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Jack Ye
ddb318567a
## 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.
117 lines
4.3 KiB
Plaintext
117 lines
4.3 KiB
Plaintext
---
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title: "Materialized view"
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sidebarTitle: "Materialized View"
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description: "Create, open, list and drop a table whose contents are defined by a query."
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icon: table
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keywords: ["materialized view", "create_materialized_view", "catalog", "ddl"]
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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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A materialized view is a table whose contents are defined by a query over
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another table. The query is recorded in the view's schema, and a refresh
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brings its stored rows up to date with the source.
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The result is an ordinary table: queryable, indexable, searchable, and present
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in `table_names()`. Nothing about reading it is special.
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This page covers creating and managing one. Keeping it current is
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[Refresh a materialized view](/feature-engineering/refresh-materialized-view).
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<Note>
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In SQL, see [`REFRESH MATERIALIZED VIEW`](/sql/dml/refresh-materialized-view) and [`SHOW MATERIALIZED VIEWS`](/sql/ddl/materialized-view#show).
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</Note>
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## Create a materialized view {#create}
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<CodeGroup>
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```python Python icon="python"
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view = db.create_materialized_view(
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"frames_captioned",
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source="frames",
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select=["frame_id", "video_id", "ts", "caption"],
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where="selected = true",
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)
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```
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```typescript TypeScript icon="square-js"
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const view = await db.createMaterializedView("frames_captioned", "frames", {
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select: ["frame_id", "video_id", "ts", "caption"],
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where: "selected = true",
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});
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```
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</CodeGroup>
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`source` names the table the view reads — here, a `frames` table with a
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`caption` column, filtered to the frames selected for captioning. See
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[Create a materialized view](/feature-engineering/materialized-views#create)
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for the full walkthrough. `select`, `where` and `limit` define the query.
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## Open, list and drop views {#manage}
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| | Python | TypeScript | SQL |
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| --- | --- | --- | --- |
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| create | `create_materialized_view` | `createMaterializedView` | `CREATE MATERIALIZED VIEW` |
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| open | `open_materialized_view` | `openMaterializedView` | -- |
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| list | `list_materialized_views` | `listMaterializedViews` | `SHOW MATERIALIZED VIEWS` |
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| refresh | `refresh` | `refresh` | `REFRESH MATERIALIZED VIEW` |
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| drop | `drop_table` | `dropTable` | `DROP TABLE` |
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<Badge color="red">Enterprise</Badge> Creating, refreshing and dropping a
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materialized view each have an async, job-returning counterpart --
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`create_materialized_view_async`, `view.refresh_async()`,
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`drop_materialized_view_async` -- the same pattern as
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[`refresh_column_async`](/feature-engineering/refresh-column#async): each
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returns a [job](/basics/jobs) you `wait()` on instead of blocking. The async
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counterpart of the example [above](#create):
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<CodeGroup>
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```python Python icon="python"
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from datetime import timedelta
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job = db.create_materialized_view_async(
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"frames_captioned", source="frames",
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select=["frame_id", "video_id", "ts", "caption"], where="selected = true",
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)
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view = job.wait(timeout=timedelta(minutes=15))
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```
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</CodeGroup>
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`create_materialized_view_async` also accepts `auto_refresh_enabled` and
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`auto_refresh_interval_seconds`; see
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[Automatic refresh](/feature-engineering/refresh-materialized-view#auto-refresh).
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<Note>
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On a local database, `list_materialized_views` reads table schemas to find
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views. On Enterprise, it asks the server for the view listing, as
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`SHOW MATERIALIZED VIEWS` does.
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</Note>
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A view is dropped with `drop_table`, because a materialized view **is** a table.
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That also means dropping one removes stored rows, unlike dropping a
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[view](/management/view), which removes only a saved query.
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## Read the view and its definition {#working}
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`view.table` is the underlying table, for querying, indexing, or search.
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`view.definition` contains the query's select list, predicate and limit. Both are properties; on an async view, the definition is read with
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`await view.definition()`.
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## Enterprise compatibility {#deployment}
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Enterprise supports creating and refreshing materialized views on remote
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compute. Use the SDK version supported by your deployment, or the
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[SQL interface](/sql/ddl/materialized-view).
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## Related guides {#next}
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<CardGroup cols={2}>
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<Card title="Refresh a materialized view" icon="arrows-rotate" href="/feature-engineering/refresh-materialized-view">
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How a refresh works, and what it writes.
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</Card>
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<Card title="Views" icon="eye" href="/management/view">
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The non-materialized counterpart, defined in SQL.
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</Card>
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</CardGroup>
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