Long ago, while I was running Cloudera VM 5.10.0.0, I thought to download the most recent version (of that time) to see what modifications or new features were added. I downloaded the VM 5.12.0 and attempted to access Hive and Impala. Because the daemons were not operational, I was unable to complete the task.
I received the following error:
Exception in thread “main” java.lang.RunTimeException: java.net.ConnectException
ConnectionException: Connection refused;
Even in Impala, the daemon is not got connected to Hive metastore.
It took some time to figure out what was required.
This post will help those beginners who is struggling in starting up the daemon services or hosts in Cloudera VM versions.
1) Go to Cloudera Manager.
Open the browser and type the URL “quickstart.cloudera:7180/cmf/login.
2) Enter the credentials. The default username and password will be “cloudera/cloudera”.
3) Once you logged into the “Cloudera Manager”, at the top menu, you’ll see “Hosts” tab. Once you click on it you’ll see the menu-option “All Hosts”. You can either click on “All Hosts” or “Roles” to see the status of the deamons.
4) The “quickstart.cloudera” VM is visible and you can see the status of the “Commission State” of the single node/host which usually be “Commission” unless decommissioned by you. Select the node and click on “Actions for Selected(1)”.
5) Once you click on the “Actions for Selected”, click on the option “Start Roles on Hosts”. This will invoke a dialog box which states you are about to start all the daemon services. If you do not want all the services, you can abort even when the services of the specific daemons are starting.
6) Click on “Confirm” to start the services. This will take a while to start all the daemon services including Hive and Impala.
7) You need not to perform any action while it’s starting. You’ll be able to see if the services are started successfully or if there is any error.
8) Once services are UP, go to the terminal and see if you are able to connect to “Hive” and “Impala”.
Hope you find this article helpful.
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Big Data and SQL 
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