Amazon Athena adds support for invoking machine learning models in SQL queries
Today, Amazon Athena released a new feature that allows users to easily invoke machine learning models for inference directly from their SQL queries. The ability to use machine learning models in SQL queries makes complex tasks such anomaly detection, customer cohort analysis, and sales predictions as simple as invoking a function in a SQL query.
Today, Amazon Athena released a new feature that allows users to easily invoke machine learning models for inference directly from their SQL queries. The ability to use machine learning models in SQL queries makes complex tasks such anomaly detection, customer cohort analysis, and sales predictions as simple as invoking a function in a SQL query.
Customers can use more than a dozen built-in machine learning algorithms provided by Amazon SageMaker, train their own models, or find and subscribe to model packages from AWS Marketplace and deploy on Amazon SageMaker Hosting Services. There is no additional setup required. Users can invoke these ML models in their SQL queries from the Athena console, Athena APIs, and through Athena’s preview JDBC driver.
Amazon Athena’s ML functionality is available today in preview in the us-east-1 (N. Virginia) region. Begin your preview now by following these steps.
To learn more about the feature, please visit our documentation.
To learn how to create and train ML models in Amazon SageMaker, please visit this link.