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Lei XuandClaude Opus 5.5
1772f4ef83
## Problem
`permutation_builder(table).execute()` and `StreamingDataset(table,
...)` (which builds a permutation at construction) panic with
`RustPanic` on any table whose Arrow schema has schema-level metadata:
```python
schema = pa.schema([pa.field("x", pa.int64())], metadata={b"huggingface": b"{}"})
t = lancedb.connect(tmp).create_table("t", pa.table({"x": list(range(100))}, schema=schema))
permutation_builder(t).split_random(fixed=2, seed=1).execute() # RustPanic
```
Every Hugging Face Lance dataset triggers this, e.g.
`hf://datasets/lance-format/lerobot-xvla-soft-fold/data` table `frames`
carries `source-column-name-map`.
## Root cause
`PermutationBuilder::add_config_metadata` replaced the stream schema's
metadata with the permutation config and then called
`batch.with_schema(schema).unwrap()`. The base-table scan's batches
carry the base schema metadata, and `RecordBatch::with_schema` requires
the target to be a superset of the current schema, metadata included. It
returned `SchemaError("target schema is not superset of current schema
...")`, and the `unwrap` turned that into a panic on a tokio worker.
## Fix
- The permutation table deliberately does **not** inherit base-table
schema metadata. That metadata describes columns the permutation table
(`row_id`, `split_id`) does not have, and its keys can collide with
config keys such as `split_names`. A merge would let a base table's
`split_names` leak into, or override, the permutation's split names.
Batches are rebuilt with `RecordBatch::try_new(schema, columns)`.
- Errors are propagated (`map_ok` → `and_then`) instead of `unwrap`.
- The same panic-on-worker pattern in the splitter's streaming closures
(`split.rs`: `try_new`/`filter(...).unwrap()`) now propagates errors
too. Nothing else in `dataloader/` used `with_schema(...).unwrap()`.
## Tests
- Rust: `test_permutation_over_table_with_schema_metadata` in
`builder.rs` builds a random split + shuffled permutation over a table
with `huggingface` and a colliding `split_names` key. It panics with the
original `SchemaError` on the old code and passes now.
- Python: `test_permutation_over_table_with_schema_metadata` in
`test_permutation.py` covers the repro and reads both splits through
`Permutations`/`Permutation.from_tables`.
`test_streaming_dataset_over_table_with_schema_metadata` in
`test_elastic_dataloader.py` covers `StreamingDataset` construction and
iteration.
- `cargo fmt`, `cargo clippy --features remote --tests --examples`, the
dataloader Rust tests (42), `test_permutation.py` (72), and
`test_elastic_dataloader.py` all pass.
`test_torch.py::test_remote_permutation_dataloader_multiprocessing`
fails locally with `take query result did not include ordering column
'__lancedb_take_row_offset'`. It uses `Permutation.identity`, which does
not go through `PermutationBuilder`, so this change does not cause it.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
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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.
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