SageMaker Studio now supports Glue Interactive Sessions
Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) that enables data scientists and developers to perform every step of the machine learning workflow, from preparing data to building, training, tuning, and deploying models. SageMaker Studio comes with fast start, collaborative notebooks. You can quickly launch notebooks in Studio, easily dial up or down the underlying compute resources without interrupting your work, and even share your notebook as a link in few simple clicks. Today, we are excited to announce that Amazon SageMaker Studio notebooks now come with built-in integration with AWS Glue Interactive Sessions. Data scientists and data engineers can use the serverless Apache Spark runtime environment managed by AWS Glue Interactive Sessions to interactively prepare data at scale right in their Studio notebooks.
Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) that enables data scientists and developers to perform every step of the machine learning workflow, from preparing data to building, training, tuning, and deploying models. SageMaker Studio comes with fast start, collaborative notebooks. You can quickly launch notebooks in Studio, easily dial up or down the underlying compute resources without interrupting your work, and even share your notebook as a link in few simple clicks. Today, we are excited to announce that Amazon SageMaker Studio notebooks now come with built-in integration with AWS Glue Interactive Sessions. Data scientists and data engineers can use the serverless Apache Spark runtime environment managed by AWS Glue Interactive Sessions to interactively prepare data at scale right in their Studio notebooks.
Using Glue Interactive Session from SageMaker Studio Notebooks is simple; you choose the built-in Glue PySpark or Glue Spark kernel for your Studio notebook to initialize interactive, serverless Spark sessions within seconds, without having to worry about provisioning and managing complex compute cluster infrastructure. Once initialized, you can quickly browse the Glue data catalog, run large queries, and interactively analyze and prepare data using Spark, right in your Studio notebook. You can then use the prepared data to build, train, tune and deploy models using the purpose-built ML tools within SageMaker Studio.
Glue Interactive Sessions in SageMaker Studio is generally available in the following AWS Regions: US East (Ohio), US East (N. Virginia), US West (N.California), US West (Oregon), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (Stockholm), Europe (Milan), Europe (Paris) and Europe (London), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Hong Kong), Asia Pacific (Sydney), and Asia Pacific (Tokyo), Asia Pacific (Osaka), Middle East (Bahrain), Africa (Cape Town) and South America (São Paulo), Middle East (Bahrain), Africa (Cape Town). To learn more, see this blog and documentation.