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)
A broad documentation pass across the areas LanceDB Enterprise and
Embedded
diverge on most:
**Data Curation** -- GPU Function execution, Slurm scheduling (and what
Slurm is, for readers new to it), blob late materialization as its own
page, joins, aggregation/profiling, sampling, near-duplicate detection,
chunking, distributed shuffle, and IVF-partition clustering.
**Feature Engineering** -- computed columns and materialized views,
restructured to lead with the Function-based path and show the SQL form
side by side with Python throughout; a single Auto Refresh page instead
of
duplicating scheduling details on every refresh page; adaptive
execution;
checkpointing; GPU and Slurm placement for refresh workers; a Training
Cache page for the PyTorch data loader's automatic cache benefit.
**Security & Governance** -- an Audit Log reference (schema, access,
grants), Secrets promoted to an ordinary catalog object with their own
SQL
DDL and a vending/rotation guide, and privilege-table fixes verified
against the authorization source.
**Deployment & Maintenance** -- Horizontal Scaling and OpenTelemetry
moved
into a real Deployment area; Automated Cleanup folded into Intelligent
Auto-Maintenance (every other maintenance decision already lived there);
RTE Compaction and Advanced Conflict Resolution documented in depth.
**Landing page** -- the Enterprise feature comparison table reorganized
(several redundant or stale rows removed, several new areas added), and
the
"why Enterprise" bullets replaced with ones tied to a concrete page
(Performance, Scale, Fault tolerance, Multicloud deployment, Simplify
operations) instead of vague promises.
Plus a full pass addressing lancedb-gatekeeper's review: a real
test-safety
bug (a quickstart test could silently overwrite and delete a
deployment's
own `frames` table), a fabricated SQL statement with no backing
implementation, an actual dedup-guarantee bug in `take_row_ids`, and
dozens
of documentation-accuracy fixes verified against source rather than
taken
on faith -- each either fixed, or left with an explicit note on why it
needs a feature or deployment owner's sign-off instead of being guessed
at.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
https://claude.ai/code/session_018PXMCbRH6i5w47TsjeEUMT
---------
Co-authored-by: Claude Sonnet 5 <noreply@anthropic.com>
## Summary
- Complete the SQL reference: `ATTACH DATABASE`, the `CHANGES` clause,
and
`dedupe()`/`duplicate_pairs()` (verified against current sophon source;
these were recently renamed from
`vector_dedup`/`vector_duplicate_pairs`).
Fix the blob-column default-projection claim and add the previously
undocumented `blob_descriptor()`.
- Enrich the gated Functions draft (still `.mintignore`'d, pre-release):
chained Functions over blob outputs, GPU-produced blobs, Secrets,
multi-input/output binding, `code=[module]` packaging.
- Upgrade the materialized-view and computed-column auto-refresh drafts
with
precise, verified catch-up semantics, and add the missing `ALTER
MATERIALIZED VIEW` / `CREATE ... WITH(...)` sections (also gated — the
automatic-refresh scheduler is still dev/staging-only).
- Thread one running example (video frames → GPU extract/caption → dedup
→
auto-refreshing materialized view) through Functions, materialized
views,
and the LeRobotDataset integration guide instead of a separate tutorial.
- Rename "LanceDB OSS"/"OSS" to "LanceDB Embedded"/"Embedded" throughout
(52 files); activate the existing availability-comparison mechanism on
`basics/offerings.mdx` for a full feature-by-feature comparison table.
Jack Ye
