Frequently asked questions on materialized views in Azure Cosmos DB for Apache Cassandra (preview)

• Specifying a partition key that is different from the base table partition key.
• Support for projecting a selected subset of columns from the base table.
• Filtering rows from a base table in the materialized view based on conditions evaluated on primary key columns of the base table row.
  • Filters supported include: equalities, inequalities, and contains.

Only eventual consistency is guaranteed on the materialized view. You may read stale rows when compared to data on base table due to retrying some operations on materialized views.

You can scale up or scale down the materialized view builder layer depending on your latency requirements for the view to be consistent with base table.

Autoscaling for the materialized view builder isn't available right now. The materialized view builder instances can be manually scaled by modifying the instance count or size.

Time to live (TTL) from base table rows is applied on the matching row in the materialized view. Setting table-level TTL on materialized views is currently not allowed.

First, check if the materialized view builder instances are provisioned. Then, check if enough request units (RUs) are provisioned on the base table. Finally, check for service availability of the base table or materialized view.

The following metrics are available:

• Max Materialized View Catchup Gap in Minutes: The value t indicates rows written to base table in last t minutes that are yet to be propagated to the materialized view.
• Read change feed cost: Request units consumed on the base table to read data for the materialized view.
• Write cost: Request units consumed on the materialized view to transform and persist data that was read from the base table.
• Other metrics related to typical resource consumption on materialized view builders. These metrics include CPU and memory usage.

Materialized views can't be restored. Hence, thee views need to be recreated once the base table is restored.

Multiple materialized views can be created on the same base table. There's a service limit of five views per base table.

The partition and clustering key of the base table are always part of the primary key of any materialized view defined. The primary key on the materialized views will enforce uniqueness after data repartitioning.

You're able to add a column to the base table, but you can't remove a column. After a materialized view is created against a base table, ALTER TABLE ADD`` operations aren't allowed on the base table. ALTER TABLE ADDoperations are only allowed if none of the views have selected*`` in their definition.

Apache Cassandra doesn't support dropping columns on the base table if it has a materialized view defined on it.

No. Materialized views can't be created on a table that existed before the account was onboarded to support materialized views.

Materialized views can't be created on a table that existed before support for materialized views was enabled on the account.

To use materialized views, create a new table after the feature is enabled.

Here are some of the identified cases where data from a base table can't be written to materialized view as they violate known constraints on a materialized view table:

• Rows that don't satisfy partition key size (2 kb) limit in the materialized views
• Rows that don't satisfy clustering key size (1 kb) limit in materialized views

Currently, the builder drops these rows.

To create an account with support for both customer-managed keys and materialized views, create a support request.

Next steps