CREATE MATERIALIZED VIEW

Use CREATE MATERIALIZED VIEW to:

• Create a materialized view that maintains fresh results by persisting them in durable storage and incrementally updating them as new data arrives.

• Create a replacement for an existing materialized view that can be applied in place with ALTER MATERIALIZED VIEW ... APPLY REPLACEMENT.

Materialized views are particularly useful when you need cross-cluster access to results or want to sink data to external systems like Kafka. When you create a materialized view, a cluster, responsible for maintaining the view, is associated with it, but the results can be queried from any cluster. This allows you to separate the compute resources used for view maintenance from those used for serving queries.

If you do not need durability or cross-cluster sharing, and you are primarily interested in fast query performance within a single cluster, you may prefer to create a view and index it. In Materialize, indexes on views also maintain results incrementally, but store them in memory, scoped to the cluster where the index was created. This approach offers lower latency for direct querying within that cluster.

Syntax

CREATE MATERIALIZED VIEW [IF NOT EXISTS] <view_name>
[(<col_ident>, ...)]
[IN CLUSTER <cluster_name>]
[WITH (<with_options>)]
AS <select_stmt>;

CREATE REPLACEMENT MATERIALIZED VIEW <name>
FOR <target_name>
[IN CLUSTER <cluster_name>]
[WITH (<with_options>)]
AS <select_stmt>;

Details

Usage pattern

In Materialize, both indexes on views and materialized views incrementally update the view results when Materialize ingests new data. Whereas materialized views persist the view results in durable storage and can be accessed across clusters, indexes on views compute and store view results in memory within a single cluster.

Some general guidelines for usage patterns include:

Indexing materialized views

Although you can query a materialized view directly, these queries will be issued against Materialize’s storage layer. This is expected to be fast, but still slower than reading from memory. To improve the speed of queries on materialized views, we recommend creating indexes based on common query patterns.

It’s important to keep in mind that indexes are local to a cluster, and maintained in memory. As an example, if you create a materialized view and build an index on it in the quickstart cluster, querying the view from a different cluster will not use the index; you should create the appropriate indexes in each cluster you are referencing the materialized view in.

Non-null assertions

Because materialized views may be created on arbitrary queries, it may not in all cases be possible for Materialize to automatically infer non-nullability of some columns that can in fact never be null. In such a case, ASSERT NOT NULL clauses may be used as described in the syntax section above. Specifying ASSERT NOT NULL for a column forces that column’s type in the materialized view to include NOT NULL. If this clause is used erroneously, and a NULL value is in fact produced in a column for which ASSERT NOT NULL was specified, querying the materialized view will produce an error until the offending row is deleted.

Refresh strategies

Materialized views in Materialize are incrementally maintained by default, meaning their results are automatically updated as soon as new data arrives. This guarantees that queries returns the most up-to-date information available with minimal delay and that results are always as fresh as the input data itself.

In most cases, this default behavior is ideal. However, in some very specific scenarios like reporting over slow changing historical data, it may be acceptable to relax freshness in order to reduce compute usage. For these cases, Materialize supports refresh strategies, which allow you to configure a materialized view to recompute itself on a fixed schedule rather than maintaining them incrementally.

Refresh on commit

Syntax: REFRESH ON COMMIT

Materialized views in Materialize are incrementally updated by default. This means that as soon as new data arrives in the system, any dependent materialized views are automatically and continuously updated. This behavior, known as refresh on commit, ensures that the view’s contents are always as fresh as the underlying data.

REFRESH ON COMMIT is:

• Generally available
• The default behavior for all materialized views
• Implicit and does not need to be manually specified
• Strongly recommended for the vast majority of use cases

With REFRESH ON COMMIT, Materialize provides low-latency, up-to-date results without requiring user-defined schedules or manual refreshes. This model is ideal for most workloads, including streaming analytics, live dashboards, customer-facing queries, and applications that rely on timely, accurate results.

Only in rare cases—such as batch-oriented processing or reporting over slowly changing historical datasets—might it make sense to trade off freshness for potential cost savings. In such cases, consider defining an explicit refresh strategy to control when recomputation occurs.

Refresh at

Syntax: REFRESH AT { CREATION | timestamp }

This strategy allows configuring a materialized view to refresh at a specific time. The refresh time can be specified as a timestamp, or using the AT CREATION clause, which triggers a first refresh when the materialized view is created.

Example

To create a materialized view that is refreshed at creation, and then at the specified times:

CREATE MATERIALIZED VIEW mv_refresh_at
IN CLUSTER my_scheduled_cluster
WITH (
  -- Refresh at creation, so the view is populated ahead of
  -- the first user-specified refresh time
  REFRESH AT CREATION,
  -- Refresh at a user-specified (future) time
  REFRESH AT '2024-06-06 12:00:00',
  -- Refresh at another user-specified (future) time
  REFRESH AT '2024-06-08 22:00:00'
)
AS SELECT ... FROM ...;

You can specify multiple REFRESH AT strategies in the same CREATE statement, and combine them with the REFRESH EVERY strategy.

Refresh every

Syntax: REFRESH EVERY interval [ ALIGNED TO timestamp ]

This strategy allows configuring a materialized view to refresh at regular intervals. The ALIGNED TO clause additionally allows specifying the phase of the scheduled refreshes: for daily refreshes, it specifies the time of the day when the refresh will happen; for weekly refreshes, it specifies the day of the week and the time of the day when the refresh will happen. If ALIGNED TO is not specified, it defaults to the time when the materialized view is created.

Example

To create a materialized view that is refreshed at creation, and then once a day at 10PM UTC:

CREATE MATERIALIZED VIEW mv_refresh_every
IN CLUSTER my_scheduled_cluster
WITH (
  -- Refresh at creation, so the view is populated ahead of
  -- the first user-specified refresh time
  REFRESH AT CREATION,
  -- Refresh every day at 10PM UTC
  REFRESH EVERY '1 day' ALIGNED TO '2024-06-06 22:00:00'
) AS
SELECT ...;

You can specify multiple REFRESH EVERY strategies in the same CREATE statement, and combine them with the REFRESH AT strategy. When this strategy, we recommend always using the REFRESH AT CREATION clause, so the materialized view is available for querying ahead of the first user-specified refresh time.

Querying materialized views with refresh strategies

Materialized views configured with REFRESH EVERY strategies have a period of unavailability around the scheduled refresh times — during this period, the view will not return any results. To avoid unavailability during the refresh operation, you must host these views in scheduled clusters, which can be configured to automatically turn on ahead of the scheduled refresh time.

Example

To create a scheduled cluster that turns on 1 hour ahead of any scheduled refresh times:

CREATE CLUSTER my_scheduled_cluster (
  SIZE = '3200cc',
  SCHEDULE = ON REFRESH (HYDRATION TIME ESTIMATE = '1 hour')
);

You can then create a materialized view in this cluster, configured to refresh at creation, then once a day at 12PM UTC:

CREATE MATERIALIZED VIEW mv_refresh_every
IN CLUSTER my_scheduled_cluster
WITH (
  -- Refresh at creation, so the view is populated ahead of
  -- the first user-specified refresh time
  REFRESH AT CREATION,
  -- Refresh every day at 12PM UTC
  REFRESH EVERY '1 day' ALIGNED TO '2024-06-18 00:00:00'
) AS
SELECT ...;

Because the materialized view is hosted on a scheduled cluster that is configured to turn on ahead of any scheduled refreshes, you can expect my_scheduled_cluster to be provisioned at 11PM UTC — or, 1 hour ahead of the scheduled refresh time for mv_refresh_every. This means that the cluster can backfill the view with pre-existing data — a process known as hydration — ahead of the refresh operation, which reduces the total unavailability window of the view to just the duration of the refresh.

If the cluster is not configured to turn on ahead of scheduled refreshes (i.e., using the HYDRATION TIME ESTIMATE option), the total unavailability window of the view will be a combination of the hydration time for all objects in the cluster (typically long) and the duration of the refresh for the materialized view (typically short).

Depending on the actual time it takes to hydrate the view or set of views in the cluster, you can later adjust the hydration time estimate value for the cluster using ALTER CLUSTER:

ALTER CLUSTER my_scheduled_cluster
SET (SCHEDULE = ON REFRESH (HYDRATION TIME ESTIMATE = '30 minutes'));

Introspection

To check details about the (non-default) refresh strategies associated with any materialized view in the system, you can query the mz_internal.mz_materialized_view_refresh_strategies and mz_internal.mz_materialized_view_refreshes system catalog tables:

SELECT mv.id AS materialized_view_id,
       mv.name AS materialized_view_name,
       rs.type AS refresh_strategy,
       rs.interval AS refresh_interval,
       rs.aligned_to AS refresh_interval_phase,
       rs.at AS refresh_time,
       r.last_completed_refresh,
       r.next_refresh
FROM mz_internal.mz_materialized_view_refresh_strategies rs
JOIN mz_internal.mz_materialized_view_refreshes r ON r.materialized_view_id = rs.materialized_view_id
JOIN mz_materialized_views mv ON rs.materialized_view_id = mv.id;

Creating replacement materialized views

You can use CREATE REPLACEMENT MATERIALIZED VIEW with ALTER MATERIALIZED VIEW ... APPLY REPLACEMENT to replace materialized views in-place without recreating dependent objects or incurring downtime.

To create a replacement materialized view, you must:

• Specify the target materialized view.
• Specify a SELECT statement for the replacement view that produces the same output schema (including column order and keys) as the target view.

Upon creation, the replacement view starts hydrating in the background.

Before applying the replacement view:

• Verify that the replacement view is hydrated to replace without downtime.
• Verify that the target materialized view results are not behind the replacement materialized view by checking their write_frontier.

The replacement view is dropped when you apply the replacement view. For more information on applying the replacement view, including recommendations and CPU/memory considerations, see ALTER MATERIALIZED VIEW ... APPLY REPLACEMENT...

See also:

• Replace materialized views guide for a step-by-step tutorial.

Query performance of replacement views

You can query a replacement materialized view to validate its results before replacing. However, queries against replacement materialized views are slower and more computationally expensive than queries against regular materialized views. This is because the replacement is treated like a view, and its results are re-computed as part of the query execution.

Restrictions and limitations

A replacement materialized view can only be applied to the target materialized view specified in the FOR clause of the CREATE REPLACEMENT MATERIALIZED VIEW statement.

You cannot create indexes on replacement materialized views.

Examples

Creating a materialized view

The following example creates a winning_bids materialized view:

CREATE MATERIALIZED VIEW winning_bids AS
SELECT DISTINCT ON (a.id) b.*, a.item, a.seller
FROM auctions AS a
JOIN bids AS b
  ON a.id = b.auction_id
WHERE b.bid_time < a.end_time
  AND mz_now() >= a.end_time
ORDER BY a.id,
  b.amount DESC,
  b.bid_time,
  b.buyer;

Using non-null assertions

CREATE MATERIALIZED VIEW users_and_orders WITH (
  -- The semantics of a FULL OUTER JOIN guarantee that user_id is not null,
  -- because one of `users.id` or `orders.user_id` must be not null, but
  -- Materialize cannot yet automatically infer that fact.
  ASSERT NOT NULL user_id
)
AS
SELECT
  coalesce(users.id, orders.user_id) AS user_id,
  ...
FROM users FULL OUTER JOIN orders ON users.id = orders.user_id

Using refresh strategies

CREATE MATERIALIZED VIEW mv
IN CLUSTER my_refresh_cluster
WITH (
  -- Refresh every Tuesday at 12PM UTC
  REFRESH EVERY '7 days' ALIGNED TO '2024-06-04 12:00:00',
  -- Refresh every Thursday at 12PM UTC
  REFRESH EVERY '7 days' ALIGNED TO '2024-06-06 12:00:00',
  -- Refresh on creation, so the view is populated ahead of
  -- the first user-specified refresh time
  REFRESH AT CREATION
)
AS SELECT ... FROM ...;

Creating a replacement materialized view

The following example creates a replacement materialized view winning_bids_replacement for the winning_bids materialized view. The replacement view specifies a different filter mz_now() > a.end_time than the existing view mz_now() >= a.end_time.

CREATE REPLACEMENT MATERIALIZED VIEW winning_bids_replacement
FOR winning_bids AS
SELECT DISTINCT ON (a.id) b.*, a.item, a.seller
FROM auctions AS a
JOIN bids AS b
  ON a.id = b.auction_id
WHERE b.bid_time < a.end_time
  AND mz_now() > a.end_time
ORDER BY a.id,
  b.amount DESC,
  b.bid_time,
  b.buyer;

To replace the existing view with its replacement, see ALTER MATERIALIZED VIEW.

See also:

• Replace materialized views guide

Privileges

The privileges required to execute this statement are:

• CREATE privileges on the containing schema.
• CREATE privileges on the containing cluster.
• USAGE privileges on all types used in the materialized view definition.
• USAGE privileges on the schemas for the types used in the statement.

Additional information

• Materialized views are not monotonic; that is, materialized views cannot be recognized as append-only.

Related pages

• ALTER MATERIALIZED VIEW
• SHOW MATERIALIZED VIEWS
• SHOW CREATE MATERIALIZED VIEW
• DROP MATERIALIZED VIEW