Amazon AWS has released an IDE for data scientists and analysts who want to develop apps in R, Python, Scala and PySpark. EMR Studio was previewed at AWS re:Invent 2020 and is now generally available.

EMR Studio provides fully managed Jupyter notebooks, and tools like Spark UI and YARN Timeline Service to simplify debugging. EMR Studio uses AWS Single Sign-On and allows you to log in directly with your corporate credentials without signing in to the AWS Management Console.

EMR Studio provides fully managed Jupyter notebooks, along with tools including Spark UI and YARN Timeline Service. It is designed to make it easy to move from prototyping to production. Developers can trigger pipelines from code repositories, and run Notebooks as pipelines using orchestration tools like Apache Airflow or Amazon Managed Workflows for Apache Airflow, or attach notebooks to a bigger cluster using a single click.

For debugging, developers can work within EMR Studio, and can use native application interfaces such as Spark UI and YARN timeline service directly from EMR Studio.

EMR Studio lets developers run notebook code on Amazon EMR running on Amazon Elastic Compute Cloud (Amazon EC2) or Amazon EMR on Amazon Elastic Kubernetes Service (Amazon EKS). EMR Studio kernels and applications run on EMR clusters, so support distributed data processing with the performance-optimized Apache Spark runtime in Amazon EMR. It can also be used to run parameterized notebooks as part of scheduled workflows using orchestration services like Apache Airflow or Amazon Managed Workflows for Apache Airflow (Amazon MWAA).

The updated version adds  the ability to use the Amazon EMR console and AWS CloudFormation to create and configure a new EMR Studio for teams, support for Microsoft Active Directory (AD) as an identity provider, a new quick start notebook experience, the ability to launch the live Apache Spark UI directly from an EMR Studio notebook, and support for private Git repositories.

More Information

EMR Studio Webpage

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