Getting started with Amazon EMR Serverless - Amazon EMR
PermissionsStorageInteractive workloadsCreate a job runtime role

Getting started with Amazon EMR Serverless

This tutorial helps you get started with EMR Serverless when you deploy a sample Spark or Hive workload. You'll create, run, and debug your own application. We show default options in most parts of this tutorial.

Before you launch an EMR Serverless application, complete the following tasks.

Topics

Grant permissions to use EMR Serverless

To use EMR Serverless, you need a user or IAM role with an attached policy that grants permissions for EMR Serverless. To create a user and attach the appropriate policy to that user, follow the instructions in Grant permissions.

Prepare storage for EMR Serverless

In this tutorial, you'll use an S3 bucket to store output files and logs from the sample Spark or Hive workload that you'll run using an EMR Serverless application. To create a bucket, follow the instructions in Creating a bucket in the Amazon Simple Storage Service Console User Guide. Replace any further reference to DOC-EXAMPLE-BUCKET with the name of the newly created bucket.

Create an EMR Studio to run interactive workloads

If you want to use EMR Serverless to execute interactive queries through notebooks that are hosted in EMR Studio, you need to specify an S3 bucket and the minimum service role for EMR Serverless to create a Workspace. For steps to get set up, see Set up an EMR Studio in the Amazon EMR Management Guide. For more information on interactive workloads, see Run interactive workloads with EMR Serverless through EMR Studio.

Create a job runtime role

Job runs in EMR Serverless use a runtime role that provides granular permissions to specific AWS services and resources at runtime. In this tutorial, a public S3 bucket hosts the data and scripts. The bucket DOC-EXAMPLE-BUCKET stores the output.

To set up a job runtime role, first create a runtime role with a trust policy so that EMR Serverless can use the new role. Next, attach the required S3 access policy to that role. The following steps guide you through the process.

Console

  1. Navigate to the IAM console at https://console.aws.amazon.com/iam/.

  2. In the left navigation pane, choose Roles.

  3. Choose Create role.

  4. For role type, choose Custom trust policy and paste the following trust policy. This allows jobs submitted to your Amazon EMR Serverless applications to access other AWS services on your behalf.

    {
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "Service": "emr-serverless.amazonaws.com"
      },
      "Action": "sts:AssumeRole"
    }
  ]
}

  5. Choose Next to navigate to the Add permissions page, then choose Create policy.

  6. The Create policy page opens on a new tab. Paste the policy JSON below.

    Important

    Replace DOC-EXAMPLE-BUCKET in the policy below with the actual bucket name created in Prepare storage for EMR Serverless. This is a basic policy for S3 access. For more job runtime role examples, see Job runtime roles for Amazon EMR Serverless.

    {
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "ReadAccessForEMRSamples",
            "Effect": "Allow",
            "Action": [
                "s3:GetObject",
                "s3:ListBucket"
            ],
            "Resource": [
                "arn:aws:s3:::*.elasticmapreduce",
                "arn:aws:s3:::*.elasticmapreduce/*"
            ]
        },
        {
            "Sid": "FullAccessToOutputBucket",
            "Effect": "Allow",
            "Action": [
                "s3:PutObject",
                "s3:GetObject",
                "s3:ListBucket",
                "s3:DeleteObject"
            ],
            "Resource": [
                "arn:aws:s3:::DOC-EXAMPLE-BUCKET",
                "arn:aws:s3:::DOC-EXAMPLE-BUCKET/*"
            ]
        },
        {
            "Sid": "GlueCreateAndReadDataCatalog",
            "Effect": "Allow",
            "Action": [
                "glue:GetDatabase",
                "glue:CreateDatabase",
                "glue:GetDataBases",
                "glue:CreateTable",
                "glue:GetTable",
                "glue:UpdateTable",
                "glue:DeleteTable",
                "glue:GetTables",
                "glue:GetPartition",
                "glue:GetPartitions",
                "glue:CreatePartition",
                "glue:BatchCreatePartition",
                "glue:GetUserDefinedFunctions"
            ],
            "Resource": ["*"]
        }
    ]
}

  7. On the Review policy page, enter a name for your policy, such as EMRServerlessS3AndGlueAccessPolicy.

  8. Refresh the Attach permissions policy page, and choose EMRServerlessS3AndGlueAccessPolicy.

  9. In the Name, review, and create page, for Role name, enter a name for your role, for example, EMRServerlessS3RuntimeRole. To create this IAM role, choose Create role.

CLI

  1. Create a file named emr-serverless-trust-policy.json that contains the trust policy to use for the IAM role. The file should contain the following policy.

    {
    "Version": "2012-10-17",
    "Statement": [{
        "Sid": "EMRServerlessTrustPolicy",
        "Action": "sts:AssumeRole",
        "Effect": "Allow",
        "Principal": {
            "Service": "emr-serverless.amazonaws.com"
        }
    }]
}

  2. Create an IAM role named EMRServerlessS3RuntimeRole. Use the trust policy that you created in the previous step.

    aws iam create-role \
    --role-name EMRServerlessS3RuntimeRole \
    --assume-role-policy-document file://emr-serverless-trust-policy.json

    Note the ARN in the output. You use the ARN of the new role during job submission, referred to after this as the job-role-arn.

  3. Create a file named emr-sample-access-policy.json that defines the IAM policy for your workload. This provides read access to the script and data stored in public S3 buckets and read-write access to DOC-EXAMPLE-BUCKET.

    Important

    Replace DOC-EXAMPLE-BUCKET in the policy below with the actual bucket name created in Prepare storage for EMR Serverless.. This is a basic policy for AWS Glue and S3 access. For more job runtime role examples, see Job runtime roles for Amazon EMR Serverless.

    {
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "ReadAccessForEMRSamples",
            "Effect": "Allow",
            "Action": [
                "s3:GetObject",
                "s3:ListBucket"
            ],
            "Resource": [
                "arn:aws:s3:::*.elasticmapreduce",
                "arn:aws:s3:::*.elasticmapreduce/*"
            ]
        },
        {
            "Sid": "FullAccessToOutputBucket",
            "Effect": "Allow",
            "Action": [
                "s3:PutObject",
                "s3:GetObject",
                "s3:ListBucket",
                "s3:DeleteObject"
            ],
            "Resource": [
                "arn:aws:s3:::DOC-EXAMPLE-BUCKET",
                "arn:aws:s3:::DOC-EXAMPLE-BUCKET/*"
            ]
        },
        {
            "Sid": "GlueCreateAndReadDataCatalog",
            "Effect": "Allow",
            "Action": [
                "glue:GetDatabase",
                "glue:CreateDatabase",
                "glue:GetDataBases",
                "glue:CreateTable",
                "glue:GetTable",Understanding default application behavior, including auto-start and auto-stop, as well as maximum capacity and worker configurations for configuring an application with &EMRServerless;.
                "glue:UpdateTable",
                "glue:DeleteTable",
                "glue:GetTables",
                "glue:GetPartition",
                "glue:GetPartitions",
                "glue:CreatePartition",
                "glue:BatchCreatePartition",
                "glue:GetUserDefinedFunctions"
            ],
            "Resource": ["*"]
        }
    ]
}

  4. Create an IAM policy named EMRServerlessS3AndGlueAccessPolicy with the policy file that you created in Step 3. Take note of the ARN in the output, as you will use the ARN of the new policy in the next step. 

    aws iam create-policy \
    --policy-name EMRServerlessS3AndGlueAccessPolicy \
    --policy-document file://emr-sample-access-policy.json

    Note the new policy's ARN in the output. You'll substitute it for policy-arn in the next step.

  5. Attach the IAM policy EMRServerlessS3AndGlueAccessPolicy to the job runtime role EMRServerlessS3RuntimeRole.

    aws iam attach-role-policy \
    --role-name EMRServerlessS3RuntimeRole \
    --policy-arn policy-arn