Creating an MRS Cluster

Scenarios

This section describes how to create an MRS analysis cluster using APIs. For details on how to call APIs, see Making an API Request.

Constraints

• A VPC and subnet have been created in the region where the cluster is to be created, for details, see VPC > Querying VPCs and VPC > Creating a VPC and Subnet > Querying Subnets and Subnet > Creating a Subnet operations.
• You have obtained the region and AZ information about the cluster region. from the administrator. .
• You have obtained the project ID of the region where the cluster is to be created. For details, see Obtaining a Project ID.
• You have determined the version of the cluster to be created and the components supported by the version.
• In this example, an analysis cluster is created.

Procedure

• API

  URI format: POST /v2/{project_id}/clusters

  For details, see Creating Clusters.

• Request example

  POST: https://{endpoint}/v2/{project_id}/clusters

  • Obtain the {endpoint} information from the administrator. .
  • For details about {project_id}, see Obtaining a Project ID.
  • Obtain the value of node_size from the cluster creation page on the MRS console.
  Body:

  {
    "cluster_version": "MRS 3.1.0",
    "cluster_name": "mrs_Demo",
    "cluster_type": "ANALYSIS",
    "charge_info": {
  	  "charge_mode": "postPaid"
    },
    "region": "",
    "availability_zone": "",
    "vpc_name": "vpc-37cd",
    "subnet_name": "subnet-ed99",
    "components": "Hadoop,Spark2x,HBase,Hive,Hue,Flink,Oozie,Ranger,Tez",
    "safe_mode": "KERBEROS",
    "manager_admin_password": "Mrs@1234",
    "login_mode": "PASSWORD",
    "node_root_password": "Mrs@1234",
    "log_collection": 1,
    "mrs_ecs_default_agency": "MRS_ECS_DEFAULT_AGENCY",
    "tags": [
      {
        "key": "tag1",
        "value": "111"
      },
      {
        "key": "tag2",
        "value": "222"
      }
    ], 
    "node_groups": [
      {
        "group_name": "master_node_default_group",
        "node_num": 2,
        "node_size": "rc3.4xlarge.4.linux.bigdata",
        "root_volume": {
          "type": "SAS",
          "size": 480
        },
        "data_volume": {
          "type": "SAS",
          "size": 600
        },
        "data_volume_count": 1
      },
     {
        "group_name": "core_node_analysis_group",
        "node_num": 3,
        "node_size": "rc3.4xlarge.4.linux.bigdata",
        "root_volume": {
          "type": "SAS",
          "size": 480
        },
        "data_volume": {
          "type": "SAS",
          "size": 600
        },
        "data_volume_count": 1
      },
      {
        "group_name": "task_node_analysis_group",
        "node_num": 3,
        "node_size": "rc3.4xlarge.4.linux.bigdata",
        "root_volume": {
          "type": "SAS",
          "size": 480
        },
        "data_volume": {
          "type": "SAS",
          "size": 600
        },
        "data_volume_count": 1,
  	 "auto_scaling_policy": {
                  "auto_scaling_enable": true,
                  "min_capacity": 0,
                  "max_capacity": 1,
                  "resources_plans": [],
                  "exec_scripts": [],
                  "rules": [
                      {
                          "name": "default-expand-1",
                          "description": "",
                          "adjustment_type": "scale_out",
                          "cool_down_minutes": 5,
                          "scaling_adjustment": "1",
                          "trigger": {
                              "metric_id": 2003,
                              "metric_name": "StormSlotAvailablePercentage",
                              "metric_value": 100,
                              "comparison_operator_id": 2003,
                              "comparison_operator": "LTOE",
                              "evaluation_periods": "1"
                          }
                      }
                  ]
              }
      }
    ]
  }

  For details about the parameters, see Creating Clusters.

• Example response

  {
  	"cluster_id": "da1592c2-bb7e-468d-9ac9-83246e95447a"
  }