Considerations and best practices - Amazon EMR
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Considerations and best practices

Consider the following when you create an Amazon EMR cluster with multiple primary nodes:


To launch high-availability EMR clusters with multiple primary nodes, we strongly recommend that you use the latest Amazon EMR release. This ensures that you get the highest level of resiliency and stability for your high-availability clusters.

  • High availability for instance fleets is supported with Amazon EMR releases 5.36.1, 6.8.1, 6.9.1, 6.10.1, 6.11.1, 6.12.0, and higher. For instance groups, high availability is supported with Amazon EMR releases 5.23.0 and higher. To learn more, see About Amazon EMR Releases.

  • On high-availability clusters, Amazon EMR only supports the launch of primary nodes with On Demand instances. This ensures the highest availability for your cluster.

  • You can still specify multiple instance types for primary fleet but all the primary nodes of high-availability clusters are launched with the same instance type, including replacements for unhealthy primary nodes.

  • To continue operations, a high-availability cluster with multiple primary nodes requires two out of three primary nodes to be healthy. As a result, if any two primary nodes fail simultaneously, your EMR cluster will fail.

  • All EMR clusters, including high-availability clusters, are launched in a single Availability Zone. Therefore, they can't tolerate Availability Zone failures. In the case of an Availability Zone outage, you lose access to the cluster.

  • Amazon EMR doesn't guarantee high availability for open-source applications other than the ones that are specified in Supported applications in an Amazon EMR Cluster with multiple primary nodes.

  • In Amazon EMR releases 5.23.0 through 5.30.1, only two of the three primary nodes for an instance group cluster run HDFS NameNode.

Considerations for configuring subnet:

  • An Amazon EMR cluster with multiple primary nodes can reside only in one Availability Zone or subnet. Amazon EMR cannot replace a failed primary node if the subnet is fully utilized or oversubscribed in the event of a failover. To avoid this scenario, it is recommended that you dedicate an entire subnet to an Amazon EMRcluster. In addition, make sure that there are enough private IP addresses available in the subnet.

Considerations for configuring core nodes:

  • To ensure the core nodes are also highly available, we recommend that you launch at least four core nodes. If you decide to launch a smaller cluster with three or fewer core nodes, set dfs.replication parameter to at least 2 for HDFS to have sufficient DFS replication. For more information, see HDFS configuration.

  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.

Considerations for Setting Alarms on Metrics:

  • Amazon EMR doesn't provide application-specific metrics about HDFS or YARN. We reccomment that you set up alarms to monitor the primary node instance count. Configure the alarms using the following Amazon CloudWatch metrics: MultiMasterInstanceGroupNodesRunning, MultiMasterInstanceGroupNodesRunningPercentage, or MultiMasterInstanceGroupNodesRequested. CloudWatch will notify you in the case of primary node failure and replacement.

    • If the MultiMasterInstanceGroupNodesRunningPercentage is lower than 1.0 and greater than 0.5, the cluster may have lost a primary node. In this situation, Amazon EMR attempts to replace a primary node.

    • If the MultiMasterInstanceGroupNodesRunningPercentage drops below 0.5, two primary nodes may have failed. In this situation, the quorum is lost and the cluster can't be recovered. You must manually migrate data off of this cluster.

    For more information, see Setting alarms on metrics.