? from listing-database URIs (#3357)
## Summary
`url::Url::query_pairs_mut()` leaves the URL with `query=Some("")` after
`.clear()` even when the input had no query string. The listing-database
connect path then captured that empty query into
`ListingDatabase::query_string`, and `table_uri()` blindly appended
`?<query>` to every per-table URI — producing URIs like
`s3://bucket/prefix/foo.lance?`.
The trailing `?` is benign for normal table operations, but it breaks
any caller that constructs a sub-path from the table URI. In particular,
MemWAL flushes write to `<table_uri>/_mem_wal/<shard>/<rand>_gen_<n>`,
which `url::Url::parse` then re-parses as `path=<base table>` +
`query=/_mem_wal/...`. `Dataset::write` resolves the base table dataset,
finds it already exists, and fails with `Dataset already exists:
…_gen_1` on the very first MemTable flush (observed deterministically
against S3 across all merge_insert LSM modes; tracked in
[lance-format/lance#6713](https://github.com/lance-format/lance/pull/6715)).
## Fix
Treat `Some("")` query the same as no query when capturing
`query_string`. A real `?foo=bar` query is still propagated unchanged.
Adds a regression test covering both the empty-query and non-empty-query
paths.
## Verification
- `url::Url::parse("s3://bucket/prefix/").query()` → `None`, but after
`query_pairs_mut().clear()` → `Some("")`. Confirmed in a standalone
repro.
- Without this fix, every `table_uri()` for an `s3://`-style connection
ends with `?`, breaking MemWAL and any future sub-path consumer in the
same way.
- New unit test `test_table_uri_url_path_has_no_trailing_question_mark`
exercises both code paths.
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!
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.
