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8 Commits

Author SHA1 Message Date
Xuanwo fce9bfc3c7 fix(ci): allow recovery artifact downloads 2026-08-10 18:00:09 +08:00
Xuanwo 67fe08bf71 fix(ci): recover timed-out Windows release builds 2026-08-10 17:52:48 +08:00
Lance Release b89f87f206 Bump version: 0.37.1-beta.3 → 0.37.1 2026-08-10 07:54:42 +00:00
Lance Release a022d3bcb3 Bump version: 0.37.1-beta.2 → 0.37.1-beta.3 2026-08-10 07:53:53 +00:00
Lance Release 8268532d64 Bump version: 0.37.1-beta.1 → 0.37.1-beta.2 2026-08-10 06:30:45 +00:00
Xuanwo f933ef9b21 fix(ci): tag releases after updating lockfiles 2026-08-10 14:23:41 +08:00
Xuanwo e885e5dd00 fix(ci): validate stable Lance dependencies 2026-08-10 14:23:33 +08:00
Xuanwo 7c7efa9743 feat: update lance dependency to v10.0.0 2026-08-10 14:23:29 +08:00
86 changed files with 1077 additions and 6691 deletions
+1 -1
View File
@@ -1,5 +1,5 @@
[tool.bumpversion]
current_version = "0.38.0-beta.2"
current_version = "0.37.1"
parse = """(?x)
(?P<major>0|[1-9]\\d*)\\.
(?P<minor>0|[1-9]\\d*)\\.
@@ -4,14 +4,14 @@ on:
workflow_call:
inputs:
tag:
description: "Tag name from Lance (e.g. `v7.2.0-beta.1`). If omitted, the newest release is resolved automatically — stable releases are preferred over pre-releases — and the run is skipped if it is not newer than the version currently pinned in Cargo.toml."
description: "Tag name from Lance. If omitted, the skill will use the latest Lance release that needs an update."
required: false
default: ""
type: string
workflow_dispatch:
inputs:
tag:
description: "Tag name from Lance (e.g. `v7.2.0-beta.1`). Leave empty to resolve the newest release automatically — stable releases are preferred over pre-releases — and skip the run if it is not newer than the version currently pinned in Cargo.toml."
description: "Tag name from Lance. Leave empty to use the latest Lance release that needs an update."
required: false
default: ""
type: string
+49 -70
View File
@@ -36,9 +36,7 @@ jobs:
permissions:
contents: read
outputs:
checker_outcome: ${{ steps.lychee.outcome }}
exit_code: ${{ steps.lychee.outputs.exit_code }}
status: ${{ steps.validate.outputs.status }}
steps:
- name: Checkout
uses: actions/checkout@v6
@@ -52,7 +50,6 @@ jobs:
- name: Check links
id: lychee
continue-on-error: true
uses: lycheeverse/lychee-action@e7477775783ea5526144ba13e8db5eec57747ce8 # v2.9.0
with:
# Restricted to http(s) on purpose. Much of docs/src is generated
@@ -71,50 +68,38 @@ jobs:
format: json
output: ./lychee/out.json
jobSummary: false
# The report issue, not a red workflow run, is the signal for link
# findings and checker failures alike.
# The report, not a red build, is the signal for broken links. The
# validation step below still fails the run if the check itself
# breaks.
fail: false
- name: Validate report
id: validate
# lychee does not reserve exit code 2 for broken links: its CLI
# parser also exits 2 on an invalid option, before any link was
# checked or any report written. Only a parseable report whose
# counts agree with a completed exit code (0 or 2) counts as a link
# verdict. Everything else becomes a checker-error report instead of
# failing the workflow. Exit 2 covers timeouts as well as errors, and a
# timed-out host is exactly the transient unavailability this report
# exists to surface, so both count as findings. Requiring total > 0
# also catches a glob that silently stopped matching any file.
if: always()
# counts agree with the exit code counts as a link verdict; anything
# else fails here, and the report job below is skipped entirely, so
# the tracking issue is never touched. Exit 2 covers timeouts as
# well as errors, and a timed-out host is exactly the transient
# unavailability this report exists to surface, so both count as
# findings. Requiring total > 0 also catches a glob that silently
# stopped matching any file.
if: steps.lychee.outputs.exit_code == 0 || steps.lychee.outputs.exit_code == 2
env:
CHECKER_OUTCOME: ${{ steps.lychee.outcome }}
EXIT_CODE: ${{ steps.lychee.outputs.exit_code }}
run: |
status=checker-error
if [[ "$CHECKER_OUTCOME" == success ]] &&
[[ "$EXIT_CODE" == 0 || "$EXIT_CODE" == 2 ]] &&
jq -e --argjson code "$EXIT_CODE" '
(.total > 0) and
(if $code == 0
then .errors == 0 and .timeouts == 0
and (.error_map | length == 0) and (.timeout_map | length == 0)
else (.errors + .timeouts) > 0
and ((.error_map | length) + (.timeout_map | length)) > 0
end)
' ./lychee/out.json
then
if [[ "$EXIT_CODE" == 0 ]]; then
status=healthy
else
status=findings
fi
fi
echo "status=$status" >> "$GITHUB_OUTPUT"
echo "Validated link check as $status"
jq -e --argjson code "$EXIT_CODE" '
(.total > 0) and
(if $code == 0
then .errors == 0 and .timeouts == 0
and (.error_map | length == 0) and (.timeout_map | length == 0)
else (.errors + .timeouts) > 0
and ((.error_map | length) + (.timeout_map | length)) > 0
end)
' ./lychee/out.json
- name: Upload report
if: steps.validate.outputs.status == 'findings'
if: steps.lychee.outputs.exit_code == 2
uses: actions/upload-artifact@v7
with:
name: link-report
@@ -130,11 +115,26 @@ jobs:
permissions:
issues: write
env:
CHECKER_OUTCOME: ${{ needs.scan.outputs.checker_outcome }}
EXIT_CODE: ${{ needs.scan.outputs.exit_code }}
STATUS: ${{ needs.scan.outputs.status }}
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
steps:
- name: Classify checker result
# lychee exits 0 when every link resolves and 2 when links fail,
# both already cross-checked against the report by the scan job's
# validation step. Anything else (1 runtime, 3 bad config) means the
# check never produced a link verdict, which must surface as a failed
# run rather than be published as "broken documentation links".
run: |
case "$EXIT_CODE" in
0|2)
echo "lychee exit code $EXIT_CODE"
;;
*)
echo "::error::lychee exited with '$EXIT_CODE': the link check did not complete. Leaving the report issue untouched."
exit 1
;;
esac
- name: Find existing report issue
id: report
# Matched on title alone, and through search rather than a listing:
@@ -144,7 +144,7 @@ jobs:
# Closed issues are included because a healthy run closes the report:
# an open-only lookup would forget that identity and the next failing
# run would open a duplicate. The oldest match stays the canonical
# report and is reopened below when a problem recurs.
# report and is reopened below when links break again.
run: |
match=$(gh issue list --repo "$GITHUB_REPOSITORY" --state all \
--search "in:title \"$REPORT_TITLE\" author:app/github-actions" \
@@ -154,14 +154,14 @@ jobs:
echo "state=$(jq -r '.state // empty' <<<"$match")" >> "$GITHUB_OUTPUT"
- name: Download report
if: env.STATUS == 'findings'
if: env.EXIT_CODE == 2
uses: actions/download-artifact@v8
with:
name: link-report
path: ./lychee
- name: Compose report
if: env.STATUS == 'findings'
if: env.EXIT_CODE == 2
run: |
run_url="$GITHUB_SERVER_URL/$GITHUB_REPOSITORY/actions/runs/$GITHUB_RUN_ID"
{
@@ -185,41 +185,22 @@ jobs:
' ./lychee/out.json
} > ./lychee/issue.md
- name: Compose checker error report
if: env.STATUS == 'checker-error'
run: |
mkdir -p ./lychee
run_url="$GITHUB_SERVER_URL/$GITHUB_REPOSITORY/actions/runs/$GITHUB_RUN_ID"
{
echo "The documentation link check did not complete in [the latest run]($run_url)."
echo
echo "This issue is rewritten by every scheduled run and closed automatically once a trustworthy run finds that all links resolve."
echo
echo "The checker did not produce a trustworthy link verdict. Treat the previous result, if any, as stale until a later run completes."
echo
echo "* Action outcome: \`$CHECKER_OUTCOME\`"
echo "* Exit code: \`${EXIT_CODE:-not reported}\`"
echo "* Verdict validation: \`failed\`"
} > ./lychee/issue.md
- name: Reopen report issue
# A healthy run closes the report, and the issue action below only
# rewrites the body of whatever number it is given. Without an
# explicit reopen, a later finding or checker error would rewrite a
# closed issue. A CLOSED state implies the lookup found a canonical
# issue, so no separate emptiness check.
if: >-
env.STATUS != 'healthy' &&
steps.report.outputs.state == 'CLOSED'
# explicit reopen, the 2 -> 0 -> 2 sequence would keep rewriting a
# closed issue while links are broken. A CLOSED state implies the
# lookup found a canonical issue, so no separate emptiness check.
if: env.EXIT_CODE == 2 && steps.report.outputs.state == 'CLOSED'
env:
ISSUE_NUMBER: ${{ steps.report.outputs.number }}
run: |
run_url="$GITHUB_SERVER_URL/$GITHUB_REPOSITORY/actions/runs/$GITHUB_RUN_ID"
gh issue reopen "$ISSUE_NUMBER" --repo "$GITHUB_REPOSITORY" \
--comment "The documentation link checker reported a problem again in [the latest run]($run_url)."
--comment "Broken documentation links found again in [the latest run]($run_url)."
- name: Report link-check problem
if: env.STATUS != 'healthy'
- name: Report broken links
if: env.EXIT_CODE == 2
uses: peter-evans/create-issue-from-file@fca9117c27cdc29c6c4db3b86c48e4115a786710 # v6.0.0
with:
# Empty on the first failing run, which creates the issue; afterwards
@@ -232,9 +213,7 @@ jobs:
- name: Close report issue once links are healthy
# An OPEN state implies the lookup found a canonical issue; a report
# that is already closed needs nothing.
if: >-
env.STATUS == 'healthy' &&
steps.report.outputs.state == 'OPEN'
if: env.EXIT_CODE == 0 && steps.report.outputs.state == 'OPEN'
env:
ISSUE_NUMBER: ${{ steps.report.outputs.number }}
run: |
+4 -2
View File
@@ -1,7 +1,8 @@
name: Create release commit
# This workflow increments the version, tags it, and pushes it. All SDKs share
# a single version, so one tag releases all of them.
# This workflow increments the version, updates lockfiles, tags the final
# commit, and pushes it. All SDKs share a single version, so one tag releases
# all of them.
# When a tag is pushed, another workflow is triggered that creates a GH release
# and uploads the binaries. This workflow is only for creating the tag.
@@ -63,6 +64,7 @@ jobs:
pip install bump-my-version PyGithub packaging
bash ci/bump_version.sh ${{ inputs.type }} ${{ inputs.bump-minor }}
bash ci/update_lockfiles.sh --amend
bash ci/create_release_tag.sh
- name: Push new version tag
if: ${{ !inputs.dry_run }}
uses: ad-m/github-push-action@881a6320fdb16eb5318c5054f31c218aec2b324c # v1.3.0
+110 -14
View File
@@ -4,6 +4,16 @@ on:
push:
tags:
- 'v*'
workflow_dispatch:
inputs:
release_tag:
description: Stable release tag to recover (for example, v0.37.1)
required: true
type: string
source_run_id:
description: Failed tag workflow run containing the completed non-Windows wheels
required: true
type: string
pull_request:
# This should trigger a dry run (we skip the final publish step)
paths:
@@ -29,6 +39,7 @@ concurrency:
jobs:
linux:
name: Python ${{ matrix.config.package_name }} ${{ matrix.config.platform }} manylinux${{ matrix.config.manylinux }}
if: github.event_name != 'workflow_dispatch'
timeout-minutes: 60
strategy:
matrix:
@@ -69,16 +80,6 @@ jobs:
uses: actions/setup-python@v6
with:
python-version: "3.10"
- name: Add swap for Arm fat LTO
if: matrix.config.platform == 'aarch64'
shell: bash
run: |
swap_file="$RUNNER_TEMP/lancedb-swap"
sudo fallocate --length 16G "$swap_file"
sudo chmod 600 "$swap_file"
sudo mkswap "$swap_file"
sudo swapon "$swap_file"
free -h
- uses: ./.github/workflows/build_linux_wheel
with:
python-minor-version: 10
@@ -94,6 +95,7 @@ jobs:
path: target/wheels/*.whl
if-no-files-found: error
mac:
if: github.event_name != 'workflow_dispatch'
timeout-minutes: 90
runs-on: ${{ matrix.config.runner }}
strategy:
@@ -123,7 +125,8 @@ jobs:
path: target/wheels/lancedb-*.whl
if-no-files-found: error
windows:
timeout-minutes: 90
if: github.event_name != 'workflow_dispatch'
timeout-minutes: 120
runs-on: windows-latest
env:
# link.exe is single-threaded and the long pole on Windows builds. Use
@@ -155,6 +158,32 @@ jobs:
name: wheels-windows
path: target/wheels/lancedb-*.whl
if-no-files-found: error
recover-windows:
name: Recover Windows wheel
if: github.event_name == 'workflow_dispatch'
timeout-minutes: 120
runs-on: windows-latest
env:
CARGO_TARGET_X86_64_PC_WINDOWS_MSVC_LINKER: rust-lld
steps:
- uses: actions/checkout@v6
with:
ref: ${{ inputs.release_tag }}
fetch-depth: 0
lfs: true
- name: Set up Python
uses: actions/setup-python@v6
with:
python-version: "3.13"
- uses: ./.github/workflows/build_windows_wheel
with:
python-minor-version: 10
args: "--release --strip"
- uses: actions/upload-artifact@v7
with:
name: wheels-windows-recovery
path: target/wheels/lancedb-*.whl
if-no-files-found: error
publish:
name: Publish wheels
if: startsWith(github.ref, 'refs/tags/v')
@@ -175,11 +204,13 @@ jobs:
run: ls -la target/wheels
- name: Choose repo
id: choose_repo
env:
RELEASE_REF: ${{ github.ref }}
run: |
if [[ ${{ github.ref }} == *beta* ]]; then
echo "repo=fury" >> $GITHUB_OUTPUT
if [[ "$RELEASE_REF" == *beta* ]]; then
echo "repo=fury" >> "$GITHUB_OUTPUT"
else
echo "repo=pypi" >> $GITHUB_OUTPUT
echo "repo=pypi" >> "$GITHUB_OUTPUT"
fi
- name: Publish to Fury
if: steps.choose_repo.outputs.repo == 'fury'
@@ -206,6 +237,71 @@ jobs:
uses: pypa/gh-action-pypi-publish@release/v1
with:
packages-dir: target/wheels/
recover-publish:
name: Recover PyPI publish
if: github.event_name == 'workflow_dispatch'
needs: [recover-windows]
runs-on: ubuntu-latest
permissions:
actions: read
id-token: write
contents: read
steps:
- uses: actions/checkout@v6
with:
ref: ${{ inputs.release_tag }}
fetch-depth: 0
- name: Verify recovery source
env:
GH_TOKEN: ${{ github.token }}
RELEASE_TAG: ${{ inputs.release_tag }}
SOURCE_RUN_ID: ${{ inputs.source_run_id }}
run: |
if [[ "$RELEASE_TAG" != v* || "$RELEASE_TAG" == *beta* ]]; then
echo "Recovery only supports stable v* release tags" >&2
exit 1
fi
TAG_SHA=$(git rev-parse HEAD)
RUN_SHA=$(gh api "/repos/${{ github.repository }}/actions/runs/$SOURCE_RUN_ID" --jq .head_sha)
if [[ "$TAG_SHA" != "$RUN_SHA" ]]; then
echo "Source run $SOURCE_RUN_ID ($RUN_SHA) does not match $RELEASE_TAG ($TAG_SHA)" >&2
exit 1
fi
- name: Download Linux wheel artifacts
uses: actions/download-artifact@v8
with:
github-token: ${{ github.token }}
repository: ${{ github.repository }}
run-id: ${{ inputs.source_run_id }}
pattern: wheels-linux-*
path: target/wheels
merge-multiple: true
- name: Download macOS wheel artifacts
uses: actions/download-artifact@v8
with:
github-token: ${{ github.token }}
repository: ${{ github.repository }}
run-id: ${{ inputs.source_run_id }}
pattern: wheels-mac-*
path: target/wheels
merge-multiple: true
- name: Download recovered Windows wheel
uses: actions/download-artifact@v8
with:
name: wheels-windows-recovery
path: target/wheels
- name: Validate recovered wheels
run: |
find target/wheels -maxdepth 1 -type f -name '*.whl' -print
WHEEL_COUNT=$(find target/wheels -maxdepth 1 -type f -name '*.whl' | wc -l)
if [[ "$WHEEL_COUNT" -ne 5 ]]; then
echo "Expected 5 wheels, found $WHEEL_COUNT" >&2
exit 1
fi
- name: Publish to PyPI
uses: pypa/gh-action-pypi-publish@release/v1
with:
packages-dir: target/wheels/
report-failure:
name: Report Workflow Failure
runs-on: ubuntu-latest
Generated
+181 -140
View File
@@ -775,7 +775,7 @@ dependencies = [
"http 0.2.12",
"http 1.5.0",
"http-body 1.1.0",
"lru 0.16.4",
"lru",
"percent-encoding",
"regex-lite",
"sha2 0.11.0",
@@ -1970,6 +1970,15 @@ dependencies = [
"spin 0.10.1",
]
[[package]]
name = "crc32c"
version = "0.6.8"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "3a47af21622d091a8f0fb295b88bc886ac74efcc613efc19f5d0b21de5c89e47"
dependencies = [
"rustc_version",
]
[[package]]
name = "crc32fast"
version = "1.5.0"
@@ -3441,12 +3450,6 @@ dependencies = [
"percent-encoding",
]
[[package]]
name = "frostem"
version = "1.20260804.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "82eb03a32a1d50555353c85a7b9d3279a6f1e91af9890b789acdf544ed57c8d7"
[[package]]
name = "fs_extra"
version = "1.3.0"
@@ -3455,8 +3458,9 @@ checksum = "42703706b716c37f96a77aea830392ad231f44c9e9a67872fa5548707e11b11c"
[[package]]
name = "fsst"
version = "11.0.0-beta.13"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.13#ee41152ceb9a78e5df4d2456fdbdb98542eb2059"
version = "10.0.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "d0981ce90521824089f3cd68a48b1c4c89e9ad96d0eb74f58d6e550a3d604545"
dependencies = [
"arrow-array",
"rand 0.9.5",
@@ -3813,23 +3817,14 @@ dependencies = [
[[package]]
name = "goosefs-sdk"
version = "0.1.9"
version = "0.1.5"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "e1ea4eee6dcbc31b25ab4fd577adc55b677d2bed3aa3016c44c58fbe1b2298a5"
checksum = "9ae079b88ffe7772d12cfc5c40a5a324babb357893d95b5e3a22ae857f236c5f"
dependencies = [
"arc-swap",
"async-trait",
"bytes",
"dashmap",
"fastrand",
"futures",
"hostname",
"io-uring",
"itoa",
"libc",
"lru 0.18.2",
"memmap2 0.9.10",
"moka",
"prost",
"prost-types",
"rand 0.9.5",
@@ -3842,7 +3837,6 @@ dependencies = [
"tonic-prost",
"tracing",
"uuid",
"xxhash-rust",
]
[[package]]
@@ -4815,8 +4809,9 @@ checksum = "e037a2e1d8d5fdbd49b16a4ea09d5d6401c1f29eca5ff29d03d3824dba16256a"
[[package]]
name = "lance"
version = "11.0.0-beta.13"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.13#ee41152ceb9a78e5df4d2456fdbdb98542eb2059"
version = "10.0.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "830548f9fc92ae74b848a504282d4da06f016f2ee94b663773c2738b9cb61c42"
dependencies = [
"arc-swap",
"arrow",
@@ -4832,6 +4827,7 @@ dependencies = [
"async-recursion",
"async-trait",
"async_cell",
"aws-credential-types",
"aws-sdk-dynamodb",
"byteorder",
"bytes",
@@ -4847,6 +4843,7 @@ dependencies = [
"either",
"fst",
"futures",
"half",
"humantime",
"itertools 0.14.0",
"lance-arrow",
@@ -4888,8 +4885,9 @@ dependencies = [
[[package]]
name = "lance-arrow"
version = "11.0.0-beta.13"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.13#ee41152ceb9a78e5df4d2456fdbdb98542eb2059"
version = "10.0.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "24187f972374567bb3573cffd8728f2f4f7f06d644c3c5d4430b79d6b0b67300"
dependencies = [
"arrow-array",
"arrow-buffer",
@@ -4911,7 +4909,8 @@ dependencies = [
[[package]]
name = "lance-arrow-scalar"
version = "58.0.0"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.13#ee41152ceb9a78e5df4d2456fdbdb98542eb2059"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "771f68b04b47f3addf781116f65061808de94b05e1e9411c23c18f32d14ebe79"
dependencies = [
"arrow-array",
"arrow-buffer",
@@ -4925,17 +4924,20 @@ dependencies = [
[[package]]
name = "lance-arrow-stats"
version = "58.0.0"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.13#ee41152ceb9a78e5df4d2456fdbdb98542eb2059"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "dd47ec33c90bf29f688fd02118e37d3a5ad5c339caa3163f89e417dc0867001f"
dependencies = [
"arrow-array",
"arrow-schema",
"half",
"lance-arrow-scalar",
]
[[package]]
name = "lance-bitpacking"
version = "11.0.0-beta.13"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.13#ee41152ceb9a78e5df4d2456fdbdb98542eb2059"
version = "10.0.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "55fa50ad941e25298afb54eec107c3584f80c16db4adf7a6e4e9c4b6066f4281"
dependencies = [
"arrayref",
"crunchy",
@@ -4945,8 +4947,9 @@ dependencies = [
[[package]]
name = "lance-core"
version = "11.0.0-beta.13"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.13#ee41152ceb9a78e5df4d2456fdbdb98542eb2059"
version = "10.0.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "21f4fd872bfe948150a6878d983327c4f150dc1b629e94ae7677310fa6a3f35f"
dependencies = [
"arrow-array",
"arrow-buffer",
@@ -4954,10 +4957,12 @@ dependencies = [
"arrow-schema",
"async-trait",
"blake3",
"byteorder",
"bytes",
"datafusion-common",
"datafusion-sql",
"futures",
"itertools 0.14.0",
"lance-arrow",
"lance-derive",
"libc",
@@ -4975,6 +4980,7 @@ dependencies = [
"snafu 0.9.0",
"tempfile",
"tokio",
"tokio-stream",
"tokio-util",
"tracing",
"twox-hash",
@@ -4983,8 +4989,9 @@ dependencies = [
[[package]]
name = "lance-datafusion"
version = "11.0.0-beta.13"
source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.13#ee41152ceb9a78e5df4d2456fdbdb98542eb2059"
version = "10.0.0"
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source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "cd528ec2d49c5ca69e674ffed7b3e0686fb9cfcfea0596870de381467fda4f1b"
checksum = "328fa55e8888cbdfe00826bfea2a79042422b720e8369e9e021e46121dea5ace"
dependencies = [
"bytes",
"http 1.5.0",
"log",
"opendal-core",
"quick-xml 0.41.0",
"quick-xml 0.39.4",
"reqsign-aliyun-oss",
"reqsign-core",
"reqsign-file-read-tokio",
@@ -6722,18 +6731,18 @@ dependencies = [
[[package]]
name = "opendal-service-s3"
version = "0.58.1"
version = "0.57.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "58e80cdf192d7eff05feed747894d64f81905ac4eaf132edf7ea270abdd2d663"
checksum = "313d46c9f5ae70bca26b7c3e3fbb9b639292625f28af73aa016f47e788af9deb"
dependencies = [
"base64 0.23.1",
"base64 0.22.1",
"bytes",
"crc-fast",
"crc32c",
"http 1.5.0",
"log",
"md-5 0.11.0",
"opendal-core",
"quick-xml 0.41.0",
"quick-xml 0.39.4",
"reqsign-aws-v4",
"reqsign-core",
"reqsign-file-read-tokio",
@@ -8666,6 +8675,16 @@ dependencies = [
"ordered-multimap",
]
[[package]]
name = "rust-stemmers"
version = "1.2.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "e46a2036019fdb888131db7a4c847a1063a7493f971ed94ea82c67eada63ca54"
dependencies = [
"serde",
"serde_derive",
]
[[package]]
name = "rustc-demangle"
version = "0.1.27"
@@ -9539,6 +9558,15 @@ version = "0.11.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "7da8b5736845d9f2fcb837ea5d9e2628564b3b043a70948a3f0b778838c5fb4f"
[[package]]
name = "strum"
version = "0.26.3"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "8fec0f0aef304996cf250b31b5a10dee7980c85da9d759361292b8bca5a18f06"
dependencies = [
"strum_macros 0.26.4",
]
[[package]]
name = "strum"
version = "0.28.0"
@@ -9561,6 +9589,19 @@ dependencies = [
"syn 2.0.117",
]
[[package]]
name = "strum_macros"
version = "0.26.4"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "4c6bee85a5a24955dc440386795aa378cd9cf82acd5f764469152d2270e581be"
dependencies = [
"heck 0.5.0",
"proc-macro2",
"quote",
"rustversion",
"syn 2.0.117",
]
[[package]]
name = "strum_macros"
version = "0.28.0"
+14 -14
View File
@@ -13,20 +13,20 @@ categories = ["database-implementations"]
rust-version = "1.91.0"
[workspace.dependencies]
lance = { "version" = "=11.0.0-beta.13", default-features = false, "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
lance-core = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
lance-datagen = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
lance-file = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
lance-io = { "version" = "=11.0.0-beta.13", default-features = false, "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
lance-index = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
lance-linalg = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
lance-namespace-impls = { "version" = "=11.0.0-beta.13", default-features = false, "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
lance-table = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
lance-testing = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
lance-datafusion = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
lance-encoding = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
lance-arrow = { "version" = "=11.0.0-beta.13", "tag" = "v11.0.0-beta.13", "git" = "https://github.com/lance-format/lance.git" }
lance = { "version" = "=10.0.0", default-features = false }
lance-core = "=10.0.0"
lance-datagen = "=10.0.0"
lance-file = "=10.0.0"
lance-io = { "version" = "=10.0.0", default-features = false }
lance-index = "=10.0.0"
lance-linalg = "=10.0.0"
lance-namespace = "=10.0.0"
lance-namespace-impls = { "version" = "=10.0.0", default-features = false }
lance-table = "=10.0.0"
lance-testing = "=10.0.0"
lance-datafusion = "=10.0.0"
lance-encoding = "=10.0.0"
lance-arrow = "=10.0.0"
ahash = "0.8"
# Note that this one does not include pyarrow
arrow = { version = "58.0.0", optional = false }
+4 -9
View File
@@ -6,16 +6,11 @@ HEAD_SHA=$(git rev-parse HEAD)
readonly TAG_PREFIX="v"
readonly SELF_DIR=$(cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )
readonly BUMP_ARGS="--no-tag"
PREV_TAG=$(git tag --sort='version:refname' | grep ^$TAG_PREFIX | python $SELF_DIR/semver_sort.py $TAG_PREFIX | tail -n 1)
echo "Found previous tag $PREV_TAG"
# Initially, we don't want to tag if we are doing stable, because we will bump
# again later. See comment at end for why.
if [[ "$RELEASE_TYPE" == 'stable' ]]; then
BUMP_ARGS="--no-tag"
fi
# If last is stable and not bumping minor
if [[ $PREV_TAG != *beta* ]]; then
if [[ "$BUMP_MINOR" != "false" ]]; then
@@ -39,12 +34,12 @@ fi
# a stable version, bump the pre-release level ("pre_l") to make it stable.
if [[ $RELEASE_TYPE == 'stable' ]]; then
# X.Y.Z-beta.N -> X.Y.Z
bump-my-version bump -vv pre_l
bump-my-version bump -vv $BUMP_ARGS pre_l
fi
# Validate that we have incremented version appropriately for breaking changes
NEW_TAG=$(git describe --tags --exact-match HEAD)
NEW_VERSION=$(echo $NEW_TAG | sed "s/^$TAG_PREFIX//")
NEW_VERSION=$(python -c 'import tomllib; print(tomllib.load(open(".bumpversion.toml", "rb"))["tool"]["bumpversion"]["current_version"])')
NEW_TAG="$TAG_PREFIX$NEW_VERSION"
LAST_STABLE_RELEASE=$(git tag --sort='version:refname' | grep ^$TAG_PREFIX | grep -v beta | grep -vF "$NEW_TAG" | python $SELF_DIR/semver_sort.py $TAG_PREFIX | tail -n 1)
LAST_STABLE_VERSION=$(echo $LAST_STABLE_RELEASE | sed "s/^$TAG_PREFIX//")
+21
View File
@@ -0,0 +1,21 @@
#!/usr/bin/env bash
set -euo pipefail
RELEASE_VERSION=$(python -c 'import tomllib; print(tomllib.load(open(".bumpversion.toml", "rb"))["tool"]["bumpversion"]["current_version"])')
RELEASE_TAG="v${RELEASE_VERSION}"
if git rev-parse --quiet --verify "refs/tags/${RELEASE_TAG}" >/dev/null; then
echo "Release tag ${RELEASE_TAG} already exists" >&2
exit 1
fi
git tag --annotate "$RELEASE_TAG" --message "Release ${RELEASE_TAG}"
HEAD_SHA=$(git rev-parse HEAD)
TAG_SHA=$(git rev-parse "refs/tags/${RELEASE_TAG}^{}")
if [[ "$TAG_SHA" != "$HEAD_SHA" ]]; then
echo "Release tag ${RELEASE_TAG} points to ${TAG_SHA}, expected ${HEAD_SHA}" >&2
exit 1
fi
echo "Created ${RELEASE_TAG} at ${HEAD_SHA}"
+72
View File
@@ -0,0 +1,72 @@
import tempfile
import unittest
from pathlib import Path
from validate_stable_lance import validate
class ValidateStableLanceTest(unittest.TestCase):
def write_fixture(
self,
root: Path,
*,
rust: str = "=10.0.0",
python: str = "10.0.0",
java: str = "10.0.0",
) -> None:
(root / "python").mkdir()
(root / "java").mkdir()
(root / "Cargo.toml").write_text(
f'[workspace.dependencies]\nlance = "{rust}"\nlance-core = "{rust}"\n'
)
(root / "python" / "pyproject.toml").write_text(
'[project.optional-dependencies]\ntests = ["pylance==' + python + '"]\n'
)
(root / "java" / "pom.xml").write_text(
"<project><properties><lance-core.version>"
+ java
+ "</lance-core.version></properties></project>"
)
def test_accepts_matching_stable_versions(self) -> None:
with tempfile.TemporaryDirectory() as temp_dir:
root = Path(temp_dir)
self.write_fixture(root)
self.assertEqual(validate(root), "10.0.0")
def test_rejects_prerelease(self) -> None:
with tempfile.TemporaryDirectory() as temp_dir:
root = Path(temp_dir)
self.write_fixture(root, python="10.0.0rc1")
with self.assertRaisesRegex(ValueError, "not stable"):
validate(root)
def test_rejects_sdk_mismatch(self) -> None:
with tempfile.TemporaryDirectory() as temp_dir:
root = Path(temp_dir)
self.write_fixture(root, java="9.0.0")
with self.assertRaisesRegex(ValueError, "do not match across SDKs"):
validate(root)
def test_rejects_non_exact_rust_dependency(self) -> None:
with tempfile.TemporaryDirectory() as temp_dir:
root = Path(temp_dir)
self.write_fixture(root, rust="10.0.0")
with self.assertRaisesRegex(ValueError, "not exact"):
validate(root)
def test_rejects_unpublished_rust_source(self) -> None:
with tempfile.TemporaryDirectory() as temp_dir:
root = Path(temp_dir)
self.write_fixture(root)
(root / "Cargo.toml").write_text(
"[workspace.dependencies]\n"
'lance = { version = "=10.0.0", git = "https://example.com/lance", '
'tag = "v10.0.0" }\n'
)
with self.assertRaisesRegex(ValueError, "unpublished source fields"):
validate(root)
if __name__ == "__main__":
unittest.main()
Regular → Executable
+104 -26
View File
@@ -1,34 +1,112 @@
#!/usr/bin/env python3
"""Validate that every SDK uses the same published stable Lance release."""
from __future__ import annotations
import re
import xml.etree.ElementTree as ET
from pathlib import Path
import tomllib
found_preview_lance = False
STABLE_VERSION = re.compile(r"[0-9]+\.[0-9]+\.[0-9]+")
with open("Cargo.toml", "rb") as f:
cargo_data = tomllib.load(f)
for name, dep in cargo_data["workspace"]["dependencies"].items():
if name == "lance" or name.startswith("lance-"):
if isinstance(dep, str):
version = dep
elif isinstance(dep, dict):
# Version doesn't have the beta tag in it, so we instead look
# at the git tag.
version = dep.get('tag', dep.get('version'))
else:
raise ValueError("Unexpected type for dependency: " + str(dep))
def _stable_version(raw: str, *, dependency: str, exact: bool = False) -> str:
value = raw.strip()
if exact and not value.startswith("="):
raise ValueError(f"Dependency '{dependency}' is not exact: {raw}")
value = value.removeprefix("=").removeprefix("v")
if STABLE_VERSION.fullmatch(value) is None:
raise ValueError(f"Dependency '{dependency}' is not stable: {raw}")
return value
if "beta" in version:
found_preview_lance = True
print(f"Dependency '{name}' is a preview version: {version}")
with open("python/pyproject.toml", "rb") as f:
py_proj_data = tomllib.load(f)
def rust_lance_version(repo_root: Path) -> str:
with (repo_root / "Cargo.toml").open("rb") as cargo_file:
dependencies = tomllib.load(cargo_file)["workspace"]["dependencies"]
for dep in py_proj_data["project"]["dependencies"]:
if dep.startswith("pylance"):
if "b" in dep:
found_preview_lance = True
print(f"Dependency '{dep}' is a preview version")
break # Only one pylance dependency
versions: dict[str, str] = {}
for name, dependency in dependencies.items():
if name != "lance" and not name.startswith("lance-"):
continue
if found_preview_lance:
raise ValueError("Found preview version of Lance in dependencies")
if isinstance(dependency, str):
raw_version = dependency
elif isinstance(dependency, dict):
forbidden_sources = [
source
for source in ("git", "path", "branch", "rev", "tag")
if source in dependency
]
if forbidden_sources:
joined = ", ".join(forbidden_sources)
raise ValueError(
f"Dependency '{name}' uses unpublished source fields: {joined}"
)
raw_version = dependency.get("version")
if raw_version is None:
raise ValueError(f"Dependency '{name}' has no version")
else:
raise TypeError(f"Dependency '{name}' has an unexpected definition")
versions[name] = _stable_version(raw_version, dependency=name, exact=True)
if not versions:
raise ValueError("No Rust Lance dependencies found")
unique_versions = set(versions.values())
if len(unique_versions) != 1:
details = ", ".join(f"{name}={version}" for name, version in versions.items())
raise ValueError(f"Rust Lance dependency versions do not match: {details}")
return unique_versions.pop()
def python_lance_version(repo_root: Path) -> str:
with (repo_root / "python" / "pyproject.toml").open("rb") as pyproject_file:
pyproject = tomllib.load(pyproject_file)
requirements = pyproject["project"]["optional-dependencies"]["tests"]
pylance_requirements = [
requirement for requirement in requirements if requirement.startswith("pylance")
]
if len(pylance_requirements) != 1:
raise ValueError(
"Expected exactly one pylance requirement in the Python test dependencies"
)
requirement = pylance_requirements[0]
prefix = "pylance=="
if not requirement.startswith(prefix):
raise ValueError(f"Python test dependency is not exact: {requirement}")
return _stable_version(requirement[len(prefix) :], dependency="pylance")
def java_lance_version(repo_root: Path) -> str:
pom_root = ET.parse(repo_root / "java" / "pom.xml").getroot()
versions = [
element.text
for element in pom_root.iter()
if element.tag.rsplit("}", 1)[-1] == "lance-core.version"
]
if len(versions) != 1 or versions[0] is None:
raise ValueError("Expected exactly one Java lance-core.version property")
return _stable_version(versions[0], dependency="Java lance-core")
def validate(repo_root: Path) -> str:
versions = {
"Rust": rust_lance_version(repo_root),
"Python": python_lance_version(repo_root),
"Java": java_lance_version(repo_root),
}
if len(set(versions.values())) != 1:
details = ", ".join(f"{sdk}={version}" for sdk, version in versions.items())
raise ValueError(
f"Lance dependency versions do not match across SDKs: {details}"
)
return versions["Rust"]
if __name__ == "__main__":
version = validate(Path(__file__).resolve().parents[1])
print(f"Validated published stable Lance v{version} across Rust, Python, and Java")
-7
View File
@@ -101,13 +101,6 @@ ignore = [
# https://rustsec.org/advisories/RUSTSEC-2026-0195
{ id = "RUSTSEC-2026-0194", reason = "transitive via inferno/lance/opendal; XML from trusted cloud endpoints, not attacker-controlled" },
{ id = "RUSTSEC-2026-0195", reason = "transitive via inferno/lance/opendal; XML from trusted cloud endpoints, not attacker-controlled" },
# smartstring: unmaintained — the repository was archived by its author on
# 2026-05-03. Not a vulnerability. Reached only transitively through polars
# (polars-core/-io/-ops/-time/-utils); nothing in LanceDB depends on it directly.
# The advisory states no safe upgrade is available: upstream recommends
# compact_str/smol_str, so clearing this requires polars to migrate.
# https://rustsec.org/advisories/RUSTSEC-2026-0249
{ id = "RUSTSEC-2026-0249", reason = "smartstring unmaintained via polars; no fixed upstream release" },
]
# ---------------------------------------------------------------------------
+1 -33
View File
@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
<dependency>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-core</artifactId>
<version>0.38.0-beta.2</version>
<version>0.37.1</version>
</dependency>
```
@@ -55,38 +55,6 @@ LanceNamespace namespaceClient = LanceDbNamespaceClientBuilder.newBuilder()
| `region(String)` | AWS region (default: "us-east-1") | No |
| `config(String, String)` | Additional configuration parameters | No |
### Opening a Table with Vended Credentials
When the catalog vends temporary object store credentials, open the table through the
namespace client. The Lance dataset builder fetches the table location and storage options
from the catalog and refreshes the credentials when they expire.
```java
import com.lancedb.LanceDbNamespaceClientBuilder;
import org.lance.Dataset;
import org.lance.namespace.LanceNamespace;
import java.util.Arrays;
LanceNamespace namespaceClient = LanceDbNamespaceClientBuilder.newBuilder()
.apiKey(System.getenv("LANCEDB_API_KEY"))
.database(System.getenv("LANCEDB_DATABASE"))
// Set the endpoint for a LanceDB Enterprise deployment.
// .endpoint("https://your-enterprise-endpoint")
.build();
try (Dataset dataset = Dataset.open()
.namespaceClient(namespaceClient)
.tableId(Arrays.asList("my_namespace", "my_table"))
.build()) {
System.out.println("Rows: " + dataset.countRows());
}
```
Do not call `describeTable()` and then open the returned location with `Dataset.open(uri)`.
Opening through `namespaceClient()` is what applies the vended storage options and enables
automatic credential refresh. No object store credentials need to be passed by the application.
## Metadata Operations
### Creating a Namespace Path
-23
View File
@@ -386,29 +386,6 @@ Drop an existing table.
***
### dropTableAsync()
```ts
abstract dropTableAsync(name, namespacePath?): Promise<Job>
```
Start dropping a table and return its cleanup job.
The table may become unavailable before its data files are removed. Wait
on the returned job to know when cleanup has finished.
#### Parameters
* **name**: `string`
* **namespacePath?**: `string`[]
#### Returns
`Promise`&lt;[`Job`](Job.md)&gt;
***
### getJob()
```ts
+4 -98
View File
@@ -69,34 +69,14 @@ abstract addColumns(newColumnTransforms): Promise<AddColumnsResult>
Add new columns with defined values.
The `{ computed }` form stores the expression rather than evaluating it
now: the column is committed with no values, and rows get them from
[Table#refreshColumn](Table.md#refreshcolumn). Declaring one therefore costs the same on a
large table as on an empty one.
A refresh does not revisit rows it has already filled, so mutating an
input leaves the value computed at fill time; recomputing means dropping
the column and declaring it again. While a declaration reads a column,
that column cannot be renamed, retyped or dropped.
On LanceDB Cloud and Enterprise the expression is planned by the
server, and the refresh runs as a server job -- see
[Table#refreshColumnAsync](Table.md#refreshcolumnasync).
#### Parameters
* **newColumnTransforms**:
\| `Field`&lt;`any`&gt;
\| `Field`&lt;`any`&gt;[]
\| `Schema`&lt;`any`&gt;
\| [`AddColumnsSql`](../interfaces/AddColumnsSql.md)[]
\| `object`
* **newColumnTransforms**: `Field`&lt;`any`&gt; \| `Field`&lt;`any`&gt;[] \| `Schema`&lt;`any`&gt; \| [`AddColumnsSql`](../interfaces/AddColumnsSql.md)[]
Either:
- An array of objects with column names and SQL expressions to calculate values
- A single Arrow Field defining one column with its data type (column will be initialized with null values)
- An array of Arrow Fields defining columns with their data types (columns will be initialized with null values)
- An Arrow Schema defining columns with their data types (columns will be initialized with null values)
- `{ computed }`, declaring columns defined by a SQL expression whose type and inputs are derived from it
#### Returns
@@ -105,13 +85,6 @@ server, and the refresh runs as a server job -- see
A promise that resolves to an object
containing the new version number of the table after adding the columns.
#### Example
```ts
await table.addColumns({ computed: [{ name: "doubled", valueSql: "x * 2" }] });
const { rowsFilled } = await table.refreshColumn("doubled");
```
***
### alterColumns()
@@ -458,10 +431,9 @@ Read the [LsmWriteSpec](../interfaces/LsmWriteSpec.md) currently installed on th
Resolves to `undefined` when the MemWAL LSM write path is not enabled (no
spec has been set, or it was removed with [Table#unsetLsmWriteSpec](Table.md#unsetlsmwritespec)).
The returned spec mirrors what was passed to
[Table#setLsmWriteSpec](Table.md#setlsmwritespec), except that `maintainedIndexes` always
reports the concrete list resolved when the spec was set — `undefined`
never round-trips.
The returned spec — including its `maintainedIndexes` and
`writerConfigDefaults` — mirrors what was passed to
[Table#setLsmWriteSpec](Table.md#setlsmwritespec).
#### Returns
@@ -745,67 +717,6 @@ for await (const batch of table.query()) {
***
### refreshColumn()
```ts
abstract refreshColumn(column): Promise<RefreshColumnResult>
```
Fill the rows of a computed column that hold no value yet.
Rows appended since the last refresh are filled by the next one; rows
already filled are left as they are, so the call is idempotent and does
not observe a mutated input. Local tables only: a remote refresh runs
as a server job, through [Table#refreshColumnAsync](Table.md#refreshcolumnasync).
#### Parameters
* **column**: `string`
The name of the computed column to fill.
#### Returns
`Promise`&lt;[`RefreshColumnResult`](../interfaces/RefreshColumnResult.md)&gt;
A promise that resolves to the
number of rows filled and the new version number of the table.
***
### refreshColumnAsync()
```ts
abstract refreshColumnAsync(column): Promise<Job>
```
Like [Table#refreshColumn](Table.md#refreshcolumn), but returns a handle to the refresh
job instead of blocking until it completes.
The job may already be complete when returned; callers must not assume
the column is filled until [Job.wait](Job.md#wait) resolves. Invalid input --
an unknown column, or one that is not computed -- rejects here rather
than failing the job. On local tables the job runs in-process; on
LanceDB Cloud and Enterprise it is the server's backfill job.
#### Parameters
* **column**: `string`
The name of the computed column to fill.
#### Returns
`Promise`&lt;[`Job`](Job.md)&gt;
#### Example
```ts
const job = await table.refreshColumnAsync("doubled");
await job.wait();
console.log(await job.status()); // "finished"
```
***
### restore()
```ts
@@ -895,11 +806,6 @@ All variants require the table to have an unenforced primary key
([Table#setUnenforcedPrimaryKey](Table.md#setunenforcedprimarykey)); bucket sharding additionally
requires it to be the single column being bucketed.
Omitting `maintainedIndexes` maintains every index on the table, resolved
here, failing if one cannot be maintained — name them to install anyway.
Naming them pins an exact set, and a still-building index is rejected
rather than quietly omitted.
#### Parameters
* **spec**: [`LsmWriteSpec`](../interfaces/LsmWriteSpec.md)
-1
View File
@@ -105,7 +105,6 @@
- [OptimizeOptions](interfaces/OptimizeOptions.md)
- [OptimizeStats](interfaces/OptimizeStats.md)
- [QueryExecutionOptions](interfaces/QueryExecutionOptions.md)
- [RefreshColumnResult](interfaces/RefreshColumnResult.md)
- [RemovalStats](interfaces/RemovalStats.md)
- [RenameTableOptions](interfaces/RenameTableOptions.md)
- [RestNamespaceConfig](interfaces/RestNamespaceConfig.md)
+1 -3
View File
@@ -34,9 +34,7 @@ Bucket and identity variants: the sharding column.
optional maintainedIndexes: string[];
```
Indexes the MemWAL keeps up to date. Omit to maintain every supported
index, resolved on install — a snapshot, so indexes created later are not
maintained. Pass `[]` for none.
Names of indexes the MemWAL should keep up to date during writes.
***
@@ -1,23 +0,0 @@
[**@lancedb/lancedb**](../README.md) • **Docs**
***
[@lancedb/lancedb](../globals.md) / RefreshColumnResult
# Interface: RefreshColumnResult
## Properties
### rowsFilled
```ts
rowsFilled: number;
```
***
### version
```ts
version: number;
```
+1 -1
View File
@@ -8,7 +8,7 @@
<parent>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.38.0-beta.2</version>
<version>0.37.1-final.0</version>
<relativePath>../pom.xml</relativePath>
</parent>
+2 -2
View File
@@ -6,7 +6,7 @@
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.38.0-beta.2</version>
<version>0.37.1-final.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>11.0.0-beta.13</lance-core.version>
<lance-core.version>10.0.0</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 -1
View File
@@ -1,7 +1,7 @@
[package]
name = "lancedb-nodejs"
edition.workspace = true
version = "0.38.0-beta.2"
version = "0.37.1"
publish = false
license.workspace = true
description.workspace = true
-10
View File
@@ -89,16 +89,6 @@ describe("given a connection", () => {
await db.createTable("test4", [{ id: 1 }, { id: 2 }]);
});
it("should return a completed job when dropping a local table", async () => {
await db.createTable("async-drop", [{ id: 1 }]);
const job = await db.dropTableAsync("async-drop");
expect(job.id).toBeNull();
await expect(job.status()).resolves.toBe("finished");
await job.wait();
await expect(db.tableNames()).resolves.toEqual([]);
});
it("should fail if creating table twice, unless overwrite is true", async () => {
let tbl = await db.createTable("test", [{ id: 1 }, { id: 2 }]);
await expect(tbl.countRows()).resolves.toBe(2);
-64
View File
@@ -3340,67 +3340,3 @@ describe("LSM merge insert", () => {
await expect(table.query().useLsm(true).toArray()).rejects.toThrow();
});
});
describe("computed columns", () => {
let tmpDir: tmp.DirResult;
beforeEach(() => {
tmpDir = tmp.dirSync({ unsafeCleanup: true });
});
afterEach(() => tmpDir.removeCallback());
it("declares a column and fills it on refresh", async () => {
const db = await connect(tmpDir.name);
const table = await db.createTable("computed", [{ x: 1 }, { x: 2 }]);
await table.addColumns({
computed: [{ name: "doubled", valueSql: "x * 2" }],
});
let rows = await table.query().toArray();
expect(rows.map((r) => r.doubled)).toEqual([null, null]);
const result = await table.refreshColumn("doubled");
expect(result.rowsFilled).toBe(2);
rows = await table.query().toArray();
expect(rows.map((r) => r.doubled).sort()).toEqual([2, 4]);
});
it("returns a job handle from refreshColumnAsync", async () => {
const db = await connect(tmpDir.name);
const table = await db.createTable("computed_job", [{ x: 1 }, { x: 2 }]);
await table.addColumns({
computed: [{ name: "doubled", valueSql: "x * 2" }],
});
const job = await table.refreshColumnAsync("doubled");
expect(job.id).toBeNull();
await job.wait();
expect(await job.status()).toBe("finished");
const rows = await table.query().toArray();
expect(rows.map((r) => r.doubled).sort()).toEqual([2, 4]);
// Bad input rejects at the call, not through the job.
await expect(table.refreshColumnAsync("x")).rejects.toThrow(
"not a computed column",
);
});
it("fills rows added since the last refresh", async () => {
const db = await connect(tmpDir.name);
const table = await db.createTable("computed_append", [{ x: 1 }]);
await table.addColumns({
computed: [{ name: "doubled", valueSql: "x * 2" }],
});
await table.refreshColumn("doubled");
await table.add([{ x: 5 }]);
const result = await table.refreshColumn("doubled");
expect(result.rowsFilled).toBe(1);
const rows = await table.query().toArray();
expect(rows.map((r) => r.doubled).sort()).toEqual([10, 2]);
});
});
-12
View File
@@ -327,14 +327,6 @@ export abstract class Connection {
*/
abstract dropTable(name: string, namespacePath?: string[]): Promise<void>;
/**
* Start dropping a table and return its cleanup job.
*
* The table may become unavailable before its data files are removed. Wait
* on the returned job to know when cleanup has finished.
*/
abstract dropTableAsync(name: string, namespacePath?: string[]): Promise<Job>;
/**
* Drop all tables in the database.
* @param {string[]} namespacePath The namespace path to drop tables from (defaults to root namespace).
@@ -713,10 +705,6 @@ export class LocalConnection extends Connection {
return this.inner.dropTable(name, namespacePath ?? []);
}
async dropTableAsync(name: string, namespacePath?: string[]): Promise<Job> {
return this.inner.dropTableAsync(name, namespacePath ?? []);
}
async dropAllTables(namespacePath?: string[]): Promise<void> {
return this.inner.dropAllTables(namespacePath ?? []);
}
-1
View File
@@ -50,7 +50,6 @@ export {
MergeResult,
AddResult,
AddColumnsResult,
RefreshColumnResult,
AlterColumnsResult,
UpdateFieldMetadataResult,
DeleteResult,
+6 -96
View File
@@ -33,7 +33,6 @@ import {
Job,
Branches as NativeBranches,
OptimizeStats,
RefreshColumnResult,
TableStatistics,
Tags,
UpdateFieldMetadataResult,
@@ -198,11 +197,7 @@ export interface LsmWriteSpec {
column?: string;
/** Bucket variant: the number of buckets, in `[1, 1024]`. */
numBuckets?: number;
/**
* Indexes the MemWAL keeps up to date. Omit to maintain every supported
* index, resolved on install — a snapshot, so indexes created later are not
* maintained. Pass `[]` for none.
*/
/** Names of indexes the MemWAL should keep up to date during writes. */
maintainedIndexes?: string[];
/** Default `ShardWriter` configuration recorded in the MemWAL index. */
writerConfigDefaults?: Record<string, string>;
@@ -526,75 +521,18 @@ export abstract class Table {
abstract vectorSearch(vector: IntoVector | MultiVector): VectorQuery;
/**
* Add new columns with defined values.
*
* The `{ computed }` form stores the expression rather than evaluating it
* now: the column is committed with no values, and rows get them from
* {@link Table#refreshColumn}. Declaring one therefore costs the same on a
* large table as on an empty one.
*
* A refresh does not revisit rows it has already filled, so mutating an
* input leaves the value computed at fill time; recomputing means dropping
* the column and declaring it again. While a declaration reads a column,
* that column cannot be renamed, retyped or dropped.
*
* On LanceDB Cloud and Enterprise the expression is planned by the
* server, and the refresh runs as a server job -- see
* {@link Table#refreshColumnAsync}.
* @param {AddColumnsSql[] | Field | Field[] | Schema} newColumnTransforms Either:
* - An array of objects with column names and SQL expressions to calculate values
* - A single Arrow Field defining one column with its data type (column will be initialized with null values)
* - An array of Arrow Fields defining columns with their data types (columns will be initialized with null values)
* - An Arrow Schema defining columns with their data types (columns will be initialized with null values)
* - `{ computed }`, declaring columns defined by a SQL expression whose type and inputs are derived from it
* @returns {Promise<AddColumnsResult>} A promise that resolves to an object
* containing the new version number of the table after adding the columns.
* @example
* ```ts
* await table.addColumns({ computed: [{ name: "doubled", valueSql: "x * 2" }] });
* const { rowsFilled } = await table.refreshColumn("doubled");
* ```
*/
abstract addColumns(
newColumnTransforms:
| AddColumnsSql[]
| Field
| Field[]
| Schema
| { computed: AddColumnsSql[] },
newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
): Promise<AddColumnsResult>;
/**
* Fill the rows of a computed column that hold no value yet.
*
* Rows appended since the last refresh are filled by the next one; rows
* already filled are left as they are, so the call is idempotent and does
* not observe a mutated input. Local tables only: a remote refresh runs
* as a server job, through {@link Table#refreshColumnAsync}.
* @param {string} column The name of the computed column to fill.
* @returns {Promise<RefreshColumnResult>} A promise that resolves to the
* number of rows filled and the new version number of the table.
*/
abstract refreshColumn(column: string): Promise<RefreshColumnResult>;
/**
* Like {@link Table#refreshColumn}, but returns a handle to the refresh
* job instead of blocking until it completes.
*
* The job may already be complete when returned; callers must not assume
* the column is filled until {@link Job.wait} resolves. Invalid input --
* an unknown column, or one that is not computed -- rejects here rather
* than failing the job. On local tables the job runs in-process; on
* LanceDB Cloud and Enterprise it is the server's backfill job.
* @param {string} column The name of the computed column to fill.
* @example
* ```ts
* const job = await table.refreshColumnAsync("doubled");
* await job.wait();
* console.log(await job.status()); // "finished"
* ```
*/
abstract refreshColumnAsync(column: string): Promise<Job>;
/**
* Alter the name or nullability of columns.
* @param {ColumnAlteration[]} columnAlterations One or more alterations to
@@ -657,11 +595,6 @@ export abstract class Table {
* All variants require the table to have an unenforced primary key
* ({@link Table#setUnenforcedPrimaryKey}); bucket sharding additionally
* requires it to be the single column being bucketed.
*
* Omitting `maintainedIndexes` maintains every index on the table, resolved
* here, failing if one cannot be maintained — name them to install anyway.
* Naming them pins an exact set, and a still-building index is rejected
* rather than quietly omitted.
* @param {LsmWriteSpec} spec The sharding spec to install.
* @returns {Promise<void>}
* @example
@@ -689,10 +622,9 @@ export abstract class Table {
*
* Resolves to `undefined` when the MemWAL LSM write path is not enabled (no
* spec has been set, or it was removed with {@link Table#unsetLsmWriteSpec}).
* The returned spec mirrors what was passed to
* {@link Table#setLsmWriteSpec}, except that `maintainedIndexes` always
* reports the concrete list resolved when the spec was set — `undefined`
* never round-trips.
* The returned spec — including its `maintainedIndexes` and
* `writerConfigDefaults` — mirrors what was passed to
* {@link Table#setLsmWriteSpec}.
* @returns {Promise<LsmWriteSpec | undefined>}
*/
abstract getLsmWriteSpec(): Promise<LsmWriteSpec | undefined>;
@@ -1146,22 +1078,8 @@ export class LocalTable extends Table {
// TODO: Support BatchUDF
async addColumns(
newColumnTransforms:
| AddColumnsSql[]
| Field
| Field[]
| Schema
| { computed: AddColumnsSql[] },
newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
): Promise<AddColumnsResult> {
// Columns defined by an expression are declared, not materialized here.
if (
typeof newColumnTransforms === "object" &&
!Array.isArray(newColumnTransforms) &&
"computed" in newColumnTransforms
) {
return await this.inner.addComputedColumns(newColumnTransforms.computed);
}
// Handle single Field -> convert to array of Fields
if (newColumnTransforms instanceof Field) {
newColumnTransforms = [newColumnTransforms];
@@ -1196,14 +1114,6 @@ export class LocalTable extends Table {
throw new Error("Invalid input type for addColumns");
}
async refreshColumn(column: string): Promise<RefreshColumnResult> {
return await this.inner.refreshColumn(column);
}
async refreshColumnAsync(column: string): Promise<Job> {
return await this.inner.refreshColumnAsync(column);
}
async alterColumns(
columnAlterations: ColumnAlteration[],
): Promise<AlterColumnsResult> {
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-darwin-arm64",
"version": "0.38.0-beta.2",
"version": "0.37.1",
"os": ["darwin"],
"cpu": ["arm64"],
"main": "lancedb.darwin-arm64.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-arm64-gnu",
"version": "0.38.0-beta.2",
"version": "0.37.1",
"os": ["linux"],
"cpu": ["arm64"],
"main": "lancedb.linux-arm64-gnu.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-arm64-musl",
"version": "0.38.0-beta.2",
"version": "0.37.1",
"os": ["linux"],
"cpu": ["arm64"],
"main": "lancedb.linux-arm64-musl.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-x64-gnu",
"version": "0.38.0-beta.2",
"version": "0.37.1",
"os": ["linux"],
"cpu": ["x64"],
"main": "lancedb.linux-x64-gnu.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-x64-musl",
"version": "0.38.0-beta.2",
"version": "0.37.1",
"os": ["linux"],
"cpu": ["x64"],
"main": "lancedb.linux-x64-musl.node",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-win32-arm64-msvc",
"version": "0.38.0-beta.2",
"version": "0.37.1",
"os": [
"win32"
],
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-win32-x64-msvc",
"version": "0.38.0-beta.2",
"version": "0.37.1",
"os": ["win32"],
"cpu": ["x64"],
"main": "lancedb.win32-x64-msvc.node",
+2 -2
View File
@@ -1,12 +1,12 @@
{
"name": "@lancedb/lancedb",
"version": "0.38.0-beta.1",
"version": "0.37.1",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "@lancedb/lancedb",
"version": "0.38.0-beta.1",
"version": "0.37.1",
"cpu": [
"x64",
"arm64"
+1 -1
View File
@@ -11,7 +11,7 @@
"ann"
],
"private": false,
"version": "0.38.0-beta.2",
"version": "0.37.1",
"main": "dist/index.js",
"exports": {
".": "./dist/index.js",
-16
View File
@@ -334,22 +334,6 @@ impl Connection {
.default_error()
}
/// Start dropping a table and return its cleanup job.
#[napi(catch_unwind)]
pub async fn drop_table_async(
&self,
name: String,
namespace_path: Option<Vec<String>>,
) -> napi::Result<crate::job::Job> {
let ns = namespace_path.unwrap_or_default();
let job = self
.get_inner()?
.drop_table_async(&name, &ns)
.await
.default_error()?;
Ok(crate::job::Job::new(job))
}
#[napi(catch_unwind)]
pub async fn drop_all_tables(&self, namespace_path: Option<Vec<String>>) -> napi::Result<()> {
let ns = namespace_path.unwrap_or_default();
+6 -55
View File
@@ -347,40 +347,6 @@ impl Table {
Ok(res.into())
}
#[napi(catch_unwind)]
pub async fn add_computed_columns(
&self,
columns: Vec<AddColumnsSql>,
) -> napi::Result<AddColumnsResult> {
let table = self.inner_ref()?;
let mut builder = table.add_columns();
for column in columns {
builder = builder.computed(column.name, column.value_sql);
}
let res = builder.execute().await.default_error()?;
Ok(res.into())
}
#[napi(catch_unwind)]
pub async fn refresh_column(&self, column: String) -> napi::Result<RefreshColumnResult> {
let res = self
.inner_ref()?
.refresh_column(column)
.await
.default_error()?;
Ok(res.into())
}
#[napi(catch_unwind)]
pub async fn refresh_column_async(&self, column: String) -> napi::Result<crate::job::Job> {
let job = self
.inner_ref()?
.refresh_column_async(column)
.await
.default_error()?;
Ok(crate::job::Job::new(job))
}
#[napi(catch_unwind)]
pub async fn add_columns_with_schema(
&self,
@@ -806,8 +772,7 @@ pub struct LsmWriteSpec {
pub column: Option<String>,
/// Bucket variant: the number of buckets, in `[1, 1024]`.
pub num_buckets: Option<u32>,
/// Indexes the MemWAL keeps up to date. Omitted resolves every
/// maintainable index on install; an empty array means none.
/// Names of indexes the MemWAL should keep up to date during writes.
pub maintained_indexes: Option<Vec<String>>,
/// Default `ShardWriter` configuration recorded in the MemWAL index.
pub writer_config_defaults: Option<HashMap<String, String>>,
@@ -817,6 +782,7 @@ impl TryFrom<LsmWriteSpec> for lancedb::table::LsmWriteSpec {
type Error = napi::Error;
fn try_from(value: LsmWriteSpec) -> napi::Result<Self> {
let maintained = value.maintained_indexes.unwrap_or_default();
let writer_config_defaults = value.writer_config_defaults.unwrap_or_default();
let spec = match value.spec_type.as_str() {
"bucket" => {
@@ -843,7 +809,7 @@ impl TryFrom<LsmWriteSpec> for lancedb::table::LsmWriteSpec {
}
};
Ok(spec
.with_maintained_indexes(value.maintained_indexes)
.with_maintained_indexes(maintained)
.with_writer_config_defaults(writer_config_defaults))
}
}
@@ -861,7 +827,7 @@ impl From<lancedb::table::LsmWriteSpec> for LsmWriteSpec {
spec_type: "bucket".to_string(),
column: Some(column),
num_buckets: Some(num_buckets),
maintained_indexes,
maintained_indexes: Some(maintained_indexes),
writer_config_defaults: Some(writer_config_defaults),
},
Native::Identity {
@@ -872,7 +838,7 @@ impl From<lancedb::table::LsmWriteSpec> for LsmWriteSpec {
spec_type: "identity".to_string(),
column: Some(column),
num_buckets: None,
maintained_indexes,
maintained_indexes: Some(maintained_indexes),
writer_config_defaults: Some(writer_config_defaults),
},
Native::Unsharded {
@@ -882,7 +848,7 @@ impl From<lancedb::table::LsmWriteSpec> for LsmWriteSpec {
spec_type: "unsharded".to_string(),
column: None,
num_buckets: None,
maintained_indexes,
maintained_indexes: Some(maintained_indexes),
writer_config_defaults: Some(writer_config_defaults),
},
}
@@ -1230,21 +1196,6 @@ pub struct AddColumnsResult {
pub version: i64,
}
#[napi(object)]
pub struct RefreshColumnResult {
pub rows_filled: i64,
pub version: i64,
}
impl From<lancedb::table::RefreshColumnResult> for RefreshColumnResult {
fn from(value: lancedb::table::RefreshColumnResult) -> Self {
Self {
rows_filled: value.rows_filled as i64,
version: value.version as i64,
}
}
}
impl From<lancedb::table::AddColumnsResult> for AddColumnsResult {
fn from(value: lancedb::table::AddColumnsResult) -> Self {
Self {
+1 -1
View File
@@ -1,6 +1,6 @@
[package]
name = "lancedb-python"
version = "0.38.0-beta.2"
version = "0.37.1"
publish = false
edition.workspace = true
description = "Python bindings for LanceDB"
+1 -1
View File
@@ -63,7 +63,7 @@ tests = [
"polars>=0.19, <=1.32.3",
"pyarrow<25",
"pyarrow-stubs>=16.0",
"pylance==9.0.0rc1",
"pylance==10.0.0",
"requests>=2.31.0",
"datafusion>=54,<55",
"opentelemetry-sdk>=1.30.0",
+4 -19
View File
@@ -198,9 +198,6 @@ class Connection(object):
async def drop_table(
self, name: str, namespace_path: Optional[List[str]] = None
) -> None: ...
async def drop_table_async(
self, name: str, namespace_path: Optional[List[str]] = None
) -> Job: ...
async def drop_all_tables(
self, namespace_path: Optional[List[str]] = None
) -> None: ...
@@ -338,11 +335,6 @@ class Table:
) -> list[FtsToken]: ...
async def delete(self, filter: Union[str, PyExpr]) -> DeleteResult: ...
async def add_columns(self, columns: list[tuple[str, str]]) -> AddColumnsResult: ...
async def add_computed_columns(
self, columns: list[tuple[str, str]]
) -> AddColumnsResult: ...
async def refresh_column(self, column: str) -> RefreshColumnResult: ...
async def refresh_column_async(self, column: str) -> Job: ...
async def add_columns_with_schema(self, schema: pa.Schema) -> AddColumnsResult: ...
async def alter_columns(
self, columns: list[dict[str, Any]]
@@ -661,10 +653,9 @@ class LsmWriteSpec:
def identity(column: str) -> "LsmWriteSpec": ...
@staticmethod
def unsharded() -> "LsmWriteSpec": ...
def with_maintained_indexes(self, indexes: Optional[List[str]]) -> "LsmWriteSpec":
"""Set which indexes the MemWAL keeps up to date. None resolves every
index on the table at install, failing if one cannot be maintained;
a list is verbatim, empty means none."""
def with_maintained_indexes(self, indexes: List[str]) -> "LsmWriteSpec":
"""Return a copy of this spec asking the MemWAL to keep the named
indexes up to date as rows are appended."""
...
def with_writer_config_defaults(self, defaults: Dict[str, str]) -> "LsmWriteSpec":
"""Return a copy of this spec recording the given default
@@ -679,19 +670,13 @@ class LsmWriteSpec:
@property
def num_buckets(self) -> Optional[int]: ...
@property
def maintained_indexes(self) -> Optional[List[str]]:
"""Indexes the MemWAL keeps up to date, or None for every supported one."""
...
def maintained_indexes(self) -> List[str]: ...
@property
def writer_config_defaults(self) -> Dict[str, str]: ...
class AddColumnsResult:
version: int
class RefreshColumnResult:
rows_filled: int
version: int
class AlterColumnsResult:
version: int
-37
View File
@@ -524,12 +524,6 @@ class DBConnection(EnforceOverrides):
namespace_path = []
raise NotImplementedError
def drop_table_async(
self, name: str, namespace_path: Optional[List[str]] = None
) -> Job:
"""Start dropping a table and return its cleanup job."""
raise NotImplementedError
def rename_table(
self,
cur_name: str,
@@ -1192,20 +1186,6 @@ class LanceDBConnection(DBConnection):
)
)
@override
def drop_table_async(
self, name: str, namespace_path: Optional[List[str]] = None
) -> Job:
"""Start dropping a table and return its cleanup job.
The table may become unavailable before its data files are removed.
Call :meth:`Job.wait` to wait for cleanup to finish.
"""
if namespace_path is None:
namespace_path = []
job = LOOP.run(self._conn.drop_table_async(name, namespace_path=namespace_path))
return Job(job if isinstance(job, AsyncJob) else AsyncJob(job))
@override
def drop_all_tables(self, namespace_path: Optional[List[str]] = None):
if namespace_path is None:
@@ -1983,23 +1963,6 @@ class AsyncConnection(object):
if f"Table '{name}' was not found" not in str(e):
raise e
async def drop_table_async(
self,
name: str,
*,
namespace_path: Optional[List[str]] = None,
) -> AsyncJob:
"""Start dropping a table and return its cleanup job.
The table may become unavailable before its data files are removed.
Await :meth:`AsyncJob.wait` to wait for cleanup to finish.
"""
if namespace_path is None:
namespace_path = []
return AsyncJob(
await self._inner.drop_table_async(name, namespace_path=namespace_path)
)
async def drop_all_tables(self, namespace_path: Optional[List[str]] = None):
"""Drop all tables from the database.
-21
View File
@@ -49,7 +49,6 @@ from lancedb._lancedb import (
)
from lancedb.background_loop import LOOP
from lancedb.db import AsyncConnection, DBConnection
from lancedb.job import AsyncJob, Job
from lance_namespace import (
LanceNamespace,
connect as namespace_connect,
@@ -625,18 +624,6 @@ class LanceNamespaceDBConnection(DBConnection):
namespace_path = []
LOOP.run(self._inner.drop_table(name, namespace_path=namespace_path))
@override
def drop_table_async(
self, name: str, namespace_path: Optional[List[str]] = None
) -> Job:
"""Start dropping a table and return its cleanup job."""
if namespace_path is None:
namespace_path = []
job = LOOP.run(
self._inner.drop_table_async(name, namespace_path=namespace_path)
)
return Job(job if isinstance(job, AsyncJob) else AsyncJob(job))
@override
def rename_table(
self,
@@ -1147,14 +1134,6 @@ class AsyncLanceNamespaceDBConnection:
namespace_path = []
await self._inner.drop_table(name, namespace_path=namespace_path)
async def drop_table_async(
self, name: str, namespace_path: Optional[List[str]] = None
) -> AsyncJob:
"""Start dropping a table and return its cleanup job."""
if namespace_path is None:
namespace_path = []
return await self._inner.drop_table_async(name, namespace_path=namespace_path)
async def rename_table(
self,
cur_name: str,
+3 -9
View File
@@ -2235,7 +2235,6 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
reranker=self._reranker,
limit=self._limit,
with_row_ids=True,
offset=self._offset,
)
return self._finish_hybrid_results(results)
@@ -2257,7 +2256,6 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
reranker,
limit: int,
with_row_ids: bool,
offset: Optional[int] = None,
) -> pa.Table:
if norm == "rank":
vector_results = LanceHybridQueryBuilder._rank(vector_results, "_distance")
@@ -2334,7 +2332,7 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
score_i = results.column_names.index("_score")
results = results.set_column(score_i, "_score", original_scores)
results = results.slice(offset=offset or 0, length=limit)
results = results.slice(length=limit)
if not with_row_ids:
results = results.drop(["_rowid"])
@@ -2681,12 +2679,8 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
# Apply common configurations
if self._limit:
# The final offset/limit window is sliced out of the combined,
# reranked results, so each sub-query must fetch enough rows to
# cover the skipped prefix as well as the window itself.
sub_query_limit = self._limit + (self._offset or 0)
self._vector_query.limit(sub_query_limit)
self._fts_query.limit(sub_query_limit)
self._vector_query.limit(self._limit)
self._fts_query.limit(self._limit)
if self._columns:
self._vector_query.select(self._columns)
self._fts_query.select(self._columns)
+1 -11
View File
@@ -23,7 +23,7 @@ import pyarrow as pa
from ..common import DATA
from ..db import DBConnection, LOOP
from ..job import AsyncJob, Job
from ..job import Job
if TYPE_CHECKING:
from .._lancedb import JobDescription, JobInfo
@@ -663,16 +663,6 @@ class RemoteDBConnection(DBConnection):
namespace_path = []
LOOP.run(self._conn.drop_table(name, namespace_path=namespace_path))
@override
def drop_table_async(
self, name: str, namespace_path: Optional[List[str]] = None
) -> Job:
"""Start dropping a table and return its cleanup job."""
if namespace_path is None:
namespace_path = []
job = LOOP.run(self._conn.drop_table_async(name, namespace_path=namespace_path))
return Job(job if isinstance(job, AsyncJob) else AsyncJob(job))
@override
def rename_table(
self,
+4 -37
View File
@@ -958,19 +958,8 @@ class RemoteTable(Table):
def count_rows(self, filter: Optional[str] = None) -> int:
return LOOP.run(self._table.count_rows(filter))
def add_columns(
self,
transforms: Dict[str, str] | None = None,
*,
computed: Dict[str, str] | None = None,
) -> AddColumnsResult:
return LOOP.run(self._table.add_columns(transforms, computed=computed))
def refresh_column(self, column: str):
return LOOP.run(self._table.refresh_column(column))
def refresh_column_async(self, column: str) -> Job:
return Job(LOOP.run(self._table.refresh_column_async(column)))
def add_columns(self, transforms: Dict[str, str]) -> AddColumnsResult:
return LOOP.run(self._table.add_columns(transforms))
def alter_columns(
self, *alterations: Iterable[Dict[str, str]]
@@ -990,39 +979,17 @@ class RemoteTable(Table):
return LOOP.run(self._table.set_unenforced_primary_key(columns))
def set_lsm_write_spec(self, spec: "LsmWriteSpec") -> None:
"""Install an LsmWriteSpec."""
"""Not supported on LanceDB Cloud."""
return LOOP.run(self._table.set_lsm_write_spec(spec))
def unset_lsm_write_spec(self) -> None:
"""Remove the LsmWriteSpec."""
"""Not supported on LanceDB Cloud."""
return LOOP.run(self._table.unset_lsm_write_spec())
def get_lsm_write_spec(self) -> Optional["LsmWriteSpec"]:
"""Read the installed LsmWriteSpec, or ``None``."""
return LOOP.run(self._table.get_lsm_write_spec())
def checkpoint_lsm(self) -> None:
"""Synchronous version of
[`AsyncTable.checkpoint_lsm`][lancedb.AsyncTable.checkpoint_lsm]."""
return LOOP.run(self._table.checkpoint_lsm())
def flush_lsm(self) -> None:
"""Synchronous version of
[`AsyncTable.flush_lsm`][lancedb.AsyncTable.flush_lsm]."""
return LOOP.run(self._table.flush_lsm())
def compact_lsm(self) -> None:
"""Synchronous version of
[`AsyncTable.compact_lsm`][lancedb.AsyncTable.compact_lsm]."""
return LOOP.run(self._table.compact_lsm())
def get_lsm_stats(self, *, include_generation_rows: bool = False) -> Optional[dict]:
"""Synchronous version of
[`AsyncTable.get_lsm_stats`][lancedb.AsyncTable.get_lsm_stats]."""
return LOOP.run(
self._table.get_lsm_stats(include_generation_rows=include_generation_rows)
)
def close_lsm_writers(self) -> None:
"""No-op on LanceDB Cloud (no local shard writers)."""
return LOOP.run(self._table.close_lsm_writers())
+27 -315
View File
@@ -11,11 +11,6 @@ Provides StreamingDataset, a PyTorch IterableDataset that guarantees:
- **Resumability**: state_dict / load_state_dict capture per-split consumption
counts so training can resume from an exact mid-epoch position even when the
distributed topology changes between runs.
Transform failures on bad rows (e.g. nulls or NaNs from incomplete data) can
be tolerated with ``on_transform_error="skip"``; see the parameter
documentation on StreamingDataset for how this interacts with the guarantees
above.
"""
import ctypes
@@ -27,7 +22,7 @@ import time
from collections import deque
from concurrent.futures import ThreadPoolExecutor
from multiprocessing import RawArray
from typing import Any, Callable, Iterator, Optional, Union
from typing import Any, Callable, Iterator, Optional
from torch.utils.data import IterableDataset, get_worker_info
@@ -132,49 +127,6 @@ class StreamingDataset(IterableDataset):
Maximum number of transforms to run concurrently. Must be greater
than zero. When ``None`` (the default), uses ``os.cpu_count()`` or 1
when the CPU count is unavailable.
on_transform_error:
What to do when the transform raises an exception:
- ``"raise"`` (the default): the exception propagates and iteration
aborts.
- ``"skip"``: the failing rows are dropped and iteration continues.
- ``"warn"``: like ``"skip"``, but a warning is logged for each
failing batch.
- a callable ``handler(exc) -> bool``: called with the exception;
return ``True`` to skip the failing rows or ``False`` to re-raise.
Useful to skip only expected error types (compatible with
``webdataset.handlers`` style handlers).
When a batch fails, the transform is re-invoked on each single-row
slice of the batch so that only the rows that actually fail are
dropped. Transforms should therefore be deterministic and accept
batches of any size (including one row). Skipped rows are counted in
``rows_skipped``.
Skipping weakens the elastic-determinism guarantee at the end of the
epoch: splits that lose more rows than others run dry earlier, and
each rank's iterator ends at the last cycle where every split *it
owns* still has a row. Because bad rows are not distributed evenly
across splits, this means one rank's iterator can yield noticeably
fewer or more steps than another rank's *in the same run* — there is
no cross-rank coordination that stops every rank at the same global
step. This is generally safe for asynchronous or single-rank use,
but synchronous distributed training (e.g. ranks that call
``all_reduce`` every step) can hang or deadlock if one rank's
iterator is exhausted while others are still stepping; callers doing
synchronous multi-rank training with ``on_transform_error != "raise"``
are responsible for their own cross-rank stopping mechanism (e.g.
broadcasting a stop signal on ``StopIteration``). The final few
global steps can also differ across topologies (bounded by the skew
in bad-row counts across splits). The sequence of samples yielded
from each split remains deterministic. Mid-epoch
checkpoints remain exact provided the transform fails
deterministically; in multi-rank training each rank must save its
own ``state_dict`` and the states must be combined with
``merge_state_dicts`` before resuming on a different topology.
Prefer the ``filter`` parameter when bad rows can be expressed as a
SQL predicate (e.g. ``"col IS NOT NULL"``) filtering happens before
splits are built, so every guarantee is fully preserved.
worker_info_override:
If set, used in place of ``torch.utils.data.get_worker_info()`` to
determine the DataLoader worker assignment. Intended for unit tests
@@ -200,7 +152,6 @@ class StreamingDataset(IterableDataset):
filter: Optional[str] = None,
transform: Optional[Callable] = None,
transform_parallelism: Optional[int] = None,
on_transform_error: Union[str, Callable[[Exception], bool]] = "raise",
connection_factory: Optional[Callable[[str], Any]] = None,
worker_info_override=None,
):
@@ -216,13 +167,6 @@ class StreamingDataset(IterableDataset):
)
if transform_parallelism is not None and transform_parallelism <= 0:
raise ValueError("transform_parallelism must be greater than 0")
if on_transform_error not in ("raise", "skip", "warn") and not callable(
on_transform_error
):
raise ValueError(
"on_transform_error must be 'raise', 'skip', 'warn', or a "
f"callable, got {on_transform_error!r}"
)
self._table = table
self._num_splits = num_splits
@@ -238,7 +182,6 @@ class StreamingDataset(IterableDataset):
self._filter = filter
self._transform = transform
self._transform_parallelism = transform_parallelism
self._on_transform_error = on_transform_error
self._connection_factory = connection_factory
self._worker_info_override = worker_info_override
@@ -256,28 +199,19 @@ class StreamingDataset(IterableDataset):
# in the main process. RawArray is picklable via the forkserver
# reduction protocol so it survives the dataset pickle round-trip.
# Layout: [unscanned_rows, raw_rows, cooked_rows, consumed_rows,
# bytes_loaded, fetch_time_us, transform_time_us,
# rows_skipped]
self._worker_stats: RawArray = RawArray(ctypes.c_int64, 8)
# bytes_loaded, fetch_time_us, transform_time_us]
self._worker_stats: RawArray = RawArray(ctypes.c_int64, 7)
# Cumulative bytes of Arrow buffer data fetched across all iterations.
self._bytes_loaded: int = 0
# Cumulative seconds spent in LanceDB I/O and in transform functions.
self._fetch_time: float = 0.0
self._transform_time: float = 0.0
# Cumulative rows dropped by on_transform_error across all iterations.
self._rows_skipped: int = 0
# Number of samples each split has already been consumed. At global
# step boundaries all splits have consumed this many samples, so a
# single scalar captures the topology-independent checkpoint state.
self._resume_offset: int = 0
# Permutation position each split has consumed through, keyed by
# global split index. Equal to _resume_offset for every split unless
# on_transform_error skipped rows, in which case skipped positions
# push the watermark of the affected splits further ahead. Splits
# this instance has never iterated have no entry.
self._resume_positions: dict[int, int] = {}
# Build the permutation table once, deterministically.
builder = permutation_builder(table)
@@ -341,7 +275,6 @@ class StreamingDataset(IterableDataset):
# Set identity transform on each Permutation so __getitems__ returns
# the raw RecordBatch. Stage 2 applies the real transform.
permutations: list[Permutation] = []
initial_positions: list[int] = []
for split_idx in my_splits:
perm = Permutation.from_tables(
self._table, self._perm_table, split=split_idx
@@ -349,20 +282,14 @@ class StreamingDataset(IterableDataset):
if self._columns is not None:
perm = perm.select_columns(self._columns)
perm = perm.with_transform(lambda batch: batch)
start_pos = self._resume_positions.get(split_idx, self._resume_offset)
if start_pos > 0:
perm = perm.with_skip(start_pos)
initial_positions.append(start_pos)
if self._resume_offset > 0:
perm = perm.with_skip(self._resume_offset)
permutations.append(perm)
n = len(permutations)
split_sizes = [perm.num_rows for perm in permutations]
initial_offset = self._resume_offset
local_consumed = [0] * n
# Permutation position each split has consumed through (absolute,
# i.e. counted from the start of the unskipped split). Runs ahead of
# initial + local_consumed when rows are skipped.
pos_consumed = list(initial_positions)
batch_size = self._read_batch_size
max_prefetch = self._prefetch_batches
@@ -375,14 +302,12 @@ class StreamingDataset(IterableDataset):
self._transform if self._transform is not None else Transforms.arrow2python
)
# Per-split pipeline state. Batches are paired with the absolute
# permutation position of their first row so that skipped rows can be
# accounted for in pos_consumed.
# Per-split pipeline state.
fetch_head = [0] * n
io_pending = [deque() for _ in range(n)] # (abs_start, Future[RecordBatch])
raw_batches = [deque() for _ in range(n)] # (abs_start, RecordBatch)
tx_pending = [deque() for _ in range(n)] # Future[list[(abs_pos, row)]]
cooked = [deque() for _ in range(n)] # (abs_pos, row) ready to yield
io_pending = [deque() for _ in range(n)] # Future[RecordBatch]
raw_batches = [deque() for _ in range(n)] # RecordBatch — fetched, awaiting tx
tx_pending = [deque() for _ in range(n)] # Future[list[Any]]
cooked = [deque() for _ in range(n)] # rows ready to yield
# Limit simultaneous transforms to transform_workers across all splits.
tx_semaphore = threading.Semaphore(transform_workers)
@@ -405,8 +330,7 @@ class StreamingDataset(IterableDataset):
fetch_head[i] += fetch
perm_i = permutations[i]
indices = list(range(start, start + fetch))
abs_start = initial_positions[i] + start
io_pending[i].append((abs_start, io_pool.submit(_io_call, perm_i, indices)))
io_pending[i].append(io_pool.submit(_io_call, perm_i, indices))
def _fill_io(i: int) -> None:
while len(io_pending[i]) < max_prefetch and fetch_head[i] < split_sizes[i]:
@@ -414,72 +338,15 @@ class StreamingDataset(IterableDataset):
def _drain_io(i: int) -> None:
"""Move completed I/O futures into raw_batches non-blockingly."""
while io_pending[i] and io_pending[i][0][1].done():
abs_start, fut = io_pending[i].popleft()
raw_batches[i].append((abs_start, fut.result()))
while io_pending[i] and io_pending[i][0].done():
raw_batches[i].append(io_pending[i].popleft().result())
# ── Stage 2 helpers ───────────────────────────────────────────────────
on_error = self._on_transform_error
def _should_skip(exc: Exception) -> bool:
if on_error == "raise":
return False
if callable(on_error):
return bool(on_error(exc))
return True # "skip" or "warn"
def _check_row_count(rows: list, num_rows: int) -> None:
if len(rows) != num_rows:
raise ValueError(
f"transform returned {len(rows)} rows for a batch of "
f"{num_rows}; transforms must return exactly one output "
"row per input row. To drop bad rows, raise inside the "
"transform and pass on_transform_error='skip'."
)
def _transform_isolated(abs_start, batch, batch_exc):
"""Re-run the transform on single-row slices, dropping failures."""
out = []
skipped = 0
first_exc = None
for j in range(batch.num_rows):
try:
rows = list(final_transform(batch.slice(j, 1)))
except Exception as exc:
if not _should_skip(exc):
raise
skipped += 1
if first_exc is None:
first_exc = exc
continue
_check_row_count(rows, 1)
out.append((abs_start + j, rows[0]))
self._rows_skipped += skipped
if skipped and on_error == "warn":
logger.warning(
"Skipped %d of %d rows whose transform failed (first error: %r)",
skipped,
batch.num_rows,
first_exc if first_exc is not None else batch_exc,
)
return out
def _transform_batch(abs_start, batch):
"""Apply the transform, returning [(abs_pos, row), ...]."""
try:
rows = list(final_transform(batch))
except Exception as exc:
if not _should_skip(exc):
raise
return _transform_isolated(abs_start, batch, exc)
_check_row_count(rows, batch.num_rows)
return [(abs_start + j, row) for j, row in enumerate(rows)]
def _tx_call_guarded(abs_start, batch):
def _tx_call_guarded(batch):
try:
t0 = time.perf_counter()
result = _transform_batch(abs_start, batch)
result = final_transform(batch)
self._transform_time += time.perf_counter() - t0
return result
finally:
@@ -488,8 +355,8 @@ class StreamingDataset(IterableDataset):
def _try_submit_tx(i: int) -> None:
"""Submit transforms for raw_batches[i] up to available capacity."""
while raw_batches[i] and tx_semaphore.acquire(blocking=False):
abs_start, batch = raw_batches[i].popleft()
tx_pending[i].append(tx_pool.submit(_tx_call_guarded, abs_start, batch))
batch = raw_batches[i].popleft()
tx_pending[i].append(tx_pool.submit(_tx_call_guarded, batch))
def _drain_tx(i: int) -> None:
"""Move completed transform futures into cooked non-blockingly."""
@@ -517,14 +384,11 @@ class StreamingDataset(IterableDataset):
# Acquire a transform slot (may block briefly if all
# transform_workers are busy with other splits).
tx_semaphore.acquire()
abs_start, batch = raw_batches[i].popleft()
tx_pending[i].append(
tx_pool.submit(_tx_call_guarded, abs_start, batch)
)
batch = raw_batches[i].popleft()
tx_pending[i].append(tx_pool.submit(_tx_call_guarded, batch))
elif io_pending[i]:
# Block on the oldest in-flight I/O fetch.
abs_start, fut = io_pending[i].popleft()
raw_batches[i].append((abs_start, fut.result()))
raw_batches[i].append(io_pending[i].popleft().result())
_advance(i)
else:
break # split exhausted
@@ -543,28 +407,15 @@ class StreamingDataset(IterableDataset):
_fill_io(i)
while True:
# A cycle only runs if every split can still produce a
# row. Without skips all splits exhaust simultaneously
# (equal split sizes + round-robin); when
# on_transform_error drops rows a split can run dry
# early, ending the epoch at the last complete cycle.
# This check only sees splits owned by this rank/worker
# (my_splits) — there is no cross-rank coordination, so
# a different rank with fewer skipped rows keeps going;
# see the on_transform_error docstring.
exhausted = False
for i in range(n):
_ensure_cooked(i)
if not cooked[i]:
exhausted = True
break
if exhausted:
# Stop when any split is exhausted (all exhaust
# simultaneously: equal split sizes + round-robin).
if any(local_consumed[i] >= split_sizes[i] for i in range(n)):
break
for i in range(n):
pos, row = cooked[i].popleft()
_ensure_cooked(i)
row = cooked[i].popleft()
local_consumed[i] += 1
pos_consumed[i] = pos + 1
_advance(i)
# After the last split in each cycle: update the
@@ -573,39 +424,21 @@ class StreamingDataset(IterableDataset):
# even when __iter__ runs in a worker process.
if i == n - 1:
self._resume_offset = initial_offset + local_consumed[i]
for j, split_idx in enumerate(my_splits):
self._resume_positions[split_idx] = pos_consumed[j]
ws = self._worker_stats
ws[0] = sum(
split_sizes[j] - fetch_head[j] for j in range(n)
)
ws[1] = sum(
batch.num_rows
for q in raw_batches
for _, batch in q
batch.num_rows for q in raw_batches for batch in q
)
ws[2] = sum(len(q) for q in cooked)
ws[3] = sum(local_consumed)
ws[4] = self._bytes_loaded
ws[5] = int(self._fetch_time * 1_000_000)
ws[6] = int(self._transform_time * 1_000_000)
ws[7] = self._rows_skipped
yield row
finally:
# Final stats flush: the per-cycle write above never runs
# when iteration ends mid-cycle (e.g. a split whose rows
# were all skipped before completing a single cycle), so
# counters like rows_skipped would otherwise be stale.
ws = self._worker_stats
ws[0] = sum(split_sizes[j] - fetch_head[j] for j in range(n))
ws[1] = 0 # queue-depth properties document 0 when idle
ws[2] = 0
ws[3] = sum(local_consumed)
ws[4] = self._bytes_loaded
ws[5] = int(self._fetch_time * 1_000_000)
ws[6] = int(self._transform_time * 1_000_000)
ws[7] = self._rows_skipped
self._raw_batches_ref = None
self._cooked_ref = None
self._fetch_head_ref = None
@@ -659,7 +492,7 @@ class StreamingDataset(IterableDataset):
batches. Returns 0 when not iterating.
"""
if self._raw_batches_ref is not None:
return sum(batch.num_rows for q in self._raw_batches_ref for _, batch in q)
return sum(batch.num_rows for q in self._raw_batches_ref for batch in q)
return int(self._worker_stats[1])
@property
@@ -689,19 +522,6 @@ class StreamingDataset(IterableDataset):
)
return int(self._worker_stats[0])
@property
def rows_skipped(self) -> int:
"""Number of rows dropped because their transform raised an exception.
Only ever non-zero when ``on_transform_error`` is set to ``"skip"``,
``"warn"``, or a callable that returned ``True``. Accumulates across
multiple iterations of the same dataset instance and is never reset
automatically.
"""
if self._raw_batches_ref is not None:
return self._rows_skipped
return int(self._worker_stats[7])
@property
def consumed_rows(self) -> int:
"""Number of rows already yielded to the caller across all splits.
@@ -767,27 +587,12 @@ class StreamingDataset(IterableDataset):
every split has been consumed the same number of times (by the
round-robin design), so the per-split count is a single uniform value
that is identical across all ranks and DataLoader workers.
``positions_consumed_per_split`` records how far into each split's
permutation iteration has advanced. It only differs from
``samples_consumed_per_split`` when ``on_transform_error`` skipped
rows, in which case entries are exact for the splits this instance
iterated and a lower bound (the sample count) for splits owned by
other ranks or workers. Combine the state dicts from all ranks with
[merge_state_dicts][lancedb.streaming.StreamingDataset.merge_state_dicts]
to recover the exact value for every split before resuming on a
different topology.
"""
positions = [
self._resume_positions.get(split, self._resume_offset)
for split in range(self._num_splits)
]
return {
"shuffle_seed": self._shuffle_seed,
"num_splits": self._num_splits,
"epoch": self._epoch,
"samples_consumed_per_split": [self._resume_offset] * self._num_splits,
"positions_consumed_per_split": positions,
}
def load_state_dict(self, state: dict) -> None:
@@ -813,96 +618,3 @@ class StreamingDataset(IterableDataset):
self._resume_offset = consumed[0] if consumed else 0
else:
self._resume_offset = int(consumed)
# Older checkpoints predate positions_consumed_per_split; without
# skipped rows positions equal sample counts, so falling back to
# _resume_offset (the .get default in __iter__) is exact.
positions = state.get("positions_consumed_per_split")
if positions is None:
self._resume_positions = {}
else:
self._resume_positions = {
split: int(pos) for split, pos in enumerate(positions)
}
@staticmethod
def merge_state_dicts(states: list[dict]) -> dict:
"""Merge state dicts saved by different ranks into one exact state.
Only needed when ``on_transform_error`` skips rows in multi-rank
training: each rank then knows the exact permutation position only for
its own splits, and records a lower bound for the rest. Because
exactly one rank owns each split, the elementwise maximum across all
ranks' ``positions_consumed_per_split`` recovers the exact position of
every split. Without skipped rows every rank's state is already
identical and merging is a no-op.
Raises ``ValueError`` if the states are empty or were not produced by
the same run (mismatched seed, split count, epoch, or sample counts).
The merge is always all-to-all and topology-agnostic: collect the
``state_dict()`` from every rank of the *previous* run into one list,
merge that whole list, and hand the identical merged result to every
rank of the *next* run regardless of whether the rank count grew,
shrank, or stayed the same. There is no pairwise or subset merging
step, because each split's exact position is only known to whichever
rank owned that split, and the elementwise maximum needs every rank's
contribution to be correct.
For example, checkpointing 8 ranks and resuming on 4 (the same
pattern applies when growing, e.g. 4 ranks resuming on 8)::
states = [ds.state_dict() for ds in previous_run_datasets] # 8
merged = StreamingDataset.merge_state_dicts(states)
for ds in resumed_datasets: # now only 4 ranks
ds.load_state_dict(merged) # same dict on every rank
The rank count on either side never affects the merge itself, since
``merge_state_dicts`` only cares about the list of states it is
given. Each split's position is recovered by elementwise maximum;
here rank 0 owned split 0 (and skipped two rows there) while rank 1
owned split 1 (and skipped one row):
>>> rank0 = {
... "shuffle_seed": 0, "num_splits": 2, "epoch": 0,
... "samples_consumed_per_split": [3, 3],
... "positions_consumed_per_split": [5, 3],
... }
>>> rank1 = {
... "shuffle_seed": 0, "num_splits": 2, "epoch": 0,
... "samples_consumed_per_split": [3, 3],
... "positions_consumed_per_split": [3, 4],
... }
>>> merged = StreamingDataset.merge_state_dicts([rank0, rank1])
>>> merged["positions_consumed_per_split"]
[5, 4]
"""
if not states:
raise ValueError("merge_state_dicts requires at least one state dict")
first = states[0]
for state in states[1:]:
for key in ("shuffle_seed", "num_splits", "epoch"):
if state[key] != first[key]:
raise ValueError(
f"{key} mismatch across state dicts: "
f"{state[key]} != {first[key]}"
)
if (
state["samples_consumed_per_split"]
!= first["samples_consumed_per_split"]
):
raise ValueError(
"samples_consumed_per_split mismatch across state dicts; "
"state_dict() must be called at the same global step "
"boundary on every rank"
)
merged = dict(first)
all_positions = [
state.get(
"positions_consumed_per_split", state["samples_consumed_per_split"]
)
for state in states
]
merged["positions_consumed_per_split"] = [
max(per_split) for per_split in zip(*all_positions)
]
return merged
+10 -211
View File
@@ -176,7 +176,6 @@ if TYPE_CHECKING:
CompactionStats,
Tag,
AddColumnsResult,
RefreshColumnResult,
AddResult,
AlterColumnsResult,
UpdateFieldMetadataResult,
@@ -1917,14 +1916,7 @@ class Table(ABC):
@abstractmethod
def add_columns(
self,
transforms: Dict[str, str]
| pa.Field
| List[pa.Field]
| pa.Schema
| None = None,
*,
computed: Dict[str, str] | None = None,
self, transforms: Dict[str, str] | pa.Field | List[pa.Field] | pa.Schema
):
"""
Add new columns with defined values.
@@ -1938,95 +1930,11 @@ class Table(ABC):
Alternatively, a pyarrow Field or Schema can be provided to add
new columns with the specified data types. The new columns will
be initialized with null values.
computed: Dict[str, str], optional
A map of column name to a SQL expression defining the column. The
column's type and inputs are derived from the expression, so no
data type is supplied.
Unlike ``transforms``, the expression is stored rather than
evaluated now: the column is committed with no values, and rows get
them from [`refresh_column`][lancedb.table.Table.refresh_column].
Declaring one therefore costs the same on a large table as on an
empty one.
A refresh does not revisit rows it has already filled, so mutating
an input leaves the value computed at fill time; recomputing means
dropping the column and declaring it again. While a declaration
reads a column, that column cannot be renamed, retyped or dropped.
On LanceDB Cloud and Enterprise the expression is planned by the
server, and the refresh runs as a server job -- see
[`refresh_column_async`][lancedb.table.Table.refresh_column_async].
Cannot be combined with ``transforms``.
Returns
-------
AddColumnsResult
version: the new version number of the table after adding columns.
Examples
--------
>>> import lancedb
>>> db = lancedb.connect("./.lancedb")
>>> table = db.create_table("computed_demo", [{"x": 1}, {"x": 2}])
>>> table.add_columns(computed={"doubled": "x * 2"})
AddColumnsResult(version=2)
>>> table.refresh_column("doubled")
RefreshColumnResult(rows_filled=2, version=3)
>>> table.to_arrow().sort_by("x").to_pandas()
x doubled
0 1 2
1 2 4
"""
@abstractmethod
def refresh_column(self, column: str) -> "RefreshColumnResult":
"""
Fill the rows of a computed column that hold no value yet.
Declared with ``add_columns(computed=...)``, a column starts empty and
gets its values here. Rows appended since the last refresh are filled
by the next one; rows already filled are left as they are, so the call
is idempotent and does not observe a mutated input.
Local tables only: a remote refresh runs as a server job, through
[`refresh_column_async`][lancedb.table.Table.refresh_column_async].
Parameters
----------
column: str
The name of the computed column to fill.
Returns
-------
RefreshColumnResult
rows_filled: the number of rows given a value.
version: the new version number of the table.
"""
@abstractmethod
def refresh_column_async(self, column: str) -> Job:
"""
Like :meth:`refresh_column`, but returns a handle to the refresh job
instead of blocking until it completes.
The job may already be complete when returned; callers must not assume
the column is filled until :meth:`Job.wait` returns. Invalid input --
an unknown column, or one that is not computed -- raises here rather
than failing the job. On local tables the job runs in-process; on
LanceDB Cloud and Enterprise it is the server's backfill job.
Examples
--------
>>> import lancedb
>>> db = lancedb.connect("./.lancedb")
>>> table = db.create_table("computed_job_demo", [{"x": 1}, {"x": 2}])
>>> table.add_columns(computed={"doubled": "x * 2"})
AddColumnsResult(version=2)
>>> job = table.refresh_column_async("doubled")
>>> job.wait()
>>> job.status()
'finished'
"""
@abstractmethod
@@ -4031,28 +3939,9 @@ class LanceTable(Table):
return LOOP.run(self._table.index_stats(index_name))
def add_columns(
self,
transforms: Dict[str, str]
| pa.field
| List[pa.field]
| pa.Schema
| None = None,
*,
computed: Dict[str, str] | None = None,
self, transforms: Dict[str, str] | pa.field | List[pa.field] | pa.Schema
) -> AddColumnsResult:
return LOOP.run(self._table.add_columns(transforms, computed=computed))
def refresh_column(self, column: str) -> "RefreshColumnResult":
"""Fill a computed column's unfilled rows. See
[`AsyncTable.refresh_column`][lancedb.AsyncTable.refresh_column]."""
return LOOP.run(self._table.refresh_column(column))
def refresh_column_async(self, column: str) -> Job:
"""Fill a computed column's unfilled rows, returning a handle to the
refresh job. See
[`Table.refresh_column_async`][lancedb.table.Table.refresh_column_async].
"""
return Job(LOOP.run(self._table.refresh_column_async(column)))
return LOOP.run(self._table.add_columns(transforms))
def alter_columns(
self, *alterations: Iterable[Dict[str, str]]
@@ -4787,13 +4676,6 @@ class AsyncTable:
via [`set_unenforced_primary_key`]; bucket sharding additionally
requires it to be the single column being bucketed.
By default the MemWAL maintains every index on the table, resolved
here a snapshot, so an index created afterwards needs the spec unset
and set again. This fails if one cannot be maintained; name the set
with ``with_maintained_indexes`` to install anyway. That pins an exact
set (a still-building index is rejected, not omitted); ``[]`` maintains
none.
Parameters
----------
spec : LsmWriteSpec
@@ -4820,9 +4702,9 @@ class AsyncTable:
Returns ``None`` when the MemWAL LSM write path is not enabled (no
spec has been set, or it was removed with `unset_lsm_write_spec`).
The returned spec mirrors what was passed to `set_lsm_write_spec`,
except that ``maintained_indexes`` always reports the concrete list
resolved when the spec was set ``None`` never round-trips.
The returned spec including its ``maintained_indexes`` and
``writer_config_defaults`` mirrors what was passed to
`set_lsm_write_spec`.
"""
return await self._inner.get_lsm_write_spec()
@@ -4846,7 +4728,7 @@ class AsyncTable:
``asyncio.wait_for`` for a wall-clock bound; abandoning it partway
costs nothing.
"""
await self._inner.checkpoint_lsm()
return await self._inner.checkpoint_lsm()
async def flush_lsm(self) -> None:
"""Seal every bucket's active memtable into L0.
@@ -4855,7 +4737,7 @@ class AsyncTable:
`compact_lsm`. On a node that has not claimed this table, this claims
it and replays its WAL log first.
"""
await self._inner.flush_lsm()
return await self._inner.flush_lsm()
async def compact_lsm(self) -> None:
"""Trigger a background L0 to base compaction pass per bucket.
@@ -4864,7 +4746,7 @@ class AsyncTable:
``get_lsm_stats`` for progress, or use ``checkpoint_lsm`` to loop
until the current L0 has reached base.
"""
await self._inner.compact_lsm()
return await self._inner.compact_lsm()
async def get_lsm_stats(
self, *, include_generation_rows: bool = False
@@ -5967,14 +5849,7 @@ class AsyncTable:
return await self._inner.update(updates_sql, where)
async def add_columns(
self,
transforms: dict[str, str]
| pa.field
| List[pa.field]
| pa.Schema
| None = None,
*,
computed: dict[str, str] | None = None,
self, transforms: dict[str, str] | pa.field | List[pa.field] | pa.Schema
) -> AddColumnsResult:
"""
Add new columns with defined values.
@@ -5987,22 +5862,6 @@ class AsyncTable:
each row in the table, and can reference existing columns.
Alternatively, you can pass a pyarrow field or schema to add
new columns with NULLs.
computed: Dict[str, str], optional
A map of column name to a SQL expression defining the column. The
column's type and inputs are derived from the expression.
Unlike ``transforms``, the expression is stored rather than
evaluated now: the column is committed with no values, and rows get
them from
[`refresh_column`][lancedb.table.AsyncTable.refresh_column].
A refresh does not revisit rows it has already filled, so mutating
an input leaves the value computed at fill time. While a
declaration reads a column, that column cannot be renamed, retyped
or dropped.
On LanceDB Cloud and Enterprise the expression is planned by
the server. Cannot be combined with ``transforms``.
Returns
-------
@@ -6016,71 +5875,11 @@ class AsyncTable:
{isinstance(f, pa.Field) for f in transforms}
):
transforms = pa.schema(transforms)
if computed:
if transforms:
raise ValueError(
"add_columns cannot take both transforms and computed columns"
)
return await self._inner.add_computed_columns(list(computed.items()))
if transforms is None:
raise ValueError("add_columns requires transforms or computed columns")
if isinstance(transforms, pa.Schema):
return await self._inner.add_columns_with_schema(transforms)
else:
return await self._inner.add_columns(list(transforms.items()))
async def refresh_column(self, column: str) -> RefreshColumnResult:
"""
Fill the rows of a computed column that hold no value yet.
Declared with ``add_columns(computed=...)``, a column starts empty and
gets its values here. Rows appended since the last refresh are filled
by the next one; rows already filled are left as they are, so the call
is idempotent and does not observe a mutated input.
Local tables only: a remote refresh runs as a server job, through
[`refresh_column_async`][lancedb.table.Table.refresh_column_async].
Parameters
----------
column: str
The name of the computed column to fill.
Returns
-------
RefreshColumnResult
The number of rows filled and the new version of the table.
"""
return await self._inner.refresh_column(column)
async def refresh_column_async(self, column: str) -> AsyncJob:
"""
Like :meth:`refresh_column`, but returns a handle to the refresh job
instead of blocking until it completes.
The job may already be complete when returned; callers must not assume
the column is filled until :meth:`AsyncJob.wait` resolves. Invalid
input -- an unknown column, or one that is not computed -- raises here
rather than failing the job. On local tables the job runs
in-process; on LanceDB Cloud and Enterprise it is the server's
backfill job.
Examples
--------
>>> import asyncio
>>> import lancedb
>>> async def refresh_in_background():
... db = await lancedb.connect_async("./.lancedb")
... table = await db.create_table("computed_job_async_demo", [{"x": 1}])
... await table.add_columns(computed={"doubled": "x * 2"})
... job = await table.refresh_column_async("doubled")
... await job.wait()
... return await job.status()
>>> asyncio.run(refresh_in_background())
'finished'
"""
return AsyncJob(await self._inner.refresh_column_async(column))
async def alter_columns(
self, *alterations: Iterable[dict[str, Any]]
) -> AlterColumnsResult:
+3 -16
View File
@@ -755,7 +755,8 @@ def test_delete_table(tmp_db: lancedb.DBConnection):
assert tmp_db.table_names() == []
def test_drop_table_async(tmp_db: lancedb.DBConnection):
@pytest.mark.asyncio
async def test_delete_table_async(tmp_db: lancedb.DBConnection):
data = pd.DataFrame(
{
"vector": [[3.1, 4.1], [5.9, 26.5]],
@@ -771,10 +772,7 @@ def test_drop_table_async(tmp_db: lancedb.DBConnection):
assert tmp_db.table_names() == ["test"]
job = tmp_db.drop_table_async("test")
assert job.id is None
assert job.status() == "finished"
job.wait()
tmp_db.drop_table("test")
assert tmp_db.table_names() == []
tmp_db.create_table("test", data=data)
@@ -783,17 +781,6 @@ def test_drop_table_async(tmp_db: lancedb.DBConnection):
tmp_db.drop_table("does_not_exist", ignore_missing=True)
@pytest.mark.asyncio
async def test_drop_table_async_connection(tmp_db_async: lancedb.AsyncConnection):
await tmp_db_async.create_table("test", data=pa.table({"id": [1, 2]}))
job = await tmp_db_async.drop_table_async("test")
assert job.id is None
assert await job.status() == "finished"
await job.wait()
assert await tmp_db_async.table_names() == []
def test_drop_database(tmp_db: lancedb.DBConnection):
data = pd.DataFrame(
{
@@ -1456,408 +1456,6 @@ def test_shuffle_clump_size_yields_all_rows(lance_table):
)
# ---------------------------------------------------------------------------
# on_transform_error tests
# ---------------------------------------------------------------------------
class BadRowError(ValueError):
"""Raised by the failing transforms below when a batch contains a bad id."""
def _failing_transform(bad_ids: set):
"""A transform that raises BadRowError whenever the batch has a bad id.
Raises on the full batch and on any single-row slice containing a bad id,
so per-row isolation drops exactly the bad rows.
"""
def transform(batch: pa.RecordBatch) -> list:
ids = batch.column("id").to_pylist()
bad = sorted(set(ids) & bad_ids)
if bad:
raise BadRowError(f"bad ids in batch: {bad}")
return [{"id": i} for i in ids]
return transform
def _sequential_split_members(table) -> list[list[int]]:
"""Return each split's ids in yield order for shuffle=False.
With a single rank and no workers the round-robin yields one row per split
per cycle, so item k of a clean run belongs to split k % NUM_SPLITS.
"""
ds = StreamingDataset(table, num_splits=NUM_SPLITS, shuffle=False)
members: list[list[int]] = [[] for _ in range(NUM_SPLITS)]
for k, row in enumerate(ds):
members[k % NUM_SPLITS].append(row["id"])
return members
def test_on_transform_error_default_raises(lance_table):
"""By default a transform exception propagates and aborts iteration."""
ds = StreamingDataset(
lance_table,
num_splits=NUM_SPLITS,
shuffle_seed=SHUFFLE_SEED,
transform=_failing_transform({7}),
)
with pytest.raises(BadRowError):
list(ds)
def test_on_transform_error_invalid_value(lance_table):
with pytest.raises(ValueError, match="on_transform_error"):
StreamingDataset(lance_table, num_splits=NUM_SPLITS, on_transform_error="bogus")
def test_on_transform_error_skip_drops_bad_rows(lance_table):
"""With one bad row per split, 'skip' yields every good row exactly once
and counts the dropped rows in rows_skipped."""
members = _sequential_split_members(lance_table)
bad_ids = {members[i][4] for i in range(NUM_SPLITS)}
ds = StreamingDataset(
lance_table,
num_splits=NUM_SPLITS,
shuffle=False,
transform=_failing_transform(bad_ids),
on_transform_error="skip",
)
assert ds.rows_skipped == 0
ids = [row["id"] for row in ds]
assert sorted(ids) == sorted(set(range(NUM_ROWS)) - bad_ids)
assert ds.rows_skipped == NUM_SPLITS
def test_on_transform_error_skip_uneven_ends_at_last_complete_cycle(lance_table):
"""When one split loses more rows than the others, the epoch ends at the
last cycle where every split still has a row no crash, no bad rows, and
every step remains one sample per split."""
members = _sequential_split_members(lance_table)
bad_ids = set(members[0][:3]) # all 3 bad rows in split 0
ds = StreamingDataset(
lance_table,
num_splits=NUM_SPLITS,
shuffle=False,
transform=_failing_transform(bad_ids),
on_transform_error="skip",
)
items = [row["id"] for row in ds]
rows_per_split = NUM_ROWS // NUM_SPLITS
expected_cycles = rows_per_split - len(bad_ids)
assert len(items) == expected_cycles * NUM_SPLITS
assert len(set(items)) == len(items), "duplicate samples yielded"
assert not set(items) & bad_ids, "a bad row was yielded"
# Split 0 contributed exactly its surviving rows, in order, one per cycle.
survivors = [i for i in members[0] if i not in bad_ids]
assert items[0::NUM_SPLITS] == survivors[:expected_cycles]
def test_on_transform_error_warn_logs(lance_table, caplog):
"""'warn' skips like 'skip' but logs a warning for the failing batch."""
members = _sequential_split_members(lance_table)
bad_ids = {members[i][3] for i in range(NUM_SPLITS)}
ds = StreamingDataset(
lance_table,
num_splits=NUM_SPLITS,
shuffle=False,
transform=_failing_transform(bad_ids),
on_transform_error="warn",
)
with caplog.at_level(logging.WARNING, logger="lancedb.streaming"):
items = list(ds)
assert len(items) == NUM_ROWS - NUM_SPLITS
assert ds.rows_skipped == NUM_SPLITS
assert "Skipped" in caplog.text
assert "BadRowError" in caplog.text
def test_on_transform_error_callable_selective(lance_table):
"""A callable handler can skip expected errors and re-raise the rest."""
members = _sequential_split_members(lance_table)
bad_ids = {members[i][0] for i in range(NUM_SPLITS)}
handled: list[Exception] = []
def handler(exc: Exception) -> bool:
handled.append(exc)
return isinstance(exc, BadRowError)
ds = StreamingDataset(
lance_table,
num_splits=NUM_SPLITS,
shuffle=False,
transform=_failing_transform(bad_ids),
on_transform_error=handler,
)
items = list(ds)
assert len(items) == NUM_ROWS - NUM_SPLITS
assert handled and all(isinstance(exc, BadRowError) for exc in handled)
def broken_transform(batch: pa.RecordBatch) -> list:
raise TypeError("boom")
ds2 = StreamingDataset(
lance_table,
num_splits=NUM_SPLITS,
shuffle=False,
transform=broken_transform,
on_transform_error=handler,
)
with pytest.raises(TypeError, match="boom"):
list(ds2)
def test_transform_wrong_row_count_raises(lance_table):
"""A transform that returns the wrong number of rows is an error even with
on_transform_error='skip' silent shrinkage would corrupt accounting."""
def drops_rows(batch: pa.RecordBatch) -> list:
return batch.column("id").to_pylist()[:-1]
ds = StreamingDataset(
lance_table,
num_splits=NUM_SPLITS,
shuffle_seed=SHUFFLE_SEED,
transform=drops_rows,
on_transform_error="skip",
)
with pytest.raises(ValueError, match="one output row per input row"):
list(ds)
def test_skip_deterministic_across_runs(lance_table):
"""With a fixed seed, skipping produces the identical sample sequence on
every run skips are data-dependent, not run-dependent."""
bad_ids = {5, 17, 46}
def run() -> tuple[list[int], int]:
ds = StreamingDataset(
lance_table,
num_splits=NUM_SPLITS,
shuffle_seed=SHUFFLE_SEED,
transform=_failing_transform(bad_ids),
on_transform_error="skip",
)
return [row["id"] for row in ds], ds.rows_skipped
ids_a, skipped_a = run()
ids_b, skipped_b = run()
assert ids_a == ids_b
assert skipped_a == skipped_b
assert not set(ids_a) & bad_ids
def test_skip_elastic_det_across_world_sizes(lance_table):
"""With equal bad-row counts per split, skipping preserves the full
elastic-determinism guarantee: identical global batches at every step for
every compatible world_size."""
members = _sequential_split_members(lance_table)
bad_ids = {members[i][6] for i in range(NUM_SPLITS)}
def collect(world_size: int) -> list[frozenset[int]]:
micro = GLOBAL_BATCH_SIZE // world_size
iters = [
iter(
StreamingDataset(
lance_table,
num_splits=NUM_SPLITS,
shuffle=False,
rank=rank,
world_size=world_size,
transform=_failing_transform(bad_ids),
on_transform_error="skip",
)
)
for rank in range(world_size)
]
_STOP = object()
batches: list[frozenset[int]] = []
while True:
step_samples: set[int] = set()
exhausted = 0
for it in iters:
for _ in range(micro):
val = next(it, _STOP)
if val is _STOP:
exhausted += 1
break
step_samples.add(val["id"])
if exhausted == len(iters):
break
assert exhausted == 0, (
"Rank iterators exhausted at different steps despite equal "
"bad-row counts per split"
)
batches.append(frozenset(step_samples))
return batches
reference = collect(1)
assert len(reference) == NUM_ROWS // NUM_SPLITS - 1
for ws in (2, 3, 4):
assert collect(ws) == reference, f"world_size={ws} diverged"
def test_resumability_with_skips_same_topology(lance_table):
"""Checkpointing mid-epoch with skipped rows resumes exactly: no sample
repeated, no sample lost, skipped rows stay skipped."""
members = _sequential_split_members(lance_table)
# Uneven skips: positions diverge across splits (2 bad in split 0, 1 in
# split 5), which only a position-based checkpoint can resume exactly.
bad_ids = {members[0][2], members[0][3], members[5][7]}
kwargs = dict(
num_splits=NUM_SPLITS,
shuffle=False,
transform=_failing_transform(bad_ids),
on_transform_error="skip",
)
reference = [row["id"] for row in StreamingDataset(lance_table, **kwargs)]
rows_per_split = NUM_ROWS // NUM_SPLITS
assert len(reference) == (rows_per_split - 2) * NUM_SPLITS
steps = 3
ds = StreamingDataset(lance_table, **kwargs)
it = iter(ds)
consumed = [next(it)["id"] for _ in range(steps * NUM_SPLITS)]
checkpoint = ds.state_dict()
it.close()
# Split 0 skipped positions 2 and 3 within its first 3 yields; split 5's
# bad row is beyond the checkpoint. Everything else is at 3 = the sample
# count.
positions = checkpoint["positions_consumed_per_split"]
assert positions[0] == 5
assert positions[1:] == [3] * (NUM_SPLITS - 1)
assert checkpoint["samples_consumed_per_split"] == [3] * NUM_SPLITS
ds2 = StreamingDataset(lance_table, **kwargs)
ds2.load_state_dict(checkpoint)
resumed = [row["id"] for row in ds2]
assert consumed == reference[: steps * NUM_SPLITS]
assert resumed == reference[steps * NUM_SPLITS :]
def test_resumability_with_skips_elastic_merge(lance_table):
"""Elastic resume with skips: each rank's checkpoint knows exact positions
only for its own splits; merge_state_dicts recovers the global state, and
a run on a different world_size continues exactly."""
members = _sequential_split_members(lance_table)
# Bad rows early in split 0 (rank 0) and split 6 (rank 1 of a ws=2 run) so
# both ranks' position vectors diverge before the checkpoint.
bad_ids = {members[0][0], members[0][2], members[6][1]}
kwargs = dict(
num_splits=NUM_SPLITS,
shuffle=False,
transform=_failing_transform(bad_ids),
on_transform_error="skip",
)
reference = [row["id"] for row in StreamingDataset(lance_table, **kwargs)]
steps = 3
world_size = 2
micro = GLOBAL_BATCH_SIZE // world_size
datasets = [
StreamingDataset(lance_table, rank=rank, world_size=world_size, **kwargs)
for rank in range(world_size)
]
iters = [iter(ds) for ds in datasets]
seen: list[frozenset[int]] = []
for _ in range(steps):
step_samples = set()
for it in iters:
for _ in range(micro):
step_samples.add(next(it)["id"])
seen.append(frozenset(step_samples))
states = [ds.state_dict() for ds in datasets]
for it in iters:
it.close()
merged = StreamingDataset.merge_state_dicts(states)
expected_positions = [3] * NUM_SPLITS
expected_positions[0] = 5 # skipped positions 0 and 2
expected_positions[6] = 4 # skipped position 1
assert merged["positions_consumed_per_split"] == expected_positions
# The first 3 global batches match the world_size=1 reference.
ref_batches = [
frozenset(reference[s * NUM_SPLITS : (s + 1) * NUM_SPLITS])
for s in range(len(reference) // NUM_SPLITS)
]
assert seen == ref_batches[:steps]
# Resume on world_size=1 from the merged state.
ds_resume = StreamingDataset(lance_table, **kwargs)
ds_resume.load_state_dict(merged)
resumed = [row["id"] for row in ds_resume]
assert resumed == reference[steps * NUM_SPLITS :]
def test_rows_skipped_flushed_when_split_entirely_bad(lance_table):
"""A split whose rows all fail never completes a cycle, so the epoch ends
immediately but rows_skipped must still report the drops after the
iterator exits (the shared-memory counter is flushed on exhaustion)."""
members = _sequential_split_members(lance_table)
bad_ids = set(members[0]) # every row of split 0 is bad
ds = StreamingDataset(
lance_table,
num_splits=NUM_SPLITS,
shuffle=False,
transform=_failing_transform(bad_ids),
on_transform_error="skip",
)
assert list(ds) == []
assert ds.rows_skipped == len(bad_ids)
def test_merge_state_dicts_validates_consistency(lance_table):
ds = StreamingDataset(lance_table, num_splits=NUM_SPLITS, shuffle_seed=SHUFFLE_SEED)
state = ds.state_dict()
other = dict(state, shuffle_seed=SHUFFLE_SEED + 1)
with pytest.raises(ValueError, match="shuffle_seed mismatch"):
StreamingDataset.merge_state_dicts([state, other])
with pytest.raises(ValueError, match="at least one"):
StreamingDataset.merge_state_dicts([])
def test_load_state_dict_without_positions_key(lance_table):
"""Checkpoints from before positions_consumed_per_split existed still
resume exactly (positions equal sample counts when nothing is skipped)."""
reference = [
row["id"]
for row in StreamingDataset(
lance_table, num_splits=NUM_SPLITS, shuffle_seed=SHUFFLE_SEED
)
]
steps = 4
ds = StreamingDataset(lance_table, num_splits=NUM_SPLITS, shuffle_seed=SHUFFLE_SEED)
it = iter(ds)
for _ in range(steps * NUM_SPLITS):
next(it)
checkpoint = ds.state_dict()
it.close()
del checkpoint["positions_consumed_per_split"]
ds2 = StreamingDataset(
lance_table, num_splits=NUM_SPLITS, shuffle_seed=SHUFFLE_SEED
)
ds2.load_state_dict(checkpoint)
resumed = [row["id"] for row in ds2]
assert resumed == reference[steps * NUM_SPLITS :]
def test_num_splits_defaults_to_world_size(lance_table):
"""Omitting num_splits gives world_size splits (one per rank)."""
ds = StreamingDataset(
-98
View File
@@ -632,101 +632,3 @@ class TestExprBytesIntegration:
.to_arrow()
)
assert result.num_rows == 2
# ── datetime / timezone integration for lit() (issue #3262) ──────────────────
class TestExprDatetimeTimezoneIntegration:
"""Integration coverage for lit(datetime) against table timestamp columns.
PyArrow stores naive timestamps as UTC wall-clock microseconds. Python's
datetime.timestamp() treats naive values as *local* time, which used to
shift lit(naive) by the host UTC offset and break equality filters on
non-UTC machines. These cases lock the expected semantics.
"""
def test_both_naive_match(self, tmp_path):
"""Table naive + lit naive with the same wall clock must match."""
db = lancedb.connect(str(tmp_path / "naive"))
ts = datetime(2024, 7, 1, 10, 0, 0)
table = db.create_table(
"t", [{"id": 1, "ts": ts}, {"id": 2, "ts": datetime(2024, 7, 2, 10, 0, 0)}]
)
result = table.search().where(col("ts") == lit(ts)).to_list()
assert len(result) == 1
assert result[0]["id"] == 1
def test_both_same_timezone_match(self, tmp_path):
"""Table UTC + lit UTC for the same instant must match."""
db = lancedb.connect(str(tmp_path / "utc"))
ts = datetime(2024, 7, 1, 10, 0, 0, tzinfo=timezone.utc)
table = db.create_table(
"t",
pa.table(
{
"id": [1, 2],
"ts": pa.array(
[ts, datetime(2024, 7, 2, 10, 0, 0, tzinfo=timezone.utc)],
type=pa.timestamp("us", tz="UTC"),
),
}
),
)
result = table.search().where(col("ts") == lit(ts)).to_list()
assert len(result) == 1
assert result[0]["id"] == 1
def test_different_timezones_same_instant(self, tmp_path):
"""UTC table row equals lit of the same instant in a different zone."""
db = lancedb.connect(str(tmp_path / "diff_tz"))
ts_utc = datetime(2024, 7, 1, 10, 0, 0, tzinfo=timezone.utc)
# Same instant as 06:00 in UTC-4
ts_est = datetime(2024, 7, 1, 6, 0, 0, tzinfo=timezone(timedelta(hours=-4)))
table = db.create_table(
"t",
pa.table(
{
"id": [1],
"ts": pa.array([ts_utc], type=pa.timestamp("us", tz="UTC")),
}
),
)
result = table.search().where(col("ts") == lit(ts_est)).to_list()
assert len(result) == 1
assert result[0]["id"] == 1
def test_table_tz_literal_naive(self, tmp_path):
"""UTC table + naive lit uses wall-clock equality (10:00 == 10:00 UTC)."""
db = lancedb.connect(str(tmp_path / "tz_naive"))
ts_utc = datetime(2024, 7, 1, 10, 0, 0, tzinfo=timezone.utc)
ts_naive = datetime(2024, 7, 1, 10, 0, 0)
table = db.create_table(
"t",
pa.table(
{
"id": [1],
"ts": pa.array([ts_utc], type=pa.timestamp("us", tz="UTC")),
}
),
)
result = table.search().where(col("ts") == lit(ts_naive)).to_list()
assert len(result) == 1
assert result[0]["id"] == 1
def test_table_naive_literal_aware(self, tmp_path):
"""Naive table + UTC lit with the same wall clock must match."""
db = lancedb.connect(str(tmp_path / "naive_aware"))
ts_naive = datetime(2024, 7, 1, 10, 0, 0)
ts_utc = datetime(2024, 7, 1, 10, 0, 0, tzinfo=timezone.utc)
table = db.create_table("t", [{"id": 1, "ts": ts_naive}])
result = table.search().where(col("ts") == lit(ts_utc)).to_list()
assert len(result) == 1
assert result[0]["id"] == 1
def test_naive_lit_sql_is_wall_clock_not_local_shifted(self):
"""Regression: naive lit must not apply the host local UTC offset."""
ts = datetime(2024, 7, 1, 10, 0, 0)
sql = lit(ts).to_sql()
# Must encode 10:00 wall clock, not 10:00+local_offset.
assert "2024-07-01 10:00:00" in sql
-25
View File
@@ -203,31 +203,6 @@ async def test_async_hybrid_query_default_limit(table: AsyncTable):
assert texts.count("a") == 1
def test_hybrid_query_offset(sync_table: Table):
# The offset window of a hybrid query must be a suffix of the same query
# run without an offset -- it must not be silently ignored.
full = (
sync_table.search(query_type="hybrid")
.vector([0.0, 0.4])
.text("dog")
.limit(4)
.with_row_id(True)
.to_arrow()
)
assert len(full) == 4
offset_result = (
sync_table.search(query_type="hybrid")
.vector([0.0, 0.4])
.text("dog")
.offset(2)
.limit(2)
.with_row_id(True)
.to_arrow()
)
assert offset_result["_rowid"].to_pylist() == full["_rowid"].to_pylist()[2:]
def test_hybrid_query_minimum_nprobes_zero_raises(sync_table: Table):
# minimum_nprobes(0) must raise the same validation error a plain vector
# query raises, not silently no-op because 0 is falsy.
+4 -11
View File
@@ -83,9 +83,7 @@ def test_lsm_write_spec_repr():
assert s.spec_type == "bucket"
assert s.column == "id"
assert s.num_buckets == 4
# A fresh spec defers its maintained set to install time.
assert s.maintained_indexes is None
assert s.with_maintained_indexes([]).maintained_indexes == []
assert s.maintained_indexes == []
assert "bucket" in repr(s)
assert "id" in repr(s)
assert "4" in repr(s)
@@ -171,23 +169,18 @@ def test_get_lsm_write_spec(tmp_path):
table.unset_lsm_write_spec()
assert table.get_lsm_write_spec() is None
# Identity round-trips (column recovered from the schema). Leaving the
# maintained set to be inferred picks up the index on the table, so the
# spec reads back naming it rather than as "infer".
# Identity round-trips (column recovered from the schema).
table.set_lsm_write_spec(LsmWriteSpec.identity("id"))
spec = table.get_lsm_write_spec()
assert spec.spec_type == "identity"
assert spec.column == "id"
assert spec.maintained_indexes == [idx_name]
table.unset_lsm_write_spec()
# Unsharded round-trips (no routing column). Opting out is distinct from
# the inferred default.
table.set_lsm_write_spec(LsmWriteSpec.unsharded().with_maintained_indexes([]))
# Unsharded round-trips (no routing column).
table.set_lsm_write_spec(LsmWriteSpec.unsharded())
spec = table.get_lsm_write_spec()
assert spec.spec_type == "unsharded"
assert spec.column is None
assert spec.maintained_indexes == []
@pytest.mark.asyncio
+2 -2
View File
@@ -544,7 +544,7 @@ def test_lsm_read_fts_unmaintained_index_errors(tmp_path):
table.create_index("text", config=FTS())
# No maintained indexes: the active memtable FTS arm cannot serve un-compacted
# docs, so the search would silently omit them — reject instead.
table.set_lsm_write_spec(LsmWriteSpec.unsharded().with_maintained_indexes([]))
table.set_lsm_write_spec(LsmWriteSpec.unsharded())
with pytest.raises(Exception, match="maintained"):
table.search("fox", query_type="fts", fts_columns="text").to_arrow()
@@ -631,7 +631,7 @@ def test_lsm_read_vector_unmaintained_index_errors(tmp_path):
)
# Spec with NO maintained indexes: the base vector index's catch-up is untracked,
# so the scanner rejects rather than risk dropping compacted-but-unindexed rows.
table.set_lsm_write_spec(LsmWriteSpec.unsharded().with_maintained_indexes([]))
table.set_lsm_write_spec(LsmWriteSpec.unsharded())
with pytest.raises(Exception, match="maintained"):
table.search([1.0] * VECTOR_DIM).to_arrow()
-125
View File
@@ -1133,131 +1133,6 @@ def test_stats():
assert res == stats
@contextlib.contextmanager
def lsm_test_table(lsm_handler):
"""A remote table whose LSM routes are served by ``lsm_handler``.
``lsm_handler(request, route)`` is called for ``/v1/table/test/<route>/``
where route is one of flush_lsm, compact_lsm, get_lsm_stats, and is
responsible for writing the response.
"""
routes = ("flush_lsm", "compact_lsm", "get_lsm_stats")
def handler(request):
match = re.fullmatch(r"/v1/table/test/(\w+)/", request.path)
route = match.group(1) if match else None
if route in routes:
lsm_handler(request, route)
elif route == "describe":
request.send_response(200)
request.send_header("Content-Type", "application/json")
request.end_headers()
request.wfile.write(b'{"version": 1, "schema": {"fields": []}}')
else:
request.send_response(404)
request.end_headers()
with mock_lancedb_connection(handler) as db:
yield db.open_table("test")
def read_json_body(request):
content_len = int(request.headers.get("Content-Length"))
return json.loads(request.rfile.read(content_len))
def send_json(request, payload, status=200):
request.send_response(status)
request.send_header("Content-Type", "application/json")
request.end_headers()
request.wfile.write(json.dumps(payload).encode())
def test_get_lsm_stats_sync():
"""The sync wrapper round-trips the server payload into a dict."""
bucket = {
"shard_id": "b0",
"status": "Active",
"writer_epoch": 3,
"manifest_version": 12,
"current_generation": 6,
"replay_after_wal_entry_position": 40,
"wal_entry_position_last_seen": 42,
"generations": [{"generation": 5, "bytes": 1024, "rows": 7}],
"compacting": False,
"memtables": [
{
"generation": 6,
"rows": 2,
"bytes": 64,
"batches": 1,
"indexes": ["vec_idx"],
}
],
}
seen_bodies = []
def lsm_handler(request, route):
assert route == "get_lsm_stats"
seen_bodies.append(read_json_body(request))
send_json(request, {"lsm_stats": {"buckets": [bucket]}})
with lsm_test_table(lsm_handler) as table:
assert table.get_lsm_stats() == {"buckets": [bucket]}
# Off by default, and forwarded when asked for.
assert seen_bodies == [{"include_generation_rows": False}]
table.get_lsm_stats(include_generation_rows=True)
assert seen_bodies[-1] == {"include_generation_rows": True}
def test_get_lsm_stats_sync_returns_none_when_lsm_disabled():
"""A null envelope means the LSM write path is not enabled, not an error."""
def lsm_handler(request, route):
send_json(request, {"lsm_stats": None})
with lsm_test_table(lsm_handler) as table:
assert table.get_lsm_stats() is None
def test_flush_and_compact_lsm_sync():
"""Both are one-shot POSTs answered 202 with no body."""
called = []
def lsm_handler(request, route):
called.append(route)
request.send_response(202)
request.end_headers()
with lsm_test_table(lsm_handler) as table:
assert table.flush_lsm() is None
assert table.compact_lsm() is None
assert called == ["flush_lsm", "compact_lsm"]
def test_checkpoint_lsm_sync():
"""Seal, read the watermark, and return once L0 holds nothing.
The convergence loop itself is covered in Rust; this pins the sync
binding to the endpoints it drives.
"""
called = []
def lsm_handler(request, route):
called.append(route)
if route == "get_lsm_stats":
# An empty L0 yields no target watermark, so the loop is done
# after the seal without ever polling compaction.
send_json(request, {"lsm_stats": {"buckets": []}})
else:
request.send_response(202)
request.end_headers()
with lsm_test_table(lsm_handler) as table:
assert table.checkpoint_lsm() is None
assert called == ["flush_lsm", "get_lsm_stats"]
@contextlib.contextmanager
def query_test_table(query_handler, *, server_version=Version("0.1.0")):
def handler(request):
-62
View File
@@ -3854,65 +3854,3 @@ async def test_async_search_runs_embedding_on_dedicated_executor(
assert all(name.startswith("lancedb-embedding") for name in captured_threads), (
f"embedding ran off the dedicated executor: {captured_threads}"
)
def test_computed_column_declare_and_refresh(tmp_path):
db = lancedb.connect(tmp_path)
table = db.create_table("computed", [{"x": 1}, {"x": 2}])
table.add_columns(computed={"doubled": "x * 2"})
assert table.to_arrow()["doubled"].to_pylist() == [None, None]
result = table.refresh_column("doubled")
assert result.rows_filled == 2
assert sorted(table.to_arrow()["doubled"].to_pylist()) == [2, 4]
table.add([{"x": 5}])
assert table.refresh_column("doubled").rows_filled == 1
assert sorted(table.to_arrow()["doubled"].to_pylist()) == [2, 4, 10]
def test_computed_column_rejects_transforms_and_computed_together(tmp_path):
db = lancedb.connect(tmp_path)
table = db.create_table("computed_mixed", [{"x": 1}])
with pytest.raises(ValueError):
table.add_columns({"a": "x + 1"}, computed={"b": "x * 2"})
@pytest.mark.asyncio
async def test_computed_column_async(tmp_path):
db = await lancedb.connect_async(tmp_path)
table = await db.create_table("computed_async", [{"x": 3}])
await table.add_columns(computed={"tripled": "x * 3"})
await table.refresh_column("tripled")
assert (await table.to_arrow())["tripled"].to_pylist() == [9]
def test_refresh_column_async_returns_job(tmp_path):
db = lancedb.connect(tmp_path)
table = db.create_table("computed_job", [{"x": 1}, {"x": 2}])
table.add_columns(computed={"doubled": "x * 2"})
job = table.refresh_column_async("doubled")
assert job.id is None # in-process jobs have no server id
job.wait()
assert job.status() == "finished"
assert sorted(table.to_arrow()["doubled"].to_pylist()) == [2, 4]
# Bad input raises at the call, not through the job.
with pytest.raises(Exception, match="not a computed column"):
table.refresh_column_async("x")
@pytest.mark.asyncio
async def test_refresh_column_async_job_async_table(tmp_path):
db = await lancedb.connect_async(tmp_path)
table = await db.create_table("computed_job_async", [{"x": 3}])
await table.add_columns(computed={"tripled": "x * 3"})
job = await table.refresh_column_async("tripled")
await job.wait()
assert await job.status() == "finished"
assert (await table.to_arrow())["tripled"].to_pylist() == [9]
-17
View File
@@ -346,23 +346,6 @@ impl Connection {
})
}
#[pyo3(signature = (name, namespace_path=None))]
pub fn drop_table_async(
self_: PyRef<'_, Self>,
name: String,
namespace_path: Option<Vec<String>>,
) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.get_inner()?.clone();
let ns_path = namespace_path.unwrap_or_default();
future_into_py(self_.py(), async move {
inner
.drop_table_async(name, &ns_path)
.await
.infer_error()
.map(crate::job::Job::new)
})
}
#[pyo3(signature = (namespace_path=None,))]
pub fn drop_all_tables(
self_: PyRef<'_, Self>,
+1 -20
View File
@@ -191,27 +191,8 @@ pub fn expr_lit(value: Bound<'_, PyAny>) -> PyResult<PyExpr> {
}
// datetime.datetime is a subclass of datetime.date, so it must be checked first.
//
// Python's datetime.timestamp() treats *naive* datetimes as local wall time.
// PyArrow (and therefore Lance table storage) encodes naive timestamps as
// UTC wall-clock microseconds. Using .timestamp() for naive values therefore
// shifts the literal by the local UTC offset on non-UTC machines, so
// `col("ts") == lit(naive_dt)` fails against a table that holds the same
// naive value. Fix: treat naive datetimes as UTC wall clock (match Arrow);
// keep aware datetimes on the real .timestamp() path (correct epoch).
if let Ok(dt) = value.cast::<PyDateTime>() {
let ts: f64 = if dt.getattr("tzinfo")?.is_none() {
// Force UTC interpretation of the naive wall clock.
let utc = pyo3::types::PyModule::import(value.py(), "datetime")?
.getattr("timezone")?
.getattr("utc")?;
let kwargs = pyo3::types::PyDict::new(value.py());
kwargs.set_item("tzinfo", utc)?;
let aware = dt.call_method("replace", (), Some(&kwargs))?;
aware.call_method0("timestamp")?.extract()?
} else {
dt.call_method0("timestamp")?.extract()?
};
let ts: f64 = dt.call_method0("timestamp")?.extract()?;
let micros = (ts * 1_000_000.0).round() as i64;
return Ok(PyExpr(df_lit(ScalarValue::TimestampMicrosecond(
Some(micros),
+1 -1
View File
@@ -289,7 +289,7 @@ struct IvfHnswFlatParams {
target_partition_size: Option<u32>,
}
#[pyclass(module = "lancedb._lancedb", get_all)]
#[pyclass(get_all)]
/// A description of an index currently configured on a column
pub struct IndexConfig {
/// The type of the index
+1 -3
View File
@@ -16,8 +16,7 @@ use query::{FTSQuery, HybridQuery, Query, VectorQuery};
use session::Session;
use table::{
AddColumnsResult, AddResult, AlterColumnsResult, DeleteResult, DropColumnsResult, FtsToken,
LsmWriteSpec, MergeResult, PyBlobFile, RefreshColumnResult, Table, UpdateFieldMetadataResult,
UpdateResult,
LsmWriteSpec, MergeResult, PyBlobFile, Table, UpdateFieldMetadataResult, UpdateResult,
};
pub mod arrow;
@@ -58,7 +57,6 @@ pub fn _lancedb(_py: Python, m: &Bound<'_, PyModule>) -> PyResult<()> {
m.add_class::<VectorQuery>()?;
m.add_class::<RecordBatchStream>()?;
m.add_class::<AddColumnsResult>()?;
m.add_class::<RefreshColumnResult>()?;
m.add_class::<AlterColumnsResult>()?;
m.add_class::<UpdateFieldMetadataResult>()?;
m.add_class::<AddResult>()?;
+1 -1
View File
@@ -11,7 +11,7 @@ use pyo3::{PyResult, pyclass, pymethods};
/// Sessions allow you to configure cache sizes for index and metadata caches,
/// which can significantly impact memory use and performance. They can
/// also be re-used across multiple connections to share the same cache state.
#[pyclass(module = "lancedb._lancedb", from_py_object)]
#[pyclass(from_py_object)]
#[derive(Clone)]
pub struct Session {
pub(crate) inner: Arc<LanceSession>,
+16 -92
View File
@@ -246,22 +246,12 @@ impl From<lancedb::table::MergeResult> for MergeResult {
}
}
/// Render for `__repr__`, so the default reads as Python's `None` rather than
/// Rust's `Some([..])`.
fn fmt_maintained(maintained: &Option<Vec<String>>) -> String {
match maintained {
Some(names) => format!("{:?}", names),
None => "None".to_string(),
}
}
/// Specification selecting Lance's MemWAL LSM-style write path for
/// `merge_insert`.
///
/// Constructed via the `bucket(...)`, `identity(...)`, or `unsharded()`
/// classmethods, then optionally chain `with_maintained_indexes(...)` and
/// `with_writer_config_defaults(...)`. A fresh spec maintains every index the
/// MemWAL supports, resolved on install.
/// `with_writer_config_defaults(...)`.
#[pyclass(from_py_object)]
#[derive(Clone, Debug)]
pub struct LsmWriteSpec {
@@ -301,11 +291,11 @@ impl LsmWriteSpec {
}
}
/// Set which indexes the MemWAL maintains. `None` (the default)
/// resolves every supported index on install; a list is verbatim,
/// and an empty list maintains nothing.
#[pyo3(signature = (indexes))]
pub fn with_maintained_indexes(&self, indexes: Option<Vec<String>>) -> Self {
/// Replace the list of indexes the MemWAL should keep up to date as
/// rows are appended. Each name must reference an index that
/// already exists on the table at the time `set_lsm_write_spec`
/// is called.
pub fn with_maintained_indexes(&self, indexes: Vec<String>) -> Self {
Self {
inner: self.inner.clone().with_maintained_indexes(indexes),
}
@@ -327,29 +317,23 @@ impl LsmWriteSpec {
maintained_indexes,
writer_config_defaults,
} => format!(
"LsmWriteSpec.bucket(column={:?}, num_buckets={}, maintained_indexes={}, writer_config_defaults={:?})",
column,
num_buckets,
fmt_maintained(maintained_indexes),
writer_config_defaults,
"LsmWriteSpec.bucket(column={:?}, num_buckets={}, maintained_indexes={:?}, writer_config_defaults={:?})",
column, num_buckets, maintained_indexes, writer_config_defaults,
),
lancedb::table::LsmWriteSpec::Identity {
column,
maintained_indexes,
writer_config_defaults,
} => format!(
"LsmWriteSpec.identity(column={:?}, maintained_indexes={}, writer_config_defaults={:?})",
column,
fmt_maintained(maintained_indexes),
writer_config_defaults,
"LsmWriteSpec.identity(column={:?}, maintained_indexes={:?}, writer_config_defaults={:?})",
column, maintained_indexes, writer_config_defaults,
),
lancedb::table::LsmWriteSpec::Unsharded {
maintained_indexes,
writer_config_defaults,
} => format!(
"LsmWriteSpec.unsharded(maintained_indexes={}, writer_config_defaults={:?})",
fmt_maintained(maintained_indexes),
writer_config_defaults,
"LsmWriteSpec.unsharded(maintained_indexes={:?}, writer_config_defaults={:?})",
maintained_indexes, writer_config_defaults,
),
}
}
@@ -384,10 +368,10 @@ impl LsmWriteSpec {
}
}
/// Indexes the MemWAL keeps up to date, or `None` for every supported one.
/// Names of indexes the MemWAL should keep up to date during writes.
#[getter]
pub fn maintained_indexes(&self) -> Option<Vec<String>> {
self.inner.maintained_indexes().map(<[String]>::to_vec)
pub fn maintained_indexes(&self) -> Vec<String> {
self.inner.maintained_indexes().to_vec()
}
/// Default `ShardWriter` configuration recorded by this spec.
@@ -415,32 +399,6 @@ pub struct AddColumnsResult {
pub version: u64,
}
#[pyclass(get_all, from_py_object)]
#[derive(Clone, Debug)]
pub struct RefreshColumnResult {
pub rows_filled: u64,
pub version: u64,
}
#[pymethods]
impl RefreshColumnResult {
pub fn __repr__(&self) -> String {
format!(
"RefreshColumnResult(rows_filled={}, version={})",
self.rows_filled, self.version
)
}
}
impl From<lancedb::table::RefreshColumnResult> for RefreshColumnResult {
fn from(result: lancedb::table::RefreshColumnResult) -> Self {
Self {
rows_filled: result.rows_filled,
version: result.version,
}
}
}
#[pymethods]
impl AddColumnsResult {
pub fn __repr__(&self) -> String {
@@ -605,7 +563,7 @@ impl PyBlobFile {
}
}
#[pyclass(module = "lancedb._lancedb", get_all, from_py_object)]
#[pyclass(get_all, from_py_object)]
#[derive(Clone, Debug)]
pub struct FtsToken {
pub text: String,
@@ -1536,40 +1494,6 @@ impl Table {
})
}
pub fn add_computed_columns(
self_: PyRef<'_, Self>,
columns: Vec<(String, String)>,
) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
let mut builder = inner.add_columns();
for (name, expression) in columns {
builder = builder.computed(name, expression);
}
let result = builder.execute().await.infer_error()?;
Ok(AddColumnsResult::from(result))
})
}
pub fn refresh_column(self_: PyRef<'_, Self>, column: String) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
let result = inner.refresh_column(column).await.infer_error()?;
Ok(RefreshColumnResult::from(result))
})
}
pub fn refresh_column_async(
self_: PyRef<'_, Self>,
column: String,
) -> PyResult<Bound<'_, PyAny>> {
let inner = self_.inner_ref()?.clone();
future_into_py(self_.py(), async move {
let job = inner.refresh_column_async(column).await.infer_error()?;
Ok(crate::job::Job::new(job))
})
}
pub fn add_columns_with_schema(
self_: PyRef<'_, Self>,
schema: PyArrowType<Schema>,
+95 -95
View File
@@ -799,7 +799,7 @@ name = "cuda-bindings"
version = "13.3.1"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "cuda-pathfinder", marker = "(python_full_version < '3.14' and sys_platform == 'emscripten') or (python_full_version < '3.14' and sys_platform == 'win32') or (sys_platform != 'emscripten' and sys_platform != 'win32')" },
{ name = "cuda-pathfinder" },
]
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{ url = "https://files.pythonhosted.org/packages/a9/21/8464d133752951c154feafb3b65c297e7d80f301183d220bec4c830f1441/cuda_bindings-13.3.1-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:120fcc53d57903df529c3486962c56528cba5b7d6c57c99537320ed9922c8b86", size = 6073403, upload-time = "2026-05-29T23:11:36.22Z" },
@@ -834,37 +834,37 @@ wheels = [
[package.optional-dependencies]
cublas = [
{ name = "nvidia-cublas", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
{ name = "nvidia-cublas" },
]
cudart = [
{ name = "nvidia-cuda-runtime", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
{ name = "nvidia-cuda-runtime" },
]
cufft = [
{ name = "nvidia-cufft", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
{ name = "nvidia-cufft" },
]
cufile = [
{ name = "nvidia-cufile", marker = "sys_platform == 'linux'" },
{ name = "nvidia-cufile" },
]
cupti = [
{ name = "nvidia-cuda-cupti", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
{ name = "nvidia-cuda-cupti" },
]
curand = [
{ name = "nvidia-curand", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
{ name = "nvidia-curand" },
]
cusolver = [
{ name = "nvidia-cusolver", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
{ name = "nvidia-cusolver" },
]
cusparse = [
{ name = "nvidia-cusparse", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
{ name = "nvidia-cusparse" },
]
nvjitlink = [
{ name = "nvidia-nvjitlink", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
{ name = "nvidia-nvjitlink" },
]
nvrtc = [
{ name = "nvidia-cuda-nvrtc", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
{ name = "nvidia-cuda-nvrtc" },
]
nvtx = [
{ name = "nvidia-nvtx", marker = "(python_full_version < '3.14' and sys_platform == 'win32') or sys_platform == 'linux'" },
{ name = "nvidia-nvtx" },
]
[[package]]
@@ -1023,7 +1023,7 @@ name = "exceptiongroup"
version = "1.3.1"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "typing-extensions", marker = "python_full_version < '3.11'" },
{ name = "typing-extensions" },
]
sdist = { url = "https://files.pythonhosted.org/packages/50/79/66800aadf48771f6b62f7eb014e352e5d06856655206165d775e675a02c9/exceptiongroup-1.3.1.tar.gz", hash = "sha256:8b412432c6055b0b7d14c310000ae93352ed6754f70fa8f7c34141f91c4e3219", size = 30371, upload-time = "2025-11-21T23:01:54.787Z" }
wheels = [
@@ -1440,16 +1440,16 @@ resolution-markers = [
"python_full_version < '3.11'",
]
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{ name = "cachetools", marker = "python_full_version < '3.11'" },
{ name = "certifi", marker = "python_full_version < '3.11'" },
{ name = "httpx", marker = "python_full_version < '3.11'" },
{ name = "ibm-cos-sdk", marker = "python_full_version < '3.11'" },
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{ name = "requests", marker = "python_full_version < '3.11'" },
{ name = "tabulate", marker = "python_full_version < '3.11'" },
{ name = "urllib3", marker = "python_full_version < '3.11'" },
{ name = "cachetools" },
{ name = "certifi" },
{ name = "httpx" },
{ name = "ibm-cos-sdk" },
{ name = "lomond" },
{ name = "packaging" },
{ name = "pandas", version = "2.2.3", source = { registry = "https://pypi.org/simple" } },
{ name = "requests" },
{ name = "tabulate" },
{ name = "urllib3" },
]
sdist = { url = "https://files.pythonhosted.org/packages/c7/56/2e3df38a1f13062095d7bde23c87a92f3898982993a15186b1bfecbd206f/ibm_watsonx_ai-1.3.42.tar.gz", hash = "sha256:ee5be59009004245d957ce97d1227355516df95a2640189749487614fef674ff", size = 688651, upload-time = "2025-10-01T13:35:41.527Z" }
wheels = [
@@ -1468,17 +1468,17 @@ resolution-markers = [
"python_full_version == '3.11.*'",
]
dependencies = [
{ name = "cachetools", marker = "python_full_version >= '3.11'" },
{ name = "certifi", marker = "python_full_version >= '3.11'" },
{ name = "httpx", marker = "python_full_version >= '3.11'" },
{ name = "ibm-cos-sdk", marker = "python_full_version >= '3.11'" },
{ name = "lomond", marker = "python_full_version >= '3.11'" },
{ name = "packaging", marker = "python_full_version >= '3.11'" },
{ name = "pandas", version = "2.3.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11' and python_full_version < '3.14'" },
{ name = "cachetools" },
{ name = "certifi" },
{ name = "httpx" },
{ name = "ibm-cos-sdk" },
{ name = "lomond" },
{ name = "packaging" },
{ name = "pandas", version = "2.3.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.14'" },
{ name = "pandas", version = "3.0.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.14'" },
{ name = "requests", marker = "python_full_version >= '3.11'" },
{ name = "tabulate", marker = "python_full_version >= '3.11'" },
{ name = "urllib3", marker = "python_full_version >= '3.11'" },
{ name = "requests" },
{ name = "tabulate" },
{ name = "urllib3" },
]
sdist = { url = "https://files.pythonhosted.org/packages/29/a3/c756b534696ab2f3f29882fdb7ca7198b7a5c94e10c0a3a327853d6d6b79/ibm_watsonx_ai-1.5.14.tar.gz", hash = "sha256:a756488bd57e87c0fc51be42dcba871143cfe0ac1e805c497c5047e1e4f13e9d", size = 735804, upload-time = "2026-06-22T12:32:43.85Z" }
wheels = [
@@ -1554,17 +1554,17 @@ resolution-markers = [
"python_full_version < '3.11'",
]
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{ name = "colorama", marker = "python_full_version < '3.11' and sys_platform == 'win32'" },
{ name = "decorator", marker = "python_full_version < '3.11'" },
{ name = "exceptiongroup", marker = "python_full_version < '3.11'" },
{ name = "jedi", marker = "python_full_version < '3.11'" },
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{ name = "pexpect", marker = "python_full_version < '3.11' and sys_platform != 'emscripten' and sys_platform != 'win32'" },
{ name = "prompt-toolkit", marker = "python_full_version < '3.11'" },
{ name = "pygments", marker = "python_full_version < '3.11'" },
{ name = "stack-data", marker = "python_full_version < '3.11'" },
{ name = "traitlets", marker = "python_full_version < '3.11'" },
{ name = "typing-extensions", marker = "python_full_version < '3.11'" },
{ name = "colorama", marker = "sys_platform == 'win32'" },
{ name = "decorator" },
{ name = "exceptiongroup" },
{ name = "jedi" },
{ name = "matplotlib-inline" },
{ name = "pexpect", marker = "sys_platform != 'emscripten' and sys_platform != 'win32'" },
{ name = "prompt-toolkit" },
{ name = "pygments" },
{ name = "stack-data" },
{ name = "traitlets" },
{ name = "typing-extensions" },
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wheels = [
@@ -1583,18 +1583,18 @@ resolution-markers = [
"python_full_version == '3.11.*'",
]
dependencies = [
{ name = "colorama", marker = "python_full_version >= '3.11' and sys_platform == 'win32'" },
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{ name = "ipython-pygments-lexers", marker = "python_full_version >= '3.11'" },
{ name = "jedi", marker = "python_full_version >= '3.11'" },
{ name = "matplotlib-inline", marker = "python_full_version >= '3.11'" },
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{ name = "prompt-toolkit", marker = "python_full_version >= '3.11'" },
{ name = "psutil", marker = "python_full_version >= '3.11' and sys_platform != 'cygwin' and sys_platform != 'emscripten'" },
{ name = "pygments", marker = "python_full_version >= '3.11'" },
{ name = "stack-data", marker = "python_full_version >= '3.11'" },
{ name = "traitlets", marker = "python_full_version >= '3.11'" },
{ name = "typing-extensions", marker = "python_full_version == '3.11.*'" },
{ name = "colorama", marker = "sys_platform == 'win32'" },
{ name = "decorator" },
{ name = "ipython-pygments-lexers" },
{ name = "jedi" },
{ name = "matplotlib-inline" },
{ name = "pexpect", marker = "sys_platform != 'emscripten' and sys_platform != 'win32'" },
{ name = "prompt-toolkit" },
{ name = "psutil", marker = "sys_platform != 'cygwin' and sys_platform != 'emscripten'" },
{ name = "pygments" },
{ name = "stack-data" },
{ name = "traitlets" },
{ name = "typing-extensions", marker = "python_full_version < '3.12'" },
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wheels = [
@@ -1606,7 +1606,7 @@ name = "ipython-pygments-lexers"
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source = { registry = "https://pypi.org/simple" }
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{ name = "pygments", marker = "python_full_version >= '3.11'" },
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@@ -2005,7 +2005,7 @@ requires-dist = [
{ name = "pyarrow-stubs", marker = "extra == 'tests'", specifier = ">=16.0" },
{ name = "pydantic", specifier = ">=1.10" },
{ name = "pylance", marker = "extra == 'pylance'", specifier = ">=5.0.0b5" },
{ name = "pylance", marker = "extra == 'tests'", specifier = "==9.0.0rc1" },
{ name = "pylance", marker = "extra == 'tests'", specifier = "==10.0.0" },
{ name = "pyright", marker = "extra == 'dev'", specifier = ">=1.1.350" },
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{ name = "pytest-asyncio", marker = "extra == 'tests'", specifier = ">=0.21" },
@@ -2858,7 +2858,7 @@ name = "nvidia-cudnn-cu13"
version = "9.19.0.56"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "nvidia-cublas", marker = "(python_full_version < '3.14' and sys_platform == 'emscripten') or (python_full_version < '3.14' and sys_platform == 'win32') or (sys_platform != 'emscripten' and sys_platform != 'win32')" },
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@@ -2870,7 +2870,7 @@ name = "nvidia-cufft"
version = "12.0.0.61"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "nvidia-nvjitlink", marker = "(python_full_version < '3.14' and sys_platform == 'emscripten') or (python_full_version < '3.14' and sys_platform == 'win32') or (sys_platform != 'emscripten' and sys_platform != 'win32')" },
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wheels = [
@@ -3320,7 +3320,7 @@ name = "pexpect"
version = "4.9.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "ptyprocess", marker = "(python_full_version < '3.14' and sys_platform == 'emscripten') or (python_full_version < '3.14' and sys_platform == 'win32') or (sys_platform != 'emscripten' and sys_platform != 'win32')" },
{ name = "ptyprocess" },
]
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wheels = [
@@ -3912,7 +3912,7 @@ crypto = [
[[package]]
name = "pylance"
version = "7.0.0"
version = "10.0.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "lance-namespace" },
@@ -3922,12 +3922,12 @@ dependencies = [
{ name = "pyarrow" },
]
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]
[[package]]
@@ -4683,10 +4683,10 @@ resolution-markers = [
"python_full_version < '3.11'",
]
dependencies = [
{ name = "joblib", marker = "python_full_version < '3.11'" },
{ name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
{ name = "scipy", version = "1.15.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
{ name = "threadpoolctl", marker = "python_full_version < '3.11'" },
{ name = "joblib" },
{ name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" } },
{ name = "scipy", version = "1.15.3", source = { registry = "https://pypi.org/simple" } },
{ name = "threadpoolctl" },
]
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wheels = [
@@ -4734,13 +4734,13 @@ resolution-markers = [
"python_full_version == '3.11.*'",
]
dependencies = [
{ name = "joblib", marker = "python_full_version >= '3.11'" },
{ name = "narwhals", marker = "python_full_version >= '3.11'" },
{ name = "numpy", version = "2.4.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version == '3.11.*'" },
{ name = "joblib" },
{ name = "narwhals" },
{ name = "numpy", version = "2.4.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
{ name = "numpy", version = "2.5.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
{ name = "scipy", version = "1.17.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version == '3.11.*'" },
{ name = "scipy", version = "1.17.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
{ name = "scipy", version = "1.18.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
{ name = "threadpoolctl", marker = "python_full_version >= '3.11'" },
{ name = "threadpoolctl" },
]
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wheels = [
@@ -4784,7 +4784,7 @@ resolution-markers = [
"python_full_version < '3.11'",
]
dependencies = [
{ name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
{ name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" } },
]
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wheels = [
@@ -4843,7 +4843,7 @@ resolution-markers = [
"python_full_version == '3.11.*'",
]
dependencies = [
{ name = "numpy", version = "2.4.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version == '3.11.*'" },
{ name = "numpy", version = "2.4.6", source = { registry = "https://pypi.org/simple" } },
]
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@@ -4920,7 +4920,7 @@ resolution-markers = [
"python_full_version >= '3.12' and python_full_version < '3.14'",
]
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{ name = "numpy", version = "2.5.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
{ name = "numpy", version = "2.5.1", source = { registry = "https://pypi.org/simple" } },
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wheels = [
+1 -4
View File
@@ -1,6 +1,6 @@
[package]
name = "lancedb"
version = "0.38.0-beta.2"
version = "0.37.1"
edition.workspace = true
description = "LanceDB: A serverless, low-latency vector database for AI applications"
license.workspace = true
@@ -188,9 +188,6 @@ required-features = ["bedrock"]
[[example]]
name = "bench_streaming_dataloader"
[[example]]
name = "bench_open_missing_table"
[[example]]
name = "simple"
@@ -1,150 +0,0 @@
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
// Release benchmark for opening a missing table as sibling-table cardinality grows.
//
// The fixture uses real `.lance` directories and marker files. Fixture creation is
// outside the timed section. Defaults intentionally cover 1k, 10k, and 100k siblings
// with 10 warmups and 100 distinct missing-table opens per scale:
//
// ```text
// cargo run --release -p lancedb --example bench_open_missing_table
// ```
//
// `BENCH_SIBLINGS`, `BENCH_WARMUPS`, and `BENCH_TRIALS` override those defaults.
// Reduced settings are useful only as a smoke test. Performance comparisons require
// the same machine, filesystem, fixture sizes, settings, lockfile, and alternating
// baseline/candidate execution order.
use std::time::{Duration, Instant};
use anyhow::{Context, Result, bail};
use lancedb::connection::Connection;
use lancedb::{Error, connect};
use object_store::ObjectStoreExt as _;
use object_store::path::Path;
const MAX_SIBLINGS: usize = 1_000_000;
const MAX_WARMUPS: usize = 10_000;
const MAX_TRIALS: usize = 100_000;
fn env_usize(key: &str, default: usize, max: usize) -> Result<usize> {
let value = match std::env::var(key) {
Ok(value) => value
.parse()
.with_context(|| format!("invalid {key} value: {value}"))?,
Err(std::env::VarError::NotPresent) => default,
Err(error) => return Err(error).with_context(|| format!("reading {key}")),
};
if value == 0 || value > max {
bail!("{key} must be between 1 and {max}");
}
Ok(value)
}
fn sibling_counts() -> Result<Vec<usize>> {
let raw = std::env::var("BENCH_SIBLINGS").unwrap_or_else(|_| "1000,10000,100000".into());
let mut counts = raw
.split(',')
.map(|value| {
value
.trim()
.parse::<usize>()
.with_context(|| format!("invalid BENCH_SIBLINGS value: {value}"))
})
.collect::<Result<Vec<_>>>()?;
counts.sort_unstable();
counts.dedup();
if counts.is_empty() || counts[0] == 0 || counts[counts.len() - 1] > MAX_SIBLINGS {
bail!("BENCH_SIBLINGS values must be between 1 and {MAX_SIBLINGS}");
}
Ok(counts)
}
async fn add_siblings(
store: &object_store::local::LocalFileSystem,
start: usize,
end: usize,
) -> Result<()> {
for index in start..end {
let marker = Path::from(format!("sibling_{index:06}.lance/_marker"));
store
.put(&marker, bytes::Bytes::new().into())
.await
.with_context(|| format!("creating benchmark marker {marker}"))?;
}
Ok(())
}
async fn time_missing_open(db: &Connection, name: &str) -> Result<Duration> {
let started = Instant::now();
let result = db.open_table(name).execute().await;
let elapsed = started.elapsed();
match result {
Err(Error::TableNotFound { .. }) => Ok(elapsed),
Err(error) => bail!("expected TableNotFound for {name}, got {error:?}"),
Ok(_) => bail!("benchmark missing-table name unexpectedly exists: {name}"),
}
}
fn percentile(sorted: &[Duration], percentile: usize) -> Duration {
let rank = (sorted.len() * percentile).div_ceil(100).saturating_sub(1);
sorted[rank]
}
#[tokio::main]
async fn main() -> Result<()> {
let counts = sibling_counts()?;
let warmups = env_usize("BENCH_WARMUPS", 10, MAX_WARMUPS)?;
let trials = env_usize("BENCH_TRIALS", 100, MAX_TRIALS)?;
let fixture = tempfile::tempdir().context("creating benchmark fixture")?;
let database_path = fixture.path();
let fixture_store = object_store::local::LocalFileSystem::new_with_prefix(database_path)
.context("creating benchmark object store")?;
let db = connect(database_path.to_str().context("non-UTF-8 fixture path")?)
.execute()
.await?;
println!(
"config: siblings={counts:?} warmups={warmups} trials={trials} profile={} os={} arch={}",
if cfg!(debug_assertions) {
"debug"
} else {
"release"
},
std::env::consts::OS,
std::env::consts::ARCH,
);
println!("lower is better; fixture setup and teardown are excluded");
println!("| siblings | samples | p50 | p95 | max |");
println!("| ---: | ---: | ---: | ---: | ---: |");
let mut created = 0;
for sibling_count in counts {
add_siblings(&fixture_store, created, sibling_count).await?;
created = sibling_count;
for index in 0..warmups {
let name = format!("__missing_warmup_{sibling_count}_{index}");
let _ = time_missing_open(&db, &name).await?;
}
let mut samples = Vec::with_capacity(trials);
for index in 0..trials {
let name = format!("__missing_trial_{sibling_count}_{index}");
samples.push(time_missing_open(&db, &name).await?);
}
samples.sort_unstable();
println!(
"| {sibling_count} | {} | {:?} | {:?} | {:?} |",
samples.len(),
percentile(&samples, 50),
percentile(&samples, 95),
samples[samples.len() - 1],
);
}
Ok(())
}
+4 -7
View File
@@ -17,7 +17,7 @@ use arrow_array::builder::LargeBinaryBuilder;
use arrow_schema::{DataType, Field, Schema};
use lance::dataset::{BlobRangeRequest as LanceBlobRangeRequest, Dataset, WriteParams};
use lance_arrow::FieldExt;
use lance_file::version::{ConcreteFileVersion, LanceFileVersion};
use lance_file::version::LanceFileVersion;
use lance_io::object_store::ObjectStore;
use object_store::path::Path;
@@ -333,10 +333,7 @@ pub(crate) fn ensure_blob_storage_version(schema: &Schema, params: &mut WritePar
.data_storage_version
.unwrap_or(LanceFileVersion::Stable)
.resolve();
if matches!(
resolved,
ConcreteFileVersion::V1 | ConcreteFileVersion::V2_0 | ConcreteFileVersion::V2_1
) {
if resolved < LanceFileVersion::V2_2 {
params.data_storage_version = Some(LanceFileVersion::V2_2);
}
}
@@ -502,7 +499,7 @@ mod tests {
ensure_blob_storage_version(&blob_schema(), &mut params);
assert_eq!(
params.data_storage_version.unwrap().resolve(),
ConcreteFileVersion::V2_2
LanceFileVersion::V2_2
);
}
@@ -515,7 +512,7 @@ mod tests {
ensure_blob_storage_version(&blob_schema(), &mut params);
assert_eq!(
params.data_storage_version.unwrap().resolve(),
ConcreteFileVersion::V2_2
LanceFileVersion::V2_2
);
}
+4 -23
View File
@@ -409,11 +409,6 @@ impl Connection {
///
/// The names will be returned in lexicographical order (ascending)
///
/// Listing databases discover physical `*.lance` entries without opening every
/// dataset. The result is a point-in-time discovery snapshot: an entry may still be
/// under creation, may contain only uncommitted storage, or may be concurrently
/// dropped before it is opened.
///
/// The parameters `page_token` and `limit` can be used to paginate the results
pub fn table_names(&self) -> TableNamesBuilder {
TableNamesBuilder::new(self.internal.clone())
@@ -461,9 +456,10 @@ impl Connection {
///
/// # Returns
/// Created [`TableRef`], or [`Error::TableNotFound`] if the table does not exist.
/// On listing databases, a committed Lance manifest is authoritative for table
/// existence. Uncommitted files or a physical `<name>.lance` directory alone do not
/// make a table openable.
/// If the table's storage is present but holds no readable dataset (for example a
/// `<name>.lance` directory left behind by an interrupted drop and re-create, which
/// [`Self::table_names`] still lists) this returns [`Error::TableCorrupted`]
/// instead.
pub fn open_table(&self, name: impl Into<String>) -> OpenTableBuilder {
OpenTableBuilder::new(
self.internal.clone(),
@@ -565,21 +561,6 @@ impl Connection {
.await
}
/// Start dropping a table and return a handle to the cleanup job.
///
/// The table may become unavailable before its physical data is removed.
/// Call [`crate::job::Job::wait`] to wait for cleanup to finish. Local
/// backends may complete the drop before returning the handle.
pub async fn drop_table_async(
&self,
name: impl AsRef<str>,
namespace_path: &[String],
) -> Result<crate::job::Job> {
self.internal
.drop_table_async(name.as_ref(), namespace_path)
.await
}
/// Drop the database
///
/// This is the same as dropping all of the tables
+3 -2
View File
@@ -438,9 +438,10 @@ mod tests {
.await
.unwrap()
.data_storage_format
.lance_file_format();
.lance_file_version()
.unwrap();
// Compare resolved versions since Stable/Next are aliases that resolve at storage time
assert_eq!(storage_format, data_storage_version.resolve());
assert_eq!(storage_format.resolve(), data_storage_version.resolve());
}
#[tokio::test]
-12
View File
@@ -323,18 +323,6 @@ pub trait Database:
) -> Result<()>;
/// Drop a table in the database
async fn drop_table(&self, name: &str, namespace_path: &[String]) -> Result<()>;
/// Start dropping a table and return a handle to the cleanup job.
///
/// Backends without asynchronous cleanup complete the drop before
/// returning an already-finished job.
async fn drop_table_async(
&self,
name: &str,
namespace_path: &[String],
) -> Result<crate::job::Job> {
self.drop_table(name, namespace_path).await?;
Ok(crate::job::Job::new_done())
}
/// Drop all tables in the database
async fn drop_all_tables(&self, namespace_path: &[String]) -> Result<()>;
fn as_any(&self) -> &dyn std::any::Any;
+2 -116
View File
@@ -1032,7 +1032,6 @@ impl Database for ListingDatabase {
};
Ok(ListTablesResponse {
context: None,
tables: f,
page_token: next_page_token,
})
@@ -1292,21 +1291,16 @@ impl Database for ListingDatabase {
mod tests {
use super::*;
use crate::Table;
use crate::arrow::{SendableRecordBatchStream, SimpleRecordBatchStream};
use crate::connection::ConnectRequest;
use crate::data::scannable::Scannable;
use crate::database::{CreateTableMode, CreateTableRequest};
use crate::query::QueryRequest;
use crate::table::{AnyQuery, WriteOptions};
use arrow_array::{Int32Array, RecordBatch, StringArray};
use arrow_schema::{DataType, Field, Schema, SchemaRef};
use futures::{TryStreamExt, stream::once};
use arrow_schema::{DataType, Field, Schema};
use futures::TryStreamExt;
use std::path::PathBuf;
use std::sync::Arc;
use std::time::Duration;
use tempfile::tempdir;
use tokio::sync::Barrier;
use tokio::time::timeout;
async fn setup_database() -> (tempfile::TempDir, ListingDatabase) {
let tempdir = tempdir().unwrap();
@@ -1330,114 +1324,6 @@ mod tests {
(tempdir, db)
}
struct BarrierScannable {
batch: RecordBatch,
barrier: Arc<Barrier>,
}
impl Scannable for BarrierScannable {
fn schema(&self) -> SchemaRef {
self.batch.schema()
}
fn scan_as_stream(&mut self) -> SendableRecordBatchStream {
let batch = self.batch.clone();
let schema = batch.schema();
let barrier = self.barrier.clone();
Box::pin(SimpleRecordBatchStream {
schema,
stream: once(async move {
barrier.wait().await;
Ok(batch)
}),
})
}
}
fn create_request(name: &str, data: Box<dyn Scannable>) -> CreateTableRequest {
CreateTableRequest {
name: name.to_string(),
namespace_path: vec![],
data,
mode: CreateTableMode::Create,
write_options: Default::default(),
location: None,
namespace_client: None,
}
}
#[tokio::test]
async fn test_create_ignores_uncommitted_storage_without_manifest() {
let (tmp_dir, db) = setup_database().await;
let data_dir = tmp_dir.path().join("test.lance/data");
std::fs::create_dir_all(&data_dir).unwrap();
std::fs::write(data_dir.join("orphan.lance"), b"uncommitted").unwrap();
let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
let batch =
RecordBatch::try_new(schema, vec![Arc::new(Int32Array::from(vec![1]))]).unwrap();
let table = db
.create_table(create_request("test", Box::new(batch)))
.await
.unwrap();
assert_eq!(table.count_rows(None).await.unwrap(), 1);
}
#[tokio::test]
async fn test_concurrent_create_is_arbitrated_by_manifest_commit() {
let uri = format!("memory:///concurrent-create-{}", uuid::Uuid::new_v4());
let db = crate::connect(&uri).execute().await.unwrap();
let store: Arc<dyn object_store::ObjectStore> =
Arc::new(object_store::memory::InMemory::new());
let table_url = url::Url::parse("memory:///database/test.lance").unwrap();
let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
let batch =
RecordBatch::try_new(schema, vec![Arc::new(Int32Array::from(vec![1]))]).unwrap();
let barrier = Arc::new(Barrier::new(2));
#[allow(deprecated)]
let request = |batch, barrier| {
let mut request = create_request("test", Box::new(BarrierScannable { batch, barrier }));
request.write_options = WriteOptions {
lance_write_params: Some(lance::dataset::WriteParams {
store_params: Some(ObjectStoreParams {
object_store: Some((store.clone(), table_url.clone())),
..Default::default()
}),
commit_handler: Some(Arc::new(
lance_table::io::commit::ConditionalPutCommitHandler,
)),
..Default::default()
}),
};
request
};
let left = db
.database()
.create_table(request(batch.clone(), barrier.clone()));
let right = db.database().create_table(request(batch, barrier));
let (left, right) = timeout(Duration::from_secs(30), async { tokio::join!(left, right) })
.await
.expect("concurrent creates deadlocked");
let results = [left, right];
assert_eq!(
results.iter().filter(|result| result.is_ok()).count(),
1,
"expected one successful create, got {results:?}"
);
assert_eq!(
results
.iter()
.filter(|result| matches!(result, Err(Error::TableAlreadyExists { .. })))
.count(),
1,
"expected one manifest conflict, got {results:?}"
);
}
#[tokio::test]
async fn test_listing_database_root_ops_do_not_create_manifest() {
let tempdir = tempdir().unwrap();
@@ -12,8 +12,7 @@ use lance_encoding::decoder::{DecoderPlugins, FilterExpression};
use lance_file::{
reader::{FileReader, FileReaderOptions},
version::ConcreteFileVersion,
versions,
writer::FileWriterOptions,
writer::{FileWriter, FileWriterOptions},
};
use lance_io::{
ReadBatchParams,
@@ -154,11 +153,13 @@ impl Shuffler {
source: None,
})?;
let object_writer = object_store.create(&path).await?;
let writer = versions::create_writer(
ConcreteFileVersion::V2_1,
let writer = FileWriter::try_new(
object_writer,
schema.clone(),
FileWriterOptions::default(),
FileWriterOptions {
format_version: Some(ConcreteFileVersion::V2_1.into()),
..Default::default()
},
)?;
file_writers.push(writer);
}
-8
View File
@@ -71,14 +71,6 @@ pub enum Error {
IndexNotFound { name: String },
#[snafu(display("Embedding function '{name}' was not found. : {reason}"))]
EmbeddingFunctionNotFound { name: String, reason: String },
#[snafu(display("Column '{name}' was not found"))]
ColumnNotFound { name: String },
#[snafu(display("Column '{name}' already exists"))]
ColumnAlreadyExists { name: String },
#[snafu(display("Column '{name}' is not a computed column"))]
NotAComputedColumn { name: String },
#[snafu(display("Invalid expression for column '{column}': {message}"))]
InvalidExpression { column: String, message: String },
#[snafu(display("Table '{name}' already exists"))]
TableAlreadyExists { name: String },
+1 -1
View File
@@ -141,7 +141,7 @@ impl SpawnedJob {
Ok(Err(err)) => Outcome::Failed(Arc::new(err)),
Err(err) if err.is_cancelled() => Outcome::Cancelled,
Err(err) => Outcome::Failed(Arc::new(Error::Runtime {
message: format!("job task failed: {err}"),
message: format!("index job task failed: {err}"),
})),
};
let _ = tx.send(Some(outcome));
-9
View File
@@ -19,15 +19,6 @@ const ARROW_FILE_CONTENT_TYPE: &str = "application/vnd.apache.arrow.file";
#[cfg(test)]
const JSON_CONTENT_TYPE: &str = "application/json";
fn extract_job_id(body: &str) -> Option<String> {
serde_json::from_str::<serde_json::Value>(body)
.ok()?
.get("job_id")?
.as_str()
.filter(|job_id| !job_id.is_empty())
.map(str::to_string)
}
pub use client::{ClientConfig, HeaderProvider, RetryConfig, TimeoutConfig, TlsConfig};
pub use db::{RemoteDatabaseOptions, RemoteDatabaseOptionsBuilder};
pub use oauth::{OAuthConfig, OAuthFlow, OAuthHeaderProvider};
+8 -103
View File
@@ -9,7 +9,6 @@ use http::StatusCode;
use lance_io::object_store::StorageOptions;
use lance_namespace_impls::{DynamicContextProvider, OperationInfo};
use moka::future::Cache;
use reqwest::Response;
use reqwest::header::CONTENT_TYPE;
use lance_namespace::models::{
@@ -24,17 +23,15 @@ use crate::database::{
JobDescription, JobInfo, OpenTableRequest, ReadConsistency, TableNamesRequest,
};
use crate::error::Result;
use crate::job::Job;
use crate::remote::job::RemoteJob;
use crate::remote::util::stream_as_body;
use crate::table::BaseTable;
use super::ARROW_STREAM_CONTENT_TYPE;
use super::client::{
ClientConfig, HeaderProvider, HttpSend, RequestResultExt, RestfulLanceDbClient, Sender,
};
use super::table::RemoteTable;
use super::util::parse_server_version;
use super::{ARROW_STREAM_CONTENT_TYPE, extract_job_id};
// Request structure for the remote clone table API
#[derive(serde::Serialize)]
@@ -329,22 +326,6 @@ impl RemoteDatabase {
}
}
impl<S: HttpSend> RemoteDatabase<S> {
async fn submit_drop_table(
&self,
name: &str,
namespace_path: &[String],
) -> Result<(String, Response)> {
let identifier = build_table_identifier(name, namespace_path, &self.client.id_delimiter);
let cache_key = build_cache_key(name, namespace_path);
let req = self.client.post(&format!("/v1/table/{}/drop/", identifier));
let (request_id, resp) = self.client.send(req).await?;
let resp = self.client.check_response(&request_id, resp).await?;
self.table_cache.remove(&cache_key).await;
Ok((request_id, resp))
}
}
#[cfg(all(test, feature = "remote"))]
mod test_utils {
use super::*;
@@ -913,28 +894,13 @@ impl<S: HttpSend> Database for RemoteDatabase<S> {
}
async fn drop_table(&self, name: &str, namespace_path: &[String]) -> Result<()> {
self.submit_drop_table(name, namespace_path)
.await
.map(|_| ())
}
async fn drop_table_async(&self, name: &str, namespace_path: &[String]) -> Result<Job> {
let (request_id, response) = self.submit_drop_table(name, namespace_path).await?;
let status = response.status();
let body = response.text().await.err_to_http(request_id.clone())?;
let job_id = extract_job_id(&body);
Ok(match job_id {
Some(job_id) => Job::new(Box::new(RemoteJob::new(self.client.clone(), job_id))),
None if status == StatusCode::ACCEPTED => {
return Err(Error::Http {
source: "asynchronous drop-table response did not contain a valid job_id"
.into(),
request_id,
status_code: Some(status),
});
}
None => Job::new_done(),
})
let identifier = build_table_identifier(name, namespace_path, &self.client.id_delimiter);
let cache_key = build_cache_key(name, namespace_path);
let req = self.client.post(&format!("/v1/table/{}/drop/", identifier));
let (request_id, resp) = self.client.send(req).await?;
self.client.check_response(&request_id, resp).await?;
self.table_cache.remove(&cache_key).await;
Ok(())
}
async fn drop_all_tables(&self, namespace_path: &[String]) -> Result<()> {
@@ -1526,67 +1492,6 @@ mod tests {
// NOTE: the API will return 200 even if the table does not exist. So we shouldn't expect 404.
}
#[tokio::test]
async fn test_drop_table_does_not_read_response_body() {
let conn = Connection::new_with_handler(|_| {
http::Response::builder()
.status(200)
.body(vec![0xff])
.unwrap()
});
conn.drop_table("table1", &[]).await.unwrap();
}
#[tokio::test]
async fn test_drop_table_async_returns_job() {
let conn = Connection::new_with_handler(|request| {
assert_eq!(request.method(), &reqwest::Method::POST);
assert_eq!(request.url().path(), "/v1/table/table1/drop/");
http::Response::builder()
.status(202)
.body(r#"{"job_id":"drop-job-123"}"#)
.unwrap()
});
let job = conn.drop_table_async("table1", &[]).await.unwrap();
assert_eq!(job.id(), Some("drop-job-123"));
}
#[tokio::test]
async fn test_drop_table_async_old_server_returns_done_job() {
let conn = Connection::new_with_handler(|_| {
http::Response::builder().status(200).body("").unwrap()
});
let job = conn.drop_table_async("table1", &[]).await.unwrap();
assert_eq!(job.id(), None);
assert_eq!(job.status().await.unwrap(), "finished");
}
#[tokio::test]
async fn test_drop_table_async_rejects_accepted_response_without_job_id() {
let conn = Connection::new_with_handler(|_| {
http::Response::builder().status(202).body("{}").unwrap()
});
let error = conn.drop_table_async("table1", &[]).await.err().unwrap();
assert!(error.to_string().contains("valid job_id"));
}
#[tokio::test]
async fn test_drop_table_async_rejects_empty_job_id() {
let conn = Connection::new_with_handler(|_| {
http::Response::builder()
.status(202)
.body(r#"{"job_id":""}"#)
.unwrap()
});
let error = conn.drop_table_async("table1", &[]).await.err().unwrap();
assert!(error.to_string().contains("valid job_id"));
}
#[tokio::test]
async fn test_rename_table() {
let conn = Connection::new_with_handler(|request| {
+30 -499
View File
@@ -8,7 +8,7 @@ use self::insert::{RemoteWriteExec, WriteOp};
use super::client::RequestResultExt;
use super::client::{HttpSend, RestfulLanceDbClient, Sender};
use super::db::ServerVersion;
use super::{ARROW_FILE_CONTENT_TYPE, ARROW_STREAM_CONTENT_TYPE, extract_job_id};
use super::{ARROW_FILE_CONTENT_TYPE, ARROW_STREAM_CONTENT_TYPE};
use crate::blob::BlobFile;
use crate::data::scannable::{PeekedScannable, Scannable, estimate_write_partitions};
use crate::expr::expr_to_sql_string;
@@ -33,9 +33,7 @@ use crate::table::lsm_stats::GetLsmStatsResponse;
use crate::table::merge::MergeFilter;
use crate::table::query::create_multi_vector_plan;
use crate::table::write_progress::FinishOnDrop;
use crate::table::{
AlterColumnsResult, FieldMetadataUpdate, RefreshColumnResult, UpdateFieldMetadataResult,
};
use crate::table::{AlterColumnsResult, FieldMetadataUpdate, UpdateFieldMetadataResult};
use crate::table::{AnyQuery, Filter, Predicate, PreprocessingOutput, TableStatistics};
use crate::utils::background_cache::BackgroundCache;
use crate::utils::{
@@ -142,40 +140,6 @@ impl FreshnessHeaders {
}
}
/// A backfill job whose successful wait establishes a read-freshness
/// baseline on the submitting handle, so a later read cannot be served
/// from a cache older than the completed fill. A handle pinned by checkout
/// at completion keeps its time-travel view instead.
struct FreshnessJob<S: HttpSend> {
inner: RemoteJob<S>,
freshness: Arc<Mutex<FreshnessState>>,
version: Arc<RwLock<Option<u64>>>,
}
#[async_trait]
impl<S: HttpSend> crate::job::JobHandle for FreshnessJob<S> {
fn id(&self) -> Option<&str> {
crate::job::JobHandle::id(&self.inner)
}
async fn status(&self) -> Result<String> {
crate::job::JobHandle::status(&self.inner).await
}
async fn wait(&self) -> Result<()> {
crate::job::JobHandle::wait(&self.inner).await?;
let version = self.version.read().await;
if version.is_none() {
self.freshness.lock().unwrap().checkout_baseline = Some(SystemTime::now());
}
Ok(())
}
async fn cancel(&self) -> Result<()> {
crate::job::JobHandle::cancel(&self.inner).await
}
}
fn compute_min_timestamp(
state: &FreshnessState,
interval: Option<Duration>,
@@ -310,10 +274,10 @@ pub struct RemoteTable<S: HttpSend = Sender> {
identifier: String,
server_version: ServerVersion,
version: Arc<RwLock<Option<u64>>>,
version: RwLock<Option<u64>>,
location: RwLock<Option<String>>,
schema_cache: BackgroundCache<SchemaRef, Error>,
freshness: Arc<Mutex<FreshnessState>>,
freshness: Mutex<FreshnessState>,
/// The branch this handle is scoped to, or `None` for the main branch.
/// Stamped onto every branch-accepting request so reads and writes resolve
/// on the branch's own version chain rather than main's.
@@ -428,7 +392,13 @@ impl<S: HttpSend> RemoteTable<S> {
.text()
.await
.ok()
.and_then(|body| extract_job_id(&body));
.and_then(|body| serde_json::from_str::<serde_json::Value>(&body).ok())
.and_then(|value| {
value
.get("job_id")
.and_then(|id| id.as_str())
.map(str::to_string)
});
if let Some(wait_timeout) = index.wait_timeout {
let index_name = index.name.unwrap_or_else(|| format!("{}_idx", column));
@@ -451,10 +421,10 @@ impl<S: HttpSend> RemoteTable<S> {
namespace,
identifier,
server_version,
version: Arc::new(RwLock::new(None)),
version: RwLock::new(None),
location: RwLock::new(None),
schema_cache: BackgroundCache::new(SCHEMA_CACHE_TTL, SCHEMA_CACHE_REFRESH_WINDOW),
freshness: Arc::new(Mutex::new(FreshnessState::default())),
freshness: Mutex::new(FreshnessState::default()),
branch: None,
}
}
@@ -483,10 +453,10 @@ impl<S: HttpSend> RemoteTable<S> {
namespace: self.namespace.clone(),
identifier: self.identifier.clone(),
server_version: self.server_version.clone(),
version: Arc::new(RwLock::new(None)),
version: RwLock::new(None),
location: RwLock::new(None),
schema_cache: BackgroundCache::new(SCHEMA_CACHE_TTL, SCHEMA_CACHE_REFRESH_WINDOW),
freshness: Arc::new(Mutex::new(FreshnessState::default())),
freshness: Mutex::new(FreshnessState::default()),
branch,
}
}
@@ -1304,10 +1274,10 @@ mod test_utils {
namespace: vec![],
identifier: name,
server_version: version.map(ServerVersion).unwrap_or_default(),
version: Arc::new(RwLock::new(None)),
version: RwLock::new(None),
location: RwLock::new(None),
schema_cache: BackgroundCache::new(SCHEMA_CACHE_TTL, SCHEMA_CACHE_REFRESH_WINDOW),
freshness: Arc::new(Mutex::new(FreshnessState::default())),
freshness: Mutex::new(FreshnessState::default()),
branch: None,
}
}
@@ -1328,10 +1298,10 @@ mod test_utils {
namespace: vec![],
identifier: name,
server_version: ServerVersion::default(),
version: Arc::new(RwLock::new(None)),
version: RwLock::new(None),
location: RwLock::new(None),
schema_cache: BackgroundCache::new(SCHEMA_CACHE_TTL, SCHEMA_CACHE_REFRESH_WINDOW),
freshness: Arc::new(Mutex::new(FreshnessState::default())),
freshness: Mutex::new(FreshnessState::default()),
branch: None,
}
}
@@ -1361,10 +1331,10 @@ mod test_utils {
namespace: vec![],
identifier: name,
server_version: version.map(ServerVersion).unwrap_or_default(),
version: Arc::new(RwLock::new(None)),
version: RwLock::new(None),
location: RwLock::new(None),
schema_cache: BackgroundCache::new(SCHEMA_CACHE_TTL, SCHEMA_CACHE_REFRESH_WINDOW),
freshness: Arc::new(Mutex::new(FreshnessState::default())),
freshness: Mutex::new(FreshnessState::default()),
branch: None,
}
}
@@ -2550,9 +2520,9 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
self.check_mutable().await?;
// Map the spec onto the server's request DTO. `sharding` is internally
// tagged on `mode` to mirror sophon's `Sharding` enum. A null
// `maintained_indexes` asks the server to resolve every maintainable
// index at HEAD; a list is verbatim, an empty one meaning none.
// tagged on `mode` to mirror sophon's `Sharding` enum; `maintained_indexes`
// and `writer_config_defaults` are sent verbatim (an empty list means "no
// maintained indexes", not "default to all").
let sharding = match &spec {
LsmWriteSpec::Bucket {
column,
@@ -2744,86 +2714,6 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
}
}
async fn add_computed_columns(&self, columns: &[(String, String)]) -> Result<AddColumnsResult> {
self.check_mutable().await?;
// The server plans the declaration: expression validation, type
// inference and the persisted binding all happen there.
let entries = columns
.iter()
.map(
|(name, expression)| lance_namespace::models::AddColumnsEntry {
name: name.clone(),
computed: Some(Some(expression.clone())),
..Default::default()
},
)
.collect::<Vec<_>>();
let mut body = serde_json::json!({ "new_columns": entries });
self.apply_branch_body(&mut body);
let request = self
.client
.post(&format!("/v1/table/{}/add_columns/", self.identifier))
.json(&body);
let (request_id, response) = self.send(request, true).await?;
let response = self.check_table_response(&request_id, response).await?;
let body = response.text().await.err_to_http(request_id.clone())?;
if body.trim().is_empty() {
// Backward compatible with old servers
return Ok(AddColumnsResult { version: 0 });
}
let result: AddColumnsResult = serde_json::from_str(&body).map_err(|e| Error::Http {
source: format!("Failed to parse add_columns response: {}", e).into(),
request_id,
status_code: None,
})?;
self.invalidate_schema_cache();
self.track_write_version(result.version);
Ok(result)
}
async fn refresh_column(&self, _column: &str) -> Result<RefreshColumnResult> {
// The server runs a refresh as a job and does not report a fill
// count, so the blocking form has no honest result to return.
Err(Error::NotSupported {
message: "a remote refresh runs as a server job; use refresh_column_async and \
wait on the returned handle"
.into(),
})
}
async fn refresh_column_async(&self, column: &str) -> Result<Job> {
self.check_mutable().await?;
let mut body = serde_json::json!({ "column": column });
self.apply_branch_body(&mut body);
let request = self
.client
.post(&format!("/v1/table/{}/backfill_column", self.identifier))
.json(&body);
let (request_id, response) = self.send(request, true).await?;
let response = self.check_table_response(&request_id, response).await?;
let body = response.text().await.err_to_http(request_id.clone())?;
#[derive(serde::Deserialize)]
struct BackfillResponse {
job_id: String,
}
let response: BackfillResponse = serde_json::from_str(&body).map_err(|e| Error::Http {
source: format!("Failed to parse backfill_column response: {}", e).into(),
request_id,
status_code: None,
})?;
Ok(Job::new(Box::new(FreshnessJob {
inner: RemoteJob::new(self.client.clone(), response.job_id),
freshness: self.freshness.clone(),
version: self.version.clone(),
})))
}
async fn alter_columns(&self, alterations: &[ColumnAlteration]) -> Result<AlterColumnsResult> {
self.check_mutable().await?;
let body = alterations
@@ -6065,18 +5955,17 @@ mod tests {
.await
.unwrap();
// Positions are relative to the first retained token, so dropping the
// leading "hello" stop word does not shift the remaining tokens.
// Lance 10 retains original token positions after stop-word removal.
assert_eq!(
tokens,
vec![
FtsToken {
text: "こんにちは".to_string(),
position: 0,
position: 1,
},
FtsToken {
text: "世界".to_string(),
position: 1,
position: 2,
},
]
);
@@ -6565,346 +6454,6 @@ mod tests {
assert_eq!(result.version, if old_server { 0 } else { 43 });
}
/// A declaration is sent as `{name, computed}` entries for the server to
/// plan; the client never types the expression itself.
#[tokio::test]
async fn test_add_computed_columns_sends_the_expression() {
let table = Table::new_with_handler("my_table", |request| {
assert_eq!(request.method(), "POST");
assert_eq!(request.url().path(), "/v1/table/my_table/add_columns/");
let body = request.body().unwrap().as_bytes().unwrap();
let value: serde_json::Value = serde_json::from_slice(body).unwrap();
assert_eq!(
value["new_columns"],
serde_json::json!([{"name": "doubled", "computed": "x * 2"}])
);
http::Response::builder()
.status(200)
.body(r#"{"version": 7}"#)
.unwrap()
});
let result = table
.add_columns()
.computed("doubled", "x * 2")
.execute()
.await
.unwrap();
assert_eq!(result.version, 7);
}
/// A remote refresh is a server job: the async form returns its handle,
/// and the blocking form refuses rather than invent a fill count.
#[tokio::test]
async fn test_refresh_column_async_submits_a_backfill_job() {
let table = Table::new_with_handler("my_table", |request| {
assert_eq!(request.method(), "POST");
assert_eq!(request.url().path(), "/v1/table/my_table/backfill_column");
let body = request.body().unwrap().as_bytes().unwrap();
let value: serde_json::Value = serde_json::from_slice(body).unwrap();
assert_eq!(value["column"], "doubled");
http::Response::builder()
.status(202)
.body(r#"{"job_id": "j-42"}"#)
.unwrap()
});
let job = table.refresh_column_async("doubled").await.unwrap();
assert_eq!(job.id(), Some("j-42"));
let err = table.refresh_column("doubled").await.unwrap_err();
assert!(
matches!(&err, Error::NotSupported { message }
if message.contains("refresh_column_async")),
"{err:?}"
);
}
/// The gate's reproducer: after a successful wait, a same-handle read
/// must carry a freshness baseline so a stale server cache cannot serve
/// the pre-backfill snapshot.
#[tokio::test]
async fn test_backfill_wait_establishes_read_freshness() {
let saw_min_timestamp = Arc::new(std::sync::atomic::AtomicBool::new(false));
let saw = saw_min_timestamp.clone();
let table =
Table::new_with_handler("my_table", move |request| match request.url().path() {
"/v1/table/my_table/backfill_column" => http::Response::builder()
.status(202)
.body(r#"{"job_id": "j-7"}"#.to_string())
.unwrap(),
"/v1/jobs/describe" => http::Response::builder()
.status(200)
.body(r#"{"job_id": "j-7", "job_state": "DONE"}"#.to_string())
.unwrap(),
"/v1/table/my_table/count_rows/" => {
saw.store(
request.headers().contains_key("x-lancedb-min-timestamp"),
std::sync::atomic::Ordering::SeqCst,
);
http::Response::builder()
.status(200)
.body("1".to_string())
.unwrap()
}
path => panic!("unexpected request: {path}"),
});
let job = table.refresh_column_async("doubled").await.unwrap();
job.wait().await.unwrap();
table.count_rows(None).await.unwrap();
assert!(
saw_min_timestamp.load(std::sync::atomic::Ordering::SeqCst),
"read after wait carried no freshness baseline"
);
}
/// A checkout after submission wins over the completion fence: the
/// pinned view must not regain a timestamp floor from the job.
#[tokio::test]
async fn test_checkout_after_submit_beats_the_completion_fence() {
let saw_min_timestamp = Arc::new(std::sync::atomic::AtomicBool::new(false));
let saw = saw_min_timestamp.clone();
let table =
Table::new_with_handler("my_table", move |request| match request.url().path() {
"/v1/table/my_table/backfill_column" => http::Response::builder()
.status(202)
.body(r#"{"job_id": "j-8"}"#.to_string())
.unwrap(),
"/v1/jobs/describe" => http::Response::builder()
.status(200)
.body(r#"{"job_id": "j-8", "job_state": "DONE"}"#.to_string())
.unwrap(),
"/v1/table/my_table/describe/" => {
let schema = Schema::new(vec![Field::new("x", DataType::Int32, true)]);
http::Response::builder()
.status(200)
.body(describe_response(&schema))
.unwrap()
}
"/v1/table/my_table/count_rows/" => {
saw.store(
request.headers().contains_key("x-lancedb-min-timestamp"),
std::sync::atomic::Ordering::SeqCst,
);
http::Response::builder()
.status(200)
.body("1".to_string())
.unwrap()
}
path => panic!("unexpected request: {path}"),
});
let job = table.refresh_column_async("doubled").await.unwrap();
table.checkout(3).await.unwrap();
job.wait().await.unwrap();
table.count_rows(None).await.unwrap();
assert!(
!saw_min_timestamp.load(std::sync::atomic::Ordering::SeqCst),
"completion fence overrode an explicit checkout"
);
}
/// Tag checkout resets freshness state wholesale; the fence must not
/// survive it.
#[tokio::test]
async fn test_tag_checkout_after_submit_beats_the_completion_fence() {
let saw_min_timestamp = Arc::new(std::sync::atomic::AtomicBool::new(false));
let saw = saw_min_timestamp.clone();
let table =
Table::new_with_handler("my_table", move |request| match request.url().path() {
"/v1/table/my_table/backfill_column" => http::Response::builder()
.status(202)
.body(r#"{"job_id": "j-9"}"#.to_string())
.unwrap(),
"/v1/jobs/describe" => http::Response::builder()
.status(200)
.body(r#"{"job_id": "j-9", "job_state": "DONE"}"#.to_string())
.unwrap(),
"/v1/table/my_table/tags/version/" => http::Response::builder()
.status(200)
.body(r#"{"version": 5}"#.to_string())
.unwrap(),
"/v1/table/my_table/describe/" => {
let schema = Schema::new(vec![Field::new("x", DataType::Int32, true)]);
http::Response::builder()
.status(200)
.body(describe_response(&schema))
.unwrap()
}
"/v1/table/my_table/count_rows/" => {
saw.store(
request.headers().contains_key("x-lancedb-min-timestamp"),
std::sync::atomic::Ordering::SeqCst,
);
http::Response::builder()
.status(200)
.body("1".to_string())
.unwrap()
}
path => panic!("unexpected request: {path}"),
});
let job = table.refresh_column_async("doubled").await.unwrap();
table.checkout_tag("v1").await.unwrap();
job.wait().await.unwrap();
table.count_rows(None).await.unwrap();
assert!(
!saw_min_timestamp.load(std::sync::atomic::Ordering::SeqCst),
"completion fence overrode a tag checkout"
);
}
/// A checkout landing while the submission request is in flight advances
/// the epoch past the token captured at submit.
#[tokio::test(flavor = "multi_thread", worker_threads = 2)]
async fn test_checkout_during_submission_beats_the_completion_fence() {
let saw_min_timestamp = Arc::new(std::sync::atomic::AtomicBool::new(false));
let saw = saw_min_timestamp.clone();
let (release_tx, release_rx) = std::sync::mpsc::channel::<()>();
let release_rx = Arc::new(std::sync::Mutex::new(release_rx));
let (arrived_tx, arrived_rx) = std::sync::mpsc::channel::<()>();
let arrived_tx = Arc::new(std::sync::Mutex::new(arrived_tx));
let table = Table::new_with_handler("my_table", move |request| {
match request.url().path() {
"/v1/table/my_table/backfill_column" => {
// Signal arrival, then hold the response until the
// test's checkout completes.
arrived_tx.lock().unwrap().send(()).unwrap();
release_rx
.lock()
.unwrap()
.recv_timeout(std::time::Duration::from_secs(10))
.unwrap();
http::Response::builder()
.status(202)
.body(r#"{"job_id": "j-10"}"#.to_string())
.unwrap()
}
"/v1/jobs/describe" => http::Response::builder()
.status(200)
.body(r#"{"job_id": "j-10", "job_state": "DONE"}"#.to_string())
.unwrap(),
"/v1/table/my_table/describe/" => {
let schema = Schema::new(vec![Field::new("x", DataType::Int32, true)]);
http::Response::builder()
.status(200)
.body(describe_response(&schema))
.unwrap()
}
"/v1/table/my_table/count_rows/" => {
saw.store(
request.headers().contains_key("x-lancedb-min-timestamp"),
std::sync::atomic::Ordering::SeqCst,
);
http::Response::builder()
.status(200)
.body("1".to_string())
.unwrap()
}
path => panic!("unexpected request: {path}"),
}
});
let submit = tokio::spawn({
let table = table.clone();
async move { table.refresh_column_async("doubled").await }
});
tokio::task::spawn_blocking(move || {
arrived_rx
.recv_timeout(std::time::Duration::from_secs(10))
.unwrap()
})
.await
.unwrap();
table.checkout(7).await.unwrap();
release_tx.send(()).unwrap();
let job = submit.await.unwrap().unwrap();
job.wait().await.unwrap();
table.count_rows(None).await.unwrap();
assert!(
!saw_min_timestamp.load(std::sync::atomic::Ordering::SeqCst),
"completion fence overrode a checkout that landed mid-submission"
);
}
/// checkout_latest keeps the handle on latest, so a completed backfill
/// must still establish its post-fill baseline -- strictly later than the
/// checkout's own, or a pre-fill cache could still serve.
#[tokio::test(flavor = "multi_thread", worker_threads = 2)]
async fn test_checkout_latest_during_submission_keeps_the_fence() {
let seen_min_timestamp = Arc::new(std::sync::Mutex::new(None::<String>));
let saw = seen_min_timestamp.clone();
let (release_tx, release_rx) = std::sync::mpsc::channel::<()>();
let release_rx = Arc::new(std::sync::Mutex::new(release_rx));
let (arrived_tx, arrived_rx) = std::sync::mpsc::channel::<()>();
let arrived_tx = Arc::new(std::sync::Mutex::new(arrived_tx));
let table =
Table::new_with_handler("my_table", move |request| match request.url().path() {
"/v1/table/my_table/backfill_column" => {
arrived_tx.lock().unwrap().send(()).unwrap();
release_rx
.lock()
.unwrap()
.recv_timeout(std::time::Duration::from_secs(10))
.unwrap();
http::Response::builder()
.status(202)
.body(r#"{"job_id": "j-11"}"#.to_string())
.unwrap()
}
"/v1/jobs/describe" => http::Response::builder()
.status(200)
.body(r#"{"job_id": "j-11", "job_state": "DONE"}"#.to_string())
.unwrap(),
"/v1/table/my_table/count_rows/" => {
*saw.lock().unwrap() = request
.headers()
.get("x-lancedb-min-timestamp")
.map(|v| v.to_str().unwrap().to_string());
http::Response::builder()
.status(200)
.body("1".to_string())
.unwrap()
}
path => panic!("unexpected request: {path}"),
});
let submit = tokio::spawn({
let table = table.clone();
async move { table.refresh_column_async("doubled").await }
});
tokio::task::spawn_blocking(move || {
arrived_rx
.recv_timeout(std::time::Duration::from_secs(10))
.unwrap()
})
.await
.unwrap();
table.checkout_latest().await.unwrap();
let after_checkout = SystemTime::now();
// Real separation between the checkout baseline and completion.
tokio::time::sleep(std::time::Duration::from_millis(50)).await;
release_tx.send(()).unwrap();
let job = submit.await.unwrap().unwrap();
job.wait().await.unwrap();
table.count_rows(None).await.unwrap();
let header = seen_min_timestamp
.lock()
.unwrap()
.clone()
.expect("no baseline");
let sent: SystemTime = chrono::DateTime::parse_from_rfc3339(&header)
.unwrap()
.into();
assert!(
sent > after_checkout,
"baseline {header} did not advance past the checkout"
);
}
#[tokio::test]
async fn test_prewarm_index() {
let table = Table::new_with_handler("my_table", |request| {
@@ -7049,7 +6598,7 @@ mod tests {
.unwrap()
});
let spec = crate::table::LsmWriteSpec::unsharded()
.with_maintained_indexes(vec!["id_idx".to_string()])
.with_maintained_indexes(["id_idx"])
.with_writer_config_defaults([("max_memtable_rows", "1000")]);
table.set_lsm_write_spec(spec).await.unwrap();
}
@@ -7068,29 +6617,11 @@ mod tests {
body["sharding"],
serde_json::json!({ "mode": "bucket", "column": "id", "num_buckets": 16 })
);
// An unpinned maintained set sends null: resolve server-side.
assert_eq!(body["maintained_indexes"], serde_json::Value::Null);
http::Response::builder().status(200).body("{}").unwrap()
});
table
.set_lsm_write_spec(crate::table::LsmWriteSpec::bucket("id", 16))
.await
.unwrap();
}
/// `[]` (none) must stay distinguishable on the wire from null (all).
#[tokio::test]
async fn test_set_lsm_write_spec_no_maintained_indexes() {
let table = Table::new_with_handler("my_table", |request| {
let body = request.body().unwrap().as_bytes().unwrap();
let body: serde_json::Value = serde_json::from_slice(body).unwrap();
assert_eq!(body["maintained_indexes"], serde_json::json!([]));
http::Response::builder().status(200).body("{}").unwrap()
});
table
.set_lsm_write_spec(
crate::table::LsmWriteSpec::bucket("id", 16).with_maintained_indexes(Vec::new()),
)
.set_lsm_write_spec(crate::table::LsmWriteSpec::bucket("id", 16))
.await
.unwrap();
}
@@ -7169,7 +6700,7 @@ mod tests {
} => {
assert_eq!(column, "id");
assert_eq!(num_buckets, 4);
assert_eq!(maintained_indexes, Some(vec!["id_idx".to_string()]));
assert_eq!(maintained_indexes, vec!["id_idx".to_string()]);
assert_eq!(
writer_config_defaults
.get("durable_write")
+147 -509
View File
@@ -50,6 +50,7 @@ use crate::DistanceType;
use crate::blob::BlobRangeRequest;
use crate::data::scannable::{PeekedScannable, Scannable, estimate_write_partitions};
use crate::database::Database;
use crate::database::listing::LANCE_FILE_EXTENSION;
use crate::database::read_freshness::TableFreshness;
use crate::embeddings::{EmbeddingDefinition, EmbeddingRegistry, MemoryRegistry};
use crate::error::{Error, Result};
@@ -68,7 +69,6 @@ pub mod add_columns;
mod add_data;
pub mod branch_merge;
pub mod checkpoint;
pub mod computed_columns;
mod create_index;
pub mod datafusion;
pub(crate) mod dataset;
@@ -78,7 +78,6 @@ pub mod merge;
pub mod optimize;
mod primary_key;
pub mod query;
pub mod refresh;
pub mod schema_evolution;
pub mod update;
pub mod write_progress;
@@ -92,9 +91,6 @@ pub use branch_merge::{
MergeBranchResult, MergeBranchStatus, MergePreview, RowCountSummary,
};
pub use chrono::Duration;
pub use computed_columns::{
ComputedColumn, ComputedColumnKind, computed_column_from_field, computed_columns,
};
pub use delete::DeleteResult;
use futures::future::join_all;
pub use lance::dataset::refs::{BranchContents, Ref, TagContents, Tags as LanceTags};
@@ -102,7 +98,6 @@ pub use lance::dataset::scanner::DatasetRecordBatchStream;
pub use lance_index::optimize::OptimizeOptions;
pub use lsm_stats::{BucketStats, GenerationStats, LsmStats, MemtableStats};
pub use optimize::{CompactionOptions, OptimizeAction, OptimizeStats};
pub use refresh::RefreshColumnResult;
pub use schema_evolution::{
AddColumnsResult, AlterColumnsResult, DropColumnsResult, FieldMetadataUpdate,
UpdateFieldMetadataResult,
@@ -157,6 +152,55 @@ pub(crate) fn map_namespace_lance_error(err: lance::Error, table_name: &str) ->
}
}
/// Map a `lance::Error::DatasetNotFound` for the table at `uri` into a `lancedb::Error`.
///
/// Lance reports "there is nothing at this location" and "there is a table directory
/// here but nothing loadable inside it" with the same error. Only the first is a
/// `TableNotFound`: a `<name>.lance` directory left behind by an interrupted drop and
/// re-create is still reported by `Connection::table_names`, so callers need to be able
/// to tell "never existed" from "exists but is broken".
///
/// See <https://github.com/lancedb/lancedb/issues/3127>.
async fn map_dataset_not_found(
uri: &str,
name: &str,
params: ReadParams,
err: lance::Error,
) -> Error {
let name = name.to_string();
let source = Box::new(err);
if table_dir_exists(uri, params).await.unwrap_or(false) {
Error::TableCorrupted { name, source }
} else {
Error::TableNotFound { name, source }
}
}
/// Whether a table directory is present at `uri`, even though no dataset could be
/// loaded from it.
///
/// This looks for a `<name>.lance` entry in the parent directory, which is exactly what
/// `ListingDatabase::table_names` lists, so the two APIs agree on whether a table is
/// present. Probing `uri` itself would not work: object stores have no empty
/// directories to probe, and on a local filesystem the interesting case is precisely an
/// empty directory.
async fn table_dir_exists(uri: &str, params: ReadParams) -> Result<bool> {
let (object_store, path, _) = DatasetBuilder::from_uri(uri)
.with_read_params(params)
.build_object_store()
.await?;
// Only `*.lance` entries are ever reported as tables, so nothing else can produce
// the list-then-open mismatch this guards against.
if path.extension() != Some(LANCE_FILE_EXTENSION) {
return Ok(false);
}
let (Some(parent), Some(dir_name)) = (path.parent(), path.filename()) else {
return Ok(false);
};
let entries = object_store.read_dir(parent).await?;
Ok(entries.iter().any(|entry| entry.as_str() == dir_name))
}
/// Defines the type of column
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum ColumnKind {
@@ -326,8 +370,6 @@ pub use self::merge::MergeResult;
/// date) and [`LsmWriteSpec::with_writer_config_defaults`] (default
/// `ShardWriter` configuration recorded in the MemWAL index).
///
/// A fresh spec maintains every index on the table, resolved on install.
///
/// 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.
@@ -342,12 +384,9 @@ pub enum LsmWriteSpec {
Bucket {
column: String,
num_buckets: u32,
/// Indexes the MemWAL maintains in-memory as rows are appended.
///
/// `None` means every index it can maintain, resolved on install — a
/// snapshot, so indexes created later need the spec unset and re-set.
/// `Some([])` maintains nothing.
maintained_indexes: Option<Vec<String>>,
/// Names of indexes (already created on the table) that the
/// MemWAL should maintain in-memory as rows are appended.
maintained_indexes: Vec<String>,
/// Default `ShardWriter` configuration recorded in the MemWAL index.
writer_config_defaults: HashMap<String, String>,
},
@@ -357,41 +396,35 @@ pub enum LsmWriteSpec {
/// distinct value of `column` becomes its own shard.
Identity {
column: String,
/// Indexes the MemWAL maintains in-memory as rows are appended.
///
/// `None` means every index it can maintain, resolved on install — a
/// snapshot, so indexes created later need the spec unset and re-set.
/// `Some([])` maintains nothing.
maintained_indexes: Option<Vec<String>>,
/// Names of indexes (already created on the table) that the
/// MemWAL should maintain in-memory as rows are appended.
maintained_indexes: Vec<String>,
/// Default `ShardWriter` configuration recorded in the MemWAL index.
writer_config_defaults: HashMap<String, String>,
},
/// No sharding — every `merge_insert` call writes to a single MemWAL shard.
Unsharded {
/// Indexes the MemWAL maintains in-memory as rows are appended.
///
/// `None` means every index it can maintain, resolved on install — a
/// snapshot, so indexes created later need the spec unset and re-set.
/// `Some([])` maintains nothing.
maintained_indexes: Option<Vec<String>>,
/// Names of indexes (already created on the table) that the
/// MemWAL should maintain in-memory as rows are appended.
maintained_indexes: Vec<String>,
/// Default `ShardWriter` configuration recorded in the MemWAL index.
writer_config_defaults: HashMap<String, String>,
},
}
impl LsmWriteSpec {
/// Construct a hash-bucket sharding spec maintaining every index on the table.
/// Construct a hash-bucket sharding spec with no maintained indexes.
pub fn bucket(column: impl Into<String>, num_buckets: u32) -> Self {
Self::Bucket {
column: column.into(),
num_buckets,
maintained_indexes: None,
maintained_indexes: Vec::new(),
writer_config_defaults: HashMap::new(),
}
}
/// Construct an identity-sharding spec (shard by the raw value of
/// `column`) maintaining every index on the table.
/// `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
@@ -403,37 +436,28 @@ impl LsmWriteSpec {
pub fn identity(column: impl Into<String>) -> Self {
Self::Identity {
column: column.into(),
maintained_indexes: None,
maintained_indexes: Vec::new(),
writer_config_defaults: HashMap::new(),
}
}
/// Construct an unsharded spec maintaining every index on the table.
/// Construct an unsharded spec with no maintained indexes.
pub fn unsharded() -> Self {
Self::Unsharded {
maintained_indexes: None,
maintained_indexes: Vec::new(),
writer_config_defaults: HashMap::new(),
}
}
/// Set which indexes the MemWAL maintains.
///
/// `None` (the default) resolves to every index on the table at install,
/// failing if one cannot be maintained — name the set to install anyway. A
/// list is verbatim: each name must already exist and be maintainable, and
/// an empty list maintains nothing.
///
/// ```
/// # use lancedb::table::LsmWriteSpec;
/// // Every index the table has when the spec is installed:
/// LsmWriteSpec::unsharded().with_maintained_indexes(None);
/// // Exactly these:
/// LsmWriteSpec::unsharded().with_maintained_indexes(vec!["id_idx".to_string()]);
/// // None at all:
/// LsmWriteSpec::unsharded().with_maintained_indexes(Vec::new());
/// ```
pub fn with_maintained_indexes(mut self, indexes: impl Into<Option<Vec<String>>>) -> Self {
let indexes = indexes.into();
/// Replace the list of indexes the MemWAL should keep up to date as
/// rows are appended. Each name must reference an index that already
/// exists on the table at the time `set_lsm_write_spec` is called.
pub fn with_maintained_indexes<I, S>(mut self, indexes: I) -> Self
where
I: IntoIterator<Item = S>,
S: Into<String>,
{
let v: Vec<String> = indexes.into_iter().map(Into::into).collect();
match &mut self {
Self::Bucket {
maintained_indexes, ..
@@ -443,7 +467,7 @@ impl LsmWriteSpec {
}
| Self::Unsharded {
maintained_indexes, ..
} => *maintained_indexes = indexes,
} => *maintained_indexes = v,
}
self
}
@@ -479,9 +503,8 @@ impl LsmWriteSpec {
self
}
/// Borrow the list of index names this spec asks MemWAL to maintain, or
/// `None` when it asks for every index on the table.
pub fn maintained_indexes(&self) -> Option<&[String]> {
/// Borrow the list of index names this spec asks MemWAL to maintain.
pub fn maintained_indexes(&self) -> &[String] {
match self {
Self::Bucket {
maintained_indexes, ..
@@ -491,7 +514,7 @@ impl LsmWriteSpec {
}
| Self::Unsharded {
maintained_indexes, ..
} => maintained_indexes.as_deref(),
} => maintained_indexes,
}
}
@@ -643,15 +666,6 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
message: "set_lsm_write_spec is not supported on this table type".into(),
})
}
/// Switch this table to required index catch-up, one way.
///
/// The default implementation returns `NotSupported`. Implementations
/// that support the MemWAL LSM write path must override this.
async fn require_mem_wal_index_catchup(&self) -> Result<()> {
Err(Error::NotSupported {
message: "require_mem_wal_index_catchup is not supported on this table type".into(),
})
}
/// Remove the [`LsmWriteSpec`] from this table.
///
/// This is a no-op if no spec is currently set.
@@ -747,34 +761,6 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
transforms: NewColumnTransform,
read_columns: Option<Vec<String>>,
) -> Result<AddColumnsResult>;
/// Declare computed columns, each defined by a SQL expression.
///
/// Where the declaration is planned depends on the backend: a local table
/// validates and types the expression itself, a remote one sends the text
/// for the server to plan.
async fn add_computed_columns(
&self,
_columns: &[(String, String)],
) -> Result<AddColumnsResult> {
Err(Error::NotSupported {
message: "computed columns are not supported on this table type".into(),
})
}
/// Fill a computed column's unfilled rows.
///
/// The default returns `NotSupported`; Lance-backed tables override it.
async fn refresh_column(&self, _column: &str) -> Result<RefreshColumnResult> {
Err(Error::NotSupported {
message: "computed columns are supported only on local tables".into(),
})
}
/// Fill a computed column's unfilled rows, returning a [`Job`] tracking
/// the operation.
async fn refresh_column_async(&self, _column: &str) -> Result<Job> {
Err(Error::NotSupported {
message: "computed columns are supported only on local tables".into(),
})
}
/// Alter columns in the table.
async fn alter_columns(&self, alterations: &[ColumnAlteration]) -> Result<AlterColumnsResult>;
/// Drop columns from the table.
@@ -1667,53 +1653,6 @@ impl Table {
AddColumnsBuilder::new(self.inner.clone())
}
/// Fill the fragments of a computed column that hold no values yet.
///
/// Declared with
/// [`AddColumnsBuilder::computed`](add_columns::AddColumnsBuilder::computed),
/// a column starts empty and gets its values here. Fragments appended
/// since the last refresh are filled by the next one; fragments already
/// filled are left as they are, so the call is idempotent and does not
/// observe a mutated input.
///
/// Local tables only: a remote refresh runs as a server job, through
/// [`Table::refresh_column_async`].
///
/// ```
/// # use lancedb::Table;
/// # async fn refresh(table: &Table) -> Result<(), Box<dyn std::error::Error>> {
/// let result = table.refresh_column("doubled").await?;
/// println!("filled {} rows at version {}", result.rows_filled, result.version);
/// # Ok(())
/// # }
/// ```
pub async fn refresh_column(&self, column: impl AsRef<str>) -> Result<RefreshColumnResult> {
self.inner.refresh_column(column.as_ref()).await
}
/// Like [`Table::refresh_column`], but returns a [`Job`] tracking the
/// operation instead of blocking until it completes.
///
/// The job may already be complete when returned, and callers must not
/// assume the column is filled until [`Job::wait`] returns. Invalid input
/// -- an unknown column, or one that is not computed -- is reported by
/// this call rather than by the job. On local tables the job runs as an
/// in-process task; on LanceDB Cloud and Enterprise it is the server's
/// backfill job.
///
/// ```
/// # use lancedb::Table;
/// # async fn refresh_in_background(table: &Table) -> Result<(), Box<dyn std::error::Error>> {
/// let job = table.refresh_column_async("doubled").await?;
/// println!("refresh running: {:?}", job.status().await?);
/// job.wait().await?;
/// # Ok(())
/// # }
/// ```
pub async fn refresh_column_async(&self, column: impl AsRef<str>) -> Result<Job> {
self.inner.refresh_column_async(column.as_ref()).await
}
/// Change a column's name or nullability.
pub async fn alter_columns(
&self,
@@ -1773,7 +1712,7 @@ impl Table {
/// # async fn example(table: &Table) -> Result<(), Box<dyn std::error::Error>> {
/// table
/// .set_lsm_write_spec(
/// LsmWriteSpec::bucket("id", 16).with_maintained_indexes(vec!["id_idx".to_string()]),
/// LsmWriteSpec::bucket("id", 16).with_maintained_indexes(["id_idx"]),
/// )
/// .await?;
/// # Ok(())
@@ -1783,20 +1722,6 @@ impl Table {
self.inner.set_lsm_write_spec(spec).await
}
/// Switch this table to required index catch-up, one way.
///
/// Separate from [`Self::set_lsm_write_spec`] on purpose: a table carrying
/// the bit retains its SSTables until an index records that it holds the
/// compacted rows, so turn it on only once something can repair coverage.
/// A writer that already holds the dataset can call the equivalent on
/// `DatasetMemWalExt` instead; this is the table-level entry point.
///
/// Errors if no spec is set, or if the table already records SSTable
/// compaction progress from before this protocol.
pub async fn require_mem_wal_index_catchup(&self) -> Result<()> {
self.inner.require_mem_wal_index_catchup().await
}
/// Remove the [`LsmWriteSpec`] from this table, reverting to the standard
/// `merge_insert` write path.
///
@@ -1809,10 +1734,9 @@ impl Table {
///
/// Returns `Ok(None)` when the MemWAL LSM write path is not enabled (no
/// spec has been set, or it was removed with [`Table::unset_lsm_write_spec`]).
/// The returned spec mirrors what was passed to
/// [`Table::set_lsm_write_spec`], except that
/// [`LsmWriteSpec::maintained_indexes`] always reports the concrete list
/// resolved when the spec was set — `None` never round-trips.
/// The returned spec — including its [`LsmWriteSpec::maintained_indexes`] and
/// [`LsmWriteSpec::writer_config_defaults`] — mirrors what was passed to
/// [`Table::set_lsm_write_spec`].
///
/// # Example
///
@@ -2474,6 +2398,8 @@ impl NativeTable {
None => false,
};
// Kept so that a `DatasetNotFound` can be re-checked against storage below.
let recovery_params = params.clone();
let mut builder = DatasetBuilder::from_uri(uri).with_read_params(params);
// Set up commit handler when managed_versioning is enabled
@@ -2492,12 +2418,7 @@ impl NativeTable {
let dataset = match builder.load().await {
Ok(dataset) => dataset,
Err(e @ lance::Error::DatasetNotFound { .. }) => {
// The manifest load is the existence check. A physical prefix may be
// from a concurrent or abandoned create, so it cannot refine this error.
return Err(Error::TableNotFound {
name: name.to_string(),
source: Box::new(e),
});
return Err(map_dataset_not_found(uri, name, recovery_params, e).await);
}
Err(e) => return Err(e.into()),
};
@@ -2709,7 +2630,6 @@ impl NativeTable {
namespace_client: Option<Arc<dyn LanceNamespace>>,
pushdown_operations: HashSet<NamespaceClientPushdownOperation>,
) -> Result<Self> {
computed_columns::ensure_no_foreign_declarations(batches.arrow_schema().fields())?;
// Default params uses format v1.
let params = params.unwrap_or(WriteParams {
..Default::default()
@@ -3158,13 +3078,6 @@ impl BaseTable for NativeTable {
let ds = self.dataset.get().await?;
let table_schema = Schema::from(&ds.schema().clone());
computed_columns::ensure_not_written(
&table_schema,
add.data.schema().fields().iter().map(|f| f.name().as_str()),
)?;
if matches!(add.mode, AddDataMode::Overwrite) {
computed_columns::ensure_no_foreign_declarations(add.data.schema().fields())?;
}
let num_partitions = if let Some(parallelism) = add.write_parallelism {
parallelism
@@ -3325,11 +3238,6 @@ impl BaseTable for NativeTable {
params: MergeInsertBuilder,
new_data: Box<dyn RecordBatchReader + Send>,
) -> Result<MergeResult> {
let source_schema = arrow_array::RecordBatchReader::schema(&new_data);
computed_columns::ensure_not_written(
&Schema::from(self.dataset.get().await?.schema()),
source_schema.fields().iter().map(|f| f.name().as_str()),
)?;
let result = merge::execute_merge_insert(self, params, new_data).await?;
self.bump_freshness();
Ok(result)
@@ -3343,10 +3251,6 @@ impl BaseTable for NativeTable {
merge::lsm::set_lsm_write_spec(self, spec).await
}
async fn require_mem_wal_index_catchup(&self) -> Result<()> {
merge::lsm::require_mem_wal_index_catchup(self).await
}
async fn unset_lsm_write_spec(&self) -> Result<()> {
merge::lsm::unset_lsm_write_spec(self).await
}
@@ -3415,22 +3319,6 @@ impl BaseTable for NativeTable {
Ok(result)
}
async fn add_computed_columns(&self, columns: &[(String, String)]) -> Result<AddColumnsResult> {
let result = schema_evolution::execute_declare(self, columns).await?;
self.bump_freshness();
Ok(result)
}
async fn refresh_column(&self, column: &str) -> Result<RefreshColumnResult> {
let result = refresh::execute_refresh_column(self, column).await?;
self.bump_freshness();
Ok(result)
}
async fn refresh_column_async(&self, column: &str) -> Result<Job> {
refresh::execute_refresh_column_async(self, column).await
}
async fn alter_columns(&self, alterations: &[ColumnAlteration]) -> Result<AlterColumnsResult> {
let result = schema_evolution::execute_alter_columns(self, alterations).await?;
self.bump_freshness();
@@ -3798,7 +3686,7 @@ pub struct FragmentSummaryStats {
#[allow(deprecated)]
mod tests {
use std::sync::Arc;
use std::sync::atomic::{AtomicBool, AtomicUsize, Ordering};
use std::sync::atomic::{AtomicBool, Ordering};
use std::time::Duration;
use arrow_array::{
@@ -3880,50 +3768,73 @@ mod tests {
);
}
#[tokio::test]
async fn test_open_not_found_when_empty_directory_exists() {
let tmp_dir = tempdir().unwrap();
let dataset_path = tmp_dir.path().join("test.lance");
std::fs::create_dir(&dataset_path).unwrap();
/// Write a table and then break it, leaving the `<name>.lance` directory in place.
///
/// `remove_all` reproduces an interrupted drop + re-create (the directory is left
/// empty); otherwise only the manifests are removed, leaving the data files behind.
async fn write_then_corrupt_table(dir: &std::path::Path, remove_all: bool) -> String {
let dataset_path = dir.join("test.lance");
let uri = dataset_path.to_str().unwrap().to_string();
let err = NativeTable::open(dataset_path.to_str().unwrap())
.await
.unwrap_err();
let batch = make_test_batches();
let reader = RecordBatchIterator::new(vec![Ok(batch.clone())], batch.schema());
Dataset::write(reader, &uri, None).await.unwrap();
if remove_all {
for entry in std::fs::read_dir(&dataset_path).unwrap() {
let entry = entry.unwrap();
if entry.file_type().unwrap().is_dir() {
std::fs::remove_dir_all(entry.path()).unwrap();
} else {
std::fs::remove_file(entry.path()).unwrap();
}
}
assert_eq!(std::fs::read_dir(&dataset_path).unwrap().count(), 0);
} else {
let versions = dataset_path.join("_versions");
assert!(versions.is_dir(), "expected manifests under {versions:?}");
std::fs::remove_dir_all(&versions).unwrap();
assert!(std::fs::read_dir(&dataset_path).unwrap().count() > 0);
}
uri
}
#[tokio::test]
async fn test_open_corrupt_empty_dir() {
let tmp_dir = tempdir().unwrap();
let uri = write_then_corrupt_table(tmp_dir.path(), true).await;
let err = NativeTable::open(&uri).await.unwrap_err();
assert!(
matches!(&err, Error::TableNotFound { name, .. } if name == "test"),
matches!(&err, Error::TableCorrupted { name, .. } if name == "test"),
"got {err:?}"
);
}
#[tokio::test]
async fn test_open_not_found_when_only_uncommitted_storage_exists() {
async fn test_open_corrupt_missing_manifest() {
let tmp_dir = tempdir().unwrap();
let dataset_path = tmp_dir.path().join("test.lance");
let data_dir = dataset_path.join("data");
std::fs::create_dir_all(&data_dir).unwrap();
std::fs::write(data_dir.join("orphan.lance"), b"uncommitted").unwrap();
let uri = write_then_corrupt_table(tmp_dir.path(), false).await;
let err = NativeTable::open(dataset_path.to_str().unwrap())
.await
.unwrap_err();
let err = NativeTable::open(&uri).await.unwrap_err();
assert!(
matches!(&err, Error::TableNotFound { name, .. } if name == "test"),
matches!(&err, Error::TableCorrupted { name, .. } if name == "test"),
"got {err:?}"
);
}
/// Listing databases discover physical `*.lance` entries. That snapshot is not an
/// authoritative table-existence check: only a committed manifest makes a table
/// openable, and the entry could also be concurrently created or dropped.
/// A table listed by `table_names()` must not be reported as missing by
/// `open_table()`. See <https://github.com/lancedb/lancedb/issues/3127>.
#[tokio::test]
async fn test_table_names_may_include_uncommitted_storage() {
async fn test_open_table_corrupt_is_still_listed() {
let tmp_dir = tempdir().unwrap();
let db = connect(tmp_dir.path().to_str().unwrap())
.execute()
.await
.unwrap();
std::fs::create_dir(tmp_dir.path().join("test.lance")).unwrap();
write_then_corrupt_table(tmp_dir.path(), true).await;
assert_eq!(
db.table_names().execute().await.unwrap(),
@@ -3931,177 +3842,12 @@ mod tests {
);
let err = db.open_table("test").execute().await.unwrap_err();
assert!(
matches!(&err, Error::TableNotFound { name, .. } if name == "test"),
"physical storage without a committed manifest is not a table: {err:?}"
);
}
#[derive(Debug)]
struct ParentListGuardStore {
inner: Arc<dyn object_store::ObjectStore>,
parent: object_store::path::Path,
parent_list_calls: Arc<AtomicUsize>,
}
impl std::fmt::Display for ParentListGuardStore {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
f.write_str("ParentListGuardStore")
}
}
#[async_trait::async_trait]
#[deny(clippy::missing_trait_methods)]
impl object_store::ObjectStore for ParentListGuardStore {
async fn put_opts(
&self,
location: &object_store::path::Path,
payload: object_store::PutPayload,
opts: object_store::PutOptions,
) -> object_store::Result<object_store::PutResult> {
self.inner.put_opts(location, payload, opts).await
}
async fn put_multipart_opts(
&self,
location: &object_store::path::Path,
opts: object_store::PutMultipartOptions,
) -> object_store::Result<Box<dyn object_store::MultipartUpload>> {
self.inner.put_multipart_opts(location, opts).await
}
async fn get_opts(
&self,
location: &object_store::path::Path,
options: object_store::GetOptions,
) -> object_store::Result<object_store::GetResult> {
self.inner.get_opts(location, options).await
}
async fn get_ranges(
&self,
location: &object_store::path::Path,
ranges: &[std::ops::Range<u64>],
) -> object_store::Result<Vec<bytes::Bytes>> {
self.inner.get_ranges(location, ranges).await
}
fn delete_stream(
&self,
locations: futures::stream::BoxStream<
'static,
object_store::Result<object_store::path::Path>,
>,
) -> futures::stream::BoxStream<'static, object_store::Result<object_store::path::Path>>
{
self.inner.delete_stream(locations)
}
fn list(
&self,
prefix: Option<&object_store::path::Path>,
) -> futures::stream::BoxStream<'static, object_store::Result<object_store::ObjectMeta>>
{
if prefix == Some(&self.parent) {
self.parent_list_calls.fetch_add(1, Ordering::Relaxed);
}
self.inner.list(prefix)
}
fn list_with_offset(
&self,
prefix: Option<&object_store::path::Path>,
offset: &object_store::path::Path,
) -> futures::stream::BoxStream<'static, object_store::Result<object_store::ObjectMeta>>
{
if prefix == Some(&self.parent) {
self.parent_list_calls.fetch_add(1, Ordering::Relaxed);
}
self.inner.list_with_offset(prefix, offset)
}
async fn list_with_delimiter(
&self,
prefix: Option<&object_store::path::Path>,
) -> object_store::Result<object_store::ListResult> {
if prefix == Some(&self.parent) {
self.parent_list_calls.fetch_add(1, Ordering::Relaxed);
}
self.inner.list_with_delimiter(prefix).await
}
async fn copy_opts(
&self,
from: &object_store::path::Path,
to: &object_store::path::Path,
options: object_store::CopyOptions,
) -> object_store::Result<()> {
self.inner.copy_opts(from, to, options).await
}
async fn rename_opts(
&self,
from: &object_store::path::Path,
to: &object_store::path::Path,
options: object_store::RenameOptions,
) -> object_store::Result<()> {
self.inner.rename_opts(from, to, options).await
}
}
#[derive(Debug)]
struct ParentListGuardWrapper {
parent_list_calls: Arc<AtomicUsize>,
}
impl WrappingObjectStore for ParentListGuardWrapper {
fn wrap(
&self,
_store_prefix: &str,
inner: Arc<dyn object_store::ObjectStore>,
) -> Arc<dyn object_store::ObjectStore> {
Arc::new(ParentListGuardStore {
inner,
parent: object_store::path::Path::from("database"),
parent_list_calls: self.parent_list_calls.clone(),
})
}
}
#[tokio::test]
async fn test_open_missing_never_lists_database_parent() {
let parent_list_calls = Arc::new(AtomicUsize::new(0));
let params = ReadParams {
store_options: Some(ObjectStoreParams {
object_store_wrapper: Some(Arc::new(ParentListGuardWrapper {
parent_list_calls: parent_list_calls.clone(),
})),
..Default::default()
}),
..Default::default()
};
let err = NativeTable::open_with_params(
"memory:///database/missing.lance",
"missing",
Vec::new(),
None,
Some(params),
None,
None,
HashSet::new(),
None,
)
.await
.unwrap_err();
assert!(
matches!(&err, Error::TableNotFound { name, .. } if name == "missing"),
matches!(&err, Error::TableCorrupted { name, .. } if name == "test"),
"got {err:?}"
);
assert_eq!(
parent_list_calls.load(Ordering::Relaxed),
0,
"opening one missing table must not enumerate sibling tables"
assert!(
err.to_string().contains("exists but could not be loaded"),
"got {err}"
);
}
@@ -5339,7 +5085,7 @@ mod tests {
// Bucket spec round-trips exactly, including the routing column (recovered
// from its field id), maintained indexes, and writer config defaults.
let spec = LsmWriteSpec::bucket("id", 4)
.with_maintained_indexes(vec![idx_name.clone()])
.with_maintained_indexes([idx_name])
.with_writer_config_defaults([("durable_write", "false")]);
table.set_lsm_write_spec(spec.clone()).await.unwrap();
assert_eq!(table.get_lsm_write_spec().await.unwrap(), Some(spec));
@@ -5349,125 +5095,15 @@ mod tests {
assert_eq!(table.get_lsm_write_spec().await.unwrap(), None);
// Identity sharding round-trips (column recovered from the schema).
// A spec left at its default maintains every index on the table, so it
// reads back naming the one on the table rather than as "infer".
let spec = LsmWriteSpec::identity("region");
table.set_lsm_write_spec(spec.clone()).await.unwrap();
assert_eq!(
table.get_lsm_write_spec().await.unwrap(),
Some(spec.with_maintained_indexes(vec![idx_name.clone()]))
);
assert_eq!(table.get_lsm_write_spec().await.unwrap(), Some(spec));
table.unset_lsm_write_spec().await.unwrap();
// Unsharded round-trips (no routing column).
let spec = LsmWriteSpec::unsharded();
table.set_lsm_write_spec(spec.clone()).await.unwrap();
assert_eq!(
table.get_lsm_write_spec().await.unwrap(),
Some(spec.with_maintained_indexes(vec![idx_name]))
);
}
/// The maintained set defaults to every index on the table, resolved at
/// install. An index the memtable cannot build fails the install rather
/// than being dropped: maintaining it would take the table offline for
/// writes, dropping it would hide that from the caller.
#[tokio::test]
async fn test_set_lsm_write_spec_infers_maintained_indexes() {
let tmp_dir = tempdir().unwrap();
let uri = tmp_dir.path().to_str().unwrap();
let schema = Arc::new(Schema::new(vec![
Field::new("id", DataType::Int64, false),
Field::new("tag", DataType::Utf8, true),
]));
let batch = RecordBatch::try_new(
schema.clone(),
vec![
Arc::new(arrow_array::Int64Array::from(vec![1, 2, 3])),
Arc::new(StringArray::from(vec!["a", "b", "c"])),
],
)
.unwrap();
let reader: Box<dyn arrow_array::RecordBatchReader + Send> =
Box::new(RecordBatchIterator::new(vec![Ok(batch)], schema.clone()));
let conn = ConnectBuilder::new(uri)
.read_consistency_interval(Duration::from_secs(0))
.execute()
.await
.unwrap();
let table = conn.create_table("t", reader).execute().await.unwrap();
table
.create_index(&["id"], Index::BTree(Default::default()))
.name("id_btree".to_string())
.execute()
.await
.unwrap();
table
.create_index(&["tag"], Index::Bitmap(Default::default()))
.name("tag_bitmap".to_string())
.execute()
.await
.unwrap();
// Explicitly naming the bitmap index fails before anything commits.
let err = table
.set_lsm_write_spec(
LsmWriteSpec::unsharded().with_maintained_indexes(vec!["tag_bitmap".to_string()]),
)
.await
.unwrap_err();
assert!(
matches!(err, Error::InvalidInput { ref message } if message.contains("tag_bitmap")),
"expected the bitmap index to be rejected, got {err:?}"
);
assert_eq!(table.get_lsm_write_spec().await.unwrap(), None);
// The default covers every index, so the bitmap fails it too.
let err = table
.set_lsm_write_spec(LsmWriteSpec::unsharded())
.await
.unwrap_err();
assert!(
matches!(err, Error::InvalidInput { ref message }
if message.contains("tag_bitmap") && message.contains("maintained_indexes")),
"expected the inferred set to be rejected, got {err:?}"
);
assert_eq!(table.get_lsm_write_spec().await.unwrap(), None);
// Naming the maintainable subset installs.
table
.set_lsm_write_spec(
LsmWriteSpec::unsharded().with_maintained_indexes(vec!["id_btree".to_string()]),
)
.await
.unwrap();
assert_eq!(
table
.get_lsm_write_spec()
.await
.unwrap()
.unwrap()
.maintained_indexes(),
Some(["id_btree".to_string()].as_slice())
);
// Opting out entirely is distinct from the default.
table.unset_lsm_write_spec().await.unwrap();
table
.set_lsm_write_spec(LsmWriteSpec::unsharded().with_maintained_indexes(Vec::new()))
.await
.unwrap();
assert_eq!(
table
.get_lsm_write_spec()
.await
.unwrap()
.unwrap()
.maintained_indexes(),
Some([].as_slice())
);
assert_eq!(table.get_lsm_write_spec().await.unwrap(), Some(spec));
}
#[tokio::test]
@@ -5571,8 +5207,8 @@ mod tests {
pub async fn test_stats_includes_index_and_overlay_files() {
use lance::dataset::WriteDestination;
use lance::dataset::transaction::{DataOverlayGroup, Operation};
use lance_file::version::stable_file_version;
use lance_file::writer::FileWriterOptions;
use lance_file::version::{ConcreteFileVersion, LanceFileVersion};
use lance_file::writer::{FileWriter, FileWriterOptions};
use lance_io::utils::CachedFileSize;
use lance_table::format::DataFile;
use lance_table::format::overlay::{DataOverlayFile, OverlayCoverage};
@@ -5637,17 +5273,19 @@ mod tests {
let fragment_id = dataset.get_fragments()[0].id() as u64;
let foo_field_id = dataset.schema().field("foo").unwrap().id;
let overlay_schema = dataset.schema().project_by_ids(&[foo_field_id], true);
let file_version = stable_file_version();
let file_version = ConcreteFileVersion::from(LanceFileVersion::Stable);
let filename = "overlay.lance".to_string();
let store = dataset.object_store(None).await.unwrap();
let path = dataset.data_dir().child(filename.clone());
let obj_writer = store.create(&path).await.unwrap();
let mut writer = lance_file::versions::create_writer(
file_version,
let mut writer = FileWriter::try_new(
obj_writer,
overlay_schema,
FileWriterOptions::default(),
FileWriterOptions {
format_version: Some(file_version.into()),
..Default::default()
},
)
.unwrap();
writer
+22 -119
View File
@@ -15,7 +15,6 @@ use crate::{Error, Result};
pub struct AddColumnsBuilder {
parent: Arc<dyn BaseTable>,
transform: Option<NewColumnTransform>,
computed: Vec<(String, String)>,
read_columns: Option<Vec<String>>,
}
@@ -24,7 +23,6 @@ impl std::fmt::Debug for AddColumnsBuilder {
f.debug_struct("AddColumnsBuilder")
.field("parent", &self.parent)
.field("has_transform", &self.transform.is_some())
.field("computed", &self.computed)
.field("read_columns", &self.read_columns)
.finish()
}
@@ -35,58 +33,19 @@ impl AddColumnsBuilder {
Self {
parent,
transform: None,
computed: Vec::new(),
read_columns: None,
}
}
/// Set how the new columns' values are produced.
/// Set how the new columns' values are produced. Required.
pub fn transform(mut self, transform: NewColumnTransform) -> Self {
self.transform = Some(transform);
self
}
/// Add a column defined by `expression`, evaluated by a later refresh
/// rather than by this commit. Its type and inputs are derived from the
/// expression.
///
/// The column is committed with no values, so declaring one costs the same
/// on an empty table as on a large one. Rows get values from
/// [`Table::refresh_column`](super::Table::refresh_column), which fills
/// every fragment that has none -- including fragments appended since the
/// last refresh.
///
/// Refresh does not revisit a fragment it has filled, so mutating an input
/// leaves the value computed at fill time; recomputing means dropping the
/// column and declaring it again. An input cannot be renamed, retyped or
/// dropped while a declaration reads it, since the expression names it.
///
/// On LanceDB Cloud and Enterprise the expression is planned by the
/// server, and the refresh runs as a server job -- see
/// [`Table::refresh_column_async`](super::Table::refresh_column_async).
///
/// ```
/// # use lancedb::Table;
/// # async fn declare(table: &Table) -> Result<(), Box<dyn std::error::Error>> {
/// table
/// .add_columns()
/// .computed("doubled", "x * 2")
/// .execute()
/// .await?;
/// let filled = table.refresh_column("doubled").await?;
/// println!("filled {} rows", filled.rows_filled);
/// # Ok(())
/// # }
/// ```
pub fn computed(mut self, name: impl Into<String>, expression: impl Into<String>) -> Self {
self.computed.push((name.into(), expression.into()));
self
}
/// Limit which existing columns a [`NewColumnTransform::BatchUDF`] mapper
/// receives. Every other transform, and a computed column, determines what
/// it reads, so setting this alongside one is an error rather than a silent
/// no-op.
/// receives. Every other transform determines what it reads, so setting
/// this alongside one is an error rather than a silent no-op.
pub fn read_columns(mut self, columns: impl IntoIterator<Item = impl Into<String>>) -> Self {
self.read_columns = Some(columns.into_iter().map(Into::into).collect());
self
@@ -97,42 +56,24 @@ impl AddColumnsBuilder {
let Self {
parent,
transform,
computed,
read_columns,
} = self;
match (transform, computed.is_empty()) {
(None, true) => Err(Error::InvalidInput {
message: "add_columns requires a transform or a computed column".into(),
}),
// The two commit through different transforms, so one call covering
// both would be two commits and could half-apply.
(Some(_), false) => Err(Error::InvalidInput {
message: "add_columns cannot mix a transform with computed columns; \
they cannot be added atomically in one call"
let Some(transform) = transform else {
return Err(Error::InvalidInput {
message: "add_columns requires a transform".into(),
});
};
if read_columns.is_some() && !matches!(transform, NewColumnTransform::BatchUDF(_)) {
return Err(Error::InvalidInput {
message: "read_columns applies only to a BatchUDF transform; \
every other transform determines what it reads"
.into(),
}),
(Some(transform), true) => {
if read_columns.is_some() && !matches!(transform, NewColumnTransform::BatchUDF(_)) {
return Err(Error::InvalidInput {
message: "read_columns applies only to a BatchUDF transform; \
every other transform determines what it reads"
.into(),
});
}
parent.add_columns(transform, read_columns).await
}
(None, false) => {
if read_columns.is_some() {
return Err(Error::InvalidInput {
message: "read_columns applies only to a BatchUDF transform; \
a computed column's inputs come from its expression"
.into(),
});
}
parent.add_computed_columns(&computed).await
}
});
}
parent.add_columns(transform, read_columns).await
}
}
@@ -144,8 +85,8 @@ mod tests {
use arrow_schema::{DataType, Field, Schema};
use lance::dataset::{BatchUDF, NewColumnTransform};
use crate::Table;
use crate::connect;
use crate::{Error, Table};
async fn table_with_two_columns(name: &str) -> Table {
let conn = connect("memory://").execute().await.unwrap();
@@ -157,7 +98,10 @@ mod tests {
async fn test_requires_a_transform() {
let table = table_with_two_columns("no_transform").await;
let err = table.add_columns().execute().await.unwrap_err();
assert!(matches!(err, Error::InvalidInput { .. }));
assert!(
err.to_string().contains("requires a transform"),
"got: {err}"
);
}
#[tokio::test]
@@ -173,7 +117,7 @@ mod tests {
.execute()
.await
.unwrap_err();
assert!(matches!(err, Error::InvalidInput { .. }));
assert!(err.to_string().contains("BatchUDF"), "got: {err}");
let schema = table.schema().await.unwrap();
assert!(
@@ -182,47 +126,6 @@ mod tests {
);
}
#[tokio::test]
async fn test_mixing_transform_and_computed_is_rejected() {
let table = table_with_two_columns("mixed_add").await;
let err = table
.add_columns()
.transform(NewColumnTransform::SqlExpressions(vec![(
"eager".into(),
"x * 2".into(),
)]))
.computed("lazy", "x * 3")
.execute()
.await
.unwrap_err();
assert!(matches!(err, Error::InvalidInput { .. }));
let schema = table.schema().await.unwrap();
assert!(schema.field_with_name("eager").is_err());
assert!(schema.field_with_name("lazy").is_err());
}
#[tokio::test]
async fn test_read_columns_with_computed_is_rejected() {
let table = table_with_two_columns("read_cols_computed").await;
let err = table
.add_columns()
.computed("doubled", "x * 2")
.read_columns(["x"])
.execute()
.await
.unwrap_err();
assert!(matches!(err, Error::InvalidInput { .. }));
assert!(
table
.schema()
.await
.unwrap()
.field_with_name("doubled")
.is_err()
);
}
#[tokio::test]
async fn test_read_columns_limits_what_a_batch_udf_sees() {
let table = table_with_two_columns("read_cols_udf").await;
File diff suppressed because it is too large Load Diff
+3 -14
View File
@@ -17,7 +17,7 @@ use datafusion_physical_plan::stream::RecordBatchStreamAdapter;
use datafusion_physical_plan::{
DisplayAs, DisplayFormatType, ExecutionPlan, ExecutionPlanProperties, PlanProperties,
};
use futures::StreamExt;
use futures::TryStreamExt;
use lance::Dataset;
use lance::dataset::transaction::{Operation, Transaction};
use lance::dataset::{CommitBuilder, InsertBuilder, WriteParams, WriteProgressFn};
@@ -194,23 +194,12 @@ impl ExecutionPlan for InsertExec {
let output_bytes = MetricBuilder::new(&self.metrics).output_bytes(partition);
let input_schema = input_stream.schema();
let declared: Vec<String> = crate::table::computed_columns::computed_columns(
&arrow_schema::Schema::from(self.dataset.schema()),
)
.into_iter()
.map(|declaration| declaration.name)
.collect();
let input_stream: SendableRecordBatchStream =
Box::pin(InstrumentedRecordBatchStreamAdapter::new(
input_schema,
input_stream.map(move |batch| {
let batch = batch?;
crate::table::computed_columns::ensure_batch_writes_no_computed_values(
&declared, &batch,
)
.map_err(|e| datafusion::error::DataFusionError::External(Box::new(e)))?;
input_stream.map_ok(move |batch| {
output_bytes.add(batch.get_array_memory_size());
Ok(batch)
batch
}),
partition,
&self.metrics,
+2 -2
View File
@@ -1161,7 +1161,7 @@ mod lsm_tests {
.unwrap();
let fts_index = table.list_indices().await.unwrap()[0].name.clone();
table
.set_lsm_write_spec(LsmWriteSpec::unsharded().with_maintained_indexes(vec![fts_index]))
.set_lsm_write_spec(LsmWriteSpec::unsharded().with_maintained_indexes([fts_index]))
.await
.unwrap();
@@ -1254,7 +1254,7 @@ mod lsm_tests {
.unwrap();
let vec_index = table.list_indices().await.unwrap()[0].name.clone();
table
.set_lsm_write_spec(LsmWriteSpec::unsharded().with_maintained_indexes(vec![vec_index]))
.set_lsm_write_spec(LsmWriteSpec::unsharded().with_maintained_indexes([vec_index]))
.await
.unwrap();
+8 -113
View File
@@ -29,7 +29,6 @@ use arrow_schema::{DataType, Schema as ArrowSchema, SchemaRef};
use lance::Dataset;
use lance::dataset::mem_wal::{
DatasetMemWalExt, ShardWriter, ShardWriterConfig, evaluate_sharding_spec,
validate_maintained_indexes,
};
use lance::index::DatasetIndexExt;
use lance_core::datatypes::Schema as LanceSchema;
@@ -38,9 +37,8 @@ use tokio::sync::RwLock;
use uuid::Uuid;
use crate::error::{Error, Result};
use crate::index::IndexConfig;
use crate::table::merge::{MergeInsertBuilder, MergeResult};
use crate::table::{BaseTable, LsmWriteSpec, NativeTable};
use crate::table::{LsmWriteSpec, NativeTable};
/// Spec id of the sole sharding spec installed by [`set_lsm_write_spec`].
/// Must match Lance's `InitializeMemWalBuilder` (`SHARDING_SPEC_ID`).
@@ -82,53 +80,32 @@ pub(crate) async fn set_lsm_write_spec(table: &NativeTable, spec: LsmWriteSpec)
}
}
// Before the builder borrows the dataset clone. `list_indices` merges an
// index's segments into one entry, so the result needs no dedup.
let maintained_indexes = {
let dataset = table.dataset.get().await?;
resolve_maintained_indexes(
&dataset,
&table.list_indices().await?,
spec.maintained_indexes(),
)
.await?
};
table.checkout_latest().await?;
let mut dataset = (*table.dataset.get().await?).clone();
let schema = arrow_schema::Schema::from(dataset.schema());
if !crate::table::computed_columns::computed_columns(&schema).is_empty() {
return Err(Error::NotSupported {
message: "an LSM write spec cannot be installed on a table with computed \
columns: rows in un-compacted tiers are invisible to refresh"
.into(),
});
}
let mut builder = dataset.initialize_mem_wal();
let writer_config_defaults = match spec {
let (maintained_indexes, writer_config_defaults) = match spec {
LsmWriteSpec::Bucket {
column,
num_buckets,
maintained_indexes,
writer_config_defaults,
..
} => {
builder = builder.bucket_sharding(column, num_buckets);
writer_config_defaults
(maintained_indexes, writer_config_defaults)
}
LsmWriteSpec::Identity {
column,
maintained_indexes,
writer_config_defaults,
..
} => {
builder = builder.identity_sharding(column);
writer_config_defaults
(maintained_indexes, writer_config_defaults)
}
LsmWriteSpec::Unsharded {
maintained_indexes,
writer_config_defaults,
..
} => {
builder = builder.unsharded();
writer_config_defaults
(maintained_indexes, writer_config_defaults)
}
};
builder = builder.maintained_indexes(maintained_indexes);
@@ -140,88 +117,6 @@ pub(crate) async fn set_lsm_write_spec(table: &NativeTable, spec: LsmWriteSpec)
Ok(())
}
/// Resolve a spec's maintained-index selection against `indices`, as reported
/// by [`Table::list_indices`](crate::Table::list_indices).
///
/// `None` means every index on the table, snapshotted now. Lance validates
/// either selection against its shard-writer rules, so a spec that installs is
/// one the MemWAL can open.
///
/// An unmaintainable index fails an inferred set rather than being dropped from
/// it — dropping would leave the caller believing it is maintained.
async fn resolve_maintained_indexes(
dataset: &Dataset,
indices: &[IndexConfig],
requested: Option<&[String]>,
) -> Result<Vec<String>> {
let Some(requested) = requested else {
let all: Vec<String> = indices.iter().map(|index| index.name.clone()).collect();
validate_maintained_indexes(dataset, &all)
.await
.map_err(|source| Error::InvalidInput {
message: format!(
"cannot maintain every index on this table: {source}. Set \
maintained_indexes explicitly to choose from {}",
index_name_list(indices),
),
})?;
return Ok(all);
};
for name in requested {
if !indices.iter().any(|index| &index.name == name) {
return Err(Error::InvalidInput {
message: format!(
"maintained index '{}' does not exist on this table; it has {}",
name,
index_name_list(indices),
),
});
}
}
validate_maintained_indexes(dataset, requested).await?;
Ok(requested.to_vec())
}
/// Index names for an error message.
fn index_name_list(indices: &[IndexConfig]) -> String {
if indices.is_empty() {
return "no indexes".to_string();
}
let mut names: Vec<&str> = indices.iter().map(|index| index.name.as_str()).collect();
names.sort_unstable();
format!("[{}]", names.join(", "))
}
// =============================================================================
// require_mem_wal_index_catchup
// =============================================================================
/// Switch this table to required index catch-up, one way.
///
/// Deliberately **not** part of installing the write spec. Until something can
/// actually repair coverage, a table carrying the bit reports every index as
/// not known to hold the compacted rows, so its SSTables are retained
/// indefinitely -- and the WAL pod trims on the legacy rule meanwhile, leaving
/// readers pointed at files that are gone. Turn this on only once remote
/// maintenance owns the merge and the repair for the table.
///
/// Lance refuses the activation if the table already records SSTable
/// compaction progress: those numbers predate this protocol and cannot be
/// validated, so such a table must be drained rather than activated.
#[allow(clippy::redundant_pub_crate)]
pub(crate) async fn require_mem_wal_index_catchup(table: &NativeTable) -> Result<()> {
table.dataset.ensure_mutable()?;
let mut dataset = (*table.dataset.get().await?).clone();
if dataset.mem_wal_index_details().await?.is_none() {
return Err(Error::InvalidInput {
message: "require_mem_wal_index_catchup: no LSM write spec is set on this table".into(),
});
}
dataset.require_mem_wal_index_catchup().await?;
table.dataset.update(dataset);
Ok(())
}
// =============================================================================
// unset_lsm_write_spec
// =============================================================================
+52 -202
View File
@@ -36,7 +36,6 @@ use lance::dataset::mem_wal::{
DatasetMemWalExt, LsmScanner, ShardManifestStore, ShardSnapshot, ShardWriterConfig,
};
use lance_index::mem_wal::{MemWalIndexDetails, ShardManifest};
use lance_table::feature_flags::FLAG_MEM_WAL_INDEX_CATCHUP;
use uuid::Uuid;
use super::NativeTable;
@@ -85,8 +84,9 @@ pub(super) async fn create_lsm_plan(
let pk_columns = pk_columns(&ds_ref)?;
// The base index an indexed arm relies on may lag compaction; resolve it so the
// snapshot retains SSTables the index has not yet caught up to.
let arm_indexes = arm_maintained_index_names(&ds_ref, &query, &details).await?;
let (snapshots, in_memory) = build_read_context(table, &ds_ref, &details, &arm_indexes).await?;
let arm_index = arm_maintained_index_name(&ds_ref, &query, &details).await?;
let (snapshots, in_memory) =
build_read_context(table, &ds_ref, &details, arm_index.as_deref()).await?;
let limit = query.base.limit;
let offset = query.base.offset;
@@ -232,44 +232,28 @@ fn pk_columns(dataset: &Dataset) -> Result<Vec<String>> {
Ok(pk)
}
/// Per-shard SSTable exclusion watermark: the generation at or below which
/// SSTables are safe to drop for this query.
///
/// A generation is droppable only once it is compacted into the base table AND
/// covered by the catch-up of every index the query relies on, so the watermark
/// is the minimum across `index_names`. Gating on fewer than all of them would
/// drop SSTables holding rows an uncounted index has not yet indexed, and that
/// arm would silently return fewer rows.
///
/// See [`arm_maintained_index_names`] for which indexes are collected today: a
/// vector search with a scalar prefilter is not yet among them.
///
/// An empty `index_names` (a plain scan) uses the compaction watermark alone.
/// First occurrence per shard mirrors Lance's `compacted_generation_for_shard`.
/// Per-shard SSTable exclusion watermark: the generation at or below which SSTables
/// are safe to drop for this arm. A generation is droppable only once it is
/// compacted into the base table AND covered by `index_name`'s catch-up (for an
/// indexed arm); a plain scan (`index_name == None`) uses the compaction watermark
/// alone. Capping at the index catch-up keeps rows the base index has not yet
/// indexed visible through their SSTable. First occurrence per shard mirrors Lance's
/// `compacted_generation_for_shard`.
fn exclusion_watermarks(
details: &MemWalIndexDetails,
index_names: &[String],
catchup_required: bool,
index_name: Option<&str>,
) -> HashMap<Uuid, u64> {
let mut exclude: HashMap<Uuid, u64> = HashMap::new();
for entry in &details.compacted_sstables {
let mut watermark = entry.generation;
for name in index_names {
match details
if let Some(name) = index_name
&& let Some(caught_up) = details
.index_catchup
.iter()
.find(|icp| icp.index_name == *name)
.find(|icp| icp.index_name == name)
.and_then(|icp| icp.caught_up_generation_for_shard(&entry.shard_id))
{
Some(caught_up) => watermark = watermark.min(caught_up),
// No entry. On a table that requires catch-up this means the
// index is *not* known to hold these rows, and the base arm is
// index-only -- so every generation stays readable from its
// SSTable. Without the bit the field is not maintained at all,
// and absence carries no information.
None if catchup_required => watermark = 0,
None => {}
}
{
watermark = watermark.min(caught_up);
}
exclude.entry(entry.shard_id).or_insert(watermark);
}
@@ -283,26 +267,13 @@ fn exclusion_watermarks(
/// with a live cached `ShardWriter` (this session's in-flight writes) the
/// writer's authoritative in-memory manifest and memtables override the
/// on-disk view so a read sees data not yet flushed.
/// Whether this table reads a missing `index_catchup` entry as "not caught up".
///
/// Both words must be set. A reader honouring the bit while a writer does not
/// would retain SSTables the writer had already trimmed, and the reverse would
/// serve rows from files the writer still expects to be excluded -- so a
/// half-set manifest is treated as legacy, which is the conservative side.
fn requires_index_catchup(dataset: &Dataset) -> bool {
let manifest = dataset.manifest();
manifest.reader_feature_flags & FLAG_MEM_WAL_INDEX_CATCHUP != 0
&& manifest.writer_feature_flags & FLAG_MEM_WAL_INDEX_CATCHUP != 0
}
async fn build_read_context(
table: &NativeTable,
dataset: &Dataset,
details: &MemWalIndexDetails,
index_names: &[String],
index_name: Option<&str>,
) -> Result<(Vec<ShardSnapshot>, HashMap<Uuid, InMemoryMemTables>)> {
let catchup_required = requires_index_catchup(dataset);
let exclude = exclusion_watermarks(details, index_names, catchup_required);
let exclude = exclusion_watermarks(details, index_name);
let shard_ids = dataset.list_mem_wal_latest_shard_ids().await?;
// Use the dataset's own object store (not `ObjectStore::from_uri`, which
@@ -516,33 +487,19 @@ async fn index_maintained(
}))
}
/// Every maintained base index this query relies on, used to gate SSTable
/// exclusion by index catch-up.
///
/// Returns a list because the watermark must be the lowest across every index a
/// query relies on. Today it never holds more than one: `reject_unsupported`
/// refuses hybrid search, so the vector and full-text arms are mutually
/// exclusive.
///
/// The case that is genuinely multi-index -- a vector search with a scalar or
/// bitmap prefilter -- is **not collected yet**. Identifying those needs the
/// planner's chosen indexes, not the columns the filter names, and no Lance API
/// exposes them. Until it does, such a query is gated on its vector index alone.
///
/// Empty for a plain scan, or when no maintained index covers the searched
/// column.
async fn arm_maintained_index_names(
/// The maintained base index the query's arm relies on (vector index for ANN, FTS
/// index for full-text), used to gate SSTable compaction exclusion by index catch-up.
/// `None` for a plain scan or when no maintained index covers the searched column.
async fn arm_maintained_index_name(
dataset: &Dataset,
query: &VectorQueryRequest,
details: &MemWalIndexDetails,
) -> Result<Vec<String>> {
) -> Result<Option<String>> {
use lance::index::DatasetIndexExt;
// Each arm's searched column, the index-detail type it relies on, and a
// Resolve the arm's searched column, the index-detail type it relies on, and a
// label for diagnostics — catch-up is taken from the vector/FTS index
// specifically, not a BTree on the same column.
let mut arms: Vec<(String, &str, &str)> = Vec::new();
if !query.query_vector.is_empty() {
let (column, type_url_suffix, arm) = if !query.query_vector.is_empty() {
let arrow_schema = ArrowSchema::from(dataset.schema());
let column = match &query.column {
Some(column) => column.clone(),
@@ -551,43 +508,31 @@ async fn arm_maintained_index_names(
default_vector_column(&arrow_schema, dim)?
}
};
arms.push((column, "VectorIndexDetails", "vector"));
}
if let Some(fts) = &query.base.full_text_search
&& let Some(column) = fts.columns().into_iter().next()
{
arms.push((column, "InvertedIndexDetails", "full-text"));
}
if arms.is_empty() {
return Ok(Vec::new());
}
let indices = dataset.load_indices().await?;
let mut names = Vec::with_capacity(arms.len());
for (column, type_url_suffix, arm) in arms {
let Some(field) = dataset.schema().field(&column) else {
continue;
};
let segment_names: Vec<String> = indices
.iter()
.filter(|idx| {
idx.fields.contains(&field.id)
&& idx
.index_details
.as_ref()
.is_some_and(|d| d.type_url.ends_with(type_url_suffix))
})
.map(|idx| idx.name.clone())
.collect();
if let Some(name) =
resolve_single_index(segment_names, &details.maintained_indexes, arm, &column)?
{
names.push(name);
(column, "VectorIndexDetails", "vector")
} else if let Some(fts) = &query.base.full_text_search {
match fts.columns().into_iter().next() {
Some(column) => (column, "InvertedIndexDetails", "full-text"),
None => return Ok(None),
}
}
names.sort();
names.dedup();
Ok(names)
} else {
return Ok(None);
};
let Some(field) = dataset.schema().field(&column) else {
return Ok(None);
};
let indices = dataset.load_indices().await?;
let segment_names: Vec<String> = indices
.iter()
.filter(|idx| {
idx.fields.contains(&field.id)
&& idx
.index_details
.as_ref()
.is_some_and(|d| d.type_url.ends_with(type_url_suffix))
})
.map(|idx| idx.name.clone())
.collect();
resolve_single_index(segment_names, &details.maintained_indexes, arm, &column)
}
/// Resolve the single logical index from the names of its matching physical
@@ -789,117 +734,22 @@ mod tests {
};
// Plain scan: drop every compacted generation (through 5).
assert_eq!(
exclusion_watermarks(&details, &[], false).get(&shard),
Some(&5)
);
assert_eq!(exclusion_watermarks(&details, None).get(&shard), Some(&5));
// FTS arm with a lagging index: exclusion is capped at the index catch-up
// (2), so SSTable generations 3..=5 are retained until the index covers
// them — otherwise those documents would silently vanish from FTS results.
assert_eq!(
exclusion_watermarks(&details, &["fts_idx".to_string()], false).get(&shard),
exclusion_watermarks(&details, Some("fts_idx")).get(&shard),
Some(&2)
);
// A caught-up index — or one untracked in index_catchup — falls back to the
// compaction watermark.
assert_eq!(
exclusion_watermarks(&details, &["caught_up_idx".to_string()], false).get(&shard),
exclusion_watermarks(&details, Some("caught_up_idx")).get(&shard),
Some(&5)
);
// The same missing entry, once the table requires catch-up: absence now
// means "not known to hold these rows", so nothing may be excluded and
// every generation stays readable from its SSTable. This is the whole
// point of the protocol -- an indexed query against a table whose index
// has not caught up must not silently lose rows.
assert_eq!(
exclusion_watermarks(&details, &["untracked_idx".to_string()], true).get(&shard),
Some(&0)
);
// A tracked index is unaffected by the mode: the recorded position is
// information either way, and it still caps the exclusion.
assert_eq!(
exclusion_watermarks(&details, &["fts_idx".to_string()], true).get(&shard),
Some(&2)
);
// One missing entry is enough to hold everything back, even alongside an
// index that has caught up.
let mixed = vec!["fts_idx".to_string(), "untracked_idx".to_string()];
assert_eq!(
exclusion_watermarks(&details, &mixed, true).get(&shard),
Some(&0)
);
}
/// A hybrid search reads a vector and a full-text index, and either may lag.
/// Retaining to the lower of the two is what keeps both arms complete;
/// gating on one alone would drop SSTables the other has not indexed.
#[test]
fn exclusion_watermark_takes_the_minimum_across_every_index_used() {
let shard = Uuid::from_u128(1);
let details = MemWalIndexDetails {
compacted_sstables: vec![CompactedSsTable::new(shard, 9)],
index_catchup: vec![
IndexCatchupProgress::new(
"vec_idx".to_string(),
vec![CompactedSsTable::new(shard, 7)],
),
IndexCatchupProgress::new(
"fts_idx".to_string(),
vec![CompactedSsTable::new(shard, 4)],
),
],
maintained_indexes: vec!["vec_idx".to_string(), "fts_idx".to_string()],
..Default::default()
};
// Each index alone stops at its own catch-up.
assert_eq!(
exclusion_watermarks(&details, &["vec_idx".to_string()], false).get(&shard),
Some(&7)
);
assert_eq!(
exclusion_watermarks(&details, &["fts_idx".to_string()], false).get(&shard),
Some(&4)
);
// Used together, the lower one governs regardless of order.
let both = ["vec_idx".to_string(), "fts_idx".to_string()];
assert_eq!(
exclusion_watermarks(&details, &both, false).get(&shard),
Some(&4)
);
let reversed = ["fts_idx".to_string(), "vec_idx".to_string()];
assert_eq!(
exclusion_watermarks(&details, &reversed, false).get(&shard),
Some(&4)
);
}
/// An index with no catch-up entry contributes no cap today, so a lagging
/// sibling must still govern rather than being widened by the untracked one.
#[test]
fn an_untracked_index_does_not_widen_a_lagging_sibling() {
let shard = Uuid::from_u128(1);
let details = MemWalIndexDetails {
compacted_sstables: vec![CompactedSsTable::new(shard, 9)],
index_catchup: vec![IndexCatchupProgress::new(
"fts_idx".to_string(),
vec![CompactedSsTable::new(shard, 4)],
)],
maintained_indexes: vec!["fts_idx".to_string(), "untracked_idx".to_string()],
..Default::default()
};
let both = ["fts_idx".to_string(), "untracked_idx".to_string()];
assert_eq!(
exclusion_watermarks(&details, &both, false).get(&shard),
Some(&4)
);
}
#[test]
-954
View File
@@ -1,954 +0,0 @@
// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
//! Filling computed columns.
//!
//! A row without a value gets one; a row that has one keeps it. Refresh is
//! therefore idempotent and does not observe input mutation -- once a row is
//! filled, changing what the expression reads leaves the stored result alone.
//!
//! Two passes per fragment. The first scans only the unfilled live rows and
//! evaluates the expression over them, which yields the exact fill count and
//! decides whether the fragment is staged at all -- a fragment where nothing
//! would change stages nothing, which is what lets an expression yielding
//! null settle instead of restaging forever. The second streams the
//! fragment's physical rows into `write_column` a batch at a time, so peak
//! memory is bounded by a scan batch. The expression is evaluated by this
//! module, never through a projection alias, and only over rows being
//! filled: every other row -- deleted, or already holding a value -- has its
//! inputs masked to null first, so a poison value in a row nobody is filling
//! cannot fail the refresh.
use std::sync::Arc;
use arrow_array::{ArrayRef, BooleanArray, RecordBatch, RecordBatchOptions};
use arrow_schema::Schema as ArrowSchema;
use datafusion_expr::ColumnarValue;
use futures::{Stream, StreamExt, TryStreamExt};
use lance::Dataset;
use lance::dataset::WriteDestination;
use lance::dataset::fragment::FileFragment;
use lance::dataset::transaction::Operation;
use lance_core::ROW_ID;
use lance_core::datatypes::Schema as LanceSchema;
use serde::{Deserialize, Serialize};
use super::computed_columns::{BoundExpression, ComputedColumnKind, computed_column_from_field};
use super::{BaseTable, NativeTable};
use crate::job::Job;
use crate::{Error, Result};
/// The result of refreshing a computed column.
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize, Default)]
pub struct RefreshColumnResult {
/// Rows that had a value computed.
#[serde(default)]
pub rows_filled: u64,
/// The commit version associated with the operation.
#[serde(default)]
pub version: u64,
}
/// Internal implementation of the refresh logic.
pub(crate) async fn execute_refresh_column(
table: &NativeTable,
column: &str,
) -> Result<RefreshColumnResult> {
table.dataset.ensure_mutable()?;
ensure_no_lsm_write_spec(table).await?;
let dataset = table.dataset.get().await?;
let expression = declared_expression(&dataset, column)?;
let schema = Arc::new(ArrowSchema::from(dataset.schema()));
let bound = Arc::new(super::computed_columns::bind(schema, column, &expression)?);
let field = dataset
.schema()
.field(column)
.ok_or_else(|| Error::ColumnNotFound {
name: column.to_string(),
})?;
// The dataset's own field, so the identity write_column checks against the
// manifest holds by construction.
let column_schema = LanceSchema {
fields: vec![field.clone()],
metadata: Default::default(),
};
let mut rows_filled = 0u64;
let mut replacements = Vec::new();
for fragment in dataset.get_fragments() {
let gained = count_fragment_gains(&dataset, &fragment, &bound, column).await?;
if gained == 0 {
continue;
}
rows_filled += gained;
let values = fill_stream(&dataset, &fragment, bound.clone(), column).await?;
replacements.push(fragment.write_column(values, &column_schema).await?);
}
if replacements.is_empty() {
return Ok(RefreshColumnResult {
rows_filled: 0,
version: dataset.version().version,
});
}
let read_version = dataset.version().version;
// The dataset's own session, so registrations and caches survive the
// commit being installed on the handle.
let session = dataset.session();
let new_dataset = Dataset::commit(
WriteDestination::Dataset(dataset.clone()),
Operation::DataReplacement { replacements },
Some(read_version),
None,
None,
session,
false,
)
.await?;
let version = new_dataset.version().version;
table.dataset.update(new_dataset);
Ok(RefreshColumnResult {
rows_filled,
version,
})
}
/// Run the refresh as a [`Job`] in this process.
pub(crate) async fn execute_refresh_column_async(table: &NativeTable, column: &str) -> Result<Job> {
// Validate before spawning so bad input is reported by this call rather
// than only by the job.
table.dataset.ensure_mutable()?;
ensure_no_lsm_write_spec(table).await?;
let dataset = table.dataset.get().await?;
declared_expression(&dataset, column)?;
drop(dataset);
let table = table.clone();
let column = column.to_string();
Ok(Job::spawned(tokio::spawn(async move {
execute_refresh_column(&table, &column).await?;
table.bump_freshness();
Ok(())
})))
}
/// Refuse to refresh under an LSM write spec.
///
/// Refresh enumerates base fragments, and a write spec keeps visible rows in
/// un-compacted MemWAL tiers it cannot reach -- success would silently omit
/// readable rows.
async fn ensure_no_lsm_write_spec(table: &NativeTable) -> Result<()> {
// The catch-up flag outlives unset and marks retained SSTable rows.
let catchup = table.dataset.get().await?.manifest().reader_feature_flags
& lance_table::feature_flags::FLAG_MEM_WAL_INDEX_CATCHUP
!= 0;
if catchup || table.get_lsm_write_spec().await?.is_some() {
return Err(Error::NotSupported {
message: "refresh_column is not supported on a table with an LSM write \
spec: rows in un-compacted tiers are invisible to refresh"
.into(),
});
}
Ok(())
}
/// The SQL expression `column` is declared with.
fn declared_expression(dataset: &Dataset, column: &str) -> Result<String> {
let schema = ArrowSchema::from(dataset.schema());
let field = schema
.field_with_name(column)
.map_err(|_| Error::ColumnNotFound {
name: column.to_string(),
})?;
let declaration =
computed_column_from_field(field).ok_or_else(|| Error::NotAComputedColumn {
name: column.to_string(),
})?;
match declaration.kind {
ComputedColumnKind::Sql { expression } => Ok(expression),
ComputedColumnKind::Unrecognized { kind } => Err(Error::NotSupported {
message: format!(
"computed column '{column}' is defined by '{kind}', which this version of \
lancedb cannot evaluate"
),
}),
}
}
/// Quote `name` as a lance SQL identifier.
///
/// Lance's dialect delimits with backticks, so a double-quoted name would
/// parse as a string literal rather than a column.
fn quote_identifier(name: &str) -> String {
format!("`{}`", name.replace('`', "``"))
}
/// Assemble the batch evaluation runs against: the bound roots, in read-schema
/// order. Built by name so scan-side column order never matters.
fn evaluation_batch(
batch: &RecordBatch,
bound: &BoundExpression,
mask_out: Option<&BooleanArray>,
) -> lance_core::Result<RecordBatch> {
let mut columns = Vec::with_capacity(bound.roots.len());
for name in &bound.roots {
let column = batch.column_by_name(name).ok_or_else(|| {
lance_core::Error::invalid_input(format!(
"refreshing a computed column read no {name} column"
))
})?;
// Rows outside the mask must not reach the expression: a value in a
// deleted or already-filled row can be one it would choke on.
columns.push(match mask_out {
Some(mask) => arrow::compute::nullif(column, mask)?,
None => column.clone(),
});
}
Ok(RecordBatch::try_new_with_options(
bound.read_schema.clone(),
columns,
&RecordBatchOptions::new().with_row_count(Some(batch.num_rows())),
)?)
}
/// Evaluate the expression over `batch`, materializing a constant result to
/// the batch's length.
fn evaluate(bound: &BoundExpression, batch: &RecordBatch) -> lance_core::Result<ArrayRef> {
let value = bound
.physical
.evaluate(batch)
.map_err(lance_core::Error::from)?;
match value {
ColumnarValue::Array(array) => Ok(array),
scalar => scalar
.into_array(batch.num_rows())
.map_err(lance_core::Error::from),
}
}
/// How many rows of one fragment would gain a value.
///
/// Scans only the unfilled live rows -- deleted rows never reach the
/// expression here, the filter having already excluded them -- and counts the
/// non-null results. Exact, so it is both the staging decision and the
/// fragment's contribution to `rows_filled`.
async fn count_fragment_gains(
dataset: &Dataset,
fragment: &FileFragment,
bound: &BoundExpression,
column: &str,
) -> Result<u64> {
let mut scanner = dataset.scan();
scanner
.with_fragments(vec![fragment.metadata().clone()])
.with_row_id()
.filter(&format!("{} IS NULL", quote_identifier(column)))?
.project(&bound.roots)?;
let mut gained = 0u64;
let mut batches = scanner.try_into_stream().await?;
while let Some(batch) = batches.try_next().await? {
let evaluated = evaluate(bound, &evaluation_batch(&batch, bound, None)?)?;
gained += (batch.num_rows() - evaluated.null_count()) as u64;
}
Ok(gained)
}
/// Stream one fragment's column in physical order, filling the unfilled live
/// rows and keeping every other value.
///
/// Deleted rows are carried through so the values line up positionally with
/// the fragment's data files; they are never read back, but the column file
/// has to cover them.
async fn fill_stream(
dataset: &Dataset,
fragment: &FileFragment,
bound: Arc<BoundExpression>,
column: &str,
) -> Result<impl Stream<Item = lance_core::Result<RecordBatch>> + Send + use<>> {
let mut projection: Vec<String> = bound.roots.clone();
projection.push(column.to_string());
let mut scanner = dataset.scan();
scanner
.with_fragments(vec![fragment.metadata().clone()])
.with_row_id()
.include_deleted_rows()
.project(&projection)?;
let projected = Arc::new(ArrowSchema::new(vec![
ArrowSchema::from(dataset.schema())
.field_with_name(column)
.map_err(|_| Error::ColumnNotFound {
name: column.to_string(),
})?
.clone(),
]));
let column = column.to_string();
let batches = scanner.try_into_stream().await?;
Ok(batches.map(move |batch| {
let batch = batch?;
let missing = |name: &str| {
lance_core::Error::invalid_input(format!(
"refreshing a computed column read no {name} column"
))
};
let existing = batch
.column_by_name(&column)
.ok_or_else(|| missing(&column))?;
let row_ids = batch
.column_by_name(ROW_ID)
.ok_or_else(|| missing(ROW_ID))?;
// Only an unfilled live row gains a value; a deleted row has a null
// row id and keeps its (null) slot.
let unfilled = arrow::compute::is_null(existing.as_ref())?;
let live = arrow::compute::is_not_null(row_ids.as_ref())?;
let fill = arrow::compute::and(&unfilled, &live)?;
let keep = arrow::compute::not(&fill)?;
let computed = evaluate(&bound, &evaluation_batch(&batch, &bound, Some(&keep))?)?;
let merged = arrow_select::zip::zip(&fill, &computed, existing)?;
Ok(RecordBatch::try_new(projected.clone(), vec![merged])?)
}))
}
#[cfg(test)]
mod tests {
use std::sync::Arc;
use arrow_array::{Int32Array, record_batch};
use futures::TryStreamExt;
use crate::connect;
use crate::query::{ExecutableQuery, QueryBase, Select};
use crate::{Error, Result, Table};
async fn table_with(name: &str, values: Vec<i32>) -> Table {
let conn = connect("memory://").execute().await.unwrap();
let batch = record_batch!(("x", Int32, values)).unwrap();
conn.create_table(name, batch).execute().await.unwrap()
}
async fn declare_doubled(table: &Table) -> Result<u64> {
Ok(table
.add_columns()
.computed("doubled", "x * 2")
.execute()
.await?
.version)
}
async fn read(table: &Table, column: &str) -> Vec<Option<i32>> {
let batches = table
.query()
.select(Select::columns(&[column]))
.execute()
.await
.unwrap()
.try_collect::<Vec<_>>()
.await
.unwrap();
let mut values: Vec<Option<i32>> = batches
.iter()
.flat_map(|batch| {
batch[column]
.as_any()
.downcast_ref::<Int32Array>()
.unwrap()
.iter()
.collect::<Vec<_>>()
})
.collect();
values.sort();
values
}
async fn append(table: &Table, values: Vec<i32>) {
let batch = record_batch!(("x", Int32, values)).unwrap();
table.add(batch).execute().await.unwrap();
}
#[tokio::test]
async fn test_refresh_fills_a_declared_column() {
let table = table_with("refresh_fills", vec![1, 2, 3]).await;
let declared = declare_doubled(&table).await.unwrap();
assert_eq!(read(&table, "doubled").await, vec![None, None, None]);
let result = table.refresh_column("doubled").await.unwrap();
assert!(result.version > declared);
assert_eq!(result.rows_filled, 3);
assert_eq!(
read(&table, "doubled").await,
vec![Some(2), Some(4), Some(6)]
);
}
/// Values written after the last refresh must be reachable by another one.
#[tokio::test]
async fn test_refresh_fills_rows_appended_since_the_last_refresh() {
let table = table_with("refresh_appended", vec![1, 2]).await;
declare_doubled(&table).await.unwrap();
table.refresh_column("doubled").await.unwrap();
append(&table, vec![5, 6]).await;
assert_eq!(
read(&table, "doubled").await,
vec![None, None, Some(2), Some(4)]
);
let result = table.refresh_column("doubled").await.unwrap();
assert_eq!(result.rows_filled, 2);
assert_eq!(
read(&table, "doubled").await,
vec![Some(2), Some(4), Some(10), Some(12)]
);
}
#[tokio::test]
async fn test_refresh_with_nothing_to_fill() {
let table = table_with("refresh_noop", vec![1, 2, 3]).await;
declare_doubled(&table).await.unwrap();
table.refresh_column("doubled").await.unwrap();
let again = table.refresh_column("doubled").await.unwrap();
assert_eq!(again.rows_filled, 0);
assert_eq!(
read(&table, "doubled").await,
vec![Some(2), Some(4), Some(6)]
);
}
/// A row is filled only by gaining a value, so an expression yielding null
/// settles at once instead of re-selecting the same rows forever. Nothing
/// is staged, so the version does not move either.
#[tokio::test]
async fn test_refresh_converges_on_a_null_result() {
let table = table_with("refresh_null_result", vec![1, 2, 3]).await;
let declared = table
.add_columns()
.computed("maybe", "nullif(x, x)")
.execute()
.await
.unwrap()
.version;
let first = table.refresh_column("maybe").await.unwrap();
assert_eq!(first.rows_filled, 0);
assert_eq!(first.version, declared);
assert_eq!(read(&table, "maybe").await, vec![None, None, None]);
let again = table.refresh_column("maybe").await.unwrap();
assert_eq!(again.rows_filled, 0);
assert_eq!(again.version, declared);
}
/// The contract's boundary: a filled fragment is not revisited, so
/// mutating an input leaves the value computed at fill time.
#[tokio::test]
async fn test_refresh_does_not_observe_input_mutation() {
let table = table_with("refresh_mutation", vec![1]).await;
declare_doubled(&table).await.unwrap();
table.refresh_column("doubled").await.unwrap();
assert_eq!(read(&table, "doubled").await, vec![Some(2)]);
table.update().column("x", "3").execute().await.unwrap();
let again = table.refresh_column("doubled").await.unwrap();
assert_eq!(again.rows_filled, 0);
assert_eq!(read(&table, "doubled").await, vec![Some(2)]);
}
/// A row rewrite before the first refresh materializes the declared
/// column as null behind a covering data file. Those rows are still
/// unfilled and a later refresh has to reach them.
#[tokio::test]
async fn test_update_before_the_first_refresh() {
let table = table_with("refresh_update_first", vec![1]).await;
declare_doubled(&table).await.unwrap();
table.update().column("x", "3").execute().await.unwrap();
let result = table.refresh_column("doubled").await.unwrap();
assert_eq!(result.rows_filled, 1);
assert_eq!(read(&table, "doubled").await, vec![Some(6)]);
}
/// The contract holds row by row, not fragment by fragment: revisiting a
/// fragment to fill one row must not recompute a filled row sitting beside
/// it, even where the input behind it has since changed.
#[tokio::test]
async fn test_refresh_does_not_recompute_a_filled_row_beside_an_unfilled_one() {
let table = table_with("refresh_mixed", vec![1, 2]).await;
declare_doubled(&table).await.unwrap();
table.refresh_column("doubled").await.unwrap();
append(&table, vec![5]).await;
table
.update()
.column("x", "100")
.only_if("x = 1")
.execute()
.await
.unwrap();
table
.optimize(crate::table::OptimizeAction::Compact {
options: crate::table::CompactionOptions::default(),
remap_options: None,
})
.await
.unwrap();
let result = table.refresh_column("doubled").await.unwrap();
assert_eq!(result.rows_filled, 1);
// 2 is the mutated row keeping the value it was filled with, not 200.
assert_eq!(
read(&table, "doubled").await,
vec![Some(2), Some(4), Some(10)]
);
}
/// Filling a fragment must not disturb the values it already holds, which
/// is what makes a compaction-mixed fragment safe to revisit.
#[tokio::test]
async fn test_refresh_preserves_already_filled_rows() {
let table = table_with("refresh_preserves", vec![1, 2]).await;
declare_doubled(&table).await.unwrap();
table.refresh_column("doubled").await.unwrap();
append(&table, vec![5]).await;
table
.optimize(crate::table::OptimizeAction::Compact {
options: crate::table::CompactionOptions::default(),
remap_options: None,
})
.await
.unwrap();
let result = table.refresh_column("doubled").await.unwrap();
assert_eq!(result.rows_filled, 1);
assert_eq!(
read(&table, "doubled").await,
vec![Some(2), Some(4), Some(10)]
);
}
#[tokio::test]
async fn test_refresh_leaves_deleted_rows_alone() {
let table = table_with("refresh_deleted", vec![1, 2, 3, 4]).await;
declare_doubled(&table).await.unwrap();
table.delete("x = 2").await.unwrap();
let result = table.refresh_column("doubled").await.unwrap();
assert_eq!(result.rows_filled, 3);
assert_eq!(
read(&table, "doubled").await,
vec![Some(2), Some(6), Some(8)]
);
}
#[tokio::test]
async fn test_refresh_a_constant_expression() {
let table = table_with("refresh_constant", vec![1, 2, 3]).await;
table
.add_columns()
.computed("answer", "42")
.execute()
.await
.unwrap();
let result = table.refresh_column("answer").await.unwrap();
assert_eq!(result.rows_filled, 3);
}
/// A name needing quotes reaches the evaluator intact: it is carried as a
/// projection alias, never spliced into SQL text.
#[tokio::test]
async fn test_refresh_a_column_whose_name_needs_quoting() {
let table = table_with("refresh_quoted", vec![1, 2, 3]).await;
table
.add_columns()
.computed("double value", "x * 2")
.execute()
.await
.unwrap();
let result = table.refresh_column("double value").await.unwrap();
assert_eq!(result.rows_filled, 3);
assert_eq!(
read(&table, "double value").await,
vec![Some(2), Some(4), Some(6)]
);
}
/// A fragment spanning several scan batches exercises the streamed fill:
/// the probe buffers only until the first gained value and the rest flows
/// through write_column a batch at a time.
#[tokio::test]
async fn test_refresh_streams_a_multi_batch_fragment() {
let values: Vec<i32> = (0..20_000).collect();
let table = table_with("refresh_multi_batch", values.clone()).await;
declare_doubled(&table).await.unwrap();
let result = table.refresh_column("doubled").await.unwrap();
assert_eq!(result.rows_filled, 20_000);
let read_back = read(&table, "doubled").await;
assert_eq!(read_back.len(), 20_000);
let mut expected: Vec<Option<i32>> = values.iter().map(|v| Some(v * 2)).collect();
expected.sort();
assert_eq!(read_back, expected);
}
/// The gate's reproducer: the commit must reuse the configured session,
/// or registrations and caches vanish from the handle after a refresh.
#[tokio::test]
async fn test_refresh_preserves_the_configured_session() {
let session = Arc::new(lance::session::Session::default());
let conn = crate::connect("memory://")
.session(session.clone())
.execute()
.await
.unwrap();
let batch = record_batch!(("x", Int32, [1, 2])).unwrap();
let table = conn
.create_table("session_kept", batch)
.execute()
.await
.unwrap();
declare_doubled(&table).await.unwrap();
table.refresh_column("doubled").await.unwrap();
let dataset = table.as_native().unwrap().dataset.get().await.unwrap();
assert!(Arc::ptr_eq(&dataset.session(), &session));
}
/// The async form's job settles with the fill visible, like
/// create_index's execute_async.
#[tokio::test]
async fn test_refresh_async_job_waits_for_the_fill() {
let table = table_with("refresh_async", vec![1, 2, 3]).await;
declare_doubled(&table).await.unwrap();
let job = table.refresh_column_async("doubled").await.unwrap();
assert!(job.id().is_none(), "in-process jobs have no server id");
job.wait().await.unwrap();
assert_eq!(job.status().await.unwrap(), "finished");
assert_eq!(
read(&table, "doubled").await,
vec![Some(2), Some(4), Some(6)]
);
}
/// Bad input is reported by the call, not by the job.
#[tokio::test]
async fn test_refresh_async_rejects_bad_input_before_spawning() {
let table = table_with("refresh_async_bad", vec![1, 2, 3]).await;
let err = table.refresh_column_async("x").await.unwrap_err();
assert!(matches!(err, Error::NotAComputedColumn { name } if name == "x"));
let err = table.refresh_column_async("nope").await.unwrap_err();
assert!(matches!(err, Error::ColumnNotFound { name } if name == "nope"));
}
#[tokio::test]
async fn test_refresh_async_job_reports_success_to_every_waiter() {
let table = table_with("refresh_async_waiters", vec![1, 2]).await;
declare_doubled(&table).await.unwrap();
let job = table.refresh_column_async("doubled").await.unwrap();
job.wait().await.unwrap();
// A second wait after completion observes the same outcome.
job.wait().await.unwrap();
assert_eq!(job.status().await.unwrap(), "finished");
}
#[tokio::test]
async fn test_refresh_rejects_a_plain_column() {
let table = table_with("refresh_plain", vec![1, 2, 3]).await;
let err = table.refresh_column("x").await.unwrap_err();
assert!(matches!(err, Error::NotAComputedColumn { name } if name == "x"));
}
#[tokio::test]
async fn test_refresh_rejects_an_unknown_column() {
let table = table_with("refresh_missing", vec![1, 2, 3]).await;
let err = table.refresh_column("nope").await.unwrap_err();
assert!(matches!(err, Error::ColumnNotFound { name } if name == "nope"));
}
/// The gate's reproducer: a poison value in a deleted row must not
/// abort filling the live rows, since nobody can read it.
#[tokio::test]
async fn test_a_deleted_rows_value_is_never_evaluated() {
let table = table_with("refresh_deleted_poison", vec![1, 0]).await;
table
.add_columns()
.computed("quotient", "10 / x")
.execute()
.await
.unwrap();
table.delete("x = 0").await.unwrap();
let result = table.refresh_column("quotient").await.unwrap();
assert_eq!(result.rows_filled, 1);
assert_eq!(read(&table, "quotient").await, vec![Some(10)]);
}
/// The gate's reproducer: an already-filled row's value must not be
/// re-evaluated either -- its input may have mutated into one the
/// expression chokes on.
#[tokio::test]
async fn test_a_filled_rows_value_is_never_evaluated() {
let table = table_with("refresh_filled_poison", vec![1, 2]).await;
table
.add_columns()
.computed("quotient", "10 / x")
.execute()
.await
.unwrap();
table.refresh_column("quotient").await.unwrap();
table
.update()
.column("x", "0")
.only_if("x = 1")
.execute()
.await
.unwrap();
append(&table, vec![5]).await;
let result = table.refresh_column("quotient").await.unwrap();
assert_eq!(result.rows_filled, 1);
assert_eq!(
read(&table, "quotient").await,
vec![Some(2), Some(5), Some(10)]
);
}
/// The gate's reproducer: the old internal projection alias is an
/// ordinary column name; a computed column may use it.
#[tokio::test]
async fn test_refresh_a_column_named_like_the_old_alias() {
let table = table_with("refresh_alias_name", vec![1, 2]).await;
table
.add_columns()
.computed("__lancedb_computed", "x * 2")
.execute()
.await
.unwrap();
let result = table.refresh_column("__lancedb_computed").await.unwrap();
assert_eq!(result.rows_filled, 2);
assert_eq!(
read(&table, "__lancedb_computed").await,
vec![Some(2), Some(4)]
);
}
/// The gate's reproducer: a late-gain fragment (filled, then one null row
/// compacted onto the end) fills without the old probe's buffering, which
/// this pins behaviorally; the memory bound is structural -- the fill
/// stream retains no batches at all.
#[tokio::test]
async fn test_refresh_fills_a_late_gain_fragment() {
let values: Vec<i32> = (0..20_000).collect();
let table = table_with("refresh_late_gain", values).await;
declare_doubled(&table).await.unwrap();
table.refresh_column("doubled").await.unwrap();
append(&table, vec![2_000_000]).await;
table
.optimize(crate::table::OptimizeAction::Compact {
options: crate::table::CompactionOptions::default(),
remap_options: None,
})
.await
.unwrap();
let result = table.refresh_column("doubled").await.unwrap();
assert_eq!(result.rows_filled, 1);
let read_back = read(&table, "doubled").await;
assert_eq!(read_back.len(), 20_001);
assert_eq!(read_back.last().unwrap(), &Some(4_000_000));
}
/// The gate's reproducer: a nested input declares, refreshes, and guards
/// its root against invalidating schema changes.
#[tokio::test]
async fn test_a_nested_input_declares_and_refreshes() {
use arrow_array::{Int32Array, StructArray};
use arrow_schema::{DataType, Field, Fields};
let conn = connect("memory://").execute().await.unwrap();
let age = Arc::new(Int32Array::from(vec![30, 40]));
let fields = Fields::from(vec![Field::new("age", DataType::Int32, true)]);
let metadata = StructArray::new(fields.clone(), vec![age as _], None);
let schema = Arc::new(arrow_schema::Schema::new(vec![Field::new(
"metadata",
DataType::Struct(fields),
true,
)]));
let batch =
arrow_array::RecordBatch::try_new(schema, vec![Arc::new(metadata) as _]).unwrap();
let table = conn
.create_table("refresh_nested", batch)
.execute()
.await
.unwrap();
table
.add_columns()
.computed("next_age", "metadata.age + 1")
.execute()
.await
.unwrap();
let declaration =
&crate::table::computed_columns(table.schema().await.unwrap().as_ref())[0];
assert_eq!(declaration.inputs, vec!["metadata.age".to_string()]);
let result = table.refresh_column("next_age").await.unwrap();
assert_eq!(result.rows_filled, 2);
assert_eq!(read(&table, "next_age").await, vec![Some(31), Some(41)]);
// The dotted input guards its root.
let err = table.drop_columns(&["metadata"]).await.unwrap_err();
assert!(
matches!(&err, Error::InvalidInput { message } if message.contains("next_age")),
"{err:?}"
);
// Masking a struct input for a deleted row goes through the same
// nullif path as a primitive; a nested input plus deletions must not
// be the combination that breaks it.
table.delete("next_age = 31").await.unwrap();
append_struct_row(&table, 50).await;
let result = table.refresh_column("next_age").await.unwrap();
assert_eq!(result.rows_filled, 1);
assert_eq!(read(&table, "next_age").await, vec![Some(41), Some(51)]);
}
/// Append one `metadata: {age}` row to the nested-input table.
async fn append_struct_row(table: &Table, age: i32) {
use arrow_array::{Int32Array, StructArray};
use arrow_schema::{DataType, Field, Fields};
let ages = Arc::new(Int32Array::from(vec![age]));
let fields = Fields::from(vec![Field::new("age", DataType::Int32, true)]);
let metadata = StructArray::new(fields.clone(), vec![ages as _], None);
let schema = Arc::new(arrow_schema::Schema::new(vec![Field::new(
"metadata",
DataType::Struct(fields),
true,
)]));
let batch =
arrow_array::RecordBatch::try_new(schema, vec![Arc::new(metadata) as _]).unwrap();
table.add(batch).execute().await.unwrap();
}
/// Both orders of declare+spec are refused at the source (see the
/// schema_evolution tests); refresh's own check covers a dataset another
/// writer left in that state.
#[tokio::test]
async fn test_refresh_refuses_a_foreign_lsm_state() {
use crate::table::LsmWriteSpec;
let tmp_dir = tempfile::tempdir().unwrap();
let conn = connect(tmp_dir.path().to_str().unwrap())
.execute()
.await
.unwrap();
let schema = Arc::new(arrow_schema::Schema::new(vec![arrow_schema::Field::new(
"x",
arrow_schema::DataType::Int32,
false,
)]));
let batch =
arrow_array::RecordBatch::try_new(schema, vec![Arc::new(Int32Array::from(vec![1]))])
.unwrap();
let table = conn.create_table("lsm", batch).execute().await.unwrap();
table.set_unenforced_primary_key(["x"]).await.unwrap();
table
.set_lsm_write_spec(LsmWriteSpec::unsharded())
.await
.unwrap();
super::super::computed_columns::add_foreign_kind(&table, "doubled", "sql").await;
let err = table.refresh_column("doubled").await.unwrap_err();
assert!(
matches!(&err, Error::NotSupported { message } if message.contains("LSM")),
"{err:?}"
);
let err = table.refresh_column_async("doubled").await.unwrap_err();
assert!(matches!(err, Error::NotSupported { .. }));
}
/// After catch-up activation and unset, no spec remains but the catch-up
/// flag still marks retained SSTable rows; refresh refuses on the flag.
#[tokio::test]
async fn test_refresh_refuses_retained_catchup_state() {
use crate::table::LsmWriteSpec;
let tmp_dir = tempfile::tempdir().unwrap();
let conn = connect(tmp_dir.path().to_str().unwrap())
.execute()
.await
.unwrap();
let schema = Arc::new(arrow_schema::Schema::new(vec![arrow_schema::Field::new(
"x",
arrow_schema::DataType::Int32,
false,
)]));
let batch = arrow_array::RecordBatch::try_new(
schema.clone(),
vec![Arc::new(Int32Array::from(vec![1]))],
)
.unwrap();
let table = conn
.create_table("catchup", batch.clone())
.execute()
.await
.unwrap();
table.set_unenforced_primary_key(["x"]).await.unwrap();
table
.set_lsm_write_spec(LsmWriteSpec::unsharded())
.await
.unwrap();
table.require_mem_wal_index_catchup().await.unwrap();
let mut merge = table.merge_insert(&["x"]);
merge
.when_matched_update_all(None)
.when_not_matched_insert_all()
.use_lsm(true);
merge
.execute(Box::new(arrow_array::RecordBatchIterator::new(
vec![Ok(batch)],
schema,
)))
.await
.unwrap();
table.unset_lsm_write_spec().await.unwrap();
super::super::computed_columns::add_foreign_kind(&table, "doubled", "sql").await;
let err = table.refresh_column("doubled").await.unwrap_err();
assert!(
matches!(&err, Error::NotSupported { message } if message.contains("LSM")),
"{err:?}"
);
}
/// A declaration of a kind this version cannot evaluate is refused by
/// name, rather than mistaken for a plain column or fed to the SQL path.
#[tokio::test]
async fn test_refresh_rejects_a_kind_it_cannot_evaluate() {
let table = table_with("refresh_foreign", vec![1, 2, 3]).await;
super::super::computed_columns::add_foreign_kind(&table, "embedding", "udf").await;
let err = table.refresh_column("embedding").await.unwrap_err();
assert!(matches!(err, Error::NotSupported { message } if message.contains("udf")));
}
}
+2 -103
View File
@@ -8,14 +8,12 @@
//! - [`alter_columns`](execute_alter_columns): Rename columns, change types, or modify nullability
//! - [`drop_columns`](execute_drop_columns): Remove columns from the table
use arrow_schema::Schema as ArrowSchema;
use lance::dataset::{ColumnAlteration, NewColumnTransform};
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use super::computed_columns;
use super::{BaseTable, NativeTable};
use crate::{Error, Result};
use super::NativeTable;
use crate::Result;
/// The result of an add columns operation.
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize, Default)]
@@ -100,48 +98,6 @@ pub(crate) async fn execute_add_columns(
table: &NativeTable,
transforms: NewColumnTransform,
read_columns: Option<Vec<String>>,
) -> Result<AddColumnsResult> {
// Declarations are admitted only through [`execute_declare`].
match &transforms {
NewColumnTransform::AllNulls(schema) => {
computed_columns::ensure_no_foreign_declarations(schema.fields())?
}
NewColumnTransform::BatchUDF(udf) => {
computed_columns::ensure_no_foreign_declarations(udf.output_schema.fields())?
}
_ => {}
}
commit_add_columns(table, transforms, read_columns).await
}
/// Declare validated computed columns. The only admission path for
/// declaration metadata.
pub(crate) async fn execute_declare(
table: &NativeTable,
columns: &[(String, String)],
) -> Result<AddColumnsResult> {
// An LSM write spec keeps visible rows in tiers refresh cannot reach;
// checked against latest committed state, not this handle's snapshot.
// The catch-up flag outlives unset and marks retained SSTable rows.
table.checkout_latest().await?;
let catchup = table.dataset.get().await?.manifest().reader_feature_flags
& lance_table::feature_flags::FLAG_MEM_WAL_INDEX_CATCHUP
!= 0;
if catchup || table.get_lsm_write_spec().await?.is_some() {
return Err(Error::NotSupported {
message: "computed columns are not supported on a table with an LSM write \
spec: rows in un-compacted tiers are invisible to refresh"
.into(),
});
}
let transform = computed_columns::declare(table.schema().await?, columns)?;
commit_add_columns(table, transform, None).await
}
pub(crate) async fn commit_add_columns(
table: &NativeTable,
transforms: NewColumnTransform,
read_columns: Option<Vec<String>>,
) -> Result<AddColumnsResult> {
table.dataset.ensure_mutable()?;
let mut dataset = (*table.dataset.get().await?).clone();
@@ -160,21 +116,6 @@ pub(crate) async fn execute_alter_columns(
) -> Result<AlterColumnsResult> {
table.dataset.ensure_mutable()?;
let mut dataset = (*table.dataset.get().await?).clone();
// Nullability is not part of what an expression resolves against, so only
// a rename or a retype can invalidate a binding.
let schema = std::sync::Arc::new(ArrowSchema::from(dataset.schema()));
let rebinding = alterations
.iter()
.filter(|alteration| alteration.rename.is_some() || alteration.data_type.is_some())
.map(|alteration| alteration.path.as_str())
.collect::<Vec<_>>();
computed_columns::ensure_not_an_input(&schema, &rebinding)?;
let retyped = alterations
.iter()
.filter(|alteration| alteration.data_type.is_some())
.map(|alteration| alteration.path.as_str())
.collect::<Vec<_>>();
computed_columns::ensure_not_retyped(schema.as_ref(), &retyped)?;
dataset.alter_columns(alterations).await?;
let version = dataset.version().version;
table.dataset.update(dataset);
@@ -190,10 +131,6 @@ pub(crate) async fn execute_drop_columns(
) -> Result<DropColumnsResult> {
table.dataset.ensure_mutable()?;
let mut dataset = (*table.dataset.get().await?).clone();
computed_columns::ensure_not_an_input(
&std::sync::Arc::new(ArrowSchema::from(dataset.schema())),
columns,
)?;
dataset.drop_columns(columns).await?;
let version = dataset.version().version;
table.dataset.update(dataset);
@@ -210,44 +147,6 @@ pub(crate) async fn execute_update_field_metadata(
table.dataset.ensure_mutable()?;
let mut dataset = (*table.dataset.get().await?).clone();
// A declaration is validated as a whole at declare time; editing its keys
// here would bypass that, fabricate one on a plain column, or move a
// binding out from under a refresh. A replace on a declared column would
// silently erase it.
let schema = ArrowSchema::from(dataset.schema());
let declared: Vec<String> = computed_columns::computed_columns(&schema)
.into_iter()
.map(|declaration| declaration.name)
.collect();
for update in updates {
if update
.metadata
.keys()
.any(|key| computed_columns::is_declaration_key(key))
{
return Err(Error::InvalidInput {
message: format!(
"metadata keys of a computed-column declaration cannot be edited \
(path '{}'); drop the column and declare it again",
update.path
),
});
}
if update.replace
&& declared
.iter()
.any(|name| name == computed_columns::root(&update.path))
{
return Err(Error::InvalidInput {
message: format!(
"replacing all metadata of computed column '{}' would erase its \
declaration; drop the column and declare it again",
update.path
),
});
}
}
let mut builder = dataset.update_field_metadata();
for update in updates {
let entries = update.metadata.iter().map(|(k, v)| (k.clone(), v.clone()));
-4
View File
@@ -82,10 +82,6 @@ pub(crate) async fn execute_update(
// 1. Snapshot the current dataset
let dataset = table.dataset.get().await?;
super::computed_columns::ensure_not_written(
&arrow_schema::Schema::from(dataset.schema()),
update.columns.iter().map(|(name, _)| name.as_str()),
)?;
// 2. Initialize the Lance Core builder
let mut builder = LanceUpdateBuilder::new(dataset);
+13 -18
View File
@@ -10,7 +10,7 @@ use arrow_array::{
use arrow_schema::{DataType, Field, Fields, Schema};
use futures::TryStreamExt;
use lance::Dataset;
use lance_file::version::{ConcreteFileVersion, LanceFileVersion};
use lance_file::version::LanceFileVersion;
use lancedb::{
Connection, Error, Result, Table,
blob::{BlobRangeRequest, blob},
@@ -61,7 +61,7 @@ async fn create_inline_blob_table(
Ok(table)
}
async fn storage_format_version(table: &Table) -> ConcreteFileVersion {
async fn storage_format_version(table: &Table) -> LanceFileVersion {
table
.as_native()
.unwrap()
@@ -69,14 +69,9 @@ async fn storage_format_version(table: &Table) -> ConcreteFileVersion {
.await
.unwrap()
.data_storage_format
.lance_file_format()
}
fn supports_blob_v2(version: ConcreteFileVersion) -> bool {
matches!(
version,
ConcreteFileVersion::V2_2 | ConcreteFileVersion::V2_3
)
.lance_file_version()
.unwrap()
.resolve()
}
async fn uses_stable_row_ids(table: &Table) -> bool {
@@ -117,7 +112,7 @@ async fn declaring_blob_column_bumps_format_and_enables_stable_row_ids() -> Resu
.execute()
.await?;
assert!(supports_blob_v2(storage_format_version(&table).await));
assert!(storage_format_version(&table).await >= LanceFileVersion::V2_2);
assert!(uses_stable_row_ids(&table).await);
Ok(())
}
@@ -132,7 +127,7 @@ async fn explicit_stable_row_id_setting_wins_over_blob_default() -> Result<()> {
.execute()
.await?;
assert!(supports_blob_v2(storage_format_version(&table).await));
assert!(storage_format_version(&table).await >= LanceFileVersion::V2_2);
assert!(!uses_stable_row_ids(&table).await);
Ok(())
}
@@ -144,7 +139,7 @@ async fn non_blob_table_keeps_default_format_and_row_id_setting() -> Result<()>
let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int64, false)]));
let table = db.create_empty_table("t", schema).execute().await?;
assert!(!supports_blob_v2(storage_format_version(&table).await));
assert!(storage_format_version(&table).await < LanceFileVersion::V2_2);
assert!(!uses_stable_row_ids(&table).await);
Ok(())
}
@@ -176,7 +171,7 @@ async fn creating_with_blob_data_bumps_format() -> Result<()> {
.unwrap();
let table = db.create_table("t", batch).execute().await?;
assert!(supports_blob_v2(storage_format_version(&table).await));
assert!(storage_format_version(&table).await >= LanceFileVersion::V2_2);
assert!(uses_stable_row_ids(&table).await);
assert_eq!(table.count_rows(None).await?, 1);
Ok(())
@@ -286,7 +281,7 @@ async fn connection_level_stable_row_id_setting_wins_over_blob_default() -> Resu
.execute()
.await?;
assert!(supports_blob_v2(storage_format_version(&table).await));
assert!(storage_format_version(&table).await >= LanceFileVersion::V2_2);
assert!(!uses_stable_row_ids(&table).await);
Ok(())
}
@@ -302,7 +297,7 @@ async fn namespace_create_applies_blob_defaults() -> Result<()> {
.execute()
.await?;
assert!(supports_blob_v2(storage_format_version(&table).await));
assert!(storage_format_version(&table).await >= LanceFileVersion::V2_2);
assert!(uses_stable_row_ids(&table).await);
Ok(())
}
@@ -479,7 +474,7 @@ async fn fetch_blobs_round_trips_nested_blob_column() -> Result<()> {
let batch = RecordBatch::try_new(schema, vec![Arc::new(info_array) as ArrayRef]).unwrap();
let table = db.create_table("t", batch).execute().await?;
assert!(supports_blob_v2(storage_format_version(&table).await));
assert!(storage_format_version(&table).await >= LanceFileVersion::V2_2);
assert!(uses_stable_row_ids(&table).await);
let ids = collect_row_ids(&table).await?;
@@ -1310,7 +1305,7 @@ async fn optimize_preserves_blob_v2_null_and_empty_distinction() -> Result<()> {
.await?;
table.add(null_empty_input_batch()).execute().await?;
assert!(
supports_blob_v2(storage_format_version(&table).await),
storage_format_version(&table).await >= LanceFileVersion::V2_2,
"blob v2 columns require storage >= 2.2"
);