redshift alter table rename takes forever

#Redshift alter table rename takes forever manual#
#Redshift alter table rename takes forever full#

The author recommends starting with a dc2.large node and scaling up or down as necessary based on your workload.

Properly selecting and configuring the type of Redshift node is crucial to achieving optimal performance.

Here are the 5 key takeaways from this article: However, configuring a Redshift cluster for optimal performance can be challenging.

Scheduled refresh using the Amazon Redshift scheduler API operations or the consoleįor more information, see Autorefreshing a materialized view.Amazon Redshift is a popular cloud-based data warehousing solution that allows users to store and analyze large amounts of data quickly and efficiently.

#Redshift alter table rename takes forever manual#

Manual refresh as described in REFRESH MATERIALIZED VIEW.

To create more deterministic refresh behavior, use the following: In some cases, your materialized views might need more deterministic refresh behavior. This prioritization might stop autorefresh to preserve the performance of your workload and might delay the refresh of some materialized views. Refresh activity isn't shown on an automated refresh due to an active workloadĪmazon Redshift prioritizes your workloads over autorefresh. If you experience slow REFRESH MATERIALIZED VIEW performance, see Improve query performance. To view the type of refresh that the materialized view underwent, see SVL_MV_REFRESH_STATUS.

#Redshift alter table rename takes forever full#

Type of Refresh: Incremental or full refresh.Allocated resources: To view the service class configuration for WLM, see STV_WLM_SERVICE_CLASS_CONFIG.Table locks: To view any current updates on tables in the database, see STV_LOCKS.The REFRESH MATERIALIZED VIEW operation performance is subject to the following factors: To find out information of queries and query steps that are actively running on compute nodes, use STV_EXEC_STATE.To record the current state of queries track by workload management (WLM), use STV_WLM_QUERY_STATE.To view the active queries running on the data, use STV_INFLIGHT.To confirm the query is running, do the following: REFRESH MATERIALIZED VIEW functions as a normal query that run on your cluster. ```ERROR: Materialized view is unrefreshable as a base table was renamed.``` REFRESH MATERIALIZED VIEW was submitted and running for long time The following are example error messages you might see: ```Detail: Procedure does not exist``` In this unrefreshable state of materialized view, you must drop and recreate the materialized view to keep the materialized view up-to-date. To view the refresh activity of materialized view, use SVL_MV_REFRESH_STATUS. To find whether the data in materialized view is stale, and materialized view state information, use STV_MV_INFO.

The preceding constraints apply even if the column isn't used in the materialized view. Note: Materialized views in this condition can be queried but can't be refreshed. Change the name of a base table or schema.Unrefreshable materialized views can be caused by operations that: REFRESH MATERIALIZED VIEW is unrefreshable After the operation completes, the REFRESH MATERIALIZED VIEW can be re-submitted. The error occurs when REFRESH MATERIALIZED VIEW and VACUUM are submitted to run concurrently on the base table. Invalid operation: Materialized view mv_name could not be refreshed as a base table changed physically due to vacuum/truncate concurrently. For more information, see Autorefreshing a materialized view. If the materialized view is a full recompute instead of an incremental refresh, you must also have the CREATE privilege on the schema. SELECT privilege on the underlying base tables.Also, you must have the following privileges: You must be the owner to perform a REFRESH MATERIALIZED VIEW operation on a materialized view. Resolution REFRESH MATERIALIZED VIEW is failing with permission error Refresh activity isn't shown on an automated refresh due to an active workload.

REFRESH MATERIALIZED VIEW was submitted and running for long time.

REFRESH MATERIALIZED VIEW is unrefreshable.

You see the error: Invalid operation: Materialized view mv_name could not be refreshed as a base table changed physically due to vacuum/truncate concurrently.

REFRESH MATERIALIZED VIEW is failing with permission error.The following scenarios can cause a materialized view in Amazon Redshift to not refresh or take a long time to complete: