Troubleshooting errors in EMR Serverless

Use the following information to help diagnose and fix common issues that you might encounter when you work with Amazon EMR Serverless.

Error: Limit exceeded for max allowed capacity.

This error indicates that EMR Serverless couldn't submit the job because the application has exceeded your configured maximum capacity limits. Increase the maximum capacity limits for the application.

Error: Configured maximum capacity has been exceeded. Please try again later.

This error indicates that EMR Serverless couldn't start a new job because the application has exceeded your configured maximum capacity limits. Increase the maximum capacity limits for the application.

Error: S3 access is denied. Please check S3 access permissions of the job runtime role on the required S3 resources.

This error indicates that your job doesn't have access to your S3 resources. Verify that the job runtime role has permission to access the S3 resources that the job needs to use. To learn more about runtime roles, see Job runtime roles for Amazon EMR Serverless.

Error: ModuleNotFoundError: No module named <module>. Please refer to the user guide on how to use python libraries with EMR Serverless.

This error indicates that a Python module wasn't available for the Spark job. Check that the dependent Python libraries are available to the job. For more information on how to package Python libraries, see Using Python libraries with EMR Serverless.

Error: Could not assume execution role <role name> because it does not exist or is not set up with the required trust relationship.

This error indicates that the job runtime role that you specified for the job doesn't exist, or that the role doesn't have a trust relationship for EMR Serverless permissions. To verify that the IAM role exists and validate that you have set up the role’s trust policy properly, see the instructions in Job runtime roles for Amazon EMR Serverless.