Amazon Redshift | Scalability Flashcards
What happens to my backups if I delete my data warehouse cluster?
Scalability
Amazon Redshift | Database
When you delete a data warehouse cluster, you have the ability to specify whether a final snapshot is created upon deletion, which enables a restore of the deleted data warehouse cluster at a later date. All previously created manual snapshots of your data warehouse cluster will be retained and billed at standard Amazon S3 rates, unless you choose to delete them.
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How do I scale the size and performance of my Amazon Redshift data warehouse cluster?
Scalability
Amazon Redshift | Database
If you would like to increase query performance or respond to CPU, memory or I/O over-utilization, you can increase the number of nodes within your data warehouse cluster via the AWS Management Console or the ModifyCluster API. When you modify your data warehouse cluster, your requested changes will be applied immediately. Metrics for compute utilization, storage utilization, and read/write traffic to your Amazon Redshift data warehouse cluster are available free of charge via the AWS Management Console or Amazon CloudWatch APIs. You can also add additional, user-defined metrics via Amazon Cloudwatch’s custom metric functionality.
With Redshift Spectrum, you can run multiple Amazon Redshift clusters accessing the same data in Amazon S3. You can use different clusters for different use cases. For example, you can use one cluster for standard reporting and another for data science queries. Your marketing team can use their own clusters different from your operations team. Depending on the type and number of nodes in your local cluster, and the number of files need to be processed for your query, Redshift Spectrum automatically distributes the execution of your query to several Redshift Spectrum workers out of a shared resource pool to read and process data from Amazon S3, and pulls results back into your Amazon Redshift cluster for any remaining processing.
