Will JonesandClaude Opus 5 3be313f634 test(node): fix flaky optimize cleanup test (#4217)
Backports the test fix from #4183 (commit `21ecafe9a` on `main`) to
`release/v0.39`.

## Root cause

`when optimizing a dataset > cleanups old versions` took its cutoff with
`new Date()`. A JS `Date` has millisecond precision; Lance stores
version
timestamps with nanosecond precision. If the cutoff landed in the same
millisecond as the preceding commit, truncating to milliseconds put the
cutoff
*before* that commit, so the version was not eligible for pruning and
`stats.prune.oldVersionsRemoved` came back as `1` instead of `2`.

This became possible on this branch with #4160, which changed
`cleanupOlderThan`
to be passed to the native binding as an absolute timestamp. It is
timing- and
machine-dependent, which is why it shows up on the fast Linux runners
and not
locally.

## Fix

Wait for the clock to tick over to the next millisecond before capturing
the
cutoff, so the cutoff is strictly later than every commit the test made.
Same
change that is already on `main`.

## Observed failures

-
https://github.com/lancedb/lancedb/actions/runs/34945208311/job/104323950514
— scheduled NPM Publish on `main` at `ffe94a65a`, before #4183 landed.
- https://github.com/lancedb/lancedb/actions/runs/35257750543 — #4216
(`update-lance-12.0.0-v0.39`), which targets this branch and so does not
have the fix.

## Verification

This is a flake, so there is no deterministic local repro to show
red-then-green.
The change is byte-identical to the one merged in #4183; `main` has had
three
green NPM Publish runs since it landed, and no recurrence of this test
on `main`.

Note: `delete unverified`, immediately below, still uses `new Date()`
for its
cutoff. It asserts `toBeGreaterThan(1)` rather than an exact count, so
it has
one version of slack, but it is the same latent race. Left alone here to
keep
this a faithful backport — happy to harden it on `main` and backport
that too.

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

Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-09-17 15:45:35 -05:00
2026-09-09 15:33:04 +08:00
2023-03-17 18:15:19 -07:00
2025-03-10 09:01:23 -07:00

LanceDB Cloud Public Beta

LanceDB Website Blog Discord Twitter LinkedIn

LanceDB

The Multimodal AI Lakehouse

How to Install ✦ Detailed Documentation ✦ Tutorials and Recipes ✦ Contributors

The ultimate multimodal data platform for AI/ML applications.

LanceDB is designed for fast, scalable, and production-ready vector search. It is built on top of the Lance columnar format. You can store, index, and search over petabytes of multimodal data and vectors with ease. LanceDB is a central location where developers can build, train and analyze their AI workloads.


Demo: Multimodal Search by Keyword, Vector or with SQL

LanceDB Multimodal Search

Star LanceDB to get updates!

⭐ Click here ⭐ to see how fast we're growing!

Key Features:

  • Fast Vector Search: Search billions of vectors in milliseconds with state-of-the-art indexing.
  • Comprehensive Search: Support for vector similarity search, full-text search and SQL.
  • Multimodal Support: Store, query and filter vectors, metadata and multimodal data (text, images, videos, point clouds, and more).
  • Advanced Features: Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure. GPU support in building vector index.

Products:

  • Open Source & Local: 100% open source, runs locally or in your cloud. No vendor lock-in.
  • Cloud and Enterprise: Production-scale vector search with no servers to manage. Complete data sovereignty and security.

Ecosystem:

  • Columnar Storage: Built on the Lance columnar format for efficient storage and analytics.
  • Seamless Integration: Python, Node.js, Rust, and REST APIs for easy integration. Native Python and Javascript/Typescript support.
  • Rich Ecosystem: Integrations with LangChain 🦜️🔗, LlamaIndex 🦙, Apache-Arrow, Pandas, Polars, DuckDB and more on the way.

How to Install:

Follow the Quickstart doc to set up LanceDB locally.

API & SDK: We also support Python, Typescript and Rust SDKs

Interface Documentation
Python SDK https://lancedb.github.io/lancedb/python/python/
Typescript SDK https://lancedb.github.io/lancedb/js/globals/
Rust SDK https://docs.rs/lancedb/latest/lancedb/index.html
REST API https://docs.lancedb.com/api-reference/rest

Join Us and Contribute

We welcome contributions from everyone! Whether you're a developer, researcher, or just someone who wants to help out.

If you have any suggestions or feature requests, please feel free to open an issue on GitHub or discuss it on our Discord server.

Check out the GitHub Issues if you would like to work on the features that are planned for the future. If you have any suggestions or feature requests, please feel free to open an issue on GitHub.

Contributors

Stay in Touch With Us


Website Blog Discord Twitter LinkedIn

S
Description
Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.
Readme Apache-2.0
108 MiB
Languages
Rust 42.4%
Python 25.9%
HTML 22.8%
TypeScript 7.9%
Java 0.7%
Other 0.2%