mirror of
https://github.com/lancedb/lancedb.git
synced 2026-11-14 14:46:53 +00:00
Daniel RammerandClaude Opus 5
106f9ddb31
`checkpoint_lsm` looped flush → compact and read `generations_remaining` out of each compact response. Two problems. That count is stale the moment a concurrent write lands, so on a table taking writes "L0 is empty" never becomes true and the loop only ever exited on its deadline. And carrying it back at all meant eight public types describing work already visible in `get_lsm_stats`. It now fixes a target watermark — the newest generation per bucket, read after the opening flush — then triggers compaction and polls until no generation at or below that target remains. Generations created *while* it runs are deliberately not waited on, which is what makes it terminate under sustained writes and is why the deadline could go. * Deleted: `CheckpointOptions`, `CheckpointReport`, `CheckpointStopReason`, `CompactOptions`, `CompactReport`, `CompactBucketReport`, `FlushReport`, `FlushBucketReport`. `checkpoint_lsm`, `flush_lsm` and `compact_lsm` all return `()`; observability is `get_lsm_stats` before and after. * Progress, not time, is the bound: `MAX_IDLE_POLLS` consecutive polls with neither a drop in outstanding generations nor a running pass is an error. A saturated pool or a fenced writer fails loudly instead of spinning; a slow table waits, since a running pass resets the counter. Wrap the call in `tokio::time::timeout` for a wall-clock bound. * The metric counts generations, not buckets. One pass drains a bounded prefix, so a per-bucket boolean reads as "no progress" for every pass but the last — a bucket needing more passes than the bound would fail a checkpoint that was working. * `BucketStats` gains `compacting`, and the loop never triggers against a bucket already compacting: it would only collect 429s from the latch doing the work. * `get_lsm_stats` takes `include_generation_rows` again, off by default. Each count opens an uncached Lance dataset and this loop polls the route. * `send_lsm_route` splits from its JSON decode — flush and compact answer 202 with no body, and decoding an empty string is a parse error. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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
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