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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchCreate an Iceberg materialized view in Amazon Redshift with CREATE MATERIALIZED VIEW … USING ICEBERG, then keep it current by running REFRESH MATERIALIZED VIEW after source changes. Redshift stores the result as an Iceberg table in Amazon S3 or an S3 Table Bucket and registers it in AWS Glue Data Catalog. The procedure requires Iceberg v2 or earlier source tables, the right Glue and source-table permissions, and a query definition that fits Redshift’s refresh rules.
Check prerequisites before creating the view
- Source format and version: Every source table must be an Apache Iceberg table in the same AWS account and Region as the materialized view, and must use Iceberg format version 2 or earlier. Redshift does not support creating these views over Iceberg v3 tables. See AWS CREATE MATERIALIZED VIEW documentation and AWS Iceberg materialized-view overview.
- Identifier casing: Use lowercase identifiers in the definition. Creation and refresh are unsupported when
enable_case_sensitive_identifieris true; if necessary, disable it for the session before running the statements. The setting is session-specific. - Creation permissions: The user creating the view needs
CREATE TABLEpermission in the target AWS Glue Data Catalog database. The IAM role associated with the external schema—the materialized-view definer role—needsSELECTpermission on every source table in the query. - Supported sources and expressions: Native Redshift tables, temporary tables, system tables, user-defined functions, mutable functions, and Lake Formation filtered (FGAC) tables cannot be used as sources.
Create an Iceberg materialized view
Use a catalog-qualified name and include USING ICEBERG. Replace the example identifiers and query with your Glue catalog, database, view name, and source tables:
CREATE MATERIALIZED VIEW glue_catalog.database_name.view_name
USING ICEBERG
[LOCATION 's3://bucket/path/']
[PARTITIONED BY (partition_transform [, ...])]
[TABLE PROPERTIES ('property_name' = 'property_value' [, ...])]
AS
SELECT ...;The optional location lets you choose the S3 storage path; partition transforms let you shape the stored layout for your workload. The result is written as Parquet in Iceberg format and registered in AWS Glue Data Catalog. Compatible Iceberg engines, including Apache Spark, Amazon Athena, and Trino, can access the table.
Do not add Redshift table clauses that are unsupported for this statement, including BACKUP, DISTSTYLE, DISTKEY, or SORTKEY. Iceberg materialized views also do not support AUTO REFRESH.
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Refresh the view after source changes
Refresh an Iceberg materialized view explicitly after changes to its source data:
REFRESH MATERIALIZED VIEW glue_catalog.database_name.view_name;The caller needs ALTER permission on the materialized view, and the definer role must continue to have SELECT permission on all referenced source tables. Do not append CASCADE or RESTRICT; those options are unsupported for Iceberg materialized views. Because automatic refresh is unavailable, schedule or trigger this command through your own workflow.
Understand incremental and full refreshes
Redshift chooses whether to apply eligible changes incrementally or recompute the defining query. Incremental refresh processes changes since the previous refresh; a full refresh reruns the defining query and replaces the stored contents. AWS states: “When incremental refresh is not supported, Amazon Redshift automatically performs a full refresh.” See the REFRESH MATERIALIZED VIEW documentation.
Definitions that can support incremental refresh
For Iceberg materialized views, only COUNT and SUM aggregate functions support incremental refresh. Eligibility also depends on the rest of the defining query and on Redshift having the source-table change history it needs.
Definitions that require a full refresh
Incremental refresh is unavailable for definitions that use constructs such as outer joins, set operations, distinct aggregates, window functions, subqueries, grouping sets, ROLLUP, CUBE, or DISTINCT. A full refresh can require more work because Redshift reruns the query rather than applying only eligible changes.
Why a refresh may recompute or fail
Source snapshots have expired
If the Iceberg snapshots recorded at the previous refresh are no longer available, Redshift may be unable to identify the changes to apply and perform a full recomputation. Set source snapshot retention with your refresh cadence and recovery needs in mind.
The materialized-view data was changed outside Redshift
If an external engine or tool modifies the materialized view’s Iceberg data, Redshift performs a full recomputation on the next refresh.
Another cluster refreshed the same view first
Multiple Redshift clusters can attempt to refresh one Iceberg materialized view. Redshift uses optimistic concurrency control through Glue: only one concurrent refresh succeeds, and an attempt loses if another cluster completes first. Coordinate a single refresh owner where practical; otherwise, retry a losing refresh after the successful one completes.
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For Iceberg external-table materialized-view refreshes, AWS documents a limit of up to 4 million deleted positions in a single data file. After reaching that limit, compact the base Iceberg table before continuing to refresh. This is a documented product limit, not a refresh-speed estimate; see AWS Iceberg materialized-view documentation.
Concurrency scaling is involved
Concurrency scaling is not supported for creating or refreshing materialized views on Iceberg tables. Run these operations outside that execution path.
Quick Recap
Operational checklist
- Confirm source tables are Iceberg v2 or earlier, in the same account and Region, and accessible to the external-schema IAM role.
- Use lowercase identifiers and ensure
enable_case_sensitive_identifieris false for the session. - Verify the creator has Glue database
CREATE TABLEpermission and the definer role has source-tableSELECT. - Create the view with a catalog-qualified name and
USING ICEBERG; omit unsupported clauses and automatic refresh. - Run
REFRESH MATERIALIZED VIEWafter source changes, ensuring the caller has viewALTERpermission. - For refresh issues, check query eligibility, snapshot retention, external edits, concurrent refreshes, and the deleted-position limit.
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