Cluster scale-down - Amazon EMR

Cluster scale-down


Scale-down behavior options are no longer supported since Amazon EMR release 5.10.0. Because of the introduction of per-second billing in Amazon EC2, the default scale-down behavior for Amazon EMR clusters is now terminate at task completion.

With Amazon EMR releases 5.1.0 through 5.9.1, there are two options for scale-down behavior: terminate at the instance-hour boundary for Amazon EC2 billing, or terminate at task completion. Starting with Amazon EMR release 5.10.0, the setting for termination at instance-hour boundary is deprecated because of the introduction of per-second billing in Amazon EC2. We do not recommend specifying termination at the instance-hour boundary in versions where the option is available.


If you use the AWS CLI to issue a modify-instance-groups with EC2InstanceIdsToTerminate, these instances are terminated immediately, without consideration for these settings, and regardless of the status of applications running on them. Terminating an instance in this way risks data loss and unpredictable cluster behavior.

When terminate at task completion is specified, Amazon EMR deny lists and drains tasks from nodes before terminating the Amazon EC2 instances. With either behavior specified, Amazon EMR does not terminate Amazon EC2 instances in core instance groups if it could lead to HDFS corruption.

Terminate at task completion

Amazon EMR allows you to scale down your cluster without affecting your workload. Amazon EMR gracefully decommissions YARN, HDFS, and other daemons on core and task nodes during a resize down operation without losing data or interrupting jobs. Amazon EMR only reduces instance group size if the work assigned to the groups has completed and they are idle. For YARN NodeManager Graceful Decommission, you can manually adjust the time a node waits for decommissioning.

This time is set using a property in the YARN-site configuration classification. Using Amazon EMR release 5.12.0 and later, specify the YARN.resourcemanager.nodemanager-graceful-decommission-timeout-secs property. Using earlier Amazon EMR releases, specify the YARN.resourcemanager.decommissioning.timeout property.

If there are still running containers or YARN applications when the decommissioning timeout passes, the node is forced to be decommissioned and YARN reschedules affected containers on other nodes. The default value is 3600s (one hour). You can set this timeout to be an arbitrarily high value to force graceful reduction to wait longer. For more information, see Graceful Decommission of YARN nodes in the Apache Hadoop documentation.

Task node groups

Amazon EMR intelligently selects instances that do not have tasks that are running against any step or application, and removes those instances from a cluster first. If all instances in the cluster are in use, Amazon EMR waits for tasks to complete on an instance before removing it from the cluster. The default wait time is 1 hour. This value can be changed with the YARN.resourcemanager.decommissioning.timeout setting. Amazon EMR dynamically uses the new setting. You can set this to an arbitrarily large number to ensure that Amazon EMR doesn't terminate any tasks while reducing the cluster size.

Core node groups

On core nodes, both YARN NodeManager and HDFS DataNode daemons must be decommissioned for the instance group to reduce. For YARN, graceful reduction ensures that a node marked for decommissioning is only transitioned to the DECOMMISSIONED state if there are no pending or incomplete containers or applications. The decommissioning finishes immediately if there are no running containers on the node at the beginning of decommissioning.

For HDFS, graceful reduction ensures that the target capacity of HDFS is large enough to fit all existing blocks. If the target capacity is not large enough, only a partial amount of core instances are decommissioned such that the remaining nodes can handle the current data residing in HDFS. You should ensure additional HDFS capacity to allow further decommissioning. You should also try to minimize write I/O before attempting to reduce instance groups. Excessive write I/O might delay completion of the resize operation.

Another limit is the default replication factor, dfs.replication inside /etc/hadoop/conf/hdfs-site. When it creates a cluster, Amazon EMR configures the value based on the number of instances in the cluster: 1 with 1-3 instances, 2 for clusters with 4-9 instances, and 3 for clusters with 10+ instances.

  1. Setting dfs.replication to 1 on clusters with fewer than four nodes can lead to HDFS data loss if a single node goes down. We recommend you use a cluster with at least four core nodes for production workloads.

  2. Amazon EMR will not allow clusters to scale core nodes below dfs.replication. For example, if dfs.replication = 2, the minimum number of core nodes is 2.

  3. When you use Managed Scaling, Auto-scaling, or choose to manually resize your cluster, we recommend that you to set dfs.replication to 2 or higher.

Graceful reduction doesn't let you reduce core nodes below the HDFS replication factor. This is to allow HDFS to close files due insufficient replicas. To circumvent this limit, lower the replication factor and restart the NameNode daemon.

Configure Amazon EMR scale-down behavior


The terminate at instance hour scale-down behavior option is no longer supported for Amazon EMR release 5.10.0 and later. The following scale-down behavior options only appear in the Amazon EMR console for releases 5.1.0 through 5.9.1.

You can use the AWS Management Console, the AWS CLI, or the Amazon EMR API to configure scale-down behavior when you create a cluster.


We’ve redesigned the Amazon EMR console to make it easier to use. See What's new with the console? to learn about the differences between the old and new console experiences.

New console
To configure scale-down behavior with the new console
  1. Sign in to the AWS Management Console, and open the Amazon EMR console at

  2. Under EMR on EC2 in the left navigation pane, choose Clusters, and then choose Create cluster.

  3. In the Cluster scaling and provisioning option section, find Cluster termination and choose to manually terminate your cluster or have Amazon EMR terminate your cluster after a specified amount of idle time. Optionally, turn on termination protection against bugs or errors.

  4. Choose any other options that apply to your cluster.

  5. To launch your cluster, choose Create cluster.

Old console
To configure scale-down behavior with the old console
  1. Open the Amazon EMR console at

  2. Choose Create cluster. Go to Advanced options and choose your configuration settings in Step 1: Software and Steps and Step 2: Hardware.

  3. In Step 3: General Cluster Settings, select your preferred scale-down behavior. Complete the remaining configurations and create your cluster.

To configure scale-down behavior with the AWS CLI
  • Use the --scale-down-behavior option to specify either TERMINATE_AT_INSTANCE_HOUR or TERMINATE_AT_TASK_COMPLETION.