Amazon Redshift Uses Machine Learning to Accelerate Dashboards and Interactive Analysis
Amazon Redshift introduces Short Query Acceleration to speed up execution of short running queries. Short Query Acceleration provides higher performance, faster results, and better predictability of query execution times.
Amazon Redshift introduces Short Query Acceleration to speed up execution of short running queries. Short Query Acceleration provides higher performance, faster results, and better predictability of query execution times.
Short running queries such as reports, dashboards, and interactive analysis can be delayed when entering a queue behind a long running query like an extract, transform, and load (ETL) operation. Short Query Acceleration uses machine learning to predict the execution time of a query and move short running queries to an express ‘short query’ queue for faster processing. The acceleration varies based on your workload, though we have observed 3x improvements in short query performance for internal workloads.
You can enable SQA in three easy steps. Step one, edit your cluster parameter group, by going to your Workload Management (WLM) settings in your console and click on 'Edit'. Step two, choose Enable short query acceleration checkbox. Step three, 'Save' to enable SQA on your cluster. Alternatively, you can enable SQA using the AWS command line interface (CLI). To learn more, please refer to our documentation.
With the latest release, Amazon Redshift customers can now use Short Query Acceleration in all AWS Public Regions.