--- title: "Refresh a materialized view" sidebarTitle: "Materialized View Refresh" description: "A lakehouse object: a table defined by a query over another table, brought up to date by each refresh." icon: table keywords: ["materialized view", "create_materialized_view", "refresh", "full refresh"] availability: oss: available enterprise: varies summary: >- The SDK creates and refreshes a local view in your process. On a deployment, views are off by default, and how they work depends on its version and configuration; see [Against a deployment](#availability). --- import { PyMaterializedViewCreate as MaterializedViewCreate, PyMaterializedViewRefresh as MaterializedViewRefresh, } from '/snippets/materialized_view.mdx'; A materialized view is a lakehouse object: a table whose contents are defined by a query over another table. The query is recorded in the view's schema; creating the view computes its rows, and a refresh brings them up to date. The result is an ordinary table. It can be queried, indexed, and searched, and it appears in `table_names()` — nothing about reading it is special. In SQL this is [`REFRESH MATERIALIZED VIEW`](/sql/refresh#refresh-materialized-view). ## Create and refresh {#create-and-refresh} {MaterializedViewCreate} Creating the view computes its rows, so it is ready to read. Pass `with_no_data=True` to create it empty instead. Later changes to the source reach the view through a refresh: {MaterializedViewRefresh} These results were verified with the development SDK 0.40.0b13, built from lancedb main. The published 0.39.0 differs: the source must be created with stable row ids (the `new_table_enable_stable_row_ids` storage option), `create_materialized_view` creates the view empty and has no `with_no_data`, and `refresh()` still accepts `full`. Its first `refresh()` writes every matching row, two in this example. `select` takes column names, `(alias, expression)` pairs, or a dict of the same. Omitting it selects every source column, expanded against the schema as it was at creation time. `where` filters source rows; `limit` caps the view. ## Local sources no longer need stable row ids {#stable-row-ids} A local refresh does not track which source rows the view came from, so a local view's source does not need stable row ids (`new_table_enable_stable_row_ids`): the example above creates its source with the defaults. Earlier development builds and the published 0.39.0 required them, and an earlier deployment version may still require them; see [Against a deployment](#availability). The source is still checked, when the view is created and on every refresh: one with an LSM write spec, or with retained write-ahead-log rows not yet compacted, is refused. ## Every local refresh rebuilds the view {#incremental} Locally, `refresh()` runs the view's query against the source and replaces everything the view holds with the result, in one commit. It does not reconcile changes: `rows_written` is the size of the whole result — two after adding Bea, not one — and a refresh with nothing new to read still rewrites the view and commits a new table version. `source_version=N` refreshes against that source version instead of the latest, which is how a view reproduces a known point in time. There is no `full` argument; every local refresh is a full one. ## Against a deployment {#availability} Enterprise `create_materialized_view` and `refresh` also work on a `db://` connection. There the SDK sends them to the deployment as SQL -- `CREATE MATERIALIZED VIEW` and `REFRESH MATERIALIZED VIEW` -- and the work runs on the cluster rather than in your process. `with_no_data` and `source_version` are for local views only; the SDK refuses them on a `db://` connection. Materialized views are off by default on a deployment and have to be enabled there. How a deployment handles a view then depends on its LanceDB Enterprise version. Recent versions create and refresh every view as a SQL job: the source does not need stable row ids, [`REFRESH MATERIALIZED VIEW`](/sql/dml/refresh#refresh-materialized-view) takes no options, and whether a refresh rebuilds the whole view, as a local refresh does, or adds only what changed in the source depends on the version and on the view's query. Earlier versions could require the source to have stable row ids and took refresh options; a view they created has to be recreated once the deployment moves to a recent version. Stable row ids are set up on the deployment, not by the SDK: a `db://` connection does not send `new_table_enable_stable_row_ids`, and no SDK call adds them to an existing table. An earlier version that requires them may give new tables stable row ids, may refuse a view created through SQL -- as the SDK creates one -- over a source without them, or may convert an existing source when a view is created through its REST API, which recent versions no longer have. Check with the deployment's administrator which version it runs before relying on a source. `list_materialized_views` asks the deployment for its views, as [`SHOW MATERIALIZED VIEWS`](/sql/ddl/materialized-view#show) does. On a local database the same method opens each table to read its schema, so it costs one open per table. ## Working with the view {#working-with-the-view} `view.table` is the underlying table, for querying, indexing, or search. `view.definition` is the recorded query — the select list, predicate, and limit — which is how you check what a view actually contains without inferring it from the rows. Both are properties; on an async view, the definition is read with `await view.definition()`. An existing view is reopened with `db.open_materialized_view(name)`. ## What to read next {#next} Derive a column instead of a whole table. Every refresh commits a table version.