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## Bug Fix ### What is the bug? Namespace-backed `LanceTable.to_arrow()` full-table reads bypassed the existing `QueryTable` server-side query path and called the lower-level table `to_arrow()` implementation directly. In Geneva/Sophon this could fail while parsing the Arrow IPC response for `hist.get_table().to_arrow()` / `to_pandas()`, even though `hist.get_table().search().to_arrow()` worked. ### What issues or incorrect behavior does the bug cause? Full-table reads on namespace-backed tables with `QueryTable` pushdown could fail with Arrow IPC parse errors, while query/search reads on the same table succeeded. Since `to_pandas()` delegates through `to_arrow()` for non-blob/native cases, pandas export was affected too. ### How does this PR fix the problem? When `QueryTable` pushdown is enabled, sync and async table `to_arrow()` now construct a plain no-filter, no-limit, all-columns query and execute it through the table-level `_execute_query()` path. `AsyncTable` now preserves namespace context from async namespace connections so async full reads can make the same pushdown decision. Non-namespace tables and namespace tables without `QueryTable` pushdown keep their existing behavior. ### Tests - `uv run --extra tests --extra dev --no-sync ruff check python/lancedb/table.py python/lancedb/namespace.py python/tests/test_namespace.py` - `uv run --extra tests --extra dev --no-sync ruff format python/lancedb/table.py python/lancedb/namespace.py python/tests/test_namespace.py` - `uv run --extra tests --extra dev --no-sync pytest python/tests/test_namespace.py::TestPushdownOperations::test_lance_table_to_arrow_uses_query_pushdown python/tests/test_namespace.py::TestAsyncPushdownOperations::test_async_table_to_arrow_uses_query_pushdown python/tests/test_namespace.py::test_local_table_to_arrow_and_to_pandas_are_unchanged -q` - `uv run --extra tests --extra dev --no-sync pytest python/tests/test_namespace.py -q`
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
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⭐ 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
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