CREATE MATERIALIZED VIEW

CREATE MATERIALIZED VIEW defines a view that is persisted in durable storage and incrementally updated as new data arrives.

A materialized view specifies a cluster that is tasked with keeping its results up-to-date, but can be referenced in any cluster. This allows you to effectively decouple the computational resources used for view maintenance from the resources used for query serving.

Syntax

with_options

Details

Usage patterns

Maintaining a materialized view in durable storage has resource and latency costs that should be carefully considered depending on the main usage of the view. It’s a good idea to create a materialized view if:

• The results need to be available across clusters;
• View maintenance and query serving would benefit from being scaled independently;
• The final consumer of the view is a sink or a SUBSCRIBE operation.

On the other hand, if you only need to access a view from a single cluster, you should consider creating a non-materialized view and building an index on it instead. The index will incrementally maintain the results of the view updated in memory within that cluster, allowing you to avoid the costs and latency overhead of materialization.

Indexes

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

Depending on your use case, you might have data that doesn’t require up-to-the-second freshness, or that can be accessed using different patterns to optimize for performance and cost (e.g., hot vs. cold data). To support these use cases, you can tweak the refresh strategy of a materialized view.

Materialized views configured with a refresh strategy are not incrementally maintained, and must recompute their results from scratch on every refresh. Because these views can be hosted in scheduled clusters, which automatically turn on and off based on the configured refresh strategies, this feature can lead to significant cost savings when handling large volumes of historical data that is updated less frequently.

Refresh on commit

Syntax: REFRESH ON COMMIT

By default, Materialize refreshes a materialized view on every change to its inputs (i.e., on commit) — this guarantees that results are incrementally updated, fresh and consistent as new data arrives. Refresh on commit is the default when you create a materialized view that doesn’t explicitly specify a refresh strategy, and is the recommended behavior for the vast majority of use cases.

Depending on your use case, it might make sense to trade-off freshness for performance and cost. For example, if it’s important to keep results up-to-date for the most recent data, but not as much once data goes over a certain time threshold, it might be tolerable for changes to the older data to take a longer time to reflect.

Example

To implement this pattern, you can maintain the recent data in a regular materialized view that refreshes on commit, create a second materialized view for data that goes over a specific threshold (e.g., one week) using a refresh every strategy with the desired freshness interval (e.g., one day), and then union these views to get the entire result set.

CREATE MATERIALIZED VIEW mv AS
SELECT ...
-- Keep data newer than one week
WHERE mz_now() <= event_ts + INTERVAL '1' WEEK;

CREATE MATERIALIZED VIEW mv_refresh_every
WITH (
  -- Refresh at creation, so the view is populated ahead of
  -- the first scheduled refresh on Jun 18
  REFRESH AT '2024-06-17 00:00:00',
  -- Refresh every day at midnight UTC
  REFRESH EVERY '1 day' ALIGNED TO '2024-04-17 00:00:00'
) AS
SELECT ...
-- Keep data older than one week
WHERE mz_now() > event_ts + INTERVAL '1' WEEK

CREATE VIEW v_mv_results AS
SELECT * FROM mv
UNION ALL
SELECT * FROM mv_refresh_every;

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, we recommend hosting these views in scheduled clusters 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;

Examples

Creating a materialized view

CREATE MATERIALIZED VIEW winning_bids AS
SELECT auction_id,
       bid_id,
       item,
       amount
FROM highest_bid_per_auction
WHERE end_time < mz_now();

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 ...;

Privileges

The privileges required to execute this statement are:

• Ownership of existing view_name if OR REPLACE is specified.
• 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 that all types in the statement are contained in.

Related pages

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