HDP 3.0 Cloudbreak Deployment possible?

[#1]

Hi,

I just got a Cloudbreak 2.7.1 deployer server running. The press release for HDP 3.0 mentioned that is was possible to deploy 3.0 using Cloudbreak but HDP 3.0 isn't an available option under 2.7.1 (HDP 2.6 only). Do I need to upgrade Cloudbreak, add an MPack or how should I deploy HDP 3.0 via Cloudbreak?

Paul

[#2]

Thanks dsun, that has worked for me. Note I used Dominika's blueprint below but don't know if it makes any difference.

[#3]

@Paul NorrisGlad it helped. If you look at the JSON contents, both Dominika & I are referring to the same blueprint.

[#4]

@Paul Norris It is possible to use Cloudbreak 2.7.1 to deploy HDP 3.0; However, Cloudbreak 2.7.1 does not include any default blueprints for HDP 3.0 and so if you want to use HDP 3.0 you must first:

1) create an HDP 3.0 blueprint. Here is an example:

{
  "Blueprints": {
    "blueprint_name": "hdp30-data-science-spark2-v4",
    "stack_name": "HDP",
    "stack_version": "3.0"
  },
  "settings": [
    {
      "recovery_settings": []
    },
    {
      "service_settings": [
        {
          "name": "HIVE",
          "credential_store_enabled": "false"
        }
      ]
    },
    {
      "component_settings": []
    }
  ],
  "configurations": [
    {
      "core-site": {
        "fs.trash.interval": "4320"
      }
    },
    {
      "hdfs-site": {
        "dfs.namenode.safemode.threshold-pct": "0.99"
      }
    },
    {
      "hive-site": {
        "hive.exec.compress.output": "true",
        "hive.merge.mapfiles": "true",
        "hive.server2.tez.initialize.default.sessions": "true",
        "hive.server2.transport.mode": "http"
      }
    },
    {
      "mapred-site": {
        "mapreduce.job.reduce.slowstart.completedmaps": "0.7",
        "mapreduce.map.output.compress": "true",
        "mapreduce.output.fileoutputformat.compress": "true"
      }
    },
    {
      "yarn-site": {
        "yarn.acl.enable": "true"
      }
    }
  ],
  "host_groups": [
    {
      "name": "master",
      "configurations": [],
      "components": [
        {
          "name": "APP_TIMELINE_SERVER"
        },
        {
          "name": "HDFS_CLIENT"
        },
        {
          "name": "HISTORYSERVER"
        },
        {
          "name": "HIVE_CLIENT"
        },
        {
          "name": "HIVE_METASTORE"
        },
        {
          "name": "HIVE_SERVER"
        },
        {
          "name": "JOURNALNODE"
        },
        {
          "name": "MAPREDUCE2_CLIENT"
        },
        {
          "name": "METRICS_COLLECTOR"
        },
        {
          "name": "METRICS_MONITOR"
        },
        {
          "name": "NAMENODE"
        },
        {
          "name": "RESOURCEMANAGER"
        },
        {
          "name": "SECONDARY_NAMENODE"
        },
        {
          "name": "LIVY2_SERVER"
        },
        {
          "name": "SPARK2_CLIENT"
        },
        {
          "name": "SPARK2_JOBHISTORYSERVER"
        },
        {
          "name": "TEZ_CLIENT"
        },
        {
          "name": "YARN_CLIENT"
        },
        {
          "name": "ZEPPELIN_MASTER"
        },
        {
          "name": "ZOOKEEPER_CLIENT"
        },
        {
          "name": "ZOOKEEPER_SERVER"
        }
      ],
      "cardinality": "1"
    },
    {
      "name": "worker",
      "configurations": [],
      "components": [
        {
          "name": "HIVE_CLIENT"
        },
        {
          "name": "TEZ_CLIENT"
        },
        {
          "name": "SPARK2_CLIENT"
        },
        {
          "name": "DATANODE"
        },
        {
          "name": "METRICS_MONITOR"
        },
        {
          "name": "NODEMANAGER"
        }
      ],
      "cardinality": "1+"
    },
    {
      "name": "compute",
      "configurations": [],
      "components": [
        {
          "name": "HIVE_CLIENT"
        },
        {
          "name": "TEZ_CLIENT"
        },
        {
          "name": "SPARK2_CLIENT"
        },
        {
          "name": "METRICS_MONITOR"
        },
        {
          "name": "NODEMANAGER"
        }
      ],
      "cardinality": "1+"
    }
  ]
}

2) Upload the blueprint to Cloudbreak (you can paste it under the Blueprints menu item).

3) When creating a cluster:

- Under General Configuration, select Platform Version > HDP-3.0 and then your blueprint should appear under Cluster Type

- Under Image Settings, specify Ambari 2.7 and HDP 3.0 public repos (you can find them in Ambari 2.7 docs: https://docs.hortonworks.com/HDPDocuments/Ambari-2.7.0.0/bk_ambari-installation/content/ch_obtaining....

[#5]

Thanks, Dominika, I used your Blueprint and it didn't seem to need me to add the repo's, it had the correct information there automatically.

[#6]

Great! I wasn't sure if Cloudbreak would do it correctly.

[#7]

Hello Dominika, The blueprint in the example given was for Data Science: Apache Spark 2, Apache Zeppelin.

Do you have a sample blueprint for HDP 3.0 - EDW-ETL: Apache Hive, Apache Spark 2 which I can run on Cloudbreak 2.7.x?

[#8]

@Pushpak Nandi I do not have any EDW-ETL blueprint for HDP 3.1. Last time I heard the plan was to only ship EDW-Analytics with HDP 3.1.

[#9]

@Dominika Bialek:Thanks for your quick response.