Amazon EMR Serverless architecture options - Amazon EMR
Using x86_64 architectureUsing arm64 architecture (Graviton)Launch new apps with GravitonConvert existing apps to GravitonConsiderations
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Amazon EMR Serverless architecture options

The instruction set architecture of your Amazon EMR Serverless application determines the type of processors that the application uses to run the job. Amazon EMR provides two architecture options for your application: x86_64 and arm64. EMR Serverless automatically updates to the latest generation of instances as they become available, so your applications can use the newer instances without requiring additional effort from you.

Using x86_64 architecture

The x86_64 architecture is also known as x86 64-bit or x64. x86_64 is the default option for EMR Serverless applications. This architecture uses x86-based processors and is compatible with most third-party tools and libraries.

Most applications are compatible with the x86 hardware platform and can run successfully on the default x86_64 architecture. However, if your application is compatible with 64-bit ARM, then you can switch to arm64 to use Graviton processors for improved performance, compute power, and memory. It costs less to run instances on arm64 architecture than when you run instances of equal size on x86 architecture.

Using arm64 architecture (Graviton)

Amazon Graviton processors are custom designed by Amazon with 64-bit ARM Neoverse cores and leverage the arm64 architecture (also known as Arch64 or 64-bit ARM). The Amazon Graviton line of processors available on EMR Serverless include Graviton3 and Graviton2 processors. These processors deliver superior price-performance for Spark and Hive workloads compared to equivalent workloads that run on the x86_64 architecture. EMR Serverless automatically uses the latest generation of processors when available without any effort from your side to upgrade to the latest generation of processors.

Launching new applications with Graviton support

Use one of the following methods to launch an application that uses the arm64 architecture.

Amazon CLI

To launch an application using Graviton processors from Amazon CLI, specify ARM64 as the architecture parameter in the create-application API. Provide the appropriate values for your application in the other parameters.

aws emr-serverless create-application \
 --name my-graviton-app \
 --release-label emr-6.8.0 \
 --type "SPARK" \
 --architecture "ARM64" \
 --region us-west-2
EMR Studio

To launch an application using Graviton processors from EMR Studio, choose arm64 as the Architecture option when you create or update an application.

Configuring existing applications to use Graviton

You can configure your existing Amazon EMR Serverless applications to use the Graviton (arm64) architecture with the SDK, Amazon CLI, or EMR Studio.

To convert an existing application from x86 to arm64

  1. Confirm that you are using the latest major version of the Amazon CLI/SDK that supports the architecture parameter.

  2. Confirm that there are no jobs running and then stop the application.

    aws emr-serverless stop-application \
 --application-id application-id \
 --region us-west-2

  3. To update the application to use Graviton, specify ARM64 for the architecture parameter in the update-application API.

    aws emr-serverless update-application \
 --application-id application-id \
 --architecture 'ARM64' \
 --region us-west-2

  4. To verify that the CPU architecture of the application is now ARM64, use the get-application API.

    aws emr-serverless get-application \
 --application-id application-id \
 --region us-west-2

  5. When you're ready, restart the application.

    aws emr-serverless start-application \
 --application-id application-id \
 --region us-west-2

Considerations when using Graviton

Before you launch an EMR Serverless application using arm64 for Graviton support, confirm the following.

Library compatibility

When you select Graviton (arm64) as an architecture option, ensure that third-party packages and libraries are compatible with the 64-bit ARM architecture. For information on how to package Python libraries into a Python virtual environment that is compatible with your selected architecture, see Using Python libraries with EMR Serverless.

To learn more about how to configure a Spark or Hive workload to use 64-bit ARM, see the Amazon Graviton Getting Started repository on GitHub. This repository contains essential resources that can help you get started with the ARM-based Graviton.