Note For most workloads setting up both scale in and scale out rules is

Note for most workloads setting up both scale in and

This preview shows page 335 - 336 out of 395 pages.

Note For most workloads, setting up both scale-in and scale-out rules is desirable to optimize resource utilization. Setting either rule without the other means that you need to manually resize the instance count after a scaling activity. In other words, this sets up a "one-way" automatic scale-out or scale-in policy with a manual reset. Creating the IAM Role for Automatic Scaling Automatic scaling in Amazon EMR requires an IAM role with permissions to add and terminate instances when scaling activities are triggered. A default role configured with the appropriate role policy and trust policy, EMR_AutoScaling_DefaultRole , is available for this purpose. When you create a cluster with a scaling policy for the first time using the AWS Management Console, Amazon EMR creates the default role and attaches the default managed policy for permissions, AmazonElasticMapReduceforAutoScalingRole . When you create a cluster with an automatic scaling policy using the AWS CLI, you must first ensure that either the default IAM role exists, or that you have a custom IAM role with a policy attached that provides the appropriate permissions. To create the default role, you can run the create- default-roles command before you create a cluster. You can then specify --auto-scaling- role EMR_AutoScaling_DefaultRole option when you create a cluster. Alternatively, you can create a custom automatic scaling role and then specify it when you create a cluster, for example -- auto-scaling-role MyEMRAutoScalingRole . If you create a customized automatic scaling role for Amazon EMR, we recommend that you base permissions policies for your custom role based on the managed policy. For more information, see Configure IAM Service Roles for Amazon EMR Permissions to AWS Services and Resources (p. 177) . Understanding Automatic Scaling Rules When a scale-out rule triggers a scaling activity for an instance group, Amazon EC2 instances are added to the instance group according to your rules. New nodes can be used by applications such as Apache Spark and Apache Hive as soon as the Amazon EC2 instance enters the InService state. You can also set up a scale-in rule that terminates instances and removes nodes. For more information about the lifecycle of Amazon EC2 instances that scale automatically, see Auto Scaling Lifecycle in the Amazon EC2 Auto Scaling User Guide . You can configure how a cluster terminates Amazon EC2 instances. You can choose to either terminate at the Amazon EC2 instance-hour boundary for billing, or upon task completion. This setting applies both to automatic scaling and to manual resizing operations. For more information about this configuration, see Cluster Scale-Down (p. 343) . The following parameters for each rule in a policy determine automatic scaling behavior.
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  • Spring '12
  • LauraParker
  • Amazon Web Services, Amazon Elastic Compute Cloud

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