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Jack YeandClaude Sonnet 5
de95ed3f6d
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>
89 lines
3.1 KiB
Plaintext
89 lines
3.1 KiB
Plaintext
---
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title: "Refresh a materialized view"
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sidebarTitle: "Refresh Materialized View"
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description: "Bring a materialized view up to date after its source data changes."
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icon: arrows-rotate
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keywords: ["materialized view", "refresh", "auto_refresh_enabled", "auto_refresh_interval_seconds"]
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availability:
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embedded: unavailable
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enterprise: available
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---
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Refresh a [materialized view](/feature-engineering/materialized-views) to
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bring its stored rows up to date after the source table changes.
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<Note>
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In SQL this is [`REFRESH MATERIALIZED VIEW`](/sql/dml/refresh-materialized-view).
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</Note>
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## Refresh a view {#refresh}
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<CodeGroup>
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```python Python icon="python"
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view.refresh()
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```
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</CodeGroup>
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In LanceDB Embedded, every refresh rebuilds the view completely from its
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source query -- there is no incremental refresh there. Calling it again
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with no source changes still rebuilds and commits a new table version. In
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LanceDB Enterprise, the server chooses the refresh mode instead; pass
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`full=True` to force a full rebuild there too.
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In LanceDB Embedded, the result reports what the refresh did:
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<CodeGroup>
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```python Python icon="python"
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result = view.refresh()
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result.rows_written # rows in the rebuilt view
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result.source_version # the source table version the view now reflects
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result.version # the view's own new table version
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```
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</CodeGroup>
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LanceDB Enterprise refreshes run through its SQL job adapter, which doesn't
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expose these metrics: `mode`, `rows_written` and `source_version` are all
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`None` on an Enterprise result, even though the refresh itself ran.
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Pass `source_version=N` to refresh against a particular source version
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instead of the latest. This is a LanceDB Embedded capability only --
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LanceDB Enterprise's SQL refresh does not support pinning a source version:
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<CodeGroup>
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```python Python icon="python"
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view.refresh(source_version=12) # LanceDB Embedded only
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```
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</CodeGroup>
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Use `view.table.count_rows()` for the view's row count at any time; on
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LanceDB Embedded it always matches `rows_written` from the most recent
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refresh.
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## Automatic refresh {#auto-refresh}
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A materialized view can refresh itself on a schedule instead of waiting
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for an explicit `refresh()` call. See [Auto Refresh](/enterprise/auto-refresh)
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for enabling it at creation, the SQL and SDK forms for changing the
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setting afterward, and how it differs from a computed column's
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per-output granularity.
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## When a refresh fails {#failures}
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A refresh replaces the view's stored rows in one commit, so a failure leaves
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the view as it was after its last successful refresh. Fix the cause and
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refresh again.
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## Related guides {#next}
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<CardGroup cols={2}>
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<Card title="Create a materialized view" icon="table" href="/feature-engineering/materialized-views">
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Define the query a view stores.
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</Card>
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<Card title="Refresh a computed column" icon="arrows-rotate" href="/feature-engineering/refresh-column">
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The same idea, for a single derived column.
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</Card>
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<Card title="Auto Refresh" icon="clock-rotate-left" href="/enterprise/auto-refresh">
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Refresh on a schedule instead of calling this yourself.
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</Card>
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</CardGroup>
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