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Expose aggregate CPU, memory, and GPU budgets plus GPU-class placement
on materialized-view refreshes in Python and Rust. Forward options
through SQL and reject invalid or unsupported Embedded requests instead
of silently dropping constraints.
```python
job = view.refresh_async(
cpu_millis=8000,
memory_bytes=16 * 1024**3,
gpu_count=2,
gpu_class="h100",
)
job.wait()
```
```sql
REFRESH MATERIALIZED VIEW curated_training_set
WITH (cpu_millis = 8000, memory_bytes = 17179869184,
gpu_count = 2, gpu_class = 'h100');
```
The same options apply to blocking refreshes, async Python connections,
and the Rust refresh builder. CPU/memory budgets require all three
resource fields; GPU-only caps and class-only placement are also
supported. These are execution-wide caps and require a supporting
Enterprise server with an isolated execution backend. A cap does not
increase refresh parallelism; current MV refreshes use at most one GPU.
Updates API documentation and SQL reference, with Python sync/async and
Rust remote-submission regression coverage. Formatting and Python lint
pass; local builds and tests are intentionally skipped.
The Linux CI build and example steps explicitly select the LanceDB
package, matching the feature-test step. This avoids rebuilding and
retaining a second dependency graph after a workspace-wide build, which
exhausted runner disk space on both this branch and main.
Related: [ENT-3386](https://linear.app/lancedb/issue/ENT-3386)