View cluster status and details

After you create a cluster, you can monitor its status and get detailed information about its execution and errors that may have occurred, even after it has terminated. Amazon EMR saves metadata about terminated clusters for your reference for two months, after which the metadata is deleted. You can't delete clusters from the cluster history, but using the AWS Management Console, you can use the Filter, and using the AWS CLI, you can use options with the list-clusters command to focus on the clusters that you care about.

You can access application history stored on-cluster for one week from the time it is recorded, regardless of whether the cluster is running or terminated. In addition, persistent application user interfaces store application history off-cluster for 30 days after a cluster terminates. See View application history.

For more information about cluster states, such as Waiting and Running, see Understanding the cluster lifecycle.

View cluster status using the AWS Management Console

The Clusters List in the Amazon EMR console lists all the clusters in your account and AWS Region, including terminated clusters. The list shows the following for each cluster: the Name and ID, the Status, the Creation time, the Elapsed time that the cluster was running, and the Normalized instance hours that have accrued for all EC2 instances in the cluster. This list is the starting point for monitoring the status of your clusters. It's designed so that you can drill down into each cluster's details for analysis and troubleshooting.

To view an abridged summary of cluster information

• Select the down arrow next to the link for the cluster under Name.

  The cluster's row expands to provide more information about the cluster, hardware, steps, and bootstrap actions. Use the links in this section to drill into specifics. For example, click a link under Steps to access step log files, see the JAR associated with the step, drill into the step's jobs and tasks, and access log files.

  

To view cluster status in depth

• Choose the cluster link under Name to open a cluster details page for the cluster. Use each tab to view information as described in the following section.

  Use each tab for the following information:

  

  Tab	Information
  Summary	Use this tab to view basics of your cluster configuration, such as the URL to use for SSH connections to the master node, what open-source applications Amazon EMR installed when the cluster was created, where logs are stored in Amazon S3, and what version of Amazon EMR was used to create the cluster.
  Application user interfaces	Use this tab to view persistent off-cluster YARN timeline server and Tez UI application details. For Spark jobs, you can drill down into available information about jobs, stages, and executors. For more information, see View application history. On-cluster application user interfaces are available while the cluster is running.
  Monitoring	Use this tab to view graphs depicting key indicators of cluster operation over a time period that you specify. You can view cluster-level data, node-level data, and information about I/O and data storage.
  Hardware	Use this tab to view information about nodes in your cluster, including EC2 instance IDs, DNS names, and IP addresses, and more.
  Events	Use this tab to view the event log for your cluster. For more information, see Monitor CloudWatch events.
  Steps	Use this tab to see the status and access log files for steps that you submitted. For more information about steps, see Work with steps using the AWS CLI and console.
  Configurations	Use this tab to view any customized configuration objects applied to the cluster. For more information about configuration classifications, see Configuring applications in the Amazon EMR Release Guide.
  Bootstrap actions	Use this tab to view the status of any bootstrap actions the cluster runs when it launches. Bootstrap actions are used for custom software installations and advanced configuration. For more information, see Create bootstrap actions to install additional software.

View cluster status using the AWS CLI

The following examples demonstrate how to retrieve cluster details using the AWS CLI. For more information about available commands, see the AWS CLI Command Reference for Amazon EMR. You can use the describe-cluster command to view cluster-level details including status, hardware and software configuration, VPC settings, bootstrap actions, instance groups, and so on. For more information about cluster states, see Understanding the cluster lifecycle. The following example demonstrates using the describe-cluster command, followed by examples of the list-clusters command.

Example Viewing cluster status

To use the describe-cluster command, you need the cluster ID. This example demonstrates using to get a list of clusters created within a certain date range, and then using one of the cluster IDs returned to list more information about an individual cluster's status.

The following command describes cluster j-1K48XXXXXXHCB, which you replace with your cluster ID.

aws emr describe-cluster --cluster-id j-1K48XXXXXXHCB

The output of your command is similar to the following:

{
    "Cluster": {
        "Status": {
            "Timeline": {
                "ReadyDateTime": 1438281058.061, 
                "CreationDateTime": 1438280702.498
            }, 
            "State": "WAITING", 
            "StateChangeReason": {
                "Message": "Waiting for steps to run"
            }
        }, 
        "Ec2InstanceAttributes": {
            "EmrManagedMasterSecurityGroup": "sg-cXXXXX0", 
            "IamInstanceProfile": "EMR_EC2_DefaultRole", 
            "Ec2KeyName": "myKey", 
            "Ec2AvailabilityZone": "us-east-1c", 
            "EmrManagedSlaveSecurityGroup": "sg-example"
        }, 
        "Name": "Development Cluster", 
        "ServiceRole": "EMR_DefaultRole", 
        "Tags": [], 
        "TerminationProtected": false, 
        "ReleaseLabel": "emr-4.0.0", 
        "NormalizedInstanceHours": 16, 
        "InstanceGroups": [
            {
                "RequestedInstanceCount": 1, 
                "Status": {
                    "Timeline": {
                        "ReadyDateTime": 1438281058.101, 
                        "CreationDateTime": 1438280702.499
                    }, 
                    "State": "RUNNING", 
                    "StateChangeReason": {
                        "Message": ""
                    }
                }, 
                "Name": "CORE", 
                "InstanceGroupType": "CORE", 
                "Id": "ig-2EEXAMPLEXXP", 
                "Configurations": [], 
                "InstanceType": "m5.xlarge", 
                "Market": "ON_DEMAND", 
                "RunningInstanceCount": 1
            }, 
            {
                "RequestedInstanceCount": 1, 
                "Status": {
                    "Timeline": {
                        "ReadyDateTime": 1438281023.879, 
                        "CreationDateTime": 1438280702.499
                    }, 
                    "State": "RUNNING", 
                    "StateChangeReason": {
                        "Message": ""
                    }
                }, 
                "Name": "MASTER", 
                "InstanceGroupType": "MASTER", 
                "Id": "ig-2A1234567XP", 
                "Configurations": [], 
                "InstanceType": "m5.xlarge", 
                "Market": "ON_DEMAND", 
                "RunningInstanceCount": 1
            }
        ], 
        "Applications": [
            {
                "Version": "1.0.0", 
                "Name": "Hive"
            }, 
            {
                "Version": "2.6.0", 
                "Name": "Hadoop"
            }, 
            {
                "Version": "0.14.0", 
                "Name": "Pig"
            }, 
            {
                "Version": "1.4.1", 
                "Name": "Spark"
            }
        ], 
        "BootstrapActions": [], 
        "MasterPublicDnsName": "ec2-X-X-X-X.compute-1.amazonaws.com", 
        "AutoTerminate": false, 
        "Id": "j-jobFlowID", 
        "Configurations": [
            {
                "Properties": {
                    "hadoop.security.groups.cache.secs": "250"
                }, 
                "Classification": "core-site"
            }, 
            {
                "Properties": {
                    "mapreduce.tasktracker.reduce.tasks.maximum": "5", 
                    "mapred.tasktracker.map.tasks.maximum": "2", 
                    "mapreduce.map.sort.spill.percent": "90"
                }, 
                "Classification": "mapred-site"
            }, 
            {
                "Properties": {
                    "hive.join.emit.interval": "1000", 
                    "hive.merge.mapfiles": "true"
                }, 
                "Classification": "hive-site"
            }
        ]
    }
}

Example Listing clusters by creation date

To retrieve clusters created within a specific data range, use the list-clusters command with the --created-after and --created-before parameters.

The following command lists all clusters created between October 09, 2019 and October 12, 2019.

aws emr list-clusters --created-after 2019-10-09T00:12:00 --created-before 2019-10-12T00:12:00

Example Listing clusters by state

To list clusters by state, use the list-clusters command with the --cluster-states parameter. Valid cluster states include: STARTING, BOOTSTRAPPING, RUNNING, WAITING, TERMINATING, TERMINATED, and TERMINATED_WITH_ERRORS.

aws emr list-clusters --cluster-states TERMINATED

You can also use the following shortcut parameters to list all clusters in the states specified.:

• --active filters clusters in the STARTING,BOOTSTRAPPING, RUNNING, WAITING, or TERMINATING states.

• --terminated filters clusters in the TERMINATED state.

• --failed parameter filters clusters in the TERMINATED_WITH_ERRORS state.

The following commands return the same result.

aws emr list-clusters --cluster-states TERMINATED

aws emr list-clusters --terminated

For more information about cluster states, see Understanding the cluster lifecycle.