Note If you create a custom EMR role for EC2 follow the basic work flow which

Note if you create a custom emr role for ec2 follow

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Note If you create a custom EMR role for EC2, follow the basic work flow, which automatically creates an instance profile of the same name. Amazon EC2 allows you to create instance profiles and roles with different names, but Amazon EMR does not support this configuration, and it results in an "invalid instance profile" error when you create the cluster. Reading and Writing Data to Amazon S3 Using EMRFS When an application running on an Amazon EMR cluster references data using the s3:// mydata format, Amazon EMR uses EMRFS to make the request. Clusters typically read and write data to Amazon S3 in this way, and EMRFS uses the permissions attached to the service role for cluster EC2 instances by default. When you have multiple cluster users and multiple data stores, you may want users to have different permissions to EMRFS data in Amazon S3. To do this, you can you can use IAM roles for EMRFS. This allows EMRFS to assume different roles with different permissions policies based on the user or group making the request or the location of EMRFS data in Amazon S3. For more information, see Configure IAM Roles for EMRFS Requests to Amazon S3 (p. 197) . Because IAM roles for EMRFS will fall back to the permissions attached to the service role for cluster EC2 instances, as a best practice, we recommend that you use IAM roles for EMRFS, and limit the EMRFS and Amazon S3 permissions attached to the service role for cluster EC2 instances. The sample statement below demonstrates the permissions that EMRFS requires to make requests to Amazon S3. my-data-bucket-in-s3-for-emrfs-reads-and-writes specifies the bucket in Amazon S3 where the cluster reads and writes data and all sub-folders using /* . Add only those buckets and folders that your application requires. The policy statement that allows dynamodb actions is required only if EMRFS consistent view is enabled. EmrFSMetadata specifies the default folder for EMRFS consistent view. For more information, see Enable Consistent View (p. 64) . { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "s3:AbortMultipartUpload", "s3:CreateBucket", "s3:DeleteObject", "s3:GetBucketVersioning", "s3:GetObject", "s3:GetObjectTagging", "s3:GetObjectVersion", "s3:ListBucket", "s3:ListBucketMultipartUploads", 185
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Amazon EMR Management Guide Configure Service Roles for Amazon EMR "s3:ListBucketVersions", "s3:ListMultipartUploadParts", "s3:PutBucketVersioning", "s3:PutObject", "s3:PutObjectTagging" ], "Resource": [ "arn:aws:s3::: my-data-bucket-in-s3-for-emrfs-reads-and-writes ", "arn:aws:s3::: my-data-bucket-in-s3-for-emrfs-reads-and-writes/* " ] }, { "Effect": "Allow", "Action": [ "dynamodb:CreateTable", "dynamodb:BatchGetItem", "dynamodb:BatchWriteItem", "dynamodb:PutItem", "dynamodb:DescribeTable", "dynamodb:DeleteItem", "dynamodb:GetItem", "dynamodb:Scan", "dynamodb:Query", "dynamodb:UpdateItem", "dynamodb:DeleteTable", "dynamodb:UpdateTable" ], "Resource": "arn:aws:dynamodb: us-west-2 : 123456789012 :table/ EmrFSMetadata " }, { "Effect": "Allow", "Action": [ "cloudwatch:PutMetricData", "dynamodb:ListTables", "s3:HeadBucket" ], "Resource": "*" }, { "Effect": "Allow", "Action": [ "sqs:GetQueueUrl", "sqs:DeleteMessageBatch", "sqs:ReceiveMessage", "sqs:DeleteQueue", "sqs:SendMessage",
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  • Spring '12
  • LauraParker
  • Amazon Web Services, Amazon Elastic Compute Cloud

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