/// Note: this consistency only applies to read operations. Write operations are
|
||||
/// always consistent.
|
||||
///
|
||||
/// Stronger consistency is not free. The smaller the interval, the more
|
||||
/// often each read pays the cost of checking for updates against object
|
||||
/// storage, raising per-read latency and cost.
|
||||
pub read_consistency_interval: Option<f64>,
|
||||
/// (For LanceDB OSS only): configuration for object storage.
|
||||
///
|
||||
|
||||
@@ -50,20 +50,6 @@ impl NativeMergeInsertBuilder {
|
||||
this
|
||||
}
|
||||
|
||||
#[napi]
|
||||
pub fn use_lsm_write(&self, use_lsm_write: bool) -> Self {
|
||||
let mut this = self.clone();
|
||||
this.inner.use_lsm_write(use_lsm_write);
|
||||
this
|
||||
}
|
||||
|
||||
#[napi]
|
||||
pub fn validate_single_shard(&self, validate_single_shard: bool) -> Self {
|
||||
let mut this = self.clone();
|
||||
this.inner.validate_single_shard(validate_single_shard);
|
||||
this
|
||||
}
|
||||
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn execute(&self, buf: Buffer) -> napi::Result<MergeResult> {
|
||||
let data = ipc_file_to_batches(buf.to_vec())
|
||||
|
||||
@@ -391,11 +391,6 @@ impl Table {
|
||||
.default_error()
|
||||
}
|
||||
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn close_lsm_writers(&self) -> napi::Result<()> {
|
||||
self.inner_ref()?.close_lsm_writers().await.default_error()
|
||||
}
|
||||
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn version(&self) -> napi::Result<i64> {
|
||||
self.inner_ref()?
|
||||
@@ -945,7 +940,6 @@ pub struct MergeResult {
|
||||
pub num_updated_rows: i64,
|
||||
pub num_deleted_rows: i64,
|
||||
pub num_attempts: i64,
|
||||
pub num_rows: i64,
|
||||
}
|
||||
|
||||
impl From<lancedb::table::MergeResult> for MergeResult {
|
||||
@@ -956,7 +950,6 @@ impl From<lancedb::table::MergeResult> for MergeResult {
|
||||
num_updated_rows: value.num_updated_rows as i64,
|
||||
num_deleted_rows: value.num_deleted_rows as i64,
|
||||
num_attempts: value.num_attempts as i64,
|
||||
num_rows: value.num_rows as i64,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
[tool.bumpversion]
|
||||
current_version = "0.33.1-beta.0"
|
||||
current_version = "0.33.0-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 = "0.33.1-beta.0"
|
||||
version = "0.33.0-beta.0"
|
||||
publish = false
|
||||
edition.workspace = true
|
||||
description = "Python bindings for LanceDB"
|
||||
|
||||
@@ -94,6 +94,7 @@ def connect(
|
||||
host_override: str, optional
|
||||
The override url for LanceDB Cloud.
|
||||
read_consistency_interval: timedelta, default None
|
||||
(For LanceDB OSS only)
|
||||
The interval at which to check for updates to the table from other
|
||||
processes. If None, then consistency is not checked. For performance
|
||||
reasons, this is the default. For strong consistency, set this to
|
||||
@@ -103,10 +104,6 @@ def connect(
|
||||
the last check, then the table will be checked for updates. Note: this
|
||||
consistency only applies to read operations. Write operations are
|
||||
always consistent.
|
||||
|
||||
Stronger consistency is not free. The smaller the interval, the more
|
||||
often each read pays the cost of checking for updates against object
|
||||
storage, raising per-read latency and cost.
|
||||
client_config: ClientConfig or dict, optional
|
||||
Configuration options for the LanceDB Cloud HTTP client. If a dict, then
|
||||
the keys are the attributes of the ClientConfig class. If None, then the
|
||||
@@ -150,13 +147,6 @@ def connect(
|
||||
>>> db = lancedb.connect("s3://my-bucket/lancedb",
|
||||
... storage_options={"aws_access_key_id": "***"})
|
||||
|
||||
For tests and temporary data, use an in-memory database:
|
||||
|
||||
>>> db = lancedb.connect("memory://")
|
||||
|
||||
In-memory databases are not persisted. Tables are dropped when the last
|
||||
connection or table handle referencing them is closed.
|
||||
|
||||
Connect to LanceDB cloud:
|
||||
|
||||
>>> db = lancedb.connect("db://my_database", api_key="ldb_...",
|
||||
@@ -220,7 +210,6 @@ def connect(
|
||||
request_thread_pool=request_thread_pool,
|
||||
client_config=client_config,
|
||||
storage_options=storage_options,
|
||||
read_consistency_interval=read_consistency_interval,
|
||||
**kwargs,
|
||||
)
|
||||
_check_s3_bucket_with_dots(str(uri), storage_options)
|
||||
@@ -315,15 +304,6 @@ def deserialize_conn(
|
||||
manifest_enabled=parsed.get("manifest_enabled", False),
|
||||
namespace_client_properties=parsed.get("namespace_client_properties"),
|
||||
)
|
||||
elif connection_type == "remote":
|
||||
return RemoteDBConnection(
|
||||
parsed["db_url"],
|
||||
parsed["api_key"],
|
||||
parsed.get("region", "us-east-1"),
|
||||
host_override=parsed.get("host_override"),
|
||||
client_config=parsed.get("client_config"),
|
||||
storage_options=storage_options,
|
||||
)
|
||||
else:
|
||||
raise ValueError(f"Unknown connection_type: {connection_type}")
|
||||
|
||||
@@ -356,6 +336,7 @@ async def connect_async(
|
||||
host_override: str, optional
|
||||
The override url for LanceDB Cloud.
|
||||
read_consistency_interval: timedelta, default None
|
||||
(For LanceDB OSS only)
|
||||
The interval at which to check for updates to the table from other
|
||||
processes. If None, then consistency is not checked. For performance
|
||||
reasons, this is the default. For strong consistency, set this to
|
||||
@@ -365,10 +346,6 @@ async def connect_async(
|
||||
the last check, then the table will be checked for updates. Note: this
|
||||
consistency only applies to read operations. Write operations are
|
||||
always consistent.
|
||||
|
||||
Stronger consistency is not free. The smaller the interval, the more
|
||||
often each read pays the cost of checking for updates against object
|
||||
storage, raising per-read latency and cost.
|
||||
client_config: ClientConfig or dict, optional
|
||||
Configuration options for the LanceDB Cloud HTTP client. If a dict, then
|
||||
the keys are the attributes of the ClientConfig class. If None, then the
|
||||
@@ -401,8 +378,6 @@ async def connect_async(
|
||||
... db = await lancedb.connect_async("s3://my-bucket/lancedb",
|
||||
... storage_options={
|
||||
... "aws_access_key_id": "***"})
|
||||
... # For tests and temporary data, use an in-memory database
|
||||
... db = await lancedb.connect_async("memory://")
|
||||
... # Connect to LanceDB cloud
|
||||
... db = await lancedb.connect_async("db://my_database", api_key="ldb_...",
|
||||
... client_config={
|
||||
|
||||
@@ -217,11 +217,9 @@ class Table:
|
||||
async def uri(self) -> str: ...
|
||||
async def initial_storage_options(self) -> Optional[Dict[str, str]]: ...
|
||||
async def latest_storage_options(self) -> Optional[Dict[str, str]]: ...
|
||||
async def _table_reopen_state(self) -> Dict[str, Any]: ...
|
||||
async def set_unenforced_primary_key(self, columns: List[str]) -> None: ...
|
||||
async def set_lsm_write_spec(self, spec: LsmWriteSpec) -> None: ...
|
||||
async def unset_lsm_write_spec(self) -> None: ...
|
||||
async def close_lsm_writers(self) -> None: ...
|
||||
@property
|
||||
def tags(self) -> Tags: ...
|
||||
def query(self) -> Query: ...
|
||||
@@ -422,7 +420,6 @@ class MergeResult:
|
||||
num_inserted_rows: int
|
||||
num_deleted_rows: int
|
||||
num_attempts: int
|
||||
num_rows: int
|
||||
|
||||
class LsmWriteSpec:
|
||||
"""Specification selecting Lance's MemWAL LSM-style write path for
|
||||
|
||||
@@ -281,9 +281,6 @@ class HnswPq:
|
||||
m: int = 20
|
||||
ef_construction: int = 300
|
||||
target_partition_size: Optional[int] = None
|
||||
# Name of the accelerator (e.g. "cuda") to use for IVF training. When set,
|
||||
# create_index() dispatches to pylance to build the index on the accelerator.
|
||||
accelerator: Optional[str] = None
|
||||
|
||||
|
||||
@dataclass
|
||||
@@ -389,9 +386,6 @@ class HnswSq:
|
||||
m: int = 20
|
||||
ef_construction: int = 300
|
||||
target_partition_size: Optional[int] = None
|
||||
# Name of the accelerator (e.g. "cuda") to use for IVF training. When set,
|
||||
# create_index() dispatches to pylance to build the index on the accelerator.
|
||||
accelerator: Optional[str] = None
|
||||
|
||||
|
||||
@dataclass
|
||||
@@ -585,9 +579,6 @@ class IvfFlat:
|
||||
max_iterations: int = 50
|
||||
sample_rate: int = 256
|
||||
target_partition_size: Optional[int] = None
|
||||
# Name of the accelerator (e.g. "cuda") to use for IVF training. When set,
|
||||
# create_index() dispatches to pylance to build the index on the accelerator.
|
||||
accelerator: Optional[str] = None
|
||||
|
||||
|
||||
@dataclass
|
||||
@@ -618,9 +609,6 @@ class IvfSq:
|
||||
max_iterations: int = 50
|
||||
sample_rate: int = 256
|
||||
target_partition_size: Optional[int] = None
|
||||
# Name of the accelerator (e.g. "cuda") to use for IVF training. When set,
|
||||
# create_index() dispatches to pylance to build the index on the accelerator.
|
||||
accelerator: Optional[str] = None
|
||||
|
||||
|
||||
@dataclass
|
||||
@@ -751,9 +739,6 @@ class IvfPq:
|
||||
max_iterations: int = 50
|
||||
sample_rate: int = 256
|
||||
target_partition_size: Optional[int] = None
|
||||
# Name of the accelerator (e.g. "cuda") to use for IVF training. When set,
|
||||
# create_index() dispatches to pylance to build the index on the accelerator.
|
||||
accelerator: Optional[str] = None
|
||||
|
||||
|
||||
@dataclass
|
||||
@@ -807,9 +792,6 @@ class IvfRq:
|
||||
max_iterations: int = 50
|
||||
sample_rate: int = 256
|
||||
target_partition_size: Optional[int] = None
|
||||
# Name of the accelerator (e.g. "cuda") to use for IVF training. When set,
|
||||
# create_index() dispatches to pylance to build the index on the accelerator.
|
||||
accelerator: Optional[str] = None
|
||||
|
||||
|
||||
__all__ = [
|
||||
|
||||
@@ -34,8 +34,6 @@ class LanceMergeInsertBuilder(object):
|
||||
self._when_not_matched_by_source_condition = None
|
||||
self._timeout = None
|
||||
self._use_index = True
|
||||
self._use_lsm_write = None
|
||||
self._validate_single_shard = None
|
||||
|
||||
def when_matched_update_all(
|
||||
self, *, where: Optional[str] = None
|
||||
@@ -98,46 +96,6 @@ class LanceMergeInsertBuilder(object):
|
||||
self._use_index = use_index
|
||||
return self
|
||||
|
||||
def use_lsm_write(self, use_lsm_write: bool) -> LanceMergeInsertBuilder:
|
||||
"""
|
||||
Controls whether the merge uses the MemWAL LSM write path.
|
||||
|
||||
By default (unset), a `merge_insert` on a table with an LSM write spec
|
||||
is routed through Lance's MemWAL shard writer, and a table without one
|
||||
uses the standard path. Pass `False` to force the standard path even
|
||||
when a spec is set. Pass `True` to require a spec — `merge_insert`
|
||||
raises an error if none is installed.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
use_lsm_write: bool
|
||||
Whether to use the LSM write path.
|
||||
"""
|
||||
self._use_lsm_write = use_lsm_write
|
||||
return self
|
||||
|
||||
def validate_single_shard(
|
||||
self, validate_single_shard: bool
|
||||
) -> LanceMergeInsertBuilder:
|
||||
"""
|
||||
Controls how an LSM merge checks that its input targets a single shard.
|
||||
|
||||
When a table has an LSM write spec, every row in a `merge_insert` call
|
||||
must route to the same shard. When `True` (the default), every row is
|
||||
inspected to verify this. When `False`, only the first row is inspected
|
||||
and the shard it routes to is used for the whole input — a faster path
|
||||
for callers that have already pre-sharded their input.
|
||||
|
||||
Has no effect on tables without an LSM write spec.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
validate_single_shard: bool
|
||||
Whether to check every row routes to one shard. Defaults to `True`.
|
||||
"""
|
||||
self._validate_single_shard = validate_single_shard
|
||||
return self
|
||||
|
||||
def execute(
|
||||
self,
|
||||
new_data: DATA,
|
||||
|
||||
@@ -3,13 +3,12 @@
|
||||
|
||||
import copy
|
||||
import json
|
||||
import os
|
||||
|
||||
from deprecation import deprecated
|
||||
import pyarrow as pa
|
||||
|
||||
from ._lancedb import async_permutation_builder, PermutationReader
|
||||
from .table import LanceTable, Table
|
||||
from .table import LanceTable
|
||||
from .background_loop import LOOP
|
||||
from .util import batch_to_tensor, batch_to_tensor_rows
|
||||
from typing import Any, Callable, Iterator, Literal, Optional, TYPE_CHECKING, Union
|
||||
@@ -355,41 +354,6 @@ class Transforms:
|
||||
DEFAULT_BATCH_SIZE = 100
|
||||
|
||||
|
||||
def _table_to_pickle_state(table: Table) -> dict[str, Any]:
|
||||
from .remote.table import RemoteTable
|
||||
|
||||
if isinstance(table, LanceTable) and table._conn.uri.startswith("memory://"):
|
||||
return {
|
||||
"kind": "memory",
|
||||
"name": table.name,
|
||||
"data": table.to_arrow(),
|
||||
}
|
||||
|
||||
if isinstance(table, (LanceTable, RemoteTable)):
|
||||
return {
|
||||
"kind": "table",
|
||||
"table": table,
|
||||
}
|
||||
|
||||
raise ValueError(f"Cannot pickle table of type {type(table)!r}")
|
||||
|
||||
|
||||
def _table_from_pickle_state(state: dict[str, Any]) -> Table:
|
||||
from . import connect
|
||||
|
||||
kind = state["kind"]
|
||||
if kind == "table":
|
||||
return state["table"]
|
||||
if kind == "remote":
|
||||
return state["table"]
|
||||
if kind == "memory":
|
||||
return connect("memory://").create_table(state["name"], state["data"])
|
||||
if kind == "local":
|
||||
db = connect(state["uri"], storage_options=state["storage_options"])
|
||||
return db.open_table(state["name"], namespace_path=state["namespace"] or None)
|
||||
raise ValueError(f"Unknown table pickle state kind: {kind}")
|
||||
|
||||
|
||||
class Permutation:
|
||||
"""
|
||||
A Permutation is a view of a dataset that can be used as input to model training
|
||||
@@ -405,15 +369,15 @@ class Permutation:
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
base_table: Table,
|
||||
permutation_table: Optional[Table],
|
||||
base_table: LanceTable,
|
||||
permutation_table: Optional[LanceTable],
|
||||
split: int,
|
||||
selection: dict[str, str],
|
||||
batch_size: int,
|
||||
transform_fn: Callable[pa.RecordBatch, Any],
|
||||
offset: Optional[int] = None,
|
||||
limit: Optional[int] = None,
|
||||
connection_factory: Optional[Callable[[str], Table]] = None,
|
||||
connection_factory: Optional[Callable[[str], LanceTable]] = None,
|
||||
_reader: Optional[PermutationReader] = None,
|
||||
):
|
||||
"""
|
||||
@@ -433,7 +397,6 @@ class Permutation:
|
||||
if _reader is None:
|
||||
_reader = LOOP.run(self._build_reader())
|
||||
self.reader: PermutationReader = _reader
|
||||
self._pid = os.getpid()
|
||||
|
||||
async def _build_reader(self) -> PermutationReader:
|
||||
reader = await PermutationReader.from_tables(
|
||||
@@ -465,25 +428,29 @@ class Permutation:
|
||||
return new
|
||||
|
||||
def with_connection_factory(
|
||||
self, connection_factory: Callable[[str], Table]
|
||||
self, connection_factory: Callable[[str], LanceTable]
|
||||
) -> "Permutation":
|
||||
"""
|
||||
Creates a new permutation that will use ``connection_factory`` to reopen
|
||||
the base table when this permutation is unpickled in a worker process.
|
||||
|
||||
The factory is a callable that takes a single argument, the base table
|
||||
name, and returns a LanceDB table. It must be picklable; the worker
|
||||
The factory is a callable that takes a single argument — the base table
|
||||
name — and returns a [LanceTable]. It must be picklable; the worker
|
||||
will pickle it via standard ``pickle`` and call it to recover the base
|
||||
table. Picklable callables in practice means top-level (module-level)
|
||||
functions, ``functools.partial`` of such functions, or instances of
|
||||
picklable classes implementing ``__call__``. Lambdas and closures over
|
||||
local variables don't pickle with the default protocol.
|
||||
|
||||
A factory is optional for normal local and remote LanceDB connections:
|
||||
if not set, ``__getstate__`` captures the table's own picklable reopen
|
||||
state. Use a factory when that default state is not enough, for example
|
||||
when credentials should be loaded from the worker environment instead
|
||||
of being embedded in the pickle.
|
||||
Setting a factory is necessary when the URI alone is not enough to
|
||||
re-open the connection — most importantly for LanceDB Cloud (``db://``)
|
||||
connections, where ``api_key`` and ``region`` aren't recoverable from
|
||||
the connection object after construction.
|
||||
|
||||
For local file or cloud-storage paths the factory is optional: if not
|
||||
set, ``__getstate__`` falls back to capturing
|
||||
``(uri, storage_options, namespace_path)`` and re-opening via
|
||||
``lancedb.connect(uri, storage_options=...)``.
|
||||
|
||||
Examples
|
||||
--------
|
||||
@@ -541,7 +508,7 @@ class Permutation:
|
||||
return new
|
||||
|
||||
@classmethod
|
||||
def identity(cls, table: Table) -> "Permutation":
|
||||
def identity(cls, table: LanceTable) -> "Permutation":
|
||||
"""
|
||||
Creates an identity permutation for the given table.
|
||||
"""
|
||||
@@ -550,8 +517,8 @@ class Permutation:
|
||||
@classmethod
|
||||
def from_tables(
|
||||
cls,
|
||||
base_table: Table,
|
||||
permutation_table: Optional[Table] = None,
|
||||
base_table: LanceTable,
|
||||
permutation_table: Optional[LanceTable] = None,
|
||||
split: Optional[Union[str, int]] = None,
|
||||
) -> "Permutation":
|
||||
"""
|
||||
@@ -627,10 +594,11 @@ class Permutation:
|
||||
|
||||
The base table is captured either via a user-supplied
|
||||
``connection_factory`` (see [with_connection_factory]) or, as a
|
||||
fallback, by the table's own picklable reopen state. The permutation
|
||||
table is captured as a pyarrow Table (which pickles via Arrow IPC
|
||||
natively). The reader is dropped from the wire format and rebuilt
|
||||
lazily on first use.
|
||||
fallback, by introspecting ``(uri, storage_options, namespace_path)``
|
||||
on the connection. The permutation table — always an in-memory
|
||||
LanceDB table — is captured as a pyarrow Table (which pickles via
|
||||
Arrow IPC natively). The reader is dropped from the wire format;
|
||||
``__setstate__`` rebuilds it from the restored tables.
|
||||
"""
|
||||
permutation_data: Optional[pa.Table] = None
|
||||
if self.permutation_table is not None:
|
||||
@@ -654,9 +622,39 @@ class Permutation:
|
||||
# namespace from the existing connection.
|
||||
return common
|
||||
|
||||
# URI-introspection fallback: only viable for native (OSS) connections
|
||||
# where (uri, storage_options) is enough to reopen. Remote / cloud
|
||||
# connections don't expose recoverable api_key / region — those users
|
||||
# must call with_connection_factory().
|
||||
try:
|
||||
base_uri = self.base_table._conn.uri
|
||||
storage_options = self.base_table._conn.storage_options
|
||||
except AttributeError as e:
|
||||
raise ValueError(
|
||||
"Cannot pickle this Permutation: the base table's connection "
|
||||
"does not expose a uri/storage_options, which usually means it "
|
||||
"is a remote (LanceDB Cloud) connection. Call "
|
||||
"Permutation.with_connection_factory(...) first to provide a "
|
||||
"picklable callable that re-opens the base table from a worker "
|
||||
"process."
|
||||
) from e
|
||||
|
||||
if base_uri.startswith("memory://"):
|
||||
# In-memory base tables don't exist in any worker process by
|
||||
# default, so dump the entire base table into the pickle. This
|
||||
# can be expensive for large datasets — users with large
|
||||
# in-memory base tables should either persist them or set a
|
||||
# connection_factory.
|
||||
return {
|
||||
**common,
|
||||
"base_table_data": self.base_table.to_arrow(),
|
||||
}
|
||||
|
||||
return {
|
||||
**common,
|
||||
"base_table_state": _table_to_pickle_state(self.base_table),
|
||||
"base_table_uri": base_uri,
|
||||
"base_table_namespace": self.base_table._namespace_path,
|
||||
"base_table_storage_options": storage_options,
|
||||
}
|
||||
|
||||
def __setstate__(self, state: dict[str, Any]) -> None:
|
||||
@@ -665,8 +663,6 @@ class Permutation:
|
||||
connection_factory = state["connection_factory"]
|
||||
if connection_factory is not None:
|
||||
base_table = connection_factory(state["base_table_name"])
|
||||
elif "base_table_state" in state:
|
||||
base_table = _table_from_pickle_state(state["base_table_state"])
|
||||
elif "base_table_data" in state:
|
||||
# In-memory base table inlined into the pickle; rebuild the same
|
||||
# way we rebuild the in-memory permutation table.
|
||||
@@ -684,7 +680,7 @@ class Permutation:
|
||||
namespace_path=state["base_table_namespace"] or None,
|
||||
)
|
||||
|
||||
permutation_table: Optional[Table] = None
|
||||
permutation_table: Optional[LanceTable] = None
|
||||
if state["permutation_data"] is not None:
|
||||
mem_db = connect("memory://")
|
||||
permutation_table = mem_db.create_table(
|
||||
@@ -700,28 +696,10 @@ class Permutation:
|
||||
self.offset = state["offset"]
|
||||
self.limit = state["limit"]
|
||||
self.connection_factory = connection_factory
|
||||
self.reader = None
|
||||
self._pid = None
|
||||
|
||||
def _ensure_open(self) -> None:
|
||||
pid = os.getpid()
|
||||
if self.reader is not None and getattr(self, "_pid", None) == pid:
|
||||
return
|
||||
# The reader owns Rust-side table handles. Rebuild it after unpickle or
|
||||
# fork even though the Python table wrappers reopen themselves.
|
||||
if hasattr(self.base_table, "_ensure_open"):
|
||||
self.base_table._ensure_open()
|
||||
if self.permutation_table is not None and hasattr(
|
||||
self.permutation_table, "_ensure_open"
|
||||
):
|
||||
self.permutation_table._ensure_open()
|
||||
self.reader = LOOP.run(self._build_reader())
|
||||
self._pid = pid
|
||||
|
||||
@property
|
||||
def schema(self) -> pa.Schema:
|
||||
self._ensure_open()
|
||||
|
||||
async def do_output_schema():
|
||||
return await self.reader.output_schema(self.selection)
|
||||
|
||||
@@ -739,7 +717,6 @@ class Permutation:
|
||||
"""
|
||||
The number of rows in the permutation
|
||||
"""
|
||||
self._ensure_open()
|
||||
return self.reader.count_rows()
|
||||
|
||||
@property
|
||||
@@ -898,7 +875,6 @@ class Permutation:
|
||||
If skip_last_batch is True, the last batch will be skipped if it is not a
|
||||
multiple of batch_size.
|
||||
"""
|
||||
self._ensure_open()
|
||||
|
||||
async def get_iter():
|
||||
return await self.reader.read(self.selection, batch_size=batch_size)
|
||||
@@ -1000,7 +976,6 @@ class Permutation:
|
||||
so `with_format` and `with_transform` affect this method in the same way
|
||||
they affect iteration.
|
||||
"""
|
||||
self._ensure_open()
|
||||
|
||||
async def do_take_offsets():
|
||||
return await self.reader.take_offsets(offsets, selection=self.selection)
|
||||
@@ -1036,11 +1011,9 @@ class Permutation:
|
||||
"""
|
||||
Skip the first `skip` rows of the permutation
|
||||
"""
|
||||
self._ensure_open()
|
||||
new = copy.copy(self)
|
||||
new.offset = skip
|
||||
new.reader = LOOP.run(new._build_reader())
|
||||
new._pid = os.getpid()
|
||||
return new
|
||||
|
||||
@deprecated(details="Use with_take instead")
|
||||
@@ -1059,11 +1032,9 @@ class Permutation:
|
||||
"""
|
||||
Limit the permutation to `limit` rows (following any `skip`)
|
||||
"""
|
||||
self._ensure_open()
|
||||
new = copy.copy(self)
|
||||
new.limit = limit
|
||||
new.reader = LOOP.run(new._build_reader())
|
||||
new._pid = os.getpid()
|
||||
return new
|
||||
|
||||
@deprecated(details="Use with_repeat instead")
|
||||
|
||||
@@ -3,7 +3,6 @@
|
||||
|
||||
|
||||
from datetime import timedelta
|
||||
import json
|
||||
import logging
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
import sys
|
||||
@@ -18,7 +17,7 @@ else:
|
||||
|
||||
# Remove this import to fix circular dependency
|
||||
# from lancedb import connect_async
|
||||
from lancedb.remote import ClientConfig, RetryConfig, TimeoutConfig, TlsConfig
|
||||
from lancedb.remote import ClientConfig
|
||||
import pyarrow as pa
|
||||
|
||||
from ..common import DATA
|
||||
@@ -37,64 +36,6 @@ from ..table import Table
|
||||
from ..util import validate_table_name
|
||||
|
||||
|
||||
def _duration_seconds(value: Optional[timedelta]) -> Optional[float]:
|
||||
return value.total_seconds() if value is not None else None
|
||||
|
||||
|
||||
def _timeout_config_to_dict(
|
||||
config: Optional[TimeoutConfig],
|
||||
) -> Optional[dict[str, Any]]:
|
||||
if config is None:
|
||||
return None
|
||||
return {
|
||||
"timeout": _duration_seconds(config.timeout),
|
||||
"connect_timeout": _duration_seconds(config.connect_timeout),
|
||||
"read_timeout": _duration_seconds(config.read_timeout),
|
||||
"pool_idle_timeout": _duration_seconds(config.pool_idle_timeout),
|
||||
}
|
||||
|
||||
|
||||
def _retry_config_to_dict(config: RetryConfig) -> dict[str, Any]:
|
||||
return {
|
||||
"retries": config.retries,
|
||||
"connect_retries": config.connect_retries,
|
||||
"read_retries": config.read_retries,
|
||||
"backoff_factor": config.backoff_factor,
|
||||
"backoff_jitter": config.backoff_jitter,
|
||||
"statuses": config.statuses,
|
||||
}
|
||||
|
||||
|
||||
def _tls_config_to_dict(config: Optional[TlsConfig]) -> Optional[dict[str, Any]]:
|
||||
if config is None:
|
||||
return None
|
||||
return {
|
||||
"cert_file": config.cert_file,
|
||||
"key_file": config.key_file,
|
||||
"ssl_ca_cert": config.ssl_ca_cert,
|
||||
"assert_hostname": config.assert_hostname,
|
||||
}
|
||||
|
||||
|
||||
def _client_config_to_dict(config: ClientConfig) -> dict[str, Any]:
|
||||
if config.header_provider is not None:
|
||||
raise ValueError(
|
||||
"Cannot serialize a remote connection with a header_provider. "
|
||||
"Use static api_key/extra_headers or provide a worker-side "
|
||||
"connection factory instead."
|
||||
)
|
||||
return {
|
||||
"user_agent": config.user_agent,
|
||||
"retry_config": _retry_config_to_dict(config.retry_config),
|
||||
"timeout_config": _timeout_config_to_dict(config.timeout_config),
|
||||
"extra_headers": config.extra_headers,
|
||||
"id_delimiter": config.id_delimiter,
|
||||
"tls_config": _tls_config_to_dict(config.tls_config),
|
||||
"header_provider": None,
|
||||
"user_id": config.user_id,
|
||||
}
|
||||
|
||||
|
||||
class RemoteDBConnection(DBConnection):
|
||||
"""A connection to a remote LanceDB database."""
|
||||
|
||||
@@ -109,7 +50,6 @@ class RemoteDBConnection(DBConnection):
|
||||
connection_timeout: Optional[float] = None,
|
||||
read_timeout: Optional[float] = None,
|
||||
storage_options: Optional[Dict[str, str]] = None,
|
||||
read_consistency_interval: Optional[timedelta] = None,
|
||||
):
|
||||
"""Connect to a remote LanceDB database."""
|
||||
if isinstance(client_config, dict):
|
||||
@@ -148,11 +88,6 @@ class RemoteDBConnection(DBConnection):
|
||||
parsed = urlparse(db_url)
|
||||
if parsed.scheme != "db":
|
||||
raise ValueError(f"Invalid scheme: {parsed.scheme}, only accepts db://")
|
||||
self.db_url = db_url
|
||||
self.api_key = api_key
|
||||
self.region = region
|
||||
self.host_override = host_override
|
||||
self.storage_options = storage_options
|
||||
self.db_name = parsed.netloc
|
||||
|
||||
self.client_config = client_config
|
||||
@@ -168,27 +103,12 @@ class RemoteDBConnection(DBConnection):
|
||||
host_override=host_override,
|
||||
client_config=client_config,
|
||||
storage_options=storage_options,
|
||||
read_consistency_interval=read_consistency_interval,
|
||||
)
|
||||
)
|
||||
|
||||
def __repr__(self) -> str:
|
||||
return f"RemoteConnect(name={self.db_name})"
|
||||
|
||||
@override
|
||||
def serialize(self) -> str:
|
||||
return json.dumps(
|
||||
{
|
||||
"connection_type": "remote",
|
||||
"db_url": self.db_url,
|
||||
"api_key": self.api_key,
|
||||
"region": self.region,
|
||||
"host_override": self.host_override,
|
||||
"client_config": _client_config_to_dict(self.client_config),
|
||||
"storage_options": self.storage_options,
|
||||
}
|
||||
)
|
||||
|
||||
@override
|
||||
def list_namespaces(
|
||||
self,
|
||||
@@ -409,12 +329,7 @@ class RemoteDBConnection(DBConnection):
|
||||
)
|
||||
|
||||
table = LOOP.run(self._conn.open_table(name, namespace_path=namespace_path))
|
||||
return RemoteTable(
|
||||
table,
|
||||
self.db_name,
|
||||
connection_state=self.serialize,
|
||||
namespace_path=namespace_path,
|
||||
)
|
||||
return RemoteTable(table, self.db_name)
|
||||
|
||||
def clone_table(
|
||||
self,
|
||||
@@ -463,12 +378,7 @@ class RemoteDBConnection(DBConnection):
|
||||
is_shallow=is_shallow,
|
||||
)
|
||||
)
|
||||
return RemoteTable(
|
||||
table,
|
||||
self.db_name,
|
||||
connection_state=self.serialize,
|
||||
namespace_path=target_namespace_path,
|
||||
)
|
||||
return RemoteTable(table, self.db_name)
|
||||
|
||||
@override
|
||||
def create_table(
|
||||
@@ -613,12 +523,7 @@ class RemoteDBConnection(DBConnection):
|
||||
fill_value=fill_value,
|
||||
)
|
||||
)
|
||||
return RemoteTable(
|
||||
table,
|
||||
self.db_name,
|
||||
connection_state=self.serialize,
|
||||
namespace_path=namespace_path,
|
||||
)
|
||||
return RemoteTable(table, self.db_name)
|
||||
|
||||
@override
|
||||
def drop_table(self, name: str, namespace_path: Optional[List[str]] = None):
|
||||
|
||||
@@ -2,25 +2,11 @@
|
||||
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
from datetime import timedelta
|
||||
import deprecation
|
||||
import logging
|
||||
from functools import cached_property
|
||||
import os
|
||||
from typing import (
|
||||
Any,
|
||||
Callable,
|
||||
Dict,
|
||||
Iterable,
|
||||
List,
|
||||
Optional,
|
||||
Union,
|
||||
Literal,
|
||||
overload,
|
||||
)
|
||||
from typing import Any, Callable, Dict, Iterable, List, Optional, Union, Literal
|
||||
import warnings
|
||||
|
||||
from lancedb import __version__
|
||||
|
||||
from lancedb._lancedb import (
|
||||
AddColumnsResult,
|
||||
AddResult,
|
||||
@@ -46,7 +32,6 @@ from lancedb.index import (
|
||||
LabelList,
|
||||
)
|
||||
from lancedb.remote.db import LOOP
|
||||
from lancedb.table import IndexConfigType, KNOWN_METRICS
|
||||
import pyarrow as pa
|
||||
|
||||
from lancedb.common import DATA, VEC, VECTOR_COLUMN_NAME
|
||||
@@ -64,103 +49,14 @@ class RemoteTable(Table):
|
||||
self,
|
||||
table: AsyncTable,
|
||||
db_name: str,
|
||||
*,
|
||||
connection_state: Optional[Union[str, Callable[[], str]]] = None,
|
||||
namespace_path: Optional[List[str]] = None,
|
||||
):
|
||||
self._table_handle = table
|
||||
self._name = table.name
|
||||
self._table = table
|
||||
self.db_name = db_name
|
||||
self._connection_state = connection_state
|
||||
self._namespace_path = list(namespace_path or [])
|
||||
self._checkout_version: Optional[int] = None
|
||||
self._table_state: Optional[dict[str, Any]] = None
|
||||
self._pid = os.getpid()
|
||||
|
||||
def _serialized_connection_state(self) -> str:
|
||||
if self._connection_state is None:
|
||||
raise RuntimeError(
|
||||
"Cannot reopen this remote table because it does not carry "
|
||||
"serialized connection state"
|
||||
)
|
||||
if callable(self._connection_state):
|
||||
self._connection_state = self._connection_state()
|
||||
return self._connection_state
|
||||
|
||||
def _reopen_state(self) -> dict[str, Any]:
|
||||
if self._table_state is not None:
|
||||
return self._table_state
|
||||
self._table_state = {
|
||||
"name": self._name,
|
||||
"namespace_path": self._namespace_path,
|
||||
"storage_options": None,
|
||||
}
|
||||
return self._table_state
|
||||
|
||||
@property
|
||||
def _table(self) -> AsyncTable:
|
||||
self._ensure_open()
|
||||
assert self._table_handle is not None
|
||||
return self._table_handle
|
||||
|
||||
@_table.setter
|
||||
def _table(self, table: AsyncTable) -> None:
|
||||
self._table_handle = table
|
||||
self._name = table.name
|
||||
self._table_state = None
|
||||
self._pid = os.getpid()
|
||||
|
||||
def _ensure_open(self) -> None:
|
||||
pid = os.getpid()
|
||||
if self._table_handle is not None and self._pid == pid:
|
||||
return
|
||||
|
||||
# Pickle clears the handle; fork inherits a handle created in the
|
||||
# parent process. In both cases reopen before touching the Rust client.
|
||||
from lancedb import deserialize_conn
|
||||
|
||||
db = deserialize_conn(self._serialized_connection_state(), for_worker=True)
|
||||
table_state = self._reopen_state()
|
||||
table = db.open_table(
|
||||
table_state["name"],
|
||||
namespace_path=table_state["namespace_path"] or None,
|
||||
)
|
||||
if self._checkout_version is not None:
|
||||
table.checkout(self._checkout_version)
|
||||
|
||||
self._table_handle = table._table
|
||||
self.db_name = table.db_name
|
||||
self._pid = pid
|
||||
|
||||
def __getstate__(self) -> dict:
|
||||
return {
|
||||
"connection_state": self._serialized_connection_state(),
|
||||
"db_name": self.db_name,
|
||||
"table_state": self._reopen_state(),
|
||||
"checkout_version": self._checkout_version,
|
||||
}
|
||||
|
||||
def __setstate__(self, state: dict) -> None:
|
||||
self._table_handle = None
|
||||
table_state = state.get("table_state")
|
||||
if table_state is None:
|
||||
table_state = {
|
||||
"name": state["name"],
|
||||
"namespace_path": state["namespace_path"],
|
||||
"storage_options": None,
|
||||
}
|
||||
self._table_state = table_state
|
||||
self._name = table_state["name"]
|
||||
self.db_name = state["db_name"]
|
||||
self._connection_state = state["connection_state"]
|
||||
self._namespace_path = table_state["namespace_path"]
|
||||
self._checkout_version = state["checkout_version"]
|
||||
self._pid = None
|
||||
|
||||
@property
|
||||
def name(self) -> str:
|
||||
"""The name of the table"""
|
||||
return self._name
|
||||
return self._table.name
|
||||
|
||||
def __repr__(self) -> str:
|
||||
return f"RemoteTable({self.db_name}.{self.name})"
|
||||
@@ -210,19 +106,13 @@ class RemoteTable(Table):
|
||||
raise NotImplementedError("to_pandas() is not yet supported on LanceDB cloud.")
|
||||
|
||||
def checkout(self, version: Union[int, str]):
|
||||
result = LOOP.run(self._table.checkout(version))
|
||||
self._checkout_version = self.version
|
||||
return result
|
||||
return LOOP.run(self._table.checkout(version))
|
||||
|
||||
def checkout_latest(self):
|
||||
result = LOOP.run(self._table.checkout_latest())
|
||||
self._checkout_version = None
|
||||
return result
|
||||
return LOOP.run(self._table.checkout_latest())
|
||||
|
||||
def restore(self, version: Optional[Union[int, str]] = None):
|
||||
result = LOOP.run(self._table.restore(version))
|
||||
self._checkout_version = None
|
||||
return result
|
||||
return LOOP.run(self._table.restore(version))
|
||||
|
||||
def list_indices(self) -> Iterable[IndexConfig]:
|
||||
"""List all the indices on the table"""
|
||||
@@ -232,11 +122,6 @@ class RemoteTable(Table):
|
||||
"""List all the stats of a specified index"""
|
||||
return LOOP.run(self._table.index_stats(index_uuid))
|
||||
|
||||
@deprecation.deprecated(
|
||||
deprecated_in="0.25.0",
|
||||
current_version=__version__,
|
||||
details="Use create_index() with config=BTree()/Bitmap()/LabelList() instead.",
|
||||
)
|
||||
def create_scalar_index(
|
||||
self,
|
||||
column: str,
|
||||
@@ -246,12 +131,7 @@ class RemoteTable(Table):
|
||||
wait_timeout: Optional[timedelta] = None,
|
||||
name: Optional[str] = None,
|
||||
):
|
||||
"""Creates a scalar index.
|
||||
|
||||
.. deprecated:: 0.25.0
|
||||
Use :meth:`create_index` with a BTree, Bitmap, or LabelList config instead.
|
||||
Example: ``table.create_index("column", config=BTree())``
|
||||
|
||||
"""Creates a scalar index
|
||||
Parameters
|
||||
----------
|
||||
column : str
|
||||
@@ -282,11 +162,6 @@ class RemoteTable(Table):
|
||||
)
|
||||
)
|
||||
|
||||
@deprecation.deprecated(
|
||||
deprecated_in="0.25.0",
|
||||
current_version=__version__,
|
||||
details="Use create_index() with config=FTS() instead.",
|
||||
)
|
||||
def create_fts_index(
|
||||
self,
|
||||
column: str,
|
||||
@@ -307,12 +182,6 @@ class RemoteTable(Table):
|
||||
prefix_only: bool = False,
|
||||
name: Optional[str] = None,
|
||||
):
|
||||
"""Create a full-text search index on a column.
|
||||
|
||||
.. deprecated:: 0.25.0
|
||||
Use :meth:`create_index` with an FTS config instead.
|
||||
Example: ``table.create_index("text_column", config=FTS())``
|
||||
"""
|
||||
config = FTS(
|
||||
with_position=with_position,
|
||||
base_tokenizer=base_tokenizer,
|
||||
@@ -336,43 +205,9 @@ class RemoteTable(Table):
|
||||
)
|
||||
)
|
||||
|
||||
# New unified API overload
|
||||
@overload
|
||||
def create_index(
|
||||
self,
|
||||
column: str,
|
||||
/,
|
||||
*,
|
||||
config: IndexConfigType,
|
||||
wait_timeout: Optional[timedelta] = ...,
|
||||
name: Optional[str] = ...,
|
||||
train: bool = ...,
|
||||
) -> None: ...
|
||||
|
||||
# Legacy API overload (deprecated)
|
||||
@overload
|
||||
def create_index(
|
||||
self,
|
||||
metric: Literal["l2", "cosine", "dot", "hamming"] = ...,
|
||||
vector_column_name: str = ...,
|
||||
index_cache_size: Optional[int] = ...,
|
||||
num_partitions: Optional[int] = ...,
|
||||
num_sub_vectors: Optional[int] = ...,
|
||||
replace: Optional[bool] = ...,
|
||||
accelerator: Optional[str] = ...,
|
||||
index_type: Literal[
|
||||
"VECTOR", "IVF_FLAT", "IVF_SQ", "IVF_PQ", "IVF_HNSW_SQ", "IVF_HNSW_PQ"
|
||||
] = ...,
|
||||
wait_timeout: Optional[timedelta] = ...,
|
||||
*,
|
||||
num_bits: int = ...,
|
||||
name: Optional[str] = ...,
|
||||
train: bool = ...,
|
||||
) -> None: ...
|
||||
|
||||
def create_index(
|
||||
self,
|
||||
metric: str = "l2",
|
||||
metric="l2",
|
||||
vector_column_name: str = VECTOR_COLUMN_NAME,
|
||||
index_cache_size: Optional[int] = None,
|
||||
num_partitions: Optional[int] = None,
|
||||
@@ -383,113 +218,89 @@ class RemoteTable(Table):
|
||||
wait_timeout: Optional[timedelta] = None,
|
||||
*,
|
||||
num_bits: int = 8,
|
||||
config: Optional[IndexConfigType] = None,
|
||||
name: Optional[str] = None,
|
||||
train: bool = True,
|
||||
):
|
||||
"""Create an index on a column.
|
||||
"""Create an index on the table.
|
||||
|
||||
This method supports both the new unified API and the legacy API
|
||||
for backwards compatibility. The new API takes the column name as the
|
||||
first positional argument and an index configuration object via
|
||||
``config``; the legacy API takes the distance metric as the first
|
||||
argument plus separate ``vector_column_name`` / ``num_partitions`` /
|
||||
etc. parameters, and emits a ``DeprecationWarning``.
|
||||
Parameters
|
||||
----------
|
||||
metric : str
|
||||
The metric to use for the index. Default is "l2".
|
||||
vector_column_name : str
|
||||
The name of the vector column. Default is "vector".
|
||||
|
||||
Examples
|
||||
--------
|
||||
New API (recommended):
|
||||
|
||||
>>> table.create_index( # doctest: +SKIP
|
||||
... "vector", config=IvfPq(distance_type="l2")
|
||||
>>> import lancedb
|
||||
>>> import uuid
|
||||
>>> from lancedb.schema import vector
|
||||
>>> db = lancedb.connect("db://...", api_key="...", # doctest: +SKIP
|
||||
... region="...") # doctest: +SKIP
|
||||
>>> table_name = uuid.uuid4().hex
|
||||
>>> schema = pa.schema(
|
||||
... [
|
||||
... pa.field("id", pa.uint32(), False),
|
||||
... pa.field("vector", vector(128), False),
|
||||
... pa.field("s", pa.string(), False),
|
||||
... ]
|
||||
... )
|
||||
>>> table.create_index("category", config=BTree()) # doctest: +SKIP
|
||||
>>> table.create_index("content", config=FTS()) # doctest: +SKIP
|
||||
|
||||
Legacy API (deprecated):
|
||||
|
||||
>>> table.create_index( # doctest: +SKIP
|
||||
... "l2", vector_column_name="vector"
|
||||
>>> table = db.create_table( # doctest: +SKIP
|
||||
... table_name, # doctest: +SKIP
|
||||
... schema=schema, # doctest: +SKIP
|
||||
... )
|
||||
>>> table.create_index("l2", "vector") # doctest: +SKIP
|
||||
"""
|
||||
# Detect whether this is a legacy API call
|
||||
is_legacy = self._is_legacy_create_index_call(
|
||||
metric,
|
||||
config,
|
||||
num_partitions,
|
||||
num_sub_vectors,
|
||||
vector_column_name,
|
||||
accelerator,
|
||||
index_cache_size,
|
||||
replace,
|
||||
)
|
||||
|
||||
if is_legacy:
|
||||
warnings.warn(
|
||||
"The create_index() API with metric/num_partitions parameters is "
|
||||
"deprecated and will be removed in a future version. "
|
||||
"Please migrate to the new unified API:\n"
|
||||
" # Old (deprecated):\n"
|
||||
" table.create_index('l2', vector_column_name='my_vector')\n"
|
||||
" # New (recommended):\n"
|
||||
" table.create_index('my_vector', config=IvfPq(distance_type='l2'))",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
if accelerator is not None:
|
||||
logging.warning(
|
||||
"GPU accelerator is not yet supported on LanceDB cloud."
|
||||
"If you have 100M+ vectors to index,"
|
||||
"please contact us at contact@lancedb.com"
|
||||
)
|
||||
if replace is not None:
|
||||
logging.warning(
|
||||
"replace is not supported on LanceDB cloud."
|
||||
"Existing indexes will always be replaced."
|
||||
)
|
||||
|
||||
column = vector_column_name
|
||||
|
||||
if accelerator is not None:
|
||||
logging.warning(
|
||||
"GPU accelerator is not yet supported on LanceDB cloud."
|
||||
"If you have 100M+ vectors to index,"
|
||||
"please contact us at contact@lancedb.com"
|
||||
)
|
||||
if replace is not None:
|
||||
logging.warning(
|
||||
"replace is not supported on LanceDB cloud."
|
||||
"Existing indexes will always be replaced."
|
||||
)
|
||||
|
||||
idx_type = index_type.upper()
|
||||
if idx_type == "VECTOR" or idx_type == "IVF_PQ":
|
||||
config = IvfPq(
|
||||
distance_type=metric,
|
||||
num_partitions=num_partitions,
|
||||
num_sub_vectors=num_sub_vectors,
|
||||
num_bits=num_bits,
|
||||
)
|
||||
elif idx_type == "IVF_RQ":
|
||||
config = IvfRq(
|
||||
distance_type=metric,
|
||||
num_partitions=num_partitions,
|
||||
num_bits=num_bits,
|
||||
)
|
||||
elif idx_type == "IVF_SQ":
|
||||
config = IvfSq(distance_type=metric, num_partitions=num_partitions)
|
||||
elif idx_type == "IVF_HNSW_PQ":
|
||||
raise ValueError(
|
||||
"IVF_HNSW_PQ is not supported on LanceDB cloud."
|
||||
"Please use IVF_HNSW_SQ instead."
|
||||
)
|
||||
elif idx_type == "IVF_HNSW_SQ":
|
||||
config = HnswSq(distance_type=metric, num_partitions=num_partitions)
|
||||
elif idx_type == "IVF_HNSW_FLAT":
|
||||
config = HnswFlat(distance_type=metric, num_partitions=num_partitions)
|
||||
elif idx_type == "IVF_FLAT":
|
||||
config = IvfFlat(distance_type=metric, num_partitions=num_partitions)
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Unknown vector index type: {idx_type}. Valid options are"
|
||||
" 'IVF_FLAT', 'IVF_PQ', 'IVF_RQ', 'IVF_SQ',"
|
||||
" 'IVF_HNSW_PQ', 'IVF_HNSW_SQ', 'IVF_HNSW_FLAT'"
|
||||
)
|
||||
index_type = index_type.upper()
|
||||
if index_type == "VECTOR" or index_type == "IVF_PQ":
|
||||
config = IvfPq(
|
||||
distance_type=metric,
|
||||
num_partitions=num_partitions,
|
||||
num_sub_vectors=num_sub_vectors,
|
||||
num_bits=num_bits,
|
||||
)
|
||||
elif index_type == "IVF_RQ":
|
||||
config = IvfRq(
|
||||
distance_type=metric,
|
||||
num_partitions=num_partitions,
|
||||
num_bits=num_bits,
|
||||
)
|
||||
elif index_type == "IVF_SQ":
|
||||
config = IvfSq(distance_type=metric, num_partitions=num_partitions)
|
||||
elif index_type == "IVF_HNSW_PQ":
|
||||
raise ValueError(
|
||||
"IVF_HNSW_PQ is not supported on LanceDB cloud."
|
||||
"Please use IVF_HNSW_SQ instead."
|
||||
)
|
||||
elif index_type == "IVF_HNSW_SQ":
|
||||
config = HnswSq(distance_type=metric, num_partitions=num_partitions)
|
||||
elif index_type == "IVF_HNSW_FLAT":
|
||||
config = HnswFlat(distance_type=metric, num_partitions=num_partitions)
|
||||
elif index_type == "IVF_FLAT":
|
||||
config = IvfFlat(distance_type=metric, num_partitions=num_partitions)
|
||||
else:
|
||||
column = metric
|
||||
raise ValueError(
|
||||
f"Unknown vector index type: {index_type}. Valid options are"
|
||||
" 'IVF_FLAT', 'IVF_PQ', 'IVF_RQ', 'IVF_SQ',"
|
||||
" 'IVF_HNSW_PQ', 'IVF_HNSW_SQ', 'IVF_HNSW_FLAT'"
|
||||
)
|
||||
|
||||
LOOP.run(
|
||||
self._table.create_index(
|
||||
column,
|
||||
vector_column_name,
|
||||
config=config,
|
||||
wait_timeout=wait_timeout,
|
||||
name=name,
|
||||
@@ -497,37 +308,6 @@ class RemoteTable(Table):
|
||||
)
|
||||
)
|
||||
|
||||
def _is_legacy_create_index_call(
|
||||
self,
|
||||
first_arg: str,
|
||||
config: Optional[IndexConfigType],
|
||||
num_partitions: Optional[int],
|
||||
num_sub_vectors: Optional[int],
|
||||
vector_column_name: str,
|
||||
accelerator: Optional[str],
|
||||
index_cache_size: Optional[int],
|
||||
replace: Optional[bool],
|
||||
) -> bool:
|
||||
"""Detect if this is a legacy create_index call."""
|
||||
if config is not None:
|
||||
return False
|
||||
if any(
|
||||
x is not None
|
||||
for x in (
|
||||
num_partitions,
|
||||
num_sub_vectors,
|
||||
accelerator,
|
||||
index_cache_size,
|
||||
replace,
|
||||
)
|
||||
):
|
||||
return True
|
||||
if vector_column_name != VECTOR_COLUMN_NAME:
|
||||
return True
|
||||
if first_arg.lower() in KNOWN_METRICS:
|
||||
return True
|
||||
return False
|
||||
|
||||
def add(
|
||||
self,
|
||||
data: DATA,
|
||||
@@ -888,10 +668,6 @@ class RemoteTable(Table):
|
||||
"""Not supported on LanceDB Cloud."""
|
||||
return LOOP.run(self._table.unset_lsm_write_spec())
|
||||
|
||||
def close_lsm_writers(self) -> None:
|
||||
"""No-op on LanceDB Cloud (no local shard writers)."""
|
||||
return LOOP.run(self._table.close_lsm_writers())
|
||||
|
||||
def drop_index(self, index_name: str):
|
||||
return LOOP.run(self._table.drop_index(index_name))
|
||||
|
||||
|
||||
@@ -102,15 +102,8 @@ class LinearCombinationReranker(Reranker):
|
||||
|
||||
combined_list = []
|
||||
for row_id, result in results.items():
|
||||
# Convert vector distance to a relevance score in [0, 1] where
|
||||
# higher is better. Missing vector entries are penalised with
|
||||
# `_invert_score(fill)` = 1 - fill (= 0.0 for the default fill=1).
|
||||
vector_score = self._invert_score(result.get("_distance", fill))
|
||||
# FTS scores (BM25) are already in a "higher = more relevant" space.
|
||||
# Missing FTS entries are penalised symmetrically: we use
|
||||
# `1 - fill` so that the same `fill` value drives both missing-vector
|
||||
# and missing-FTS penalties in the same direction.
|
||||
fts_score = result.get("_score", 1 - fill)
|
||||
fts_score = result.get("_score", fill)
|
||||
result["_relevance_score"] = self._combine_score(vector_score, fts_score)
|
||||
combined_list.append(result)
|
||||
|
||||
@@ -130,12 +123,8 @@ class LinearCombinationReranker(Reranker):
|
||||
return tbl
|
||||
|
||||
def _combine_score(self, vector_score, fts_score):
|
||||
# Both vector_score (inverted distance) and fts_score are in a
|
||||
# "higher = more relevant" space. A straight weighted average gives
|
||||
# higher _relevance_score to better matches, as expected.
|
||||
# Previously this returned `1 - (...)` which inverted the final
|
||||
# ranking so that the *least* relevant document ranked first.
|
||||
return self.weight * vector_score + (1 - self.weight) * fts_score
|
||||
# these scores represent distance
|
||||
return 1 - (self.weight * vector_score + (1 - self.weight) * fts_score)
|
||||
|
||||
def _invert_score(self, dist: float):
|
||||
# Invert the score between relevance and distance
|
||||
|
||||
@@ -5,7 +5,6 @@ from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import inspect
|
||||
import os
|
||||
import deprecation
|
||||
import warnings
|
||||
from abc import ABC, abstractmethod
|
||||
@@ -175,24 +174,6 @@ if TYPE_CHECKING:
|
||||
DistanceType,
|
||||
)
|
||||
|
||||
# Type alias for index configuration objects
|
||||
IndexConfigType = Union[
|
||||
IvfFlat,
|
||||
IvfPq,
|
||||
IvfSq,
|
||||
IvfRq,
|
||||
HnswFlat,
|
||||
HnswPq,
|
||||
HnswSq,
|
||||
BTree,
|
||||
Bitmap,
|
||||
LabelList,
|
||||
FTS,
|
||||
]
|
||||
|
||||
# Known distance metrics for legacy API detection
|
||||
KNOWN_METRICS = {"l2", "cosine", "dot", "hamming"}
|
||||
|
||||
|
||||
def _into_pyarrow_reader(
|
||||
data, schema: Optional[pa.Schema] = None
|
||||
@@ -758,12 +739,8 @@ class Table(ABC):
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
def _ensure_open(self) -> None:
|
||||
pass
|
||||
|
||||
def __len__(self) -> int:
|
||||
"""The number of rows in this Table"""
|
||||
self._ensure_open()
|
||||
return self.count_rows(None)
|
||||
|
||||
@property
|
||||
@@ -830,49 +807,11 @@ class Table(ABC):
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
# New unified API overload
|
||||
@overload
|
||||
def create_index(
|
||||
self,
|
||||
column: str,
|
||||
/,
|
||||
*,
|
||||
config: IndexConfigType,
|
||||
replace: bool = ...,
|
||||
wait_timeout: Optional[timedelta] = ...,
|
||||
name: Optional[str] = ...,
|
||||
train: bool = ...,
|
||||
) -> None: ...
|
||||
|
||||
# Legacy API overload (deprecated)
|
||||
@overload
|
||||
def create_index(
|
||||
self,
|
||||
metric: Literal["l2", "cosine", "dot", "hamming"] = ...,
|
||||
num_partitions: Optional[int] = ...,
|
||||
num_sub_vectors: Optional[int] = ...,
|
||||
vector_column_name: str = ...,
|
||||
replace: bool = ...,
|
||||
accelerator: Optional[str] = ...,
|
||||
index_cache_size: Optional[int] = ...,
|
||||
*,
|
||||
index_type: VectorIndexType = ...,
|
||||
wait_timeout: Optional[timedelta] = ...,
|
||||
num_bits: int = ...,
|
||||
max_iterations: int = ...,
|
||||
sample_rate: int = ...,
|
||||
m: int = ...,
|
||||
ef_construction: int = ...,
|
||||
name: Optional[str] = ...,
|
||||
train: bool = ...,
|
||||
target_partition_size: Optional[int] = ...,
|
||||
) -> None: ...
|
||||
|
||||
def create_index(
|
||||
self,
|
||||
metric: DistanceType = "l2",
|
||||
num_partitions: Optional[int] = None,
|
||||
num_sub_vectors: Optional[int] = None,
|
||||
metric="l2",
|
||||
num_partitions=256,
|
||||
num_sub_vectors=96,
|
||||
vector_column_name: str = VECTOR_COLUMN_NAME,
|
||||
replace: bool = True,
|
||||
accelerator: Optional[str] = None,
|
||||
@@ -885,53 +824,46 @@ class Table(ABC):
|
||||
sample_rate: int = 256,
|
||||
m: int = 20,
|
||||
ef_construction: int = 300,
|
||||
config: Optional[IndexConfigType] = None,
|
||||
name: Optional[str] = None,
|
||||
train: bool = True,
|
||||
target_partition_size: Optional[int] = None,
|
||||
):
|
||||
"""Create an index on a column.
|
||||
|
||||
This method supports both the new unified API and the legacy API
|
||||
for backwards compatibility. The new API takes the column name as the
|
||||
first positional argument and an index configuration object via
|
||||
``config``; the legacy API takes the distance metric as the first
|
||||
argument plus separate ``vector_column_name`` / ``num_partitions`` /
|
||||
etc. parameters, and emits a ``DeprecationWarning``.
|
||||
"""Create an index on the table.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
metric : str
|
||||
For new API: the column name to index.
|
||||
For legacy API: the distance metric ("l2", "cosine", "dot", "hamming").
|
||||
config : IndexConfigType, optional
|
||||
The index configuration object. If provided, uses the new unified API.
|
||||
Can be one of: IvfFlat, IvfPq, IvfSq, IvfRq, HnswPq, HnswSq,
|
||||
BTree, Bitmap, LabelList, FTS.
|
||||
replace : bool, default True
|
||||
Whether to replace an existing index on this column.
|
||||
wait_timeout : timedelta, optional
|
||||
Timeout to wait for async indexing to complete.
|
||||
name : str, optional
|
||||
Custom name for the index.
|
||||
train : bool, default True
|
||||
Whether to train the index with existing data.
|
||||
metric: str, default "l2"
|
||||
The distance metric to use when creating the index.
|
||||
Valid values are "l2", "cosine", "dot", or "hamming".
|
||||
l2 is euclidean distance.
|
||||
Hamming is available only for binary vectors.
|
||||
num_partitions: int, default 256
|
||||
The number of IVF partitions to use when creating the index.
|
||||
Default is 256.
|
||||
num_sub_vectors: int, default 96
|
||||
The number of PQ sub-vectors to use when creating the index.
|
||||
Default is 96.
|
||||
vector_column_name: str, default "vector"
|
||||
The vector column name to create the index.
|
||||
replace: bool, default True
|
||||
- If True, replace the existing index if it exists.
|
||||
|
||||
Examples
|
||||
--------
|
||||
New API (recommended):
|
||||
|
||||
>>> table.create_index( # doctest: +SKIP
|
||||
... "vector", config=IvfPq(distance_type="l2")
|
||||
... )
|
||||
>>> table.create_index("category", config=BTree()) # doctest: +SKIP
|
||||
>>> table.create_index("content", config=FTS()) # doctest: +SKIP
|
||||
|
||||
Legacy API (deprecated):
|
||||
|
||||
>>> table.create_index( # doctest: +SKIP
|
||||
... "l2", vector_column_name="vector"
|
||||
... )
|
||||
- If False, raise an error if duplicate index exists.
|
||||
accelerator: str, default None
|
||||
If set, use the given accelerator to create the index.
|
||||
Only support "cuda" for now.
|
||||
index_cache_size : int, optional
|
||||
The size of the index cache in number of entries. Default value is 256.
|
||||
num_bits: int
|
||||
The number of bits to encode sub-vectors. Only used with the IVF_PQ index.
|
||||
Only 4 and 8 are supported.
|
||||
wait_timeout: timedelta, optional
|
||||
The timeout to wait if indexing is asynchronous.
|
||||
name: str, optional
|
||||
The name of the index. If not provided, a default name will be generated.
|
||||
train: bool, default True
|
||||
Whether to train the index with existing data. Vector indices always train
|
||||
with existing data.
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
@@ -1256,7 +1188,7 @@ class Table(ABC):
|
||||
... .when_not_matched_insert_all() \\
|
||||
... .execute(new_data)
|
||||
>>> res
|
||||
MergeResult(version=2, num_updated_rows=2, num_inserted_rows=1, num_deleted_rows=0, num_attempts=1, num_rows=3)
|
||||
MergeResult(version=2, num_updated_rows=2, num_inserted_rows=1, num_deleted_rows=0, num_attempts=1)
|
||||
>>> # The order of new rows is non-deterministic since we use
|
||||
>>> # a hash-join as part of this operation and so we sort here
|
||||
>>> table.to_arrow().sort_by("a").to_pandas()
|
||||
@@ -1409,7 +1341,6 @@ class Table(ABC):
|
||||
pa.RecordBatch
|
||||
A record batch containing the rows at the given offsets.
|
||||
"""
|
||||
self._ensure_open()
|
||||
# We don't know the order of the results at all. So we calculate a permutation
|
||||
# for ordering the given offsets. Then we load the data with the _rowoffset
|
||||
# column. Then we sort by _rowoffset and apply the inverse of the permutation
|
||||
@@ -1968,7 +1899,6 @@ class LanceTable(Table):
|
||||
self._location = location # Store location for use in _dataset_path
|
||||
self._namespace_client = namespace_client
|
||||
self._pushdown_operations = pushdown_operations or set()
|
||||
self._init_reopen_tracking()
|
||||
if _async is not None:
|
||||
self._table = _async
|
||||
else:
|
||||
@@ -1984,66 +1914,6 @@ class LanceTable(Table):
|
||||
)
|
||||
)
|
||||
|
||||
def _init_reopen_tracking(self) -> None:
|
||||
self._checkout_version: Optional[int] = None
|
||||
self._table_state: Optional[dict[str, Any]] = None
|
||||
self._pid = os.getpid()
|
||||
|
||||
def _reopen_state(self) -> dict[str, Any]:
|
||||
state = LOOP.run(self._table._table_reopen_state())
|
||||
if get_uri_scheme(self._conn.uri) == "memory":
|
||||
raise ValueError(
|
||||
"Cannot pickle an in-memory LanceTable. Use a persisted table "
|
||||
"or provide a worker-side connection factory."
|
||||
)
|
||||
return state
|
||||
|
||||
def _copy_reopened_table(self, table: "LanceTable") -> None:
|
||||
self._conn = table._conn
|
||||
self._namespace_path = table._namespace_path
|
||||
self._location = table._location
|
||||
self._namespace_client = table._namespace_client
|
||||
self._pushdown_operations = table._pushdown_operations
|
||||
self._table = table._table
|
||||
self._pid = os.getpid()
|
||||
|
||||
def _ensure_open(self) -> None:
|
||||
pid = os.getpid()
|
||||
if getattr(self, "_table", None) is not None and self._pid == pid:
|
||||
return
|
||||
if self._table_state is None:
|
||||
self._table_state = self._reopen_state()
|
||||
|
||||
table = self._conn.open_table(
|
||||
self._table_state["name"],
|
||||
namespace_path=self._table_state["namespace_path"] or None,
|
||||
storage_options=self._table_state["storage_options"],
|
||||
)
|
||||
if self._checkout_version is not None:
|
||||
table.checkout(self._checkout_version)
|
||||
self._copy_reopened_table(table)
|
||||
|
||||
def __getstate__(self) -> dict[str, Any]:
|
||||
return {
|
||||
"connection_state": self._conn.serialize(),
|
||||
"table_state": self._reopen_state(),
|
||||
"checkout_version": self._checkout_version,
|
||||
}
|
||||
|
||||
def __setstate__(self, state: dict[str, Any]) -> None:
|
||||
from . import deserialize_conn
|
||||
|
||||
self._conn = deserialize_conn(state["connection_state"], for_worker=True)
|
||||
self._namespace_path = list(state["table_state"]["namespace_path"] or [])
|
||||
self._location = None
|
||||
self._namespace_client = None
|
||||
self._pushdown_operations = set()
|
||||
self._checkout_version = state["checkout_version"]
|
||||
self._table_state = state["table_state"]
|
||||
self._table = None
|
||||
self._pid = None
|
||||
self._ensure_open()
|
||||
|
||||
@property
|
||||
def name(self) -> str:
|
||||
return self._table.name
|
||||
@@ -2247,7 +2117,6 @@ class LanceTable(Table):
|
||||
0 [1.1, 0.9] vector
|
||||
"""
|
||||
LOOP.run(self._table.checkout(version))
|
||||
self._checkout_version = self.version
|
||||
|
||||
def checkout_latest(self):
|
||||
"""Checkout the latest version of the table. This is an in-place operation.
|
||||
@@ -2256,7 +2125,6 @@ class LanceTable(Table):
|
||||
version of the table.
|
||||
"""
|
||||
LOOP.run(self._table.checkout_latest())
|
||||
self._checkout_version = None
|
||||
|
||||
def restore(self, version: Optional[Union[int, str]] = None):
|
||||
"""Restore a version of the table. This is an in-place operation.
|
||||
@@ -2305,7 +2173,6 @@ class LanceTable(Table):
|
||||
if version is not None:
|
||||
LOOP.run(self._table.checkout(version))
|
||||
LOOP.run(self._table.restore())
|
||||
self._checkout_version = None
|
||||
|
||||
def count_rows(self, filter: Optional[str] = None) -> int:
|
||||
return LOOP.run(self._table.count_rows(filter))
|
||||
@@ -2383,51 +2250,11 @@ class LanceTable(Table):
|
||||
dataset, allow_pyarrow_filter=False, batch_size=batch_size
|
||||
)
|
||||
|
||||
# New unified API overload
|
||||
@overload
|
||||
def create_index(
|
||||
self,
|
||||
column: str,
|
||||
/,
|
||||
*,
|
||||
config: IndexConfigType,
|
||||
replace: bool = ...,
|
||||
wait_timeout: Optional[timedelta] = ...,
|
||||
name: Optional[str] = ...,
|
||||
train: bool = ...,
|
||||
) -> None: ...
|
||||
|
||||
# Legacy API overload (deprecated)
|
||||
@overload
|
||||
def create_index(
|
||||
self,
|
||||
metric: Literal["l2", "cosine", "dot", "hamming"] = ...,
|
||||
num_partitions: Optional[int] = ...,
|
||||
num_sub_vectors: Optional[int] = ...,
|
||||
vector_column_name: str = ...,
|
||||
replace: bool = ...,
|
||||
accelerator: Optional[str] = ...,
|
||||
index_cache_size: Optional[int] = ...,
|
||||
num_bits: int = ...,
|
||||
index_type: Literal[
|
||||
"IVF_FLAT", "IVF_SQ", "IVF_PQ", "IVF_RQ", "IVF_HNSW_SQ", "IVF_HNSW_PQ"
|
||||
] = ...,
|
||||
max_iterations: int = ...,
|
||||
sample_rate: int = ...,
|
||||
m: int = ...,
|
||||
ef_construction: int = ...,
|
||||
*,
|
||||
wait_timeout: Optional[timedelta] = ...,
|
||||
name: Optional[str] = ...,
|
||||
train: bool = ...,
|
||||
target_partition_size: Optional[int] = ...,
|
||||
) -> None: ...
|
||||
|
||||
def create_index(
|
||||
self,
|
||||
metric: str = "l2",
|
||||
num_partitions: Optional[int] = None,
|
||||
num_sub_vectors: Optional[int] = None,
|
||||
metric: DistanceType = "l2",
|
||||
num_partitions=None,
|
||||
num_sub_vectors=None,
|
||||
vector_column_name: str = VECTOR_COLUMN_NAME,
|
||||
replace: bool = True,
|
||||
accelerator: Optional[str] = None,
|
||||
@@ -2447,232 +2274,47 @@ class LanceTable(Table):
|
||||
m: int = 20,
|
||||
ef_construction: int = 300,
|
||||
*,
|
||||
config: Optional[IndexConfigType] = None,
|
||||
wait_timeout: Optional[timedelta] = None,
|
||||
name: Optional[str] = None,
|
||||
train: bool = True,
|
||||
target_partition_size: Optional[int] = None,
|
||||
):
|
||||
"""Create an index on a column.
|
||||
|
||||
This method supports both the new unified API and the legacy API
|
||||
for backwards compatibility. The new API takes the column name as the
|
||||
first positional argument and an index configuration object via
|
||||
``config``; the legacy API takes the distance metric as the first
|
||||
argument plus separate ``vector_column_name`` / ``num_partitions`` /
|
||||
etc. parameters, and emits a ``DeprecationWarning``.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
metric : str
|
||||
For new API: the column name to index.
|
||||
For legacy API: the distance metric ("l2", "cosine", "dot", "hamming").
|
||||
config : IndexConfigType, optional
|
||||
The index configuration object. If provided, uses the new unified API.
|
||||
Can be one of: IvfFlat, IvfPq, IvfSq, IvfRq, HnswPq, HnswSq,
|
||||
BTree, Bitmap, LabelList, FTS.
|
||||
replace : bool, default True
|
||||
Whether to replace an existing index on this column.
|
||||
wait_timeout : timedelta, optional
|
||||
Timeout to wait for async indexing to complete.
|
||||
name : str, optional
|
||||
Custom name for the index.
|
||||
train : bool, default True
|
||||
Whether to train the index with existing data.
|
||||
|
||||
Examples
|
||||
--------
|
||||
New API (recommended):
|
||||
|
||||
>>> table.create_index( # doctest: +SKIP
|
||||
... "vector", config=IvfPq(distance_type="l2")
|
||||
... )
|
||||
>>> table.create_index("category", config=BTree()) # doctest: +SKIP
|
||||
>>> table.create_index("content", config=FTS()) # doctest: +SKIP
|
||||
|
||||
Legacy API (deprecated):
|
||||
|
||||
>>> table.create_index( # doctest: +SKIP
|
||||
... "l2", vector_column_name="vector"
|
||||
... )
|
||||
"""
|
||||
# Detect whether this is a legacy API call
|
||||
is_legacy = self._is_legacy_create_index_call(
|
||||
metric,
|
||||
config,
|
||||
num_partitions,
|
||||
num_sub_vectors,
|
||||
vector_column_name,
|
||||
accelerator,
|
||||
index_cache_size,
|
||||
)
|
||||
|
||||
if is_legacy:
|
||||
warnings.warn(
|
||||
"The create_index() API with metric/num_partitions parameters is "
|
||||
"deprecated and will be removed in a future version. "
|
||||
"Please migrate to the new unified API:\n"
|
||||
" # Old (deprecated):\n"
|
||||
" table.create_index('l2', vector_column_name='my_vector')\n"
|
||||
" # New (recommended):\n"
|
||||
" table.create_index('my_vector', config=IvfPq(distance_type='l2'))",
|
||||
DeprecationWarning,
|
||||
stacklevel=2,
|
||||
)
|
||||
|
||||
# Legacy API: first arg is the distance metric
|
||||
column = vector_column_name
|
||||
|
||||
# Build config from legacy parameters
|
||||
config = self._build_vector_config_from_legacy_params(
|
||||
metric=metric,
|
||||
"""Create an index on the table."""
|
||||
if accelerator is not None:
|
||||
# accelerator is only supported through pylance.
|
||||
self.to_lance().create_index(
|
||||
column=vector_column_name,
|
||||
index_type=index_type,
|
||||
metric=metric,
|
||||
num_partitions=num_partitions,
|
||||
num_sub_vectors=num_sub_vectors,
|
||||
replace=replace,
|
||||
accelerator=accelerator,
|
||||
index_cache_size=index_cache_size,
|
||||
num_bits=num_bits,
|
||||
max_iterations=max_iterations,
|
||||
sample_rate=sample_rate,
|
||||
m=m,
|
||||
ef_construction=ef_construction,
|
||||
target_partition_size=target_partition_size,
|
||||
accelerator=accelerator,
|
||||
)
|
||||
|
||||
# Handle accelerator through pylance
|
||||
if accelerator is not None:
|
||||
self.to_lance().create_index(
|
||||
column=column,
|
||||
index_type=index_type,
|
||||
metric=metric,
|
||||
num_partitions=num_partitions,
|
||||
num_sub_vectors=num_sub_vectors,
|
||||
replace=replace,
|
||||
accelerator=accelerator,
|
||||
index_cache_size=index_cache_size,
|
||||
num_bits=num_bits,
|
||||
m=m,
|
||||
ef_construction=ef_construction,
|
||||
target_partition_size=target_partition_size,
|
||||
)
|
||||
self.checkout_latest()
|
||||
return
|
||||
else:
|
||||
# New API: metric is the column name
|
||||
column = metric
|
||||
|
||||
# Check if config has accelerator set and dispatch to pylance
|
||||
if config is not None and hasattr(config, "accelerator"):
|
||||
acc = getattr(config, "accelerator", None)
|
||||
if acc is not None:
|
||||
# Dispatch to pylance for GPU acceleration
|
||||
index_type_map = {
|
||||
"IvfFlat": "IVF_FLAT",
|
||||
"IvfSq": "IVF_SQ",
|
||||
"IvfPq": "IVF_PQ",
|
||||
"IvfRq": "IVF_RQ",
|
||||
"HnswPq": "IVF_HNSW_PQ",
|
||||
"HnswSq": "IVF_HNSW_SQ",
|
||||
}
|
||||
cfg_type = type(config).__name__
|
||||
lance_index_type = index_type_map.get(cfg_type, "IVF_PQ")
|
||||
|
||||
self.to_lance().create_index(
|
||||
column=column,
|
||||
index_type=lance_index_type,
|
||||
metric=getattr(config, "distance_type", "l2"),
|
||||
num_partitions=getattr(config, "num_partitions", None),
|
||||
num_sub_vectors=getattr(config, "num_sub_vectors", None),
|
||||
replace=replace,
|
||||
accelerator=acc,
|
||||
num_bits=getattr(config, "num_bits", 8),
|
||||
m=getattr(config, "m", 20),
|
||||
ef_construction=getattr(config, "ef_construction", 300),
|
||||
target_partition_size=getattr(
|
||||
config, "target_partition_size", None
|
||||
),
|
||||
)
|
||||
self.checkout_latest()
|
||||
return
|
||||
|
||||
return LOOP.run(
|
||||
self._table.create_index(
|
||||
column,
|
||||
replace=replace,
|
||||
config=config,
|
||||
wait_timeout=wait_timeout,
|
||||
name=name,
|
||||
train=train,
|
||||
)
|
||||
)
|
||||
|
||||
def _is_legacy_create_index_call(
|
||||
self,
|
||||
first_arg: str,
|
||||
config: Optional[IndexConfigType],
|
||||
num_partitions: Optional[int],
|
||||
num_sub_vectors: Optional[int],
|
||||
vector_column_name: str,
|
||||
accelerator: Optional[str],
|
||||
index_cache_size: Optional[int],
|
||||
) -> bool:
|
||||
"""Detect if this is a legacy create_index call."""
|
||||
# If config is provided, it's definitely the new API
|
||||
if config is not None:
|
||||
return False
|
||||
|
||||
# If old-style parameters were explicitly set, it's legacy
|
||||
if any(
|
||||
x is not None
|
||||
for x in (num_partitions, num_sub_vectors, accelerator, index_cache_size)
|
||||
):
|
||||
return True
|
||||
|
||||
# If vector_column_name differs from default, it's legacy
|
||||
if vector_column_name != VECTOR_COLUMN_NAME:
|
||||
return True
|
||||
|
||||
# If first arg is a known metric, assume legacy
|
||||
if first_arg.lower() in KNOWN_METRICS:
|
||||
return True
|
||||
|
||||
# Otherwise assume new API
|
||||
return False
|
||||
|
||||
def _build_vector_config_from_legacy_params(
|
||||
self,
|
||||
metric: str,
|
||||
index_type: str,
|
||||
num_partitions: Optional[int],
|
||||
num_sub_vectors: Optional[int],
|
||||
num_bits: int,
|
||||
max_iterations: int,
|
||||
sample_rate: int,
|
||||
m: int,
|
||||
ef_construction: int,
|
||||
target_partition_size: Optional[int],
|
||||
accelerator: Optional[str],
|
||||
) -> IndexConfigType:
|
||||
"""Build an index config object from legacy parameters."""
|
||||
if index_type == "IVF_FLAT":
|
||||
return IvfFlat(
|
||||
self.checkout_latest()
|
||||
return
|
||||
elif index_type == "IVF_FLAT":
|
||||
config = IvfFlat(
|
||||
distance_type=metric,
|
||||
num_partitions=num_partitions,
|
||||
max_iterations=max_iterations,
|
||||
sample_rate=sample_rate,
|
||||
target_partition_size=target_partition_size,
|
||||
accelerator=accelerator,
|
||||
)
|
||||
elif index_type == "IVF_SQ":
|
||||
return IvfSq(
|
||||
config = IvfSq(
|
||||
distance_type=metric,
|
||||
num_partitions=num_partitions,
|
||||
max_iterations=max_iterations,
|
||||
sample_rate=sample_rate,
|
||||
target_partition_size=target_partition_size,
|
||||
accelerator=accelerator,
|
||||
)
|
||||
elif index_type == "IVF_PQ":
|
||||
return IvfPq(
|
||||
config = IvfPq(
|
||||
distance_type=metric,
|
||||
num_partitions=num_partitions,
|
||||
num_sub_vectors=num_sub_vectors,
|
||||
@@ -2680,20 +2322,18 @@ class LanceTable(Table):
|
||||
max_iterations=max_iterations,
|
||||
sample_rate=sample_rate,
|
||||
target_partition_size=target_partition_size,
|
||||
accelerator=accelerator,
|
||||
)
|
||||
elif index_type == "IVF_RQ":
|
||||
return IvfRq(
|
||||
config = IvfRq(
|
||||
distance_type=metric,
|
||||
num_partitions=num_partitions,
|
||||
num_bits=num_bits,
|
||||
max_iterations=max_iterations,
|
||||
sample_rate=sample_rate,
|
||||
target_partition_size=target_partition_size,
|
||||
accelerator=accelerator,
|
||||
)
|
||||
elif index_type == "IVF_HNSW_PQ":
|
||||
return HnswPq(
|
||||
config = HnswPq(
|
||||
distance_type=metric,
|
||||
num_partitions=num_partitions,
|
||||
num_sub_vectors=num_sub_vectors,
|
||||
@@ -2703,10 +2343,9 @@ class LanceTable(Table):
|
||||
m=m,
|
||||
ef_construction=ef_construction,
|
||||
target_partition_size=target_partition_size,
|
||||
accelerator=accelerator,
|
||||
)
|
||||
elif index_type == "IVF_HNSW_SQ":
|
||||
return HnswSq(
|
||||
config = HnswSq(
|
||||
distance_type=metric,
|
||||
num_partitions=num_partitions,
|
||||
max_iterations=max_iterations,
|
||||
@@ -2714,10 +2353,9 @@ class LanceTable(Table):
|
||||
m=m,
|
||||
ef_construction=ef_construction,
|
||||
target_partition_size=target_partition_size,
|
||||
accelerator=accelerator,
|
||||
)
|
||||
elif index_type == "IVF_HNSW_FLAT":
|
||||
return HnswFlat(
|
||||
config = HnswFlat(
|
||||
distance_type=metric,
|
||||
num_partitions=num_partitions,
|
||||
max_iterations=max_iterations,
|
||||
@@ -2729,6 +2367,16 @@ class LanceTable(Table):
|
||||
else:
|
||||
raise ValueError(f"Unknown index type {index_type}")
|
||||
|
||||
return LOOP.run(
|
||||
self._table.create_index(
|
||||
vector_column_name,
|
||||
replace=replace,
|
||||
config=config,
|
||||
name=name,
|
||||
train=train,
|
||||
)
|
||||
)
|
||||
|
||||
def drop_index(self, name: str) -> None:
|
||||
"""
|
||||
Drops an index from the table
|
||||
@@ -2828,11 +2476,6 @@ class LanceTable(Table):
|
||||
"""
|
||||
return LOOP.run(self._table.latest_storage_options())
|
||||
|
||||
@deprecation.deprecated(
|
||||
deprecated_in="0.25.0",
|
||||
current_version=__version__,
|
||||
details="Use create_index() with config=BTree()/Bitmap()/LabelList() instead.",
|
||||
)
|
||||
def create_scalar_index(
|
||||
self,
|
||||
column: str,
|
||||
@@ -2841,12 +2484,6 @@ class LanceTable(Table):
|
||||
index_type: ScalarIndexType = "BTREE",
|
||||
name: Optional[str] = None,
|
||||
):
|
||||
"""Create a scalar index on a column.
|
||||
|
||||
.. deprecated:: 0.25.0
|
||||
Use :meth:`create_index` with a BTree, Bitmap, or LabelList config instead.
|
||||
Example: ``table.create_index("column", config=BTree())``
|
||||
"""
|
||||
if index_type == "BTREE":
|
||||
config = BTree()
|
||||
elif index_type == "BITMAP":
|
||||
@@ -2859,11 +2496,6 @@ class LanceTable(Table):
|
||||
self._table.create_index(column, replace=replace, config=config, name=name)
|
||||
)
|
||||
|
||||
@deprecation.deprecated(
|
||||
deprecated_in="0.25.0",
|
||||
current_version=__version__,
|
||||
details="Use create_index() with config=FTS() instead.",
|
||||
)
|
||||
def create_fts_index(
|
||||
self,
|
||||
field_names: Union[str, List[str]],
|
||||
@@ -2887,12 +2519,6 @@ class LanceTable(Table):
|
||||
prefix_only: bool = False,
|
||||
name: Optional[str] = None,
|
||||
):
|
||||
"""Create a full-text search index on a column.
|
||||
|
||||
.. deprecated:: 0.25.0
|
||||
Use :meth:`create_index` with an FTS config instead.
|
||||
Example: ``table.create_index("text_column", config=FTS())``
|
||||
"""
|
||||
self._ensure_no_legacy_fts_index()
|
||||
|
||||
if use_tantivy:
|
||||
@@ -3364,7 +2990,6 @@ class LanceTable(Table):
|
||||
self._location = location
|
||||
self._namespace_client = namespace_client
|
||||
self._pushdown_operations = pushdown_operations or set()
|
||||
self._init_reopen_tracking()
|
||||
|
||||
if data_storage_version is not None:
|
||||
warnings.warn(
|
||||
@@ -3672,11 +3297,6 @@ class LanceTable(Table):
|
||||
[`AsyncTable.unset_lsm_write_spec`][lancedb.AsyncTable.unset_lsm_write_spec]."""
|
||||
return LOOP.run(self._table.unset_lsm_write_spec())
|
||||
|
||||
def close_lsm_writers(self) -> None:
|
||||
"""Close cached MemWAL shard writers. See
|
||||
[`AsyncTable.close_lsm_writers`][lancedb.AsyncTable.close_lsm_writers]."""
|
||||
return LOOP.run(self._table.close_lsm_writers())
|
||||
|
||||
def uses_v2_manifest_paths(self) -> bool:
|
||||
"""
|
||||
Check if the table is using the new v2 manifest paths.
|
||||
@@ -4285,16 +3905,6 @@ class AsyncTable:
|
||||
"""
|
||||
await self._inner.unset_lsm_write_spec()
|
||||
|
||||
async def close_lsm_writers(self) -> None:
|
||||
"""Drain and close any cached MemWAL shard writers for this table.
|
||||
|
||||
When an LSM write spec is installed, `merge_insert` opens MemWAL shard
|
||||
writers and caches them for reuse across calls. This closes them,
|
||||
flushing pending data; writers reopen lazily on the next
|
||||
`merge_insert`. It is a no-op when no writers are cached.
|
||||
"""
|
||||
await self._inner.close_lsm_writers()
|
||||
|
||||
@property
|
||||
def name(self) -> str:
|
||||
"""The name of the table."""
|
||||
@@ -4622,10 +4232,6 @@ class AsyncTable:
|
||||
"""
|
||||
return await self._inner.latest_storage_options()
|
||||
|
||||
async def _table_reopen_state(self) -> dict[str, Any]:
|
||||
"""Get the Rust-side table state needed to reopen this table."""
|
||||
return await self._inner._table_reopen_state()
|
||||
|
||||
async def add(
|
||||
self,
|
||||
data: DATA,
|
||||
@@ -4749,7 +4355,7 @@ class AsyncTable:
|
||||
... .when_not_matched_insert_all() \\
|
||||
... .execute(new_data)
|
||||
>>> res
|
||||
MergeResult(version=2, num_updated_rows=2, num_inserted_rows=1, num_deleted_rows=0, num_attempts=1, num_rows=3)
|
||||
MergeResult(version=2, num_updated_rows=2, num_inserted_rows=1, num_deleted_rows=0, num_attempts=1)
|
||||
>>> # The order of new rows is non-deterministic since we use
|
||||
>>> # a hash-join as part of this operation and so we sort here
|
||||
>>> table.to_arrow().sort_by("a").to_pandas()
|
||||
@@ -5129,8 +4735,6 @@ class AsyncTable:
|
||||
when_not_matched_by_source_condition=merge._when_not_matched_by_source_condition,
|
||||
timeout=merge._timeout,
|
||||
use_index=merge._use_index,
|
||||
use_lsm_write=merge._use_lsm_write,
|
||||
validate_single_shard=merge._validate_single_shard,
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
@@ -57,7 +57,7 @@ async def test_upsert_async(mem_db_async):
|
||||
await table.count_rows() # 3
|
||||
res
|
||||
# MergeResult(version=2, num_updated_rows=1,
|
||||
# num_inserted_rows=1, num_deleted_rows=0, num_rows=2)
|
||||
# num_inserted_rows=1, num_deleted_rows=0)
|
||||
# --8<-- [end:upsert_basic_async]
|
||||
assert await table.count_rows() == 3
|
||||
assert res.version == 2
|
||||
@@ -86,7 +86,7 @@ def test_insert_if_not_exists(mem_db):
|
||||
table.count_rows() # 3
|
||||
res
|
||||
# MergeResult(version=2, num_updated_rows=0,
|
||||
# num_inserted_rows=1, num_deleted_rows=0, num_rows=1)
|
||||
# num_inserted_rows=1, num_deleted_rows=0)
|
||||
# --8<-- [end:insert_if_not_exists]
|
||||
assert table.count_rows() == 3
|
||||
assert res.version == 2
|
||||
@@ -116,7 +116,7 @@ async def test_insert_if_not_exists_async(mem_db_async):
|
||||
await table.count_rows() # 3
|
||||
res
|
||||
# MergeResult(version=2, num_updated_rows=0,
|
||||
# num_inserted_rows=1, num_deleted_rows=0, num_rows=1)
|
||||
# num_inserted_rows=1, num_deleted_rows=0)
|
||||
# --8<-- [end:insert_if_not_exists]
|
||||
assert await table.count_rows() == 3
|
||||
assert res.version == 2
|
||||
@@ -150,7 +150,7 @@ def test_replace_range(mem_db):
|
||||
table.count_rows("doc_id = 1") # 1
|
||||
res
|
||||
# MergeResult(version=2, num_updated_rows=1,
|
||||
# num_inserted_rows=0, num_deleted_rows=1, num_rows=1)
|
||||
# num_inserted_rows=0, num_deleted_rows=1)
|
||||
# --8<-- [end:insert_if_not_exists]
|
||||
assert table.count_rows("doc_id = 1") == 1
|
||||
assert res.version == 2
|
||||
@@ -185,7 +185,7 @@ async def test_replace_range_async(mem_db_async):
|
||||
await table.count_rows("doc_id = 1") # 1
|
||||
res
|
||||
# MergeResult(version=2, num_updated_rows=1,
|
||||
# num_inserted_rows=0, num_deleted_rows=1, num_rows=1)
|
||||
# num_inserted_rows=0, num_deleted_rows=1)
|
||||
# --8<-- [end:insert_if_not_exists]
|
||||
assert await table.count_rows("doc_id = 1") == 1
|
||||
assert res.version == 2
|
||||
|
||||
@@ -466,8 +466,7 @@ async def test_create_table_v2_manifest_paths_async(tmp_path):
|
||||
assert await tbl.uses_v2_manifest_paths()
|
||||
manifests_dir = tmp_path / "test_v2_manifest_paths.lance" / "_versions"
|
||||
for manifest in os.listdir(manifests_dir):
|
||||
if manifest.endswith(".manifest"):
|
||||
assert re.match(r"\d{20}\.manifest", manifest)
|
||||
assert re.match(r"\d{20}\.manifest", manifest)
|
||||
|
||||
# Start a table in V1 mode then migrate
|
||||
tbl = await db_no_v2_paths.create_table(
|
||||
@@ -477,15 +476,13 @@ async def test_create_table_v2_manifest_paths_async(tmp_path):
|
||||
assert not await tbl.uses_v2_manifest_paths()
|
||||
manifests_dir = tmp_path / "test_v2_migration.lance" / "_versions"
|
||||
for manifest in os.listdir(manifests_dir):
|
||||
if manifest.endswith(".manifest"):
|
||||
assert re.match(r"\d\.manifest", manifest)
|
||||
assert re.match(r"\d\.manifest", manifest)
|
||||
|
||||
await tbl.migrate_manifest_paths_v2()
|
||||
assert await tbl.uses_v2_manifest_paths()
|
||||
|
||||
for manifest in os.listdir(manifests_dir):
|
||||
if manifest.endswith(".manifest"):
|
||||
assert re.match(r"\d{20}\.manifest", manifest)
|
||||
assert re.match(r"\d{20}\.manifest", manifest)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
|
||||
@@ -215,12 +215,11 @@ def test_reject_legacy_tantivy_index(table):
|
||||
|
||||
@pytest.mark.parametrize("with_position", [True, False])
|
||||
def test_create_inverted_index(table, with_position):
|
||||
with pytest.warns(DeprecationWarning, match="create_fts_index"):
|
||||
table.create_fts_index(
|
||||
"text",
|
||||
with_position=with_position,
|
||||
name="custom_fts_index",
|
||||
)
|
||||
table.create_fts_index(
|
||||
"text",
|
||||
with_position=with_position,
|
||||
name="custom_fts_index",
|
||||
)
|
||||
indices = table.list_indices()
|
||||
fts_indices = [i for i in indices if i.index_type == "FTS"]
|
||||
assert any(i.name == "custom_fts_index" for i in fts_indices)
|
||||
|
||||
@@ -162,13 +162,12 @@ async def test_create_bitmap_index(some_table: AsyncTable):
|
||||
await some_table.create_index("data", config=Bitmap())
|
||||
indices = await some_table.list_indices()
|
||||
assert len(indices) == 3
|
||||
# list_indices returns indices in alphabetical order by name
|
||||
assert indices[0].index_type == "Bitmap"
|
||||
assert indices[0].columns == ["data"]
|
||||
assert indices[0].columns == ["id"]
|
||||
assert indices[1].index_type == "Bitmap"
|
||||
assert indices[1].columns == ["id"]
|
||||
assert indices[1].columns == ["is_active"]
|
||||
assert indices[2].index_type == "Bitmap"
|
||||
assert indices[2].columns == ["is_active"]
|
||||
assert indices[2].columns == ["data"]
|
||||
|
||||
index_name = indices[0].name
|
||||
stats = await some_table.index_stats(index_name)
|
||||
|
||||
@@ -40,6 +40,16 @@ def _make_table(tmp_path):
|
||||
def test_set_lsm_write_spec_validates(tmp_path):
|
||||
_db, table = _make_table(tmp_path)
|
||||
|
||||
# No PK set yet.
|
||||
with pytest.raises(Exception, match="primary key"):
|
||||
table.set_lsm_write_spec(LsmWriteSpec.bucket("id", 4))
|
||||
|
||||
table.set_unenforced_primary_key("id")
|
||||
|
||||
# Column mismatch.
|
||||
with pytest.raises(Exception, match="match"):
|
||||
table.set_lsm_write_spec(LsmWriteSpec.bucket("v", 4))
|
||||
|
||||
# Out-of-range num_buckets.
|
||||
with pytest.raises(Exception, match="num_buckets"):
|
||||
table.set_lsm_write_spec(LsmWriteSpec.bucket("id", 0))
|
||||
@@ -60,6 +70,7 @@ def test_unset_lsm_write_spec(tmp_path):
|
||||
table.unset_lsm_write_spec()
|
||||
|
||||
# Install a spec, then remove it; afterwards a fresh spec can be set.
|
||||
table.set_unenforced_primary_key("id")
|
||||
table.set_lsm_write_spec(LsmWriteSpec.bucket("id", 4))
|
||||
table.unset_lsm_write_spec()
|
||||
# A second unset errors — there is no spec left to remove.
|
||||
|
||||
@@ -1,196 +0,0 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
"""Tests for the MemWAL LSM ``merge_insert`` dispatch."""
|
||||
|
||||
from datetime import timedelta
|
||||
|
||||
import lancedb
|
||||
import pyarrow as pa
|
||||
import pytest
|
||||
from lancedb._lancedb import LsmWriteSpec
|
||||
|
||||
SCHEMA = pa.schema(
|
||||
[
|
||||
pa.field("id", pa.int64(), nullable=False),
|
||||
pa.field("value", pa.int64(), nullable=False),
|
||||
]
|
||||
)
|
||||
|
||||
REGION_SCHEMA = pa.schema(
|
||||
[
|
||||
pa.field("id", pa.int64(), nullable=False),
|
||||
pa.field("region", pa.utf8(), nullable=False),
|
||||
]
|
||||
)
|
||||
|
||||
|
||||
def _reader(ids):
|
||||
batch = pa.RecordBatch.from_arrays(
|
||||
[
|
||||
pa.array(ids, type=pa.int64()),
|
||||
pa.array(list(range(len(ids))), type=pa.int64()),
|
||||
],
|
||||
schema=SCHEMA,
|
||||
)
|
||||
return pa.RecordBatchReader.from_batches(SCHEMA, [batch])
|
||||
|
||||
|
||||
def _region_reader(rows):
|
||||
batch = pa.RecordBatch.from_arrays(
|
||||
[
|
||||
pa.array([row[0] for row in rows], type=pa.int64()),
|
||||
pa.array([row[1] for row in rows], type=pa.utf8()),
|
||||
],
|
||||
schema=REGION_SCHEMA,
|
||||
)
|
||||
return pa.RecordBatchReader.from_batches(REGION_SCHEMA, [batch])
|
||||
|
||||
|
||||
def _bucket_table(tmp_path):
|
||||
"""A table with ``id`` as the primary key and a single-bucket LSM spec."""
|
||||
db = lancedb.connect(tmp_path, read_consistency_interval=timedelta(seconds=0))
|
||||
table = db.create_table("t", _reader([1, 2, 3]))
|
||||
table.set_unenforced_primary_key("id")
|
||||
# num_buckets = 1: every row routes to the single bucket.
|
||||
table.set_lsm_write_spec(LsmWriteSpec.bucket("id", 1))
|
||||
return table
|
||||
|
||||
|
||||
def test_lsm_merge_insert_bucket(tmp_path):
|
||||
table = _bucket_table(tmp_path)
|
||||
# Empty `on` defaults to the primary key.
|
||||
result = (
|
||||
table.merge_insert([])
|
||||
.when_matched_update_all()
|
||||
.when_not_matched_insert_all()
|
||||
.execute(_reader([3, 4, 5]))
|
||||
)
|
||||
# LSM path: rows go to the MemWAL, so only num_rows is populated.
|
||||
assert result.num_rows == 3
|
||||
assert result.version == 0
|
||||
assert result.num_inserted_rows == 0
|
||||
assert result.num_updated_rows == 0
|
||||
|
||||
|
||||
def test_lsm_merge_insert_unsharded(tmp_path):
|
||||
db = lancedb.connect(tmp_path, read_consistency_interval=timedelta(seconds=0))
|
||||
table = db.create_table("t", _reader([1, 2, 3]))
|
||||
table.set_unenforced_primary_key("id")
|
||||
table.set_lsm_write_spec(LsmWriteSpec.unsharded())
|
||||
result = (
|
||||
table.merge_insert("id")
|
||||
.when_matched_update_all()
|
||||
.when_not_matched_insert_all()
|
||||
.execute(_reader([10, 11, 12, 13]))
|
||||
)
|
||||
assert result.num_rows == 4
|
||||
|
||||
|
||||
def test_lsm_merge_insert_identity(tmp_path):
|
||||
db = lancedb.connect(tmp_path, read_consistency_interval=timedelta(seconds=0))
|
||||
table = db.create_table("t", _region_reader([(1, "us"), (2, "us")]))
|
||||
table.set_unenforced_primary_key("id")
|
||||
table.set_lsm_write_spec(LsmWriteSpec.identity("region"))
|
||||
# All rows share one identity value, so they route to one shard.
|
||||
result = (
|
||||
table.merge_insert([])
|
||||
.when_matched_update_all()
|
||||
.when_not_matched_insert_all()
|
||||
.execute(_region_reader([(3, "us"), (4, "us")]))
|
||||
)
|
||||
assert result.num_rows == 2
|
||||
|
||||
|
||||
def test_lsm_merge_insert_use_lsm_write_false(tmp_path):
|
||||
table = _bucket_table(tmp_path) # rows id = 1, 2, 3
|
||||
# use_lsm_write(False) opts out: the standard path runs and commits.
|
||||
result = (
|
||||
table.merge_insert("id")
|
||||
.when_not_matched_insert_all()
|
||||
.use_lsm_write(False)
|
||||
.execute(_reader([3, 4, 5]))
|
||||
)
|
||||
assert result.num_inserted_rows == 2
|
||||
assert table.count_rows() == 5
|
||||
|
||||
|
||||
def test_lsm_merge_insert_validate_single_shard_off(tmp_path):
|
||||
table = _bucket_table(tmp_path)
|
||||
result = (
|
||||
table.merge_insert([])
|
||||
.when_matched_update_all()
|
||||
.when_not_matched_insert_all()
|
||||
.validate_single_shard(False)
|
||||
.execute(_reader([6, 7, 8]))
|
||||
)
|
||||
assert result.num_rows == 3
|
||||
|
||||
|
||||
def test_lsm_merge_insert_use_lsm_write_true_requires_spec(tmp_path):
|
||||
# A table with a primary key but no LSM write spec installed.
|
||||
db = lancedb.connect(tmp_path, read_consistency_interval=timedelta(seconds=0))
|
||||
table = db.create_table("t", _reader([1, 2, 3]))
|
||||
table.set_unenforced_primary_key("id")
|
||||
with pytest.raises(Exception, match="use_lsm_write"):
|
||||
(
|
||||
table.merge_insert("id")
|
||||
.when_matched_update_all()
|
||||
.when_not_matched_insert_all()
|
||||
.use_lsm_write(True)
|
||||
.execute(_reader([4]))
|
||||
)
|
||||
|
||||
|
||||
def test_lsm_merge_insert_rejects_on_not_primary_key(tmp_path):
|
||||
table = _bucket_table(tmp_path)
|
||||
with pytest.raises(Exception, match="primary key"):
|
||||
(
|
||||
table.merge_insert("value")
|
||||
.when_matched_update_all()
|
||||
.when_not_matched_insert_all()
|
||||
.execute(_reader([1]))
|
||||
)
|
||||
|
||||
|
||||
def test_lsm_merge_insert_rejects_non_upsert(tmp_path):
|
||||
table = _bucket_table(tmp_path)
|
||||
# Insert-only (no when_matched_update_all) is not the upsert shape.
|
||||
with pytest.raises(Exception, match="upsert"):
|
||||
table.merge_insert([]).when_not_matched_insert_all().execute(_reader([4]))
|
||||
|
||||
|
||||
def test_lsm_close_writers(tmp_path):
|
||||
table = _bucket_table(tmp_path)
|
||||
(
|
||||
table.merge_insert([])
|
||||
.when_matched_update_all()
|
||||
.when_not_matched_insert_all()
|
||||
.execute(_reader([7, 8]))
|
||||
)
|
||||
table.close_lsm_writers()
|
||||
# The writer reopens lazily on the next merge_insert.
|
||||
result = (
|
||||
table.merge_insert([])
|
||||
.when_matched_update_all()
|
||||
.when_not_matched_insert_all()
|
||||
.execute(_reader([9]))
|
||||
)
|
||||
assert result.num_rows == 1
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_async_lsm_merge_insert(tmp_path):
|
||||
db = await lancedb.connect_async(
|
||||
tmp_path, read_consistency_interval=timedelta(seconds=0)
|
||||
)
|
||||
table = await db.create_table("t", _reader([1, 2, 3]))
|
||||
await table.set_unenforced_primary_key("id")
|
||||
await table.set_lsm_write_spec(LsmWriteSpec.bucket("id", 1))
|
||||
|
||||
builder = (
|
||||
table.merge_insert([]).when_matched_update_all().when_not_matched_insert_all()
|
||||
)
|
||||
result = await builder.execute(_reader([3, 4, 5]))
|
||||
assert result.num_rows == 3
|
||||
await table.close_lsm_writers()
|
||||
@@ -1,13 +1,12 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
import re
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
import contextlib
|
||||
from datetime import timedelta
|
||||
import http.server
|
||||
import json
|
||||
import multiprocessing as mp
|
||||
import pickle
|
||||
import re
|
||||
import sys
|
||||
import threading
|
||||
import time
|
||||
@@ -172,196 +171,6 @@ def test_table_len_sync():
|
||||
assert len(table) == 1
|
||||
|
||||
|
||||
def test_remote_connection_serializes():
|
||||
def handler(request):
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
request.wfile.write(b'{"tables": []}')
|
||||
|
||||
with mock_lancedb_connection(handler) as db:
|
||||
serialized = json.loads(db.serialize())
|
||||
assert isinstance(serialized["client_config"], dict)
|
||||
restored = lancedb.deserialize_conn(db.serialize())
|
||||
assert restored.table_names() == []
|
||||
|
||||
|
||||
def test_remote_table_is_picklable():
|
||||
def handler(request):
|
||||
request.close_connection = True
|
||||
if request.path == "/v1/table/test/describe/":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
payload = json.dumps(
|
||||
{
|
||||
"version": 1,
|
||||
"schema": {
|
||||
"fields": [
|
||||
{"name": "id", "type": {"type": "int64"}, "nullable": False}
|
||||
]
|
||||
},
|
||||
}
|
||||
)
|
||||
request.wfile.write(payload.encode())
|
||||
elif request.path == "/v1/table/test/count_rows/":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
request.wfile.write(b"3")
|
||||
else:
|
||||
request.send_response(404)
|
||||
request.end_headers()
|
||||
|
||||
with mock_lancedb_connection(handler) as db:
|
||||
table = db.open_table("test")
|
||||
state = table.__getstate__()
|
||||
assert state["table_state"] == {
|
||||
"name": "test",
|
||||
"namespace_path": [],
|
||||
"storage_options": None,
|
||||
}
|
||||
restored = pickle.loads(pickle.dumps(table))
|
||||
assert restored.count_rows() == 3
|
||||
|
||||
|
||||
def test_remote_table_reopens_when_pid_changes_without_cached_state():
|
||||
def handler(request):
|
||||
request.close_connection = True
|
||||
if request.path == "/v1/table/test/describe/":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
payload = json.dumps(
|
||||
{
|
||||
"version": 1,
|
||||
"schema": {
|
||||
"fields": [
|
||||
{"name": "id", "type": {"type": "int64"}, "nullable": False}
|
||||
]
|
||||
},
|
||||
}
|
||||
)
|
||||
request.wfile.write(payload.encode())
|
||||
elif request.path == "/v1/table/test/count_rows/":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
request.wfile.write(b"3")
|
||||
else:
|
||||
request.send_response(404)
|
||||
request.end_headers()
|
||||
|
||||
with mock_lancedb_connection(handler) as db:
|
||||
table = db.open_table("test")
|
||||
table._pid = -1
|
||||
table._table_state = None
|
||||
|
||||
assert table.count_rows() == 3
|
||||
|
||||
|
||||
def test_remote_table_open_does_not_require_picklable_client_config():
|
||||
from lancedb.remote import HeaderProvider
|
||||
|
||||
class LocalHeaderProvider(HeaderProvider):
|
||||
def get_headers(self):
|
||||
return {"X-Test-Header": "present"}
|
||||
|
||||
def handler(request):
|
||||
request.close_connection = True
|
||||
assert request.headers.get("X-Test-Header") == "present"
|
||||
if request.path == "/v1/table/test/describe/":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
request.wfile.write(b'{"version": 1, "schema": {"fields": []}}')
|
||||
elif request.path == "/v1/table/test/count_rows/":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
request.wfile.write(b"3")
|
||||
else:
|
||||
request.send_response(404)
|
||||
request.end_headers()
|
||||
|
||||
with http.server.HTTPServer(
|
||||
("localhost", 0), make_mock_http_handler(handler)
|
||||
) as server:
|
||||
port = server.server_address[1]
|
||||
handle = threading.Thread(target=server.serve_forever)
|
||||
handle.start()
|
||||
try:
|
||||
db = lancedb.connect(
|
||||
"db://dev",
|
||||
api_key="fake",
|
||||
host_override=f"http://localhost:{port}",
|
||||
client_config={
|
||||
"retry_config": {"retries": 0},
|
||||
"timeout_config": {"connect_timeout": 2, "read_timeout": 2},
|
||||
"header_provider": LocalHeaderProvider(),
|
||||
},
|
||||
)
|
||||
table = db.open_table("test")
|
||||
assert table.count_rows() == 3
|
||||
with pytest.raises(ValueError, match="header_provider"):
|
||||
pickle.dumps(table)
|
||||
finally:
|
||||
server.shutdown()
|
||||
handle.join()
|
||||
|
||||
|
||||
def test_remote_permutation_is_picklable():
|
||||
from lancedb.permutation import Permutation
|
||||
|
||||
rows = list(range(10))
|
||||
|
||||
def handler(request):
|
||||
request.close_connection = True
|
||||
if request.path == "/v1/table/test/describe/":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
payload = json.dumps(
|
||||
{
|
||||
"version": 1,
|
||||
"schema": {
|
||||
"fields": [
|
||||
{"name": "a", "type": {"type": "int64"}, "nullable": False}
|
||||
]
|
||||
},
|
||||
}
|
||||
)
|
||||
request.wfile.write(payload.encode())
|
||||
elif request.path == "/v1/table/test/count_rows/":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
request.wfile.write(str(len(rows)).encode())
|
||||
elif request.path == "/v1/table/test/query/":
|
||||
content_len = int(request.headers.get("Content-Length"))
|
||||
body = json.loads(request.rfile.read(content_len))
|
||||
if "filter" in body:
|
||||
match = re.search(r"_rowoffset in \((.*?)\)", body["filter"])
|
||||
offsets = [int(offset.strip()) for offset in match.group(1).split(",")]
|
||||
else:
|
||||
offsets = rows
|
||||
table = pa.table({"a": [rows[offset] for offset in offsets]})
|
||||
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/vnd.apache.arrow.file")
|
||||
request.end_headers()
|
||||
with pa.ipc.new_file(request.wfile, schema=table.schema) as writer:
|
||||
writer.write_table(table)
|
||||
else:
|
||||
request.send_response(404)
|
||||
request.end_headers()
|
||||
|
||||
with mock_lancedb_connection(handler) as db:
|
||||
permutation = Permutation.identity(db.open_table("test"))
|
||||
restored = pickle.loads(pickle.dumps(permutation))
|
||||
assert restored.__getitems__([0, 2, 4]) == [{"a": 0}, {"a": 2}, {"a": 4}]
|
||||
|
||||
|
||||
def test_create_table_exist_ok():
|
||||
def handler(request):
|
||||
if request.path == "/v1/table/test/create/?mode=exist_ok":
|
||||
@@ -553,22 +362,6 @@ def test_table_create_indices():
|
||||
schema=dict(
|
||||
fields=[
|
||||
dict(name="id", type={"type": "int64"}, nullable=False),
|
||||
dict(name="text", type={"type": "string"}, nullable=False),
|
||||
dict(
|
||||
name="vector",
|
||||
type={
|
||||
"type": "fixed_size_list",
|
||||
"fields": [
|
||||
dict(
|
||||
name="item",
|
||||
type={"type": "float"},
|
||||
nullable=True,
|
||||
)
|
||||
],
|
||||
"length": 2,
|
||||
},
|
||||
nullable=False,
|
||||
),
|
||||
]
|
||||
),
|
||||
)
|
||||
@@ -627,25 +420,22 @@ def test_table_create_indices():
|
||||
# This is a smoke-test.
|
||||
table = db.create_table("test", [{"id": 1}])
|
||||
|
||||
# Test create_scalar_index with custom name (legacy method)
|
||||
with pytest.warns(DeprecationWarning, match="create_scalar_index"):
|
||||
table.create_scalar_index(
|
||||
"id", wait_timeout=timedelta(seconds=2), name="custom_scalar_idx"
|
||||
)
|
||||
# Test create_scalar_index with custom name
|
||||
table.create_scalar_index(
|
||||
"id", wait_timeout=timedelta(seconds=2), name="custom_scalar_idx"
|
||||
)
|
||||
|
||||
# Test create_fts_index with custom name (legacy method)
|
||||
with pytest.warns(DeprecationWarning, match="create_fts_index"):
|
||||
table.create_fts_index(
|
||||
"text", wait_timeout=timedelta(seconds=2), name="custom_fts_idx"
|
||||
)
|
||||
# Test create_fts_index with custom name
|
||||
table.create_fts_index(
|
||||
"text", wait_timeout=timedelta(seconds=2), name="custom_fts_idx"
|
||||
)
|
||||
|
||||
# Test create_index with custom name (legacy form: vector_column_name kwarg)
|
||||
with pytest.warns(DeprecationWarning, match="create_index"):
|
||||
table.create_index(
|
||||
vector_column_name="vector",
|
||||
wait_timeout=timedelta(seconds=10),
|
||||
name="custom_vector_idx",
|
||||
)
|
||||
# Test create_index with custom name
|
||||
table.create_index(
|
||||
vector_column_name="vector",
|
||||
wait_timeout=timedelta(seconds=10),
|
||||
name="custom_vector_idx",
|
||||
)
|
||||
|
||||
# Validate that the name parameter was passed correctly in requests
|
||||
assert len(received_requests) == 3
|
||||
@@ -674,98 +464,6 @@ def test_table_create_indices():
|
||||
table.drop_index("custom_fts_idx")
|
||||
|
||||
|
||||
def test_remote_create_index_new_api():
|
||||
received_requests = []
|
||||
|
||||
def handler(request):
|
||||
if request.path == "/v1/table/test/create_index/":
|
||||
content_len = int(request.headers.get("Content-Length", 0))
|
||||
body = request.rfile.read(content_len) if content_len > 0 else b""
|
||||
received_requests.append(json.loads(body) if body else {})
|
||||
request.send_response(200)
|
||||
request.end_headers()
|
||||
elif request.path == "/v1/table/test/create/?mode=create":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
request.wfile.write(b"{}")
|
||||
elif request.path == "/v1/table/test/describe/":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
request.wfile.write(
|
||||
json.dumps(
|
||||
dict(
|
||||
version=1,
|
||||
schema=dict(
|
||||
fields=[
|
||||
dict(name="id", type={"type": "int64"}, nullable=False),
|
||||
dict(
|
||||
name="category",
|
||||
type={"type": "string"},
|
||||
nullable=False,
|
||||
),
|
||||
dict(
|
||||
name="text", type={"type": "string"}, nullable=False
|
||||
),
|
||||
dict(
|
||||
name="vector",
|
||||
type={
|
||||
"type": "fixed_size_list",
|
||||
"fields": [
|
||||
dict(
|
||||
name="item",
|
||||
type={"type": "float"},
|
||||
nullable=True,
|
||||
)
|
||||
],
|
||||
"length": 2,
|
||||
},
|
||||
nullable=False,
|
||||
),
|
||||
]
|
||||
),
|
||||
)
|
||||
).encode()
|
||||
)
|
||||
else:
|
||||
request.send_response(404)
|
||||
request.end_headers()
|
||||
|
||||
from lancedb.index import BTree, FTS, IvfPq, IvfRq
|
||||
|
||||
with mock_lancedb_connection(handler) as db:
|
||||
table = db.create_table("test", [{"id": 1}])
|
||||
|
||||
# New API: column-first, config= kwarg. Should NOT emit DeprecationWarning.
|
||||
import warnings as _warnings
|
||||
|
||||
with _warnings.catch_warnings():
|
||||
_warnings.simplefilter("error", DeprecationWarning)
|
||||
table.create_index("vector", config=IvfPq(distance_type="l2"))
|
||||
table.create_index("category", config=BTree())
|
||||
table.create_index("text", config=FTS())
|
||||
# IvfRq via new API
|
||||
table.create_index("vector", config=IvfRq(distance_type="l2"))
|
||||
|
||||
# Legacy index_type="IVF_RQ" routes to IvfRq config under the hood.
|
||||
with pytest.warns(DeprecationWarning, match="create_index"):
|
||||
table.create_index(
|
||||
vector_column_name="vector",
|
||||
index_type="IVF_RQ",
|
||||
num_partitions=8,
|
||||
)
|
||||
|
||||
assert len(received_requests) == 5
|
||||
assert [req["column"] for req in received_requests] == [
|
||||
"vector",
|
||||
"category",
|
||||
"text",
|
||||
"vector",
|
||||
"vector",
|
||||
]
|
||||
|
||||
|
||||
def test_table_wait_for_index_timeout():
|
||||
def handler(request):
|
||||
index_stats = dict(
|
||||
@@ -1591,10 +1289,6 @@ def _remote_fork_child(port: int, queue) -> None:
|
||||
queue.put(db.table_names())
|
||||
|
||||
|
||||
def _remote_table_fork_child(table, queue) -> None:
|
||||
queue.put(table.count_rows())
|
||||
|
||||
|
||||
@pytest.mark.skipif(
|
||||
sys.platform != "linux",
|
||||
reason=(
|
||||
@@ -1657,65 +1351,3 @@ def test_remote_connection_after_fork():
|
||||
finally:
|
||||
server.shutdown()
|
||||
server_thread.join()
|
||||
|
||||
|
||||
@pytest.mark.skipif(
|
||||
sys.platform != "linux",
|
||||
reason=(
|
||||
"fork() is unavailable on Windows and unsafe on macOS "
|
||||
"(Apple frameworks/TLS are not fork-safe)"
|
||||
),
|
||||
)
|
||||
def test_inherited_remote_table_reopens_after_fork():
|
||||
def handler(request):
|
||||
if request.path == "/v1/table/test/describe/":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
request.wfile.write(b'{"version": 1, "schema": {"fields": []}}')
|
||||
elif request.path == "/v1/table/test/count_rows/":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
request.wfile.write(b"7")
|
||||
else:
|
||||
request.send_response(404)
|
||||
request.end_headers()
|
||||
|
||||
server = http.server.HTTPServer(("localhost", 0), make_mock_http_handler(handler))
|
||||
port = server.server_address[1]
|
||||
server_thread = threading.Thread(target=server.serve_forever)
|
||||
server_thread.start()
|
||||
try:
|
||||
db = lancedb.connect(
|
||||
"db://dev",
|
||||
api_key="fake",
|
||||
host_override=f"http://localhost:{port}",
|
||||
client_config={
|
||||
"retry_config": {"retries": 0},
|
||||
"timeout_config": {"connect_timeout": 2, "read_timeout": 2},
|
||||
},
|
||||
)
|
||||
table = db.open_table("test")
|
||||
assert table.count_rows() == 7
|
||||
|
||||
ctx = mp.get_context("fork")
|
||||
queue = ctx.Queue()
|
||||
proc = ctx.Process(target=_remote_table_fork_child, args=(table, queue))
|
||||
proc.start()
|
||||
proc.join(timeout=15)
|
||||
|
||||
if proc.is_alive():
|
||||
proc.terminate()
|
||||
proc.join(timeout=5)
|
||||
if proc.is_alive():
|
||||
proc.kill()
|
||||
proc.join()
|
||||
pytest.fail("Remote table hung after fork")
|
||||
|
||||
assert proc.exitcode == 0, f"child exited with code {proc.exitcode}"
|
||||
assert not queue.empty(), "child produced no result"
|
||||
assert queue.get() == 7
|
||||
finally:
|
||||
server.shutdown()
|
||||
server_thread.join()
|
||||
|
||||
@@ -603,89 +603,3 @@ def test_cross_encoder_reranker_return_all(tmp_path):
|
||||
assert "_relevance_score" in result.column_names
|
||||
assert "_score" in result.column_names
|
||||
assert "_distance" in result.column_names
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Regression tests for LinearCombinationReranker scoring bugs (issue #3154)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def test_linear_combination_best_match_ranks_first():
|
||||
"""
|
||||
The document that is BOTH the closest vector match AND the only FTS match
|
||||
must rank first. Previously _combine_score subtracted from 1, inverting
|
||||
the ranking so the worst document ranked highest.
|
||||
"""
|
||||
reranker = LinearCombinationReranker(weight=0.7, return_score="all")
|
||||
|
||||
# rowid 0: perfect vector match, sole FTS match → should rank 1st
|
||||
# rowid 1: mediocre vector, no FTS match
|
||||
# rowid 2: bad vector, no FTS match
|
||||
vector_results = pa.Table.from_pydict(
|
||||
{
|
||||
"_rowid": [0, 1, 2],
|
||||
"_distance": [0.0, 0.5, 0.9],
|
||||
}
|
||||
)
|
||||
fts_results = pa.Table.from_pydict(
|
||||
{
|
||||
"_rowid": [0],
|
||||
"_score": [1.0],
|
||||
}
|
||||
)
|
||||
|
||||
combined = reranker.merge_results(vector_results, fts_results, fill=1.0)
|
||||
scores = dict(
|
||||
zip(
|
||||
combined["_rowid"].to_pylist(),
|
||||
combined["_relevance_score"].to_pylist(),
|
||||
)
|
||||
)
|
||||
|
||||
# rowid 0 must have the highest relevance score
|
||||
assert scores[0] > scores[1], (
|
||||
f"Best match (rowid 0, score={scores[0]:.4f}) should beat "
|
||||
f"mid match (rowid 1, score={scores[1]:.4f})"
|
||||
)
|
||||
assert scores[1] > scores[2], (
|
||||
f"Mid match (rowid 1, score={scores[1]:.4f}) should beat "
|
||||
f"bad match (rowid 2, score={scores[2]:.4f})"
|
||||
)
|
||||
|
||||
|
||||
def test_linear_combination_missing_fts_is_penalised():
|
||||
"""
|
||||
A document with no FTS match must score *lower* than a document that
|
||||
has a mediocre FTS match, everything else being equal. Previously
|
||||
missing-FTS entries used fill=1.0 directly, which gave them a reward
|
||||
(via the 1-(...) inversion) instead of a penalty.
|
||||
"""
|
||||
reranker = LinearCombinationReranker(weight=0.5, return_score="all")
|
||||
|
||||
vector_results = pa.Table.from_pydict(
|
||||
{
|
||||
"_rowid": [0, 1],
|
||||
"_distance": [0.2, 0.2], # identical vector scores
|
||||
}
|
||||
)
|
||||
fts_results = pa.Table.from_pydict(
|
||||
{
|
||||
"_rowid": [0], # rowid 1 has no FTS match
|
||||
"_score": [0.3], # small FTS score
|
||||
}
|
||||
)
|
||||
|
||||
combined = reranker.merge_results(vector_results, fts_results, fill=1.0)
|
||||
scores = dict(
|
||||
zip(
|
||||
combined["_rowid"].to_pylist(),
|
||||
combined["_relevance_score"].to_pylist(),
|
||||
)
|
||||
)
|
||||
|
||||
# rowid 0 has a small FTS score; rowid 1 has none.
|
||||
# Even a small FTS contribution should beat having none at all.
|
||||
assert scores[0] > scores[1], (
|
||||
f"Document with FTS score (rowid 0, {scores[0]:.4f}) should beat "
|
||||
f"document with no FTS match (rowid 1, {scores[1]:.4f})"
|
||||
)
|
||||
|
||||
@@ -3,9 +3,7 @@
|
||||
|
||||
|
||||
import os
|
||||
import pickle
|
||||
import sys
|
||||
import warnings
|
||||
from datetime import date, datetime, timedelta
|
||||
from time import sleep
|
||||
from typing import List
|
||||
@@ -13,7 +11,7 @@ from unittest.mock import patch
|
||||
|
||||
import lancedb
|
||||
from lancedb.dependencies import _PANDAS_AVAILABLE
|
||||
from lancedb.index import BTree, FTS, HnswFlat, HnswPq, HnswSq, IvfPq
|
||||
from lancedb.index import HnswFlat, HnswPq, HnswSq, IvfPq
|
||||
import numpy as np
|
||||
import polars as pl
|
||||
import pyarrow as pa
|
||||
@@ -49,36 +47,6 @@ def test_basic(mem_db: DBConnection):
|
||||
assert table.to_arrow() == expected_data
|
||||
|
||||
|
||||
def test_lance_table_is_picklable(tmp_db: DBConnection):
|
||||
table = tmp_db.create_table("pickle_table", pa.table({"id": [1, 2, 3]}))
|
||||
|
||||
restored = pickle.loads(pickle.dumps(table))
|
||||
|
||||
assert restored.name == "pickle_table"
|
||||
assert restored.count_rows() == 3
|
||||
assert restored.to_arrow().column("id").to_pylist() == [1, 2, 3]
|
||||
|
||||
|
||||
def test_lance_table_pickle_preserves_checkout(tmp_db: DBConnection):
|
||||
table = tmp_db.create_table("pickle_checkout", pa.table({"id": [1]}))
|
||||
table.add(pa.table({"id": [2]}))
|
||||
table.checkout(1)
|
||||
|
||||
restored = pickle.loads(pickle.dumps(table))
|
||||
|
||||
assert restored.count_rows() == 1
|
||||
assert restored.to_arrow().column("id").to_pylist() == [1]
|
||||
restored.checkout_latest()
|
||||
assert restored.count_rows() == 2
|
||||
|
||||
|
||||
def test_memory_lance_table_pickle_is_unsupported(mem_db: DBConnection):
|
||||
table = mem_db.create_table("memory_pickle", pa.table({"id": [1]}))
|
||||
|
||||
with pytest.raises(ValueError, match="in-memory LanceTable"):
|
||||
pickle.dumps(table)
|
||||
|
||||
|
||||
def test_table_to_pandas_default_matches_arrow(tmp_db: DBConnection):
|
||||
pd = pytest.importorskip("pandas")
|
||||
data = pa.table({"id": [1, 2], "text": ["one", "two"]})
|
||||
@@ -960,12 +928,7 @@ def test_create_index_method(mock_create_index, mem_db: DBConnection):
|
||||
num_bits=4,
|
||||
)
|
||||
mock_create_index.assert_called_with(
|
||||
"vector",
|
||||
replace=True,
|
||||
config=expected_config,
|
||||
wait_timeout=None,
|
||||
name=None,
|
||||
train=True,
|
||||
"vector", replace=True, config=expected_config, name=None, train=True
|
||||
)
|
||||
|
||||
# Test with target_partition_size
|
||||
@@ -985,12 +948,7 @@ def test_create_index_method(mock_create_index, mem_db: DBConnection):
|
||||
target_partition_size=8192,
|
||||
)
|
||||
mock_create_index.assert_called_with(
|
||||
"vector",
|
||||
replace=True,
|
||||
config=expected_config,
|
||||
wait_timeout=None,
|
||||
name=None,
|
||||
train=True,
|
||||
"vector", replace=True, config=expected_config, name=None, train=True
|
||||
)
|
||||
|
||||
# target_partition_size has a default value,
|
||||
@@ -1009,12 +967,7 @@ def test_create_index_method(mock_create_index, mem_db: DBConnection):
|
||||
num_bits=4,
|
||||
)
|
||||
mock_create_index.assert_called_with(
|
||||
"vector",
|
||||
replace=True,
|
||||
config=expected_config,
|
||||
wait_timeout=None,
|
||||
name=None,
|
||||
train=True,
|
||||
"vector", replace=True, config=expected_config, name=None, train=True
|
||||
)
|
||||
|
||||
table.create_index(
|
||||
@@ -1025,12 +978,7 @@ def test_create_index_method(mock_create_index, mem_db: DBConnection):
|
||||
)
|
||||
expected_config = HnswPq(distance_type="dot")
|
||||
mock_create_index.assert_called_with(
|
||||
"my_vector",
|
||||
replace=False,
|
||||
config=expected_config,
|
||||
wait_timeout=None,
|
||||
name=None,
|
||||
train=True,
|
||||
"my_vector", replace=False, config=expected_config, name=None, train=True
|
||||
)
|
||||
|
||||
table.create_index(
|
||||
@@ -1045,12 +993,7 @@ def test_create_index_method(mock_create_index, mem_db: DBConnection):
|
||||
distance_type="cosine", sample_rate=0.1, m=29, ef_construction=10
|
||||
)
|
||||
mock_create_index.assert_called_with(
|
||||
"my_vector",
|
||||
replace=True,
|
||||
config=expected_config,
|
||||
wait_timeout=None,
|
||||
name=None,
|
||||
train=True,
|
||||
"my_vector", replace=True, config=expected_config, name=None, train=True
|
||||
)
|
||||
|
||||
table.create_index(
|
||||
@@ -1065,12 +1008,7 @@ def test_create_index_method(mock_create_index, mem_db: DBConnection):
|
||||
distance_type="cosine", sample_rate=0.1, m=29, ef_construction=10
|
||||
)
|
||||
mock_create_index.assert_called_with(
|
||||
"my_vector",
|
||||
replace=True,
|
||||
config=expected_config,
|
||||
wait_timeout=None,
|
||||
name=None,
|
||||
train=True,
|
||||
"my_vector", replace=True, config=expected_config, name=None, train=True
|
||||
)
|
||||
|
||||
|
||||
@@ -1094,7 +1032,6 @@ def test_create_index_name_and_train_parameters(
|
||||
"vector",
|
||||
replace=True,
|
||||
config=expected_config,
|
||||
wait_timeout=None,
|
||||
name="my_custom_index",
|
||||
train=True,
|
||||
)
|
||||
@@ -1102,82 +1039,13 @@ def test_create_index_name_and_train_parameters(
|
||||
# Test with train=False
|
||||
table.create_index(vector_column_name="vector", train=False)
|
||||
mock_create_index.assert_called_with(
|
||||
"vector",
|
||||
replace=True,
|
||||
config=expected_config,
|
||||
wait_timeout=None,
|
||||
name=None,
|
||||
train=False,
|
||||
"vector", replace=True, config=expected_config, name=None, train=False
|
||||
)
|
||||
|
||||
# Test with both name and train
|
||||
table.create_index(vector_column_name="vector", name="my_index_name", train=True)
|
||||
mock_create_index.assert_called_with(
|
||||
"vector",
|
||||
replace=True,
|
||||
config=expected_config,
|
||||
wait_timeout=None,
|
||||
name="my_index_name",
|
||||
train=True,
|
||||
)
|
||||
|
||||
|
||||
@patch("lancedb.table.AsyncTable.create_index")
|
||||
def test_create_index_legacy_emits_deprecation_warning(
|
||||
mock_create_index, mem_db: DBConnection
|
||||
):
|
||||
table = mem_db.create_table(
|
||||
"test",
|
||||
data=[{"vector": [3.1, 4.1]}, {"vector": [5.9, 26.5]}],
|
||||
)
|
||||
|
||||
with pytest.warns(DeprecationWarning, match="create_index"):
|
||||
table.create_index(metric="l2", num_partitions=8, vector_column_name="vector")
|
||||
|
||||
|
||||
@patch("lancedb.table.AsyncTable.create_index")
|
||||
def test_create_index_new_api(mock_create_index, mem_db: DBConnection):
|
||||
table = mem_db.create_table(
|
||||
"test",
|
||||
data=[
|
||||
{"vector": [3.1, 4.1], "category": "a", "text": "hello world"},
|
||||
{"vector": [5.9, 26.5], "category": "b", "text": "goodbye"},
|
||||
],
|
||||
)
|
||||
|
||||
# Vector index via new API should not warn
|
||||
with warnings.catch_warnings():
|
||||
warnings.simplefilter("error", DeprecationWarning)
|
||||
table.create_index("vector", config=IvfPq(distance_type="l2"))
|
||||
mock_create_index.assert_called_with(
|
||||
"vector",
|
||||
replace=True,
|
||||
config=IvfPq(distance_type="l2"),
|
||||
wait_timeout=None,
|
||||
name=None,
|
||||
train=True,
|
||||
)
|
||||
|
||||
# Scalar index via new API
|
||||
table.create_index("category", config=BTree())
|
||||
mock_create_index.assert_called_with(
|
||||
"category",
|
||||
replace=True,
|
||||
config=BTree(),
|
||||
wait_timeout=None,
|
||||
name=None,
|
||||
train=True,
|
||||
)
|
||||
|
||||
# FTS index via new API
|
||||
table.create_index("text", config=FTS(with_position=True))
|
||||
mock_create_index.assert_called_with(
|
||||
"text",
|
||||
replace=True,
|
||||
config=FTS(with_position=True),
|
||||
wait_timeout=None,
|
||||
name=None,
|
||||
train=True,
|
||||
"vector", replace=True, config=expected_config, name="my_index_name", train=True
|
||||
)
|
||||
|
||||
|
||||
@@ -1993,9 +1861,8 @@ def test_create_scalar_index(mem_db: DBConnection):
|
||||
"my_table",
|
||||
data=test_data,
|
||||
)
|
||||
# Test with default name; confirm DeprecationWarning fires
|
||||
with pytest.warns(DeprecationWarning, match="create_scalar_index"):
|
||||
table.create_scalar_index("x")
|
||||
# Test with default name
|
||||
table.create_scalar_index("x")
|
||||
indices = table.list_indices()
|
||||
assert len(indices) == 1
|
||||
scalar_index = indices[0]
|
||||
|
||||
@@ -1,15 +1,10 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
import contextlib
|
||||
import functools
|
||||
import http.server
|
||||
import json
|
||||
import multiprocessing as mp
|
||||
import pickle
|
||||
import re
|
||||
import sys
|
||||
import threading
|
||||
|
||||
import lancedb
|
||||
import pyarrow as pa
|
||||
@@ -20,107 +15,6 @@ from lancedb.util import tbl_to_tensor
|
||||
torch = pytest.importorskip("torch")
|
||||
|
||||
|
||||
REMOTE_ROWS = list(range(100))
|
||||
|
||||
|
||||
def _make_mock_http_handler(handler):
|
||||
class MockLanceDBHandler(http.server.BaseHTTPRequestHandler):
|
||||
def do_GET(self):
|
||||
handler(self)
|
||||
|
||||
def do_POST(self):
|
||||
handler(self)
|
||||
|
||||
return MockLanceDBHandler
|
||||
|
||||
|
||||
def _remote_schema_payload():
|
||||
return {
|
||||
"version": 1,
|
||||
"schema": {
|
||||
"fields": [
|
||||
{"name": "a", "type": {"type": "int64"}, "nullable": False},
|
||||
]
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def _offsets_from_filter(filter_sql: str | None) -> list[int]:
|
||||
if filter_sql is None:
|
||||
return REMOTE_ROWS
|
||||
match = re.search(r"_rowoffset in \((.*?)\)", filter_sql)
|
||||
if match is None:
|
||||
return REMOTE_ROWS
|
||||
raw_offsets = match.group(1).strip()
|
||||
if raw_offsets == "":
|
||||
return []
|
||||
return [int(offset.strip()) for offset in raw_offsets.split(",")]
|
||||
|
||||
|
||||
def _remote_dataset_handler(request):
|
||||
request.close_connection = True
|
||||
if request.path == "/v1/table/test/describe/":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
request.wfile.write(json.dumps(_remote_schema_payload()).encode())
|
||||
elif request.path == "/v1/table/test/count_rows/":
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/json")
|
||||
request.end_headers()
|
||||
request.wfile.write(str(len(REMOTE_ROWS)).encode())
|
||||
elif request.path == "/v1/table/test/query/":
|
||||
content_len = int(request.headers.get("Content-Length"))
|
||||
body = json.loads(request.rfile.read(content_len))
|
||||
offsets = _offsets_from_filter(body.get("filter"))
|
||||
requested_columns = body.get("columns") or ["a"]
|
||||
if isinstance(requested_columns, dict):
|
||||
requested_columns = list(requested_columns)
|
||||
|
||||
data = {}
|
||||
for column in requested_columns:
|
||||
if column == "a":
|
||||
data[column] = [REMOTE_ROWS[offset] for offset in offsets]
|
||||
elif column == "_rowoffset":
|
||||
data[column] = offsets
|
||||
elif column == "_rowid":
|
||||
data[column] = offsets
|
||||
|
||||
table = pa.table(data)
|
||||
request.send_response(200)
|
||||
request.send_header("Content-Type", "application/vnd.apache.arrow.file")
|
||||
request.end_headers()
|
||||
with pa.ipc.new_file(request.wfile, schema=table.schema) as writer:
|
||||
writer.write_table(table)
|
||||
else:
|
||||
request.send_response(404)
|
||||
request.end_headers()
|
||||
|
||||
|
||||
@contextlib.contextmanager
|
||||
def _remote_dataset_table():
|
||||
with http.server.ThreadingHTTPServer(
|
||||
("localhost", 0), _make_mock_http_handler(_remote_dataset_handler)
|
||||
) as server:
|
||||
port = server.server_address[1]
|
||||
handle = threading.Thread(target=server.serve_forever)
|
||||
handle.start()
|
||||
try:
|
||||
db = lancedb.connect(
|
||||
"db://dev",
|
||||
api_key="fake",
|
||||
host_override=f"http://localhost:{port}",
|
||||
client_config={
|
||||
"retry_config": {"retries": 0},
|
||||
"timeout_config": {"connect_timeout": 2, "read_timeout": 2},
|
||||
},
|
||||
)
|
||||
yield db.open_table("test")
|
||||
finally:
|
||||
server.shutdown()
|
||||
handle.join()
|
||||
|
||||
|
||||
def _open_native_table(uri: str, table_name: str):
|
||||
"""Top-level connection factory used by the explicit-factory pickle test.
|
||||
|
||||
@@ -213,39 +107,6 @@ def test_permutation_dataloader_multiprocessing(tmp_db):
|
||||
assert seen == 1000
|
||||
|
||||
|
||||
def test_remote_table_dataloader_multiprocessing():
|
||||
with _remote_dataset_table() as table:
|
||||
dataloader = torch.utils.data.DataLoader(
|
||||
table,
|
||||
collate_fn=tbl_to_tensor,
|
||||
batch_size=10,
|
||||
num_workers=2,
|
||||
multiprocessing_context="spawn",
|
||||
)
|
||||
seen = 0
|
||||
for batch in dataloader:
|
||||
assert batch.size(0) == 1
|
||||
assert batch.size(1) == 10
|
||||
seen += batch.size(1)
|
||||
assert seen == len(REMOTE_ROWS)
|
||||
|
||||
|
||||
def test_remote_permutation_dataloader_multiprocessing():
|
||||
with _remote_dataset_table() as table:
|
||||
permutation = Permutation.identity(table)
|
||||
dataloader = torch.utils.data.DataLoader(
|
||||
permutation,
|
||||
batch_size=10,
|
||||
num_workers=2,
|
||||
multiprocessing_context="spawn",
|
||||
)
|
||||
seen = 0
|
||||
for batch in dataloader:
|
||||
assert batch["a"].size(0) == 10
|
||||
seen += batch["a"].size(0)
|
||||
assert seen == len(REMOTE_ROWS)
|
||||
|
||||
|
||||
def test_permutation_pickle_with_connection_factory(tmp_path):
|
||||
"""When the user provides a connection_factory, pickling should round-trip
|
||||
through that factory rather than introspecting the connection URI. Useful
|
||||
@@ -310,35 +171,6 @@ def _multiworker_dataloader_target(db_uri: str, result_queue):
|
||||
result_queue.put(count)
|
||||
|
||||
|
||||
def _remote_multiworker_dataloader_target(port: int, result_queue):
|
||||
import lancedb
|
||||
from lancedb.permutation import Permutation
|
||||
|
||||
db = lancedb.connect(
|
||||
"db://dev",
|
||||
api_key="fake",
|
||||
host_override=f"http://localhost:{port}",
|
||||
client_config={
|
||||
"retry_config": {"retries": 0},
|
||||
"timeout_config": {"connect_timeout": 2, "read_timeout": 2},
|
||||
},
|
||||
)
|
||||
table = db.open_table("test")
|
||||
permutation = Permutation.identity(table)
|
||||
|
||||
dataloader = torch.utils.data.DataLoader(
|
||||
permutation,
|
||||
batch_size=10,
|
||||
num_workers=2,
|
||||
multiprocessing_context="fork",
|
||||
)
|
||||
count = 0
|
||||
for batch in dataloader:
|
||||
assert batch["a"].size(0) == 10
|
||||
count += 1
|
||||
result_queue.put(count)
|
||||
|
||||
|
||||
@pytest.mark.skipif(
|
||||
sys.platform != "linux",
|
||||
reason=(
|
||||
@@ -376,46 +208,3 @@ def test_permutation_dataloader_fork_workers(tmp_path):
|
||||
assert proc.exitcode == 0, f"child exited with code {proc.exitcode}"
|
||||
assert not queue.empty(), "child produced no batches"
|
||||
assert queue.get() == 100
|
||||
|
||||
|
||||
@pytest.mark.skipif(
|
||||
sys.platform != "linux",
|
||||
reason=(
|
||||
"fork() is unavailable on Windows and unsafe on macOS "
|
||||
"(Apple frameworks/TLS are not fork-safe)"
|
||||
),
|
||||
)
|
||||
def test_remote_permutation_dataloader_fork_workers():
|
||||
with http.server.ThreadingHTTPServer(
|
||||
("localhost", 0), _make_mock_http_handler(_remote_dataset_handler)
|
||||
) as server:
|
||||
port = server.server_address[1]
|
||||
handle = threading.Thread(target=server.serve_forever)
|
||||
handle.start()
|
||||
try:
|
||||
ctx = mp.get_context("spawn")
|
||||
queue = ctx.Queue()
|
||||
proc = ctx.Process(
|
||||
target=_remote_multiworker_dataloader_target,
|
||||
args=(port, queue),
|
||||
)
|
||||
proc.start()
|
||||
proc.join(timeout=30)
|
||||
|
||||
if proc.is_alive():
|
||||
proc.terminate()
|
||||
proc.join(timeout=5)
|
||||
if proc.is_alive():
|
||||
proc.kill()
|
||||
proc.join()
|
||||
pytest.fail(
|
||||
"Remote permutation hung when iterated in a fork-based "
|
||||
"DataLoader worker"
|
||||
)
|
||||
|
||||
assert proc.exitcode == 0, f"child exited with code {proc.exitcode}"
|
||||
assert not queue.empty(), "child produced no batches"
|
||||
assert queue.get() == 10
|
||||
finally:
|
||||
server.shutdown()
|
||||
handle.join()
|
||||
|
||||
@@ -143,20 +143,18 @@ pub struct MergeResult {
|
||||
pub num_inserted_rows: u64,
|
||||
pub num_deleted_rows: u64,
|
||||
pub num_attempts: u32,
|
||||
pub num_rows: u64,
|
||||
}
|
||||
|
||||
#[pymethods]
|
||||
impl MergeResult {
|
||||
pub fn __repr__(&self) -> String {
|
||||
format!(
|
||||
"MergeResult(version={}, num_updated_rows={}, num_inserted_rows={}, num_deleted_rows={}, num_attempts={}, num_rows={})",
|
||||
"MergeResult(version={}, num_updated_rows={}, num_inserted_rows={}, num_deleted_rows={}, num_attempts={})",
|
||||
self.version,
|
||||
self.num_updated_rows,
|
||||
self.num_inserted_rows,
|
||||
self.num_deleted_rows,
|
||||
self.num_attempts,
|
||||
self.num_rows
|
||||
self.num_attempts
|
||||
)
|
||||
}
|
||||
}
|
||||
@@ -169,7 +167,6 @@ impl From<lancedb::table::MergeResult> for MergeResult {
|
||||
num_inserted_rows: result.num_inserted_rows,
|
||||
num_deleted_rows: result.num_deleted_rows,
|
||||
num_attempts: result.num_attempts,
|
||||
num_rows: result.num_rows,
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -197,12 +194,6 @@ impl LsmWriteSpec {
|
||||
}
|
||||
|
||||
/// Identity sharding — shard by the raw value of `column`.
|
||||
///
|
||||
/// `column` must be a deterministic function of the unenforced primary
|
||||
/// key: every row with a given primary key must always produce the same
|
||||
/// `column` value, or upserts of that key can land in different shards
|
||||
/// and a stale version can win. Typically `column` is the primary key
|
||||
/// itself or a stable attribute of it.
|
||||
#[staticmethod]
|
||||
pub fn identity(column: String) -> Self {
|
||||
Self {
|
||||
@@ -755,23 +746,6 @@ impl Table {
|
||||
})
|
||||
}
|
||||
|
||||
pub fn _table_reopen_state(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
|
||||
let inner = self_.inner_ref()?.clone();
|
||||
future_into_py(self_.py(), async move {
|
||||
let name = inner.name().to_string();
|
||||
let namespace_path = inner.namespace().to_vec();
|
||||
let storage_options = inner.initial_storage_options().await;
|
||||
|
||||
Python::attach(|py| {
|
||||
let dict = PyDict::new(py);
|
||||
dict.set_item("name", name)?;
|
||||
dict.set_item("namespace_path", namespace_path)?;
|
||||
dict.set_item("storage_options", storage_options)?;
|
||||
Ok(dict.unbind())
|
||||
})
|
||||
})
|
||||
}
|
||||
|
||||
pub fn __repr__(&self) -> String {
|
||||
match &self.inner {
|
||||
None => format!("ClosedTable({})", self.name),
|
||||
@@ -959,12 +933,6 @@ impl Table {
|
||||
if let Some(use_index) = parameters.use_index {
|
||||
builder.use_index(use_index);
|
||||
}
|
||||
if let Some(use_lsm_write) = parameters.use_lsm_write {
|
||||
builder.use_lsm_write(use_lsm_write);
|
||||
}
|
||||
if let Some(validate_single_shard) = parameters.validate_single_shard {
|
||||
builder.validate_single_shard(validate_single_shard);
|
||||
}
|
||||
|
||||
future_into_py(self_.py(), async move {
|
||||
let res = builder.execute(Box::new(batches)).await.infer_error()?;
|
||||
@@ -1003,13 +971,6 @@ impl Table {
|
||||
})
|
||||
}
|
||||
|
||||
pub fn close_lsm_writers(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
|
||||
let inner = self_.inner_ref()?.clone();
|
||||
future_into_py(self_.py(), async move {
|
||||
inner.close_lsm_writers().await.infer_error()
|
||||
})
|
||||
}
|
||||
|
||||
pub fn uses_v2_manifest_paths(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
|
||||
let inner = self_.inner_ref()?.clone();
|
||||
future_into_py(self_.py(), async move {
|
||||
@@ -1163,8 +1124,6 @@ pub struct MergeInsertParams {
|
||||
when_not_matched_by_source_condition: Option<String>,
|
||||
timeout: Option<std::time::Duration>,
|
||||
use_index: Option<bool>,
|
||||
use_lsm_write: Option<bool>,
|
||||
validate_single_shard: Option<bool>,
|
||||
}
|
||||
|
||||
#[pyclass]
|
||||
|
||||
@@ -1,2 +1,2 @@
|
||||
[toolchain]
|
||||
channel = "1.95.0"
|
||||
channel = "1.94.0"
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "lancedb"
|
||||
version = "0.30.1-beta.0"
|
||||
version = "0.30.0-beta.0"
|
||||
edition.workspace = true
|
||||
description = "LanceDB: A serverless, low-latency vector database for AI applications"
|
||||
license.workspace = true
|
||||
@@ -75,7 +75,7 @@ reqwest = { version = "0.12.0", default-features = false, features = [
|
||||
"stream",
|
||||
], optional = true }
|
||||
http = { version = "1", optional = true } # Matching what is in reqwest
|
||||
uuid = { version = "1.7.0", features = ["v4", "v5"] }
|
||||
uuid = { version = "1.7.0", features = ["v4"] }
|
||||
polars-arrow = { version = ">=0.37,<0.40.0", optional = true }
|
||||
polars = { version = ">=0.37,<0.40.0", optional = true }
|
||||
hf-hub = { version = "0.4.1", optional = true, default-features = false, features = [
|
||||
@@ -104,7 +104,6 @@ datafusion.workspace = true
|
||||
http-body = "1" # Matching reqwest
|
||||
rstest = "0.23.0"
|
||||
test-log = "0.2"
|
||||
serial_test = "3"
|
||||
|
||||
|
||||
[features]
|
||||
|
||||
@@ -812,7 +812,8 @@ impl ConnectBuilder {
|
||||
self
|
||||
}
|
||||
|
||||
/// The interval at which to check for updates from other processes.
|
||||
/// The interval at which to check for updates from other processes. This
|
||||
/// only affects LanceDB OSS.
|
||||
///
|
||||
/// If left unset, consistency is not checked. For maximum read
|
||||
/// performance, this is the default. For strong consistency, set this to
|
||||
@@ -824,11 +825,8 @@ impl ConnectBuilder {
|
||||
/// This only affects read operations. Write operations are always
|
||||
/// consistent.
|
||||
///
|
||||
/// # Cost
|
||||
///
|
||||
/// Stronger consistency is not free. The smaller the interval, the more
|
||||
/// often each read pays the cost of checking for updates against object
|
||||
/// storage, raising per-read latency and cost.
|
||||
/// LanceDB Cloud uses eventual consistency under the hood, and is not
|
||||
/// currently configurable.
|
||||
pub fn read_consistency_interval(
|
||||
mut self,
|
||||
read_consistency_interval: std::time::Duration,
|
||||
@@ -888,7 +886,6 @@ impl ConnectBuilder {
|
||||
options.host_override,
|
||||
self.request.client_config,
|
||||
storage_options.into(),
|
||||
self.request.read_consistency_interval,
|
||||
)?);
|
||||
Ok(Connection {
|
||||
internal,
|
||||
|
||||
@@ -464,9 +464,11 @@ mod tests {
|
||||
let mut iter = ids.into_iter().map(|o| o.unwrap());
|
||||
while let Some(first) = iter.next() {
|
||||
let rows_left_in_clump = if first == 4470 { 19 } else { 29 };
|
||||
for expected_next in (first + 1)..=(first + rows_left_in_clump) {
|
||||
let mut expected_next = first + 1;
|
||||
for _ in 0..rows_left_in_clump {
|
||||
let next = iter.next().unwrap();
|
||||
assert_eq!(next, expected_next);
|
||||
expected_next += 1;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -245,9 +245,6 @@ pub struct RestfulLanceDbClient<S: HttpSend = Sender> {
|
||||
pub(crate) sender: S,
|
||||
pub(crate) id_delimiter: String,
|
||||
pub(crate) header_provider: Option<Arc<dyn HeaderProvider>>,
|
||||
/// Connection-level read consistency interval. Drives the
|
||||
/// `x-lancedb-min-timestamp` freshness header sent on read requests.
|
||||
pub(crate) read_consistency_interval: Option<Duration>,
|
||||
}
|
||||
|
||||
impl<S: HttpSend> std::fmt::Debug for RestfulLanceDbClient<S> {
|
||||
@@ -341,7 +338,6 @@ impl RestfulLanceDbClient<Sender> {
|
||||
host_override: Option<String>,
|
||||
default_headers: HeaderMap,
|
||||
client_config: ClientConfig,
|
||||
read_consistency_interval: Option<Duration>,
|
||||
) -> Result<Self> {
|
||||
// Get the timeouts
|
||||
let timeout =
|
||||
@@ -439,7 +435,6 @@ impl RestfulLanceDbClient<Sender> {
|
||||
.clone()
|
||||
.unwrap_or("$".to_string()),
|
||||
header_provider: client_config.header_provider,
|
||||
read_consistency_interval,
|
||||
})
|
||||
}
|
||||
}
|
||||
@@ -845,16 +840,6 @@ pub mod test_utils {
|
||||
pub fn client_with_handler<T>(
|
||||
handler: impl Fn(reqwest::Request) -> http::response::Response<T> + Send + Sync + 'static,
|
||||
) -> RestfulLanceDbClient<MockSender>
|
||||
where
|
||||
T: Into<reqwest::Body>,
|
||||
{
|
||||
client_with_handler_and_interval(handler, None)
|
||||
}
|
||||
|
||||
pub fn client_with_handler_and_interval<T>(
|
||||
handler: impl Fn(reqwest::Request) -> http::response::Response<T> + Send + Sync + 'static,
|
||||
read_consistency_interval: Option<Duration>,
|
||||
) -> RestfulLanceDbClient<MockSender>
|
||||
where
|
||||
T: Into<reqwest::Body>,
|
||||
{
|
||||
@@ -872,7 +857,6 @@ pub mod test_utils {
|
||||
},
|
||||
id_delimiter: "$".to_string(),
|
||||
header_provider: None,
|
||||
read_consistency_interval,
|
||||
}
|
||||
}
|
||||
|
||||
@@ -897,7 +881,6 @@ pub mod test_utils {
|
||||
},
|
||||
id_delimiter: config.id_delimiter.unwrap_or_else(|| "$".to_string()),
|
||||
header_provider: config.header_provider,
|
||||
read_consistency_interval: None,
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -905,18 +888,8 @@ pub mod test_utils {
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
use serial_test::serial;
|
||||
use std::time::Duration;
|
||||
|
||||
// Serializes the env-var-mutating tests below: cargo test runs tests in
|
||||
// parallel, but several of these tests read and write the same process-
|
||||
// global env vars (`LANCEDB_USER_ID*`), so they would race without this.
|
||||
static ENV_MUTEX: std::sync::Mutex<()> = std::sync::Mutex::new(());
|
||||
|
||||
fn lock_env() -> std::sync::MutexGuard<'static, ()> {
|
||||
ENV_MUTEX.lock().unwrap_or_else(|e| e.into_inner())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_timeout_config_default() {
|
||||
let config = TimeoutConfig::default();
|
||||
@@ -1073,7 +1046,6 @@ mod tests {
|
||||
sender: Sender,
|
||||
id_delimiter: "+".to_string(),
|
||||
header_provider: Some(Arc::new(provider) as Arc<dyn HeaderProvider>),
|
||||
read_consistency_interval: None,
|
||||
};
|
||||
|
||||
// Apply dynamic headers
|
||||
@@ -1109,7 +1081,6 @@ mod tests {
|
||||
sender: Sender,
|
||||
id_delimiter: "+".to_string(),
|
||||
header_provider: Some(Arc::new(provider) as Arc<dyn HeaderProvider>),
|
||||
read_consistency_interval: None,
|
||||
};
|
||||
|
||||
// Apply dynamic headers
|
||||
@@ -1147,7 +1118,6 @@ mod tests {
|
||||
sender: Sender,
|
||||
id_delimiter: "+".to_string(),
|
||||
header_provider: Some(Arc::new(provider) as Arc<dyn HeaderProvider>),
|
||||
read_consistency_interval: None,
|
||||
};
|
||||
|
||||
// Header provider errors should fail the request
|
||||
@@ -1173,9 +1143,7 @@ mod tests {
|
||||
}
|
||||
|
||||
#[test]
|
||||
#[serial(user_id_env)]
|
||||
fn test_resolve_user_id_none() {
|
||||
let _guard = lock_env();
|
||||
let config = ClientConfig::default();
|
||||
// Clear env vars that might be set from other tests
|
||||
// SAFETY: This is only called in tests
|
||||
@@ -1187,9 +1155,7 @@ mod tests {
|
||||
}
|
||||
|
||||
#[test]
|
||||
#[serial(user_id_env)]
|
||||
fn test_resolve_user_id_from_env() {
|
||||
let _guard = lock_env();
|
||||
// SAFETY: This is only called in tests
|
||||
unsafe {
|
||||
std::env::set_var("LANCEDB_USER_ID", "env-user-id");
|
||||
@@ -1203,9 +1169,7 @@ mod tests {
|
||||
}
|
||||
|
||||
#[test]
|
||||
#[serial(user_id_env)]
|
||||
fn test_resolve_user_id_from_env_key() {
|
||||
let _guard = lock_env();
|
||||
// SAFETY: This is only called in tests
|
||||
unsafe {
|
||||
std::env::remove_var("LANCEDB_USER_ID");
|
||||
@@ -1225,9 +1189,7 @@ mod tests {
|
||||
}
|
||||
|
||||
#[test]
|
||||
#[serial(user_id_env)]
|
||||
fn test_resolve_user_id_direct_takes_precedence() {
|
||||
let _guard = lock_env();
|
||||
// SAFETY: This is only called in tests
|
||||
unsafe {
|
||||
std::env::set_var("LANCEDB_USER_ID", "env-user-id");
|
||||
@@ -1244,9 +1206,7 @@ mod tests {
|
||||
}
|
||||
|
||||
#[test]
|
||||
#[serial(user_id_env)]
|
||||
fn test_resolve_user_id_empty_env_ignored() {
|
||||
let _guard = lock_env();
|
||||
// SAFETY: This is only called in tests
|
||||
unsafe {
|
||||
std::env::set_var("LANCEDB_USER_ID", "");
|
||||
|
||||
@@ -206,7 +206,6 @@ impl RemoteDatabase {
|
||||
host_override: Option<String>,
|
||||
client_config: ClientConfig,
|
||||
options: RemoteOptions,
|
||||
read_consistency_interval: Option<std::time::Duration>,
|
||||
) -> Result<Self> {
|
||||
let parsed = super::client::parse_db_url(uri)?;
|
||||
let header_map = RestfulLanceDbClient::<Sender>::default_headers(
|
||||
@@ -234,7 +233,6 @@ impl RemoteDatabase {
|
||||
host_override,
|
||||
header_map,
|
||||
client_config.clone(),
|
||||
read_consistency_interval,
|
||||
)?;
|
||||
|
||||
let table_cache = Cache::builder()
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -89,6 +89,7 @@ use futures::future::join_all;
|
||||
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};
|
||||
@@ -252,36 +253,6 @@ pub enum Filter {
|
||||
Datafusion(Expr),
|
||||
}
|
||||
|
||||
/// A predicate for filtering rows in delete operations.
|
||||
///
|
||||
/// Accepts either a SQL string or a DataFusion [`Expr`]. Use the [`From`]
|
||||
/// implementations to convert from `&str` or `&Expr` automatically.
|
||||
/// See [`Table::delete`] for usage examples.
|
||||
pub enum Predicate<'a> {
|
||||
/// A SQL predicate string
|
||||
String(&'a str),
|
||||
/// A DataFusion logical expression
|
||||
Expr(&'a Expr),
|
||||
}
|
||||
|
||||
impl<'a> From<&'a str> for Predicate<'a> {
|
||||
fn from(s: &'a str) -> Self {
|
||||
Predicate::String(s)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> From<&'a String> for Predicate<'a> {
|
||||
fn from(s: &'a String) -> Self {
|
||||
Predicate::String(s.as_str())
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> From<&'a Expr> for Predicate<'a> {
|
||||
fn from(e: &'a Expr) -> Self {
|
||||
Predicate::Expr(e)
|
||||
}
|
||||
}
|
||||
|
||||
#[async_trait]
|
||||
pub trait Tags: Send + Sync {
|
||||
/// List the tags of the table.
|
||||
@@ -311,15 +282,17 @@ pub use self::merge::MergeResult;
|
||||
/// date) and [`LsmWriteSpec::with_writer_config_defaults`] (default
|
||||
/// `ShardWriter` configuration recorded in the MemWAL index).
|
||||
///
|
||||
/// All variants require the table to have an unenforced primary key.
|
||||
///
|
||||
/// Install a spec with [`Table::set_lsm_write_spec`] and remove it with
|
||||
/// [`Table::unset_lsm_write_spec`]. The actual `merge_insert` dispatch
|
||||
/// onto the MemWAL writer is a follow-up.
|
||||
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
|
||||
pub enum LsmWriteSpec {
|
||||
/// Hash-bucket sharding by a scalar column.
|
||||
/// Hash-bucket sharding by the unenforced primary key column.
|
||||
///
|
||||
/// `column` must be a non-nested column with a supported scalar type.
|
||||
/// `num_buckets` must be in `[1, 1024]`.
|
||||
/// `column` must equal the table's currently-set single-column
|
||||
/// unenforced primary key. `num_buckets` must be in `[1, 1024]`.
|
||||
/// Iceberg-compatible Murmur3-x86-32 (seed 0) is used so each row's
|
||||
/// `bucket(column, num_buckets)` value is stable across processes.
|
||||
Bucket {
|
||||
@@ -366,14 +339,6 @@ impl LsmWriteSpec {
|
||||
|
||||
/// Construct an identity-sharding spec (shard by the raw value of
|
||||
/// `column`) with no maintained indexes.
|
||||
///
|
||||
/// `column` must be a deterministic function of the unenforced primary
|
||||
/// key: every row with a given primary key must always produce the same
|
||||
/// `column` value. MemWAL dedups upserts by primary key but tracks
|
||||
/// generations per shard, so if the same key is written with two
|
||||
/// different `column` values its versions land in different shards and a
|
||||
/// stale value can win. Typically `column` is the primary key itself, or
|
||||
/// a stable attribute of it (e.g. a tenant id).
|
||||
pub fn identity(column: impl Into<String>) -> Self {
|
||||
Self::Identity {
|
||||
column: column.into(),
|
||||
@@ -526,8 +491,8 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
|
||||
|
||||
/// Add new records to the table.
|
||||
async fn add(&self, add: AddDataBuilder) -> Result<AddResult>;
|
||||
/// Delete rows from the table matching the given [`Predicate`].
|
||||
async fn delete(&self, predicate: Predicate<'_>) -> Result<DeleteResult>;
|
||||
/// Delete rows from the table.
|
||||
async fn delete(&self, predicate: &str) -> Result<DeleteResult>;
|
||||
/// Update rows in the table.
|
||||
async fn update(&self, update: UpdateBuilder) -> Result<UpdateResult>;
|
||||
/// Create an index on the provided column(s).
|
||||
@@ -588,13 +553,6 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
|
||||
message: "unset_lsm_write_spec is not supported on this table type".into(),
|
||||
})
|
||||
}
|
||||
/// Drain and close any cached MemWAL shard writers for this table.
|
||||
///
|
||||
/// The default implementation is a no-op; table types that maintain
|
||||
/// MemWAL shard writers override it.
|
||||
async fn close_lsm_writers(&self) -> Result<()> {
|
||||
Ok(())
|
||||
}
|
||||
/// Gets the table tag manager.
|
||||
async fn tags(&self) -> Result<Box<dyn Tags + '_>>;
|
||||
/// Optimize the dataset.
|
||||
@@ -698,30 +656,6 @@ mod test_utils {
|
||||
}
|
||||
}
|
||||
|
||||
pub fn new_with_handler_and_interval<T>(
|
||||
name: impl Into<String>,
|
||||
handler: impl Fn(reqwest::Request) -> http::Response<T> + Clone + Send + Sync + 'static,
|
||||
read_consistency_interval: Option<std::time::Duration>,
|
||||
) -> Self
|
||||
where
|
||||
T: Into<reqwest::Body>,
|
||||
{
|
||||
let inner = Arc::new(
|
||||
crate::remote::table::RemoteTable::new_mock_with_consistency_interval(
|
||||
name.into(),
|
||||
handler.clone(),
|
||||
read_consistency_interval,
|
||||
),
|
||||
);
|
||||
let database = Arc::new(crate::remote::db::RemoteDatabase::new_mock(handler));
|
||||
Self {
|
||||
inner,
|
||||
database: Some(database),
|
||||
// Registry is unused.
|
||||
embedding_registry: Arc::new(MemoryRegistry::new()),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn new_with_handler_version<T>(
|
||||
name: impl Into<String>,
|
||||
version: semver::Version,
|
||||
@@ -926,8 +860,7 @@ impl Table {
|
||||
/// Delete the rows from table that match the predicate.
|
||||
///
|
||||
/// # Arguments
|
||||
/// - `predicate` - A SQL string (`&str`) or DataFusion expression (`&Expr`)
|
||||
/// that selects the rows to delete.
|
||||
/// - `predicate` - The SQL predicate string to filter the rows to be deleted.
|
||||
///
|
||||
/// # Example
|
||||
///
|
||||
@@ -936,7 +869,6 @@ impl Table {
|
||||
/// # use arrow_array::{FixedSizeListArray, types::Float32Type, RecordBatch,
|
||||
/// # RecordBatchIterator, Int32Array};
|
||||
/// # use arrow_schema::{Schema, Field, DataType};
|
||||
/// use datafusion_expr::{col, lit};
|
||||
/// # tokio::runtime::Runtime::new().unwrap().block_on(async {
|
||||
/// let tmpdir = tempfile::tempdir().unwrap();
|
||||
/// let db = lancedb::connect(tmpdir.path().to_str().unwrap())
|
||||
@@ -966,17 +898,11 @@ impl Table {
|
||||
/// .execute()
|
||||
/// .await
|
||||
/// .unwrap();
|
||||
///
|
||||
/// // Using a SQL string:
|
||||
/// tbl.delete("id > 5").await.unwrap();
|
||||
///
|
||||
/// // Using a DataFusion expression:
|
||||
/// let expr = col("id").lt(lit(4));
|
||||
/// tbl.delete(&expr).await.unwrap();
|
||||
/// # });
|
||||
/// ```
|
||||
pub async fn delete(&self, predicate: impl Into<Predicate<'_>>) -> Result<DeleteResult> {
|
||||
self.inner.delete(predicate.into()).await
|
||||
pub async fn delete(&self, predicate: &str) -> Result<DeleteResult> {
|
||||
self.inner.delete(predicate).await
|
||||
}
|
||||
|
||||
/// Create an index on the provided column(s).
|
||||
@@ -1372,15 +1298,21 @@ impl Table {
|
||||
///
|
||||
/// [`LsmWriteSpec`] chooses one of three sharding strategies:
|
||||
///
|
||||
/// - [`LsmWriteSpec::bucket`] — hash-bucket writes by a scalar column.
|
||||
/// - [`LsmWriteSpec::bucket`] — hash-bucket writes by the single-column
|
||||
/// unenforced primary key.
|
||||
/// - [`LsmWriteSpec::identity`] — shard by the raw value of a scalar column.
|
||||
/// - [`LsmWriteSpec::unsharded`] — route every write to a single shard.
|
||||
///
|
||||
/// All variants require the table to have an unenforced primary key
|
||||
/// ([`Table::set_unenforced_primary_key`]); bucket sharding additionally
|
||||
/// requires it to be the single column being bucketed.
|
||||
///
|
||||
/// # Example
|
||||
///
|
||||
/// ```
|
||||
/// # use lancedb::table::{LsmWriteSpec, Table};
|
||||
/// # async fn example(table: &Table) -> Result<(), Box<dyn std::error::Error>> {
|
||||
/// table.set_unenforced_primary_key(["id"]).await?;
|
||||
/// table
|
||||
/// .set_lsm_write_spec(
|
||||
/// LsmWriteSpec::bucket("id", 16).with_maintained_indexes(["id_idx"]),
|
||||
@@ -1401,16 +1333,6 @@ impl Table {
|
||||
self.inner.unset_lsm_write_spec().await
|
||||
}
|
||||
|
||||
/// Drain and close any cached MemWAL shard writers held for this table.
|
||||
///
|
||||
/// When an [`LsmWriteSpec`] is installed, `merge_insert` opens MemWAL shard
|
||||
/// writers and caches them for reuse across calls. This closes them,
|
||||
/// flushing pending data; writers reopen lazily on the next `merge_insert`.
|
||||
/// It is a no-op when no writers are cached.
|
||||
pub async fn close_lsm_writers(&self) -> Result<()> {
|
||||
self.inner.close_lsm_writers().await
|
||||
}
|
||||
|
||||
/// Retrieve the version of the table
|
||||
///
|
||||
/// LanceDb supports versioning. Every operation that modifies the table increases
|
||||
@@ -2854,12 +2776,9 @@ impl BaseTable for NativeTable {
|
||||
merge::lsm::unset_lsm_write_spec(self).await
|
||||
}
|
||||
|
||||
async fn close_lsm_writers(&self) -> Result<()> {
|
||||
merge::lsm::close_lsm_writers(self).await
|
||||
}
|
||||
|
||||
/// Delete rows from the table
|
||||
async fn delete(&self, predicate: Predicate<'_>) -> Result<DeleteResult> {
|
||||
async fn delete(&self, predicate: &str) -> Result<DeleteResult> {
|
||||
// Delegate to the submodule implementation
|
||||
delete::execute_delete(self, predicate).await
|
||||
}
|
||||
|
||||
@@ -2892,32 +2811,71 @@ impl BaseTable for NativeTable {
|
||||
|
||||
async fn list_indices(&self) -> Result<Vec<IndexConfig>> {
|
||||
let dataset = self.dataset.get().await?;
|
||||
let indices = dataset
|
||||
.describe_indices(None)
|
||||
.await?
|
||||
.into_iter()
|
||||
.filter_map(|idx_desc| {
|
||||
let index_type: crate::index::IndexType = match idx_desc.index_type().parse() {
|
||||
Ok(index_type) => index_type,
|
||||
let indices = dataset.load_indices().await?;
|
||||
let results = futures::stream::iter(indices.as_slice())
|
||||
.then(|idx| async {
|
||||
// skip Lance internal indexes
|
||||
if idx.name == FRAG_REUSE_INDEX_NAME {
|
||||
return None;
|
||||
}
|
||||
|
||||
let stats = match dataset.index_statistics(idx.name.as_str()).await {
|
||||
Ok(stats) => stats,
|
||||
Err(e) => {
|
||||
log::warn!(
|
||||
"Failed to parse index type for index {}: {}",
|
||||
idx_desc.name(),
|
||||
"Failed to get statistics for index {} ({}): {}",
|
||||
idx.name,
|
||||
idx.uuid,
|
||||
e
|
||||
);
|
||||
return None;
|
||||
}
|
||||
};
|
||||
|
||||
let field_ids = idx_desc.field_ids();
|
||||
let mut columns = Vec::with_capacity(field_ids.len());
|
||||
for field_id in field_ids {
|
||||
let field_path = match dataset.schema().field_path(*field_id as i32) {
|
||||
let stats: serde_json::Value = match serde_json::from_str(&stats) {
|
||||
Ok(stats) => stats,
|
||||
Err(e) => {
|
||||
log::warn!(
|
||||
"Failed to deserialize index statistics for index {} ({}): {}",
|
||||
idx.name,
|
||||
idx.uuid,
|
||||
e
|
||||
);
|
||||
return None;
|
||||
}
|
||||
};
|
||||
|
||||
let Some(index_type) = stats.get("index_type").and_then(|v| v.as_str()) else {
|
||||
log::warn!(
|
||||
"Index statistics was missing 'index_type' field for index {} ({})",
|
||||
idx.name,
|
||||
idx.uuid
|
||||
);
|
||||
return None;
|
||||
};
|
||||
|
||||
let index_type: crate::index::IndexType = match index_type.parse() {
|
||||
Ok(index_type) => index_type,
|
||||
Err(e) => {
|
||||
log::warn!(
|
||||
"Failed to parse index type for index {} ({}): {}",
|
||||
idx.name,
|
||||
idx.uuid,
|
||||
e
|
||||
);
|
||||
return None;
|
||||
}
|
||||
};
|
||||
|
||||
let mut columns = Vec::with_capacity(idx.fields.len());
|
||||
for field_id in &idx.fields {
|
||||
let field_path = match dataset.schema().field_path(*field_id) {
|
||||
Ok(field_path) => field_path,
|
||||
Err(e) => {
|
||||
log::warn!(
|
||||
"Failed to resolve field path for index {} field id {}: {}",
|
||||
idx_desc.name(),
|
||||
"Failed to resolve field path for index {} ({}) field id {}: {}",
|
||||
idx.name,
|
||||
idx.uuid,
|
||||
field_id,
|
||||
e
|
||||
);
|
||||
@@ -2927,14 +2885,17 @@ impl BaseTable for NativeTable {
|
||||
columns.push(field_path);
|
||||
}
|
||||
|
||||
let name = idx.name.clone();
|
||||
Some(IndexConfig {
|
||||
name: idx_desc.name().to_string(),
|
||||
index_type,
|
||||
columns,
|
||||
name,
|
||||
})
|
||||
})
|
||||
.collect();
|
||||
Ok(indices)
|
||||
.collect::<Vec<_>>()
|
||||
.await;
|
||||
|
||||
Ok(results.into_iter().flatten().collect())
|
||||
}
|
||||
|
||||
async fn uri(&self) -> Result<String> {
|
||||
@@ -3044,12 +3005,11 @@ impl BaseTable for NativeTable {
|
||||
let p99 = *sorted_sizes.get(num_fragments * 99 / 100).unwrap_or(&0);
|
||||
let min = sorted_sizes.first().copied().unwrap_or(0);
|
||||
let max = sorted_sizes.last().copied().unwrap_or(0);
|
||||
let mean = sorted_sizes
|
||||
.iter()
|
||||
.copied()
|
||||
.sum::<usize>()
|
||||
.checked_div(num_fragments)
|
||||
.unwrap_or(0);
|
||||
let mean = if num_fragments == 0 {
|
||||
0
|
||||
} else {
|
||||
sorted_sizes.iter().copied().sum::<usize>() / num_fragments
|
||||
};
|
||||
|
||||
let frag_stats = FragmentStatistics {
|
||||
num_fragments,
|
||||
@@ -4049,27 +4009,26 @@ mod tests {
|
||||
let index_configs = table.list_indices().await.unwrap();
|
||||
assert_eq!(index_configs.len(), 5);
|
||||
|
||||
// list_indices returns indices in alphabetical order by name
|
||||
let mut configs_iter = index_configs.into_iter();
|
||||
let index = configs_iter.next().unwrap();
|
||||
assert_eq!(index.index_type, crate::index::IndexType::Bitmap);
|
||||
assert_eq!(index.columns, vec!["category".to_string()]);
|
||||
|
||||
let index = configs_iter.next().unwrap();
|
||||
assert_eq!(index.index_type, crate::index::IndexType::Bitmap);
|
||||
assert_eq!(index.columns, vec!["data".to_string()]);
|
||||
|
||||
let index = configs_iter.next().unwrap();
|
||||
assert_eq!(index.index_type, crate::index::IndexType::Bitmap);
|
||||
assert_eq!(index.columns, vec!["is_active".to_string()]);
|
||||
|
||||
let index = configs_iter.next().unwrap();
|
||||
assert_eq!(index.index_type, crate::index::IndexType::Bitmap);
|
||||
assert_eq!(index.columns, vec!["large_category".to_string()]);
|
||||
assert_eq!(index.columns, vec!["data".to_string()]);
|
||||
|
||||
let index = configs_iter.next().unwrap();
|
||||
assert_eq!(index.index_type, crate::index::IndexType::Bitmap);
|
||||
assert_eq!(index.columns, vec!["large_data".to_string()]);
|
||||
|
||||
let index = configs_iter.next().unwrap();
|
||||
assert_eq!(index.index_type, crate::index::IndexType::Bitmap);
|
||||
assert_eq!(index.columns, vec!["large_category".to_string()]);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
@@ -4641,6 +4600,21 @@ mod tests {
|
||||
.unwrap();
|
||||
let table = conn.create_table("t", reader).execute().await.unwrap();
|
||||
|
||||
// Reject when no PK is set.
|
||||
let err = table
|
||||
.set_lsm_write_spec(LsmWriteSpec::bucket("id", 4))
|
||||
.await
|
||||
.expect_err("should reject without PK");
|
||||
assert!(matches!(err, Error::Lance { .. }), "got {:?}", err);
|
||||
|
||||
// Set PK, then a mismatched column on the spec must be rejected.
|
||||
table.set_unenforced_primary_key(["id"]).await.unwrap();
|
||||
let err = table
|
||||
.set_lsm_write_spec(LsmWriteSpec::bucket("name", 4))
|
||||
.await
|
||||
.expect_err("should reject column != PK");
|
||||
assert!(matches!(err, Error::Lance { .. }), "got {:?}", err);
|
||||
|
||||
// Reject num_buckets out of range.
|
||||
for bad in [0u32, 1025] {
|
||||
let err = table
|
||||
@@ -4706,6 +4680,9 @@ mod tests {
|
||||
.unwrap();
|
||||
let table = conn.create_table("t", reader).execute().await.unwrap();
|
||||
|
||||
// Lance's MemWAL still requires *some* unenforced primary key on
|
||||
// the dataset; Unsharded just skips the per-row hashing step.
|
||||
table.set_unenforced_primary_key(["id"]).await.unwrap();
|
||||
table
|
||||
.set_lsm_write_spec(LsmWriteSpec::unsharded())
|
||||
.await
|
||||
@@ -4752,6 +4729,7 @@ mod tests {
|
||||
.unwrap();
|
||||
let table = conn.create_table("t", reader).execute().await.unwrap();
|
||||
|
||||
table.set_unenforced_primary_key(["id"]).await.unwrap();
|
||||
table
|
||||
.set_lsm_write_spec(
|
||||
LsmWriteSpec::identity("region")
|
||||
@@ -4807,6 +4785,7 @@ mod tests {
|
||||
table.unset_lsm_write_spec().await.unwrap_err();
|
||||
|
||||
// Install a spec, then unset it.
|
||||
table.set_unenforced_primary_key(["id"]).await.unwrap();
|
||||
table
|
||||
.set_lsm_write_spec(LsmWriteSpec::bucket("id", 4))
|
||||
.await
|
||||
|
||||
@@ -982,105 +982,4 @@ mod tests {
|
||||
table2.add(struct_batch).execute().await.unwrap();
|
||||
assert_eq!(table2.count_rows(None).await.unwrap(), 2);
|
||||
}
|
||||
|
||||
/// Regression test: appending `arrow.json` (PyArrow `pa.json_()`) data into a table
|
||||
/// whose schema was created with `pa.json_()` (internally stored as `lance.json`, backed
|
||||
/// by `LargeBinary`) must succeed without a schema-mismatch error.
|
||||
///
|
||||
/// Previously `build_field_exprs` would attempt a `Utf8 → LargeBinary` DataFusion cast,
|
||||
/// which produced a field whose Arrow extension metadata still read `arrow.json` instead
|
||||
/// of `lance.json`. Lance-core then rejected the append with
|
||||
/// `"json vs large_binary" schema mismatch`.
|
||||
///
|
||||
/// PyArrow's `pa.json_()` may be backed by either `Utf8` or `LargeUtf8` depending on the
|
||||
/// constructor used, so the test is parameterized over the input backing type.
|
||||
#[rstest::rstest]
|
||||
#[case::utf8(DataType::Utf8)]
|
||||
#[case::large_utf8(DataType::LargeUtf8)]
|
||||
#[tokio::test]
|
||||
async fn test_add_arrow_json_into_lance_json_table(#[case] input_type: DataType) {
|
||||
use arrow_array::{Array, cast::AsArray};
|
||||
use lance_arrow::ARROW_EXT_NAME_KEY;
|
||||
use lance_arrow::json::{ARROW_JSON_EXT_NAME, JSON_EXT_NAME};
|
||||
|
||||
// Build a table whose "data" column is lance.json (LargeBinary +
|
||||
// ARROW:extension:name = "lance.json").
|
||||
let lance_json_field = lance_arrow::json::json_field("data", true);
|
||||
let table_schema = Arc::new(Schema::new(vec![lance_json_field]));
|
||||
|
||||
let db = connect("memory://").execute().await.unwrap();
|
||||
let table = db
|
||||
.create_empty_table("json_test", table_schema)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Sanity-check the stored schema.
|
||||
let stored_field = table.schema().await.unwrap();
|
||||
let data_field = stored_field.field_with_name("data").unwrap();
|
||||
assert_eq!(data_field.data_type(), &DataType::LargeBinary);
|
||||
assert_eq!(
|
||||
data_field
|
||||
.metadata()
|
||||
.get(ARROW_EXT_NAME_KEY)
|
||||
.map(|s| s.as_str()),
|
||||
Some(JSON_EXT_NAME),
|
||||
);
|
||||
|
||||
// Build an arrow.json input field (Utf8/LargeUtf8 + arrow.json extension).
|
||||
// This is what PyArrow produces for pa.json_() arrays.
|
||||
let arrow_json_metadata = std::collections::HashMap::from([(
|
||||
ARROW_EXT_NAME_KEY.to_string(),
|
||||
ARROW_JSON_EXT_NAME.to_string(),
|
||||
)]);
|
||||
let arrow_json_field =
|
||||
Field::new("data", input_type.clone(), true).with_metadata(arrow_json_metadata);
|
||||
let arrow_json_schema = Arc::new(Schema::new(vec![arrow_json_field]));
|
||||
|
||||
let rows: Vec<Option<&str>> = vec![None, Some(r#"{"a": 1}"#), Some(r#"{"b": 2}"#)];
|
||||
let string_array: Arc<dyn arrow_array::Array> = match input_type {
|
||||
DataType::Utf8 => Arc::new(arrow_array::StringArray::from(rows.clone())),
|
||||
DataType::LargeUtf8 => Arc::new(arrow_array::LargeStringArray::from(rows.clone())),
|
||||
other => panic!("unsupported arrow.json backing type for this test: {other:?}"),
|
||||
};
|
||||
let batch = RecordBatch::try_new(arrow_json_schema, vec![string_array]).unwrap();
|
||||
|
||||
// This must not fail with a schema-mismatch error.
|
||||
table.add(batch).execute().await.unwrap();
|
||||
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), rows.len());
|
||||
|
||||
// A lance.json column is read back as Utf8 carrying arrow.json extension metadata.
|
||||
let results: Vec<RecordBatch> = table
|
||||
.query()
|
||||
.select(Select::columns(&["data"]))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
assert_eq!(results.len(), 1);
|
||||
let batch = &results[0];
|
||||
assert_eq!(batch.num_rows(), rows.len());
|
||||
|
||||
let json_col = batch.column(0);
|
||||
assert_eq!(json_col.data_type(), &DataType::Utf8);
|
||||
let json_strs = json_col.as_string::<i32>();
|
||||
|
||||
for (i, expected) in rows.iter().enumerate() {
|
||||
match expected {
|
||||
None => assert!(json_strs.is_null(i), "row {i} expected null"),
|
||||
Some(raw) => {
|
||||
assert!(!json_strs.is_null(i), "row {i} expected non-null");
|
||||
let actual: serde_json::Value = serde_json::from_str(json_strs.value(i))
|
||||
.expect("read-back JSON should be valid");
|
||||
let expected: serde_json::Value =
|
||||
serde_json::from_str(raw).expect("expected JSON should be valid");
|
||||
assert_eq!(actual, expected, "row {i} JSON mismatch");
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -13,7 +13,6 @@ use datafusion_physical_expr::expressions::{CastExpr, Literal};
|
||||
use datafusion_physical_plan::expressions::Column;
|
||||
use datafusion_physical_plan::projection::ProjectionExec;
|
||||
use datafusion_physical_plan::{ExecutionPlan, PhysicalExpr};
|
||||
use lance_arrow::json::{is_arrow_json_field, is_json_field};
|
||||
|
||||
use crate::{Error, Result};
|
||||
|
||||
@@ -65,18 +64,6 @@ fn build_field_exprs(
|
||||
let input_field = &input_fields[input_idx];
|
||||
let input_expr = get_input_expr(input_idx);
|
||||
|
||||
// Special case: input is arrow.json (PyArrow pa.json_() extension type backed by
|
||||
// Utf8/LargeUtf8) and the table field is lance.json (backed by LargeBinary).
|
||||
// Lance-core's write path already handles the arrow.json → lance.json conversion
|
||||
// (including JSONB encoding), so we pass the expression through unchanged and let
|
||||
// lance-core deal with it. Attempting to cast Utf8 → LargeBinary here would
|
||||
// produce a field whose metadata still identifies it as arrow.json, which then
|
||||
// causes a schema-mismatch error inside lance-core.
|
||||
if is_arrow_json_field(input_field) && is_json_field(table_field) {
|
||||
result.push((input_expr, Arc::clone(input_field) as FieldRef));
|
||||
continue;
|
||||
}
|
||||
|
||||
let expr = match (input_field.data_type(), table_field.data_type()) {
|
||||
// Both are structs: recurse into sub-fields to handle subschemas and casts.
|
||||
(DataType::Struct(in_children), DataType::Struct(tbl_children))
|
||||
@@ -631,75 +618,4 @@ mod tests {
|
||||
.unwrap();
|
||||
assert_eq!(a.values(), &[1, 3]);
|
||||
}
|
||||
|
||||
/// `arrow.json` input (PyArrow `pa.json_()`, Utf8/LargeUtf8 + extension metadata) against a
|
||||
/// `lance.json` table field (LargeBinary + extension metadata) must be passed through
|
||||
/// without a cast so that lance-core can perform its own arrow.json → JSONB conversion.
|
||||
///
|
||||
/// Before the fix, `cast_to_table_schema` attempted a `Utf8 → LargeBinary` DataFusion
|
||||
/// cast that preserved the wrong extension metadata, causing lance-core to reject the
|
||||
/// batch with a "json vs large_binary" schema-mismatch error.
|
||||
#[rstest::rstest]
|
||||
#[case::utf8(DataType::Utf8)]
|
||||
#[case::large_utf8(DataType::LargeUtf8)]
|
||||
#[tokio::test]
|
||||
async fn test_arrow_json_passthrough_to_lance_json(#[case] input_type: DataType) {
|
||||
use lance_arrow::ARROW_EXT_NAME_KEY;
|
||||
use lance_arrow::json::{ARROW_JSON_EXT_NAME, json_field};
|
||||
|
||||
// Build a table schema with a lance.json field (LargeBinary + lance.json metadata).
|
||||
let lance_field = json_field("data", true);
|
||||
let table_schema = Schema::new(vec![lance_field]);
|
||||
|
||||
// Build an input batch with an arrow.json field (Utf8/LargeUtf8 + arrow.json metadata).
|
||||
let arrow_meta = std::collections::HashMap::from([(
|
||||
ARROW_EXT_NAME_KEY.to_string(),
|
||||
ARROW_JSON_EXT_NAME.to_string(),
|
||||
)]);
|
||||
let arrow_field = Field::new("data", input_type.clone(), true).with_metadata(arrow_meta);
|
||||
let input_schema = Arc::new(Schema::new(vec![arrow_field]));
|
||||
|
||||
let values = vec![Some(r#"{"x": 1}"#), None, Some(r#"{"y": 2}"#)];
|
||||
let input_array: Arc<dyn arrow_array::Array> = match input_type {
|
||||
DataType::Utf8 => Arc::new(StringArray::from(values)),
|
||||
DataType::LargeUtf8 => Arc::new(arrow_array::LargeStringArray::from(values)),
|
||||
other => panic!("unsupported arrow.json backing type for this test: {other:?}"),
|
||||
};
|
||||
let input_batch = RecordBatch::try_new(input_schema, vec![input_array]).unwrap();
|
||||
|
||||
let plan = plan_from_batch(input_batch).await;
|
||||
let projected = cast_to_table_schema(plan, &table_schema).unwrap();
|
||||
|
||||
// The projected schema's "data" field must carry arrow.json metadata
|
||||
// (the input field), not be silently dropped or miscast.
|
||||
let out_field = projected.schema().field_with_name("data").unwrap().clone();
|
||||
assert_eq!(out_field.data_type(), &input_type);
|
||||
assert_eq!(
|
||||
out_field
|
||||
.metadata()
|
||||
.get(ARROW_EXT_NAME_KEY)
|
||||
.map(|s| s.as_str()),
|
||||
Some(ARROW_JSON_EXT_NAME),
|
||||
"output field must still carry arrow.json metadata so lance-core can handle it"
|
||||
);
|
||||
|
||||
// The data must flow through correctly (3 rows, no panic).
|
||||
let result = collect(projected).await;
|
||||
assert_eq!(result.num_rows(), 3);
|
||||
let (v0, v2) = match input_type {
|
||||
DataType::Utf8 => {
|
||||
let col: &StringArray = result.column(0).as_any().downcast_ref().unwrap();
|
||||
(col.value(0).to_string(), col.value(2).to_string())
|
||||
}
|
||||
DataType::LargeUtf8 => {
|
||||
let col: &arrow_array::LargeStringArray =
|
||||
result.column(0).as_any().downcast_ref().unwrap();
|
||||
(col.value(0).to_string(), col.value(2).to_string())
|
||||
}
|
||||
_ => unreachable!(),
|
||||
};
|
||||
assert_eq!(v0, r#"{"x": 1}"#);
|
||||
assert!(result.column(0).is_null(1));
|
||||
assert_eq!(v2, r#"{"y": 2}"#);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -8,7 +8,6 @@ use std::{
|
||||
|
||||
use lance::{Dataset, dataset::refs};
|
||||
|
||||
use crate::table::merge::lsm::ShardWriterCache;
|
||||
use crate::{Error, error::Result, utils::background_cache::BackgroundCache};
|
||||
|
||||
/// A wrapper around a [Dataset] that provides consistency checks.
|
||||
@@ -19,10 +18,6 @@ use crate::{Error, error::Result, utils::background_cache::BackgroundCache};
|
||||
pub struct DatasetConsistencyWrapper {
|
||||
state: Arc<Mutex<DatasetState>>,
|
||||
consistency: ConsistencyMode,
|
||||
/// The single MemWAL `ShardWriter` for this dataset, co-located so it is
|
||||
/// cached for the session and shares the dataset's lifecycle. A dataset
|
||||
/// writes to one shard at a time. Shared by `Arc` across clones.
|
||||
shard_writer: Arc<ShardWriterCache>,
|
||||
}
|
||||
|
||||
/// The current dataset and whether it is pinned to a specific version.
|
||||
@@ -72,15 +67,9 @@ impl DatasetConsistencyWrapper {
|
||||
pinned_version: None,
|
||||
})),
|
||||
consistency,
|
||||
shard_writer: Arc::new(ShardWriterCache::default()),
|
||||
}
|
||||
}
|
||||
|
||||
/// The MemWAL `ShardWriter` cache co-located with this dataset.
|
||||
pub(crate) fn shard_writer(&self) -> &Arc<ShardWriterCache> {
|
||||
&self.shard_writer
|
||||
}
|
||||
|
||||
/// Get the current dataset.
|
||||
///
|
||||
/// Behavior depends on the consistency mode:
|
||||
|
||||
@@ -1,12 +1,9 @@
|
||||
use std::sync::Arc;
|
||||
|
||||
use futures::FutureExt;
|
||||
use lance::dataset::DeleteBuilder;
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
use super::{NativeTable, Predicate};
|
||||
use super::NativeTable;
|
||||
use crate::Result;
|
||||
|
||||
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize, Default)]
|
||||
@@ -24,39 +21,17 @@ pub struct DeleteResult {
|
||||
/// Internal implementation of the delete logic
|
||||
///
|
||||
/// This logic was moved from NativeTable::delete to keep table.rs clean.
|
||||
pub(crate) async fn execute_delete(
|
||||
table: &NativeTable,
|
||||
predicate: Predicate<'_>,
|
||||
) -> Result<DeleteResult> {
|
||||
pub(crate) async fn execute_delete(table: &NativeTable, predicate: &str) -> Result<DeleteResult> {
|
||||
table.dataset.ensure_mutable()?;
|
||||
match predicate {
|
||||
Predicate::String(s) => {
|
||||
let mut dataset = (*table.dataset.get().await?).clone();
|
||||
let delete_result = dataset.delete(s).boxed().await?;
|
||||
let num_deleted_rows = delete_result.num_deleted_rows;
|
||||
let version = dataset.version().version;
|
||||
table.dataset.update(dataset);
|
||||
Ok(DeleteResult {
|
||||
num_deleted_rows,
|
||||
version,
|
||||
})
|
||||
}
|
||||
Predicate::Expr(expr) => {
|
||||
let dataset = table.dataset.get().await?;
|
||||
let delete_result = DeleteBuilder::from_expr(Arc::clone(&dataset), expr.clone())
|
||||
.execute()
|
||||
.await?;
|
||||
let num_deleted_rows = delete_result.num_deleted_rows;
|
||||
let version = delete_result.new_dataset.version().version;
|
||||
table.dataset.update(
|
||||
Arc::try_unwrap(delete_result.new_dataset).unwrap_or_else(|arc| (*arc).clone()),
|
||||
);
|
||||
Ok(DeleteResult {
|
||||
num_deleted_rows,
|
||||
version,
|
||||
})
|
||||
}
|
||||
}
|
||||
let mut dataset = (*table.dataset.get().await?).clone();
|
||||
let delete_result = dataset.delete(predicate).boxed().await?;
|
||||
let num_deleted_rows = delete_result.num_deleted_rows;
|
||||
let version = dataset.version().version;
|
||||
table.dataset.update(dataset);
|
||||
Ok(DeleteResult {
|
||||
num_deleted_rows,
|
||||
version,
|
||||
})
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
@@ -201,100 +176,4 @@ mod tests {
|
||||
"Table version must increment after delete operation"
|
||||
);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_delete_expr() {
|
||||
use datafusion_expr::{col, lit};
|
||||
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
// 1. Create a table with values 0 to 9
|
||||
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_delete_expr", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// 2. Verify initial state
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 10);
|
||||
let initial_version = table.version().await.unwrap();
|
||||
|
||||
// 3. Execute Delete with Expr (removes values > 5)
|
||||
let expr = col("i").gt(lit(5));
|
||||
table.delete(&expr).await.unwrap();
|
||||
|
||||
// 4. Verify results
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 6); // 0, 1, 2, 3, 4, 5 remain
|
||||
let current_version = table.version().await.unwrap();
|
||||
assert!(
|
||||
current_version > initial_version,
|
||||
"Table version must increment after delete_expr operation"
|
||||
);
|
||||
|
||||
// 5. Verify specific data consistency
|
||||
let batches = table
|
||||
.query()
|
||||
.execute()
|
||||
.await
|
||||
.unwrap()
|
||||
.try_collect::<Vec<_>>()
|
||||
.await
|
||||
.unwrap();
|
||||
let batch = &batches[0];
|
||||
let array = batch
|
||||
.column(0)
|
||||
.as_any()
|
||||
.downcast_ref::<Int32Array>()
|
||||
.unwrap();
|
||||
|
||||
// Ensure no value > 5 exists
|
||||
for val in array.iter() {
|
||||
assert!(val.unwrap() <= 5);
|
||||
}
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn test_delete_expr_increments_version() {
|
||||
use datafusion_expr::lit;
|
||||
|
||||
let conn = connect("memory://").execute().await.unwrap();
|
||||
|
||||
// Create a table with 5 rows
|
||||
let batch = record_batch!(("id", Int32, [1, 2, 3, 4, 5])).unwrap();
|
||||
|
||||
let table = conn
|
||||
.create_table("test_delete_expr_noop", batch)
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Capture the initial state (Rows = 5, Version = 1)
|
||||
let initial_rows = table.count_rows(None).await.unwrap();
|
||||
let initial_version = table.version().await.unwrap();
|
||||
|
||||
assert_eq!(initial_rows, 5);
|
||||
let expr = lit(false);
|
||||
table.delete(&expr).await.unwrap();
|
||||
|
||||
// Rows should still be 5
|
||||
let current_rows = table.count_rows(None).await.unwrap();
|
||||
assert_eq!(
|
||||
current_rows, initial_rows,
|
||||
"Data should not change when predicate is false"
|
||||
);
|
||||
|
||||
// version check
|
||||
let current_version = table.version().await.unwrap();
|
||||
assert!(
|
||||
current_version > initial_version,
|
||||
"Table version must increment after delete_expr operation"
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -41,16 +41,6 @@ pub struct MergeResult {
|
||||
/// A value of 1 means the operation succeeded on the first try.
|
||||
#[serde(default)]
|
||||
pub num_attempts: u32,
|
||||
/// Total number of rows written.
|
||||
///
|
||||
/// On the standard `merge_insert` path this equals
|
||||
/// `num_inserted_rows + num_updated_rows`. On the MemWAL LSM write path the
|
||||
/// insert/update breakdown is not known until compaction; in that mode
|
||||
/// `num_inserted_rows`, `num_updated_rows`, `num_deleted_rows`, `version`
|
||||
/// and `num_attempts` are all `0` and this field holds the total number of
|
||||
/// rows written through the shard writer.
|
||||
#[serde(default)]
|
||||
pub num_rows: u64,
|
||||
}
|
||||
|
||||
/// A builder used to create and run a merge insert operation
|
||||
@@ -67,8 +57,6 @@ pub struct MergeInsertBuilder {
|
||||
pub(crate) when_not_matched_by_source_delete_filt: Option<String>,
|
||||
pub(crate) timeout: Option<Duration>,
|
||||
pub(crate) use_index: bool,
|
||||
pub(crate) use_lsm_write: Option<bool>,
|
||||
pub(crate) validate_single_shard: bool,
|
||||
}
|
||||
|
||||
impl MergeInsertBuilder {
|
||||
@@ -83,8 +71,6 @@ impl MergeInsertBuilder {
|
||||
when_not_matched_by_source_delete_filt: None,
|
||||
timeout: None,
|
||||
use_index: true,
|
||||
use_lsm_write: None,
|
||||
validate_single_shard: true,
|
||||
}
|
||||
}
|
||||
|
||||
@@ -164,34 +150,6 @@ impl MergeInsertBuilder {
|
||||
self
|
||||
}
|
||||
|
||||
/// Controls whether `merge_insert` uses the MemWAL LSM write path.
|
||||
///
|
||||
/// By default (unset), a `merge_insert` on a table with an
|
||||
/// [`LsmWriteSpec`](super::LsmWriteSpec) installed is routed through
|
||||
/// Lance's MemWAL shard writer, and a table without one uses the standard
|
||||
/// path. Calling this with `false` forces the standard path even when a
|
||||
/// spec is set. Calling it with `true` requires a spec — `merge_insert`
|
||||
/// errors if none is installed.
|
||||
pub fn use_lsm_write(&mut self, use_lsm_write: bool) -> &mut Self {
|
||||
self.use_lsm_write = Some(use_lsm_write);
|
||||
self
|
||||
}
|
||||
|
||||
/// Controls how an LSM `merge_insert` checks that its input targets a
|
||||
/// single shard.
|
||||
///
|
||||
/// When a table has an LSM write spec, every row in a `merge_insert` call
|
||||
/// must route to the same shard. When `true` (the default), every row is
|
||||
/// inspected to verify this. When `false`, only the first row is inspected
|
||||
/// and the shard it routes to is used for the whole input — a faster path
|
||||
/// for callers that have already pre-sharded their input.
|
||||
///
|
||||
/// Has no effect on tables without an LSM write spec.
|
||||
pub fn validate_single_shard(&mut self, validate_single_shard: bool) -> &mut Self {
|
||||
self.validate_single_shard = validate_single_shard;
|
||||
self
|
||||
}
|
||||
|
||||
/// Executes the merge insert operation
|
||||
///
|
||||
/// Returns version and statistics about the merge operation including the number of rows
|
||||
@@ -209,23 +167,6 @@ pub(crate) async fn execute_merge_insert(
|
||||
params: MergeInsertBuilder,
|
||||
new_data: Box<dyn RecordBatchReader + Send>,
|
||||
) -> Result<MergeResult> {
|
||||
match lsm::lsm_dispatch_decision(table, ¶ms).await? {
|
||||
lsm::LsmDispatch::Lsm(plan) => {
|
||||
let future =
|
||||
lsm::execute_lsm_merge_insert(table, plan, params.validate_single_shard, new_data);
|
||||
return match params.timeout {
|
||||
Some(timeout) => match tokio::time::timeout(timeout, future).await {
|
||||
Ok(result) => result,
|
||||
Err(_) => Err(Error::Runtime {
|
||||
message: "merge insert timed out".to_string(),
|
||||
}),
|
||||
},
|
||||
None => future.await,
|
||||
};
|
||||
}
|
||||
lsm::LsmDispatch::Standard => {}
|
||||
}
|
||||
|
||||
let dataset = table.dataset.get().await?;
|
||||
let mut builder = LanceMergeInsertBuilder::try_new(dataset.clone(), params.on)?;
|
||||
match (
|
||||
@@ -278,7 +219,6 @@ pub(crate) async fn execute_merge_insert(
|
||||
num_inserted_rows: stats.num_inserted_rows,
|
||||
num_deleted_rows: stats.num_deleted_rows,
|
||||
num_attempts: stats.num_attempts,
|
||||
num_rows: stats.num_inserted_rows + stats.num_updated_rows,
|
||||
})
|
||||
}
|
||||
|
||||
@@ -387,366 +327,3 @@ mod tests {
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 25);
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod lsm_tests {
|
||||
use std::sync::Arc;
|
||||
|
||||
use arrow_array::{
|
||||
Int64Array, RecordBatch, RecordBatchIterator, RecordBatchReader, StringArray,
|
||||
};
|
||||
use arrow_schema::{DataType, Field, Schema};
|
||||
use tempfile::{TempDir, tempdir};
|
||||
|
||||
use crate::connect;
|
||||
use crate::error::Error;
|
||||
use crate::table::{LsmWriteSpec, Table};
|
||||
|
||||
/// A reader of `[id: Int64, value: Int64]` rows; `value` is `0..n`.
|
||||
fn id_value_reader(ids: Vec<i64>) -> Box<dyn RecordBatchReader + Send> {
|
||||
let schema = Arc::new(Schema::new(vec![
|
||||
Field::new("id", DataType::Int64, false),
|
||||
Field::new("value", DataType::Int64, false),
|
||||
]));
|
||||
let n = ids.len() as i64;
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![
|
||||
Arc::new(Int64Array::from(ids)),
|
||||
Arc::new(Int64Array::from_iter_values(0..n)),
|
||||
],
|
||||
)
|
||||
.unwrap();
|
||||
Box::new(RecordBatchIterator::new(vec![Ok(batch)], schema))
|
||||
}
|
||||
|
||||
/// A reader of `[id: Int64, region: Utf8]` rows.
|
||||
fn id_region_reader(rows: Vec<(i64, &str)>) -> Box<dyn RecordBatchReader + Send> {
|
||||
let schema = Arc::new(Schema::new(vec![
|
||||
Field::new("id", DataType::Int64, false),
|
||||
Field::new("region", DataType::Utf8, false),
|
||||
]));
|
||||
let ids: Vec<i64> = rows.iter().map(|(id, _)| *id).collect();
|
||||
let regions: Vec<&str> = rows.iter().map(|(_, region)| *region).collect();
|
||||
let batch = RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![
|
||||
Arc::new(Int64Array::from(ids)),
|
||||
Arc::new(StringArray::from(regions)),
|
||||
],
|
||||
)
|
||||
.unwrap();
|
||||
Box::new(RecordBatchIterator::new(vec![Ok(batch)], schema))
|
||||
}
|
||||
|
||||
/// A multi-batch reader of `[id: Int64, region: Utf8]` rows.
|
||||
fn id_region_multi_reader(batches: Vec<Vec<(i64, &str)>>) -> Box<dyn RecordBatchReader + Send> {
|
||||
let schema = Arc::new(Schema::new(vec![
|
||||
Field::new("id", DataType::Int64, false),
|
||||
Field::new("region", DataType::Utf8, false),
|
||||
]));
|
||||
let records: Vec<_> = batches
|
||||
.into_iter()
|
||||
.map(|rows| {
|
||||
let ids: Vec<i64> = rows.iter().map(|(id, _)| *id).collect();
|
||||
let regions: Vec<&str> = rows.iter().map(|(_, region)| *region).collect();
|
||||
Ok(RecordBatch::try_new(
|
||||
schema.clone(),
|
||||
vec![
|
||||
Arc::new(Int64Array::from(ids)),
|
||||
Arc::new(StringArray::from(regions)),
|
||||
],
|
||||
)
|
||||
.unwrap())
|
||||
})
|
||||
.collect();
|
||||
Box::new(RecordBatchIterator::new(records, schema))
|
||||
}
|
||||
|
||||
/// Create an `[id, value]` table with `id` as the unenforced primary key.
|
||||
async fn id_value_table(dir: &TempDir) -> Table {
|
||||
let conn = connect(dir.path().to_str().unwrap())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let table = conn
|
||||
.create_table("t", id_value_reader(vec![1, 2, 3]))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
table.set_unenforced_primary_key(["id"]).await.unwrap();
|
||||
table
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn lsm_merge_insert_bucket() {
|
||||
let dir = tempdir().unwrap();
|
||||
let table = id_value_table(&dir).await;
|
||||
// num_buckets = 1: every row routes to the single bucket.
|
||||
table
|
||||
.set_lsm_write_spec(LsmWriteSpec::bucket("id", 1))
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Empty `on` defaults to the primary key.
|
||||
let mut builder = table.merge_insert(&[]);
|
||||
builder
|
||||
.when_matched_update_all(None)
|
||||
.when_not_matched_insert_all();
|
||||
let result = builder
|
||||
.execute(id_value_reader(vec![3, 4, 5]))
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// LSM path: rows go to the MemWAL, the breakdown is unknown until
|
||||
// compaction, so only `num_rows` is populated.
|
||||
assert_eq!(result.num_rows, 3);
|
||||
assert_eq!(result.version, 0);
|
||||
assert_eq!(result.num_inserted_rows, 0);
|
||||
assert_eq!(result.num_updated_rows, 0);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn lsm_merge_insert_unsharded() {
|
||||
let dir = tempdir().unwrap();
|
||||
let table = id_value_table(&dir).await;
|
||||
table
|
||||
.set_lsm_write_spec(LsmWriteSpec::unsharded())
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let mut builder = table.merge_insert(&["id"]);
|
||||
builder
|
||||
.when_matched_update_all(None)
|
||||
.when_not_matched_insert_all();
|
||||
let result = builder
|
||||
.execute(id_value_reader(vec![10, 11, 12, 13]))
|
||||
.await
|
||||
.unwrap();
|
||||
assert_eq!(result.num_rows, 4);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn lsm_merge_insert_identity() {
|
||||
let dir = tempdir().unwrap();
|
||||
let conn = connect(dir.path().to_str().unwrap())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let table = conn
|
||||
.create_table("t", id_region_reader(vec![(1, "us"), (2, "us")]))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
table.set_unenforced_primary_key(["id"]).await.unwrap();
|
||||
table
|
||||
.set_lsm_write_spec(LsmWriteSpec::identity("region"))
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// All rows share one identity value, so they route to one shard.
|
||||
let mut builder = table.merge_insert(&[]);
|
||||
builder
|
||||
.when_matched_update_all(None)
|
||||
.when_not_matched_insert_all();
|
||||
let result = builder
|
||||
.execute(id_region_reader(vec![(3, "us"), (4, "us")]))
|
||||
.await
|
||||
.unwrap();
|
||||
assert_eq!(result.num_rows, 2);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn lsm_merge_insert_use_lsm_write_false_falls_back() {
|
||||
let dir = tempdir().unwrap();
|
||||
let table = id_value_table(&dir).await;
|
||||
table
|
||||
.set_lsm_write_spec(LsmWriteSpec::bucket("id", 1))
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// use_lsm_write(false) opts out: the standard path runs and commits.
|
||||
let mut builder = table.merge_insert(&["id"]);
|
||||
builder.when_not_matched_insert_all().use_lsm_write(false);
|
||||
let result = builder
|
||||
.execute(id_value_reader(vec![3, 4, 5]))
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
assert_eq!(result.num_inserted_rows, 2);
|
||||
assert_eq!(table.count_rows(None).await.unwrap(), 5);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn lsm_merge_insert_rejects_on_not_primary_key() {
|
||||
let dir = tempdir().unwrap();
|
||||
let table = id_value_table(&dir).await;
|
||||
table
|
||||
.set_lsm_write_spec(LsmWriteSpec::bucket("id", 1))
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let mut builder = table.merge_insert(&["value"]);
|
||||
builder
|
||||
.when_matched_update_all(None)
|
||||
.when_not_matched_insert_all();
|
||||
let err = builder.execute(id_value_reader(vec![1])).await.unwrap_err();
|
||||
assert!(matches!(err, Error::InvalidInput { .. }), "got {err:?}");
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn lsm_merge_insert_rejects_non_upsert() {
|
||||
let dir = tempdir().unwrap();
|
||||
let table = id_value_table(&dir).await;
|
||||
table
|
||||
.set_lsm_write_spec(LsmWriteSpec::bucket("id", 1))
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Insert-only (no when_matched_update_all) is not the upsert shape.
|
||||
let mut builder = table.merge_insert(&[]);
|
||||
builder.when_not_matched_insert_all();
|
||||
let err = builder.execute(id_value_reader(vec![4])).await.unwrap_err();
|
||||
assert!(matches!(err, Error::InvalidInput { .. }), "got {err:?}");
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn lsm_close_writers_then_reopen() {
|
||||
let dir = tempdir().unwrap();
|
||||
let table = id_value_table(&dir).await;
|
||||
table
|
||||
.set_lsm_write_spec(LsmWriteSpec::bucket("id", 1))
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
let mut builder = table.merge_insert(&[]);
|
||||
builder
|
||||
.when_matched_update_all(None)
|
||||
.when_not_matched_insert_all();
|
||||
builder.execute(id_value_reader(vec![7, 8])).await.unwrap();
|
||||
|
||||
table.close_lsm_writers().await.unwrap();
|
||||
|
||||
// The writer reopens lazily on the next merge_insert.
|
||||
let mut builder = table.merge_insert(&[]);
|
||||
builder
|
||||
.when_matched_update_all(None)
|
||||
.when_not_matched_insert_all();
|
||||
let result = builder.execute(id_value_reader(vec![9])).await.unwrap();
|
||||
assert_eq!(result.num_rows, 1);
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn lsm_merge_insert_multi_batch() {
|
||||
let dir = tempdir().unwrap();
|
||||
let conn = connect(dir.path().to_str().unwrap())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let table = conn
|
||||
.create_table("t", id_region_reader(vec![(1, "us")]))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
table.set_unenforced_primary_key(["id"]).await.unwrap();
|
||||
table
|
||||
.set_lsm_write_spec(LsmWriteSpec::identity("region"))
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// Multiple batches that all route to one shard are written together.
|
||||
let mut builder = table.merge_insert(&[]);
|
||||
builder
|
||||
.when_matched_update_all(None)
|
||||
.when_not_matched_insert_all();
|
||||
let result = builder
|
||||
.execute(id_region_multi_reader(vec![
|
||||
vec![(2, "us"), (3, "us")],
|
||||
vec![(4, "us")],
|
||||
]))
|
||||
.await
|
||||
.unwrap();
|
||||
assert_eq!(result.num_rows, 3);
|
||||
|
||||
// Batches that route to different shards are rejected; the validation
|
||||
// runs before any write, so no partial write is left behind.
|
||||
let mut builder = table.merge_insert(&[]);
|
||||
builder
|
||||
.when_matched_update_all(None)
|
||||
.when_not_matched_insert_all();
|
||||
let err = builder
|
||||
.execute(id_region_multi_reader(vec![
|
||||
vec![(5, "us")],
|
||||
vec![(6, "eu")],
|
||||
]))
|
||||
.await
|
||||
.unwrap_err();
|
||||
assert!(matches!(err, Error::InvalidInput { .. }), "got {err:?}");
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn lsm_merge_insert_use_lsm_write_true_requires_spec() {
|
||||
let dir = tempdir().unwrap();
|
||||
// id_value_table sets a primary key but no LSM write spec.
|
||||
let table = id_value_table(&dir).await;
|
||||
|
||||
let mut builder = table.merge_insert(&["id"]);
|
||||
builder
|
||||
.when_matched_update_all(None)
|
||||
.when_not_matched_insert_all()
|
||||
.use_lsm_write(true);
|
||||
let err = builder.execute(id_value_reader(vec![4])).await.unwrap_err();
|
||||
assert!(matches!(err, Error::InvalidInput { .. }), "got {err:?}");
|
||||
}
|
||||
|
||||
#[tokio::test]
|
||||
async fn lsm_merge_insert_rejects_second_shard() {
|
||||
let dir = tempdir().unwrap();
|
||||
let conn = connect(dir.path().to_str().unwrap())
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
let table = conn
|
||||
.create_table("t", id_region_reader(vec![(1, "us")]))
|
||||
.execute()
|
||||
.await
|
||||
.unwrap();
|
||||
table.set_unenforced_primary_key(["id"]).await.unwrap();
|
||||
table
|
||||
.set_lsm_write_spec(LsmWriteSpec::identity("region"))
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// The first merge_insert opens the single writer for shard "us".
|
||||
let mut builder = table.merge_insert(&[]);
|
||||
builder
|
||||
.when_matched_update_all(None)
|
||||
.when_not_matched_insert_all();
|
||||
builder
|
||||
.execute(id_region_reader(vec![(2, "us")]))
|
||||
.await
|
||||
.unwrap();
|
||||
|
||||
// A merge_insert routing to a different shard is rejected.
|
||||
let mut builder = table.merge_insert(&[]);
|
||||
builder
|
||||
.when_matched_update_all(None)
|
||||
.when_not_matched_insert_all();
|
||||
let err = builder
|
||||
.execute(id_region_reader(vec![(3, "eu")]))
|
||||
.await
|
||||
.unwrap_err();
|
||||
assert!(matches!(err, Error::InvalidInput { .. }), "got {err:?}");
|
||||
|
||||
// After closing the writer, a different shard can be written.
|
||||
table.close_lsm_writers().await.unwrap();
|
||||
let mut builder = table.merge_insert(&[]);
|
||||
builder
|
||||
.when_matched_update_all(None)
|
||||
.when_not_matched_insert_all();
|
||||
builder
|
||||
.execute(id_region_reader(vec![(4, "eu")]))
|
||||
.await
|
||||
.unwrap();
|
||||
}
|
||||
}
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -6,7 +6,7 @@ pub(crate) mod background_cache;
|
||||
use std::sync::Arc;
|
||||
|
||||
use arrow_array::RecordBatch;
|
||||
use arrow_schema::{DataType, Field, Schema, SchemaRef};
|
||||
use arrow_schema::{DataType, Field, Fields, Schema, SchemaRef};
|
||||
use datafusion_common::{DataFusionError, Result as DataFusionResult};
|
||||
use datafusion_execution::RecordBatchStream;
|
||||
use futures::{FutureExt, Stream};
|
||||
@@ -199,32 +199,38 @@ fn collect_vector_columns(
|
||||
path.pop();
|
||||
}
|
||||
|
||||
pub(crate) fn resolve_arrow_field_path(schema: &Schema, column: &str) -> Result<(String, Field)> {
|
||||
lance_core::datatypes::parse_field_path(column).map_err(|e| Error::InvalidInput {
|
||||
message: format!("Invalid field path `{}`: {}", column, e),
|
||||
})?;
|
||||
pub(crate) fn resolve_arrow_field_path(schema: &Schema, column: &str) -> Result<Field> {
|
||||
let segments =
|
||||
lance_core::datatypes::parse_field_path(column).map_err(|e| Error::InvalidInput {
|
||||
message: format!("Invalid field path `{}`: {}", column, e),
|
||||
})?;
|
||||
let mut fields = schema.fields();
|
||||
|
||||
let lance_schema =
|
||||
lance_core::datatypes::Schema::try_from(schema).map_err(|e| Error::Schema {
|
||||
message: format!("Invalid schema: {}", e),
|
||||
for (idx, segment) in segments.iter().enumerate() {
|
||||
let field = find_field(fields, segment).ok_or_else(|| Error::Schema {
|
||||
message: format!("Field path `{}` not found in schema", column),
|
||||
})?;
|
||||
let field_path = lance_schema
|
||||
.resolve_case_insensitive(column)
|
||||
.ok_or_else(|| Error::Schema {
|
||||
message: format!(
|
||||
"Field path `{}` not found in schema. Available field paths: {}",
|
||||
column,
|
||||
lance_schema.field_paths().join(", ")
|
||||
),
|
||||
})?;
|
||||
let field = field_path.last().expect("field path should be non-empty");
|
||||
let path_segments = field_path
|
||||
if idx + 1 == segments.len() {
|
||||
return Ok(field.clone());
|
||||
}
|
||||
fields = match field.data_type() {
|
||||
DataType::Struct(fields) => fields,
|
||||
_ => {
|
||||
return Err(Error::Schema {
|
||||
message: format!("Field path `{}` not found in schema", column),
|
||||
});
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
unreachable!("parse_field_path returns at least one segment")
|
||||
}
|
||||
|
||||
fn find_field<'a>(fields: &'a Fields, name: &str) -> Option<&'a Field> {
|
||||
fields
|
||||
.iter()
|
||||
.map(|field| field.name.as_str())
|
||||
.collect::<Vec<_>>();
|
||||
let canonical_path = lance_core::datatypes::format_field_path(&path_segments);
|
||||
|
||||
Ok((canonical_path, Field::from(*field)))
|
||||
.find(|field| field.name() == name)
|
||||
.map(|field| field.as_ref())
|
||||
}
|
||||
|
||||
pub fn supported_btree_data_type(dtype: &DataType) -> bool {
|
||||
|
||||
Reference in New Issue
Block a user