Ambari by default store such information in a PostgreSQL database. We are not going to perform any advanced configuration, we are going to stick with the defaults. So we say no to this prompt. Setup is now complete. Now we are ready to start Ambari. Ambari is now started. We can check the status of Ambari by running ambari-server status command.
We can get to Ambari user interface on port on the node where it is installed. By default the username and password is admin and admin. Here is the ambari home page. We have 3 main options on the home screen, to deploy a cluster, which is what we will do next, to manage users and groups and deploy views.
Think of views as a pluggable UI component. In that case, you can create a small web application using Hadoop API and create a visual representation of the running currently running and the ones that failed and succeeded. You can customize the view as per your need. You need to code the application of course to create a view from scratch. But Ambari already comes with few views to help us perform day to day admin tasks.
We need to provide a name to the cluster. Next, we need to provide the list of nodes that will be part of our Hadoop cluster. A mbari server needs the private key to login to these nodes. So we will select the. The username associated with key is ubuntu so we enter that on this screen. Your form submission has failed. If you have an ad blocking plugin please disable it and close this message to reload the page.
The Tez View helps you understand and optimize your cluster resource usage. Using the view, you can optimize and accelerate individual SQL queries or Pig jobs to get the best performance in a multi-tenant Hadoop environment. It also provides graphical view of the query execution plan.
This helps the user debug the query for correctness and for tuning the performance. It integrates Tez View that allows the user to debug any Tez job, including monitoring the progress of a job whether from Hive or Pig while it is running. This view contribution can be found here. Pig View is similar to the Hive View.
It allows writing and running a Pig script. Summary 4. Troubleshooting Ambari Deployments 1. Getting the Logs 2. Quick Checks 3. Specific Issues 3. Problem: Browser crashed before Install Wizard completed 3. Problem: Install Wizard reports that the cluster install has failed 3. Problem: Trouble starting Ambari on system reboot 3.
Problem: Metrics and Host information display incorrectly in Ambari Web 3. Problem: Multiple Ambari Agent processes are running, causing re-register 3. Problem: Some graphs do not show a complete hour of data until the cluster has been running for an hour 3. Problem: After performing a cluster install the Nagios server is not started 3.
Problem: A service with a customized service user is not appearing properly in Ambari Web 3. Appendix: Installing Ambari Agents Manually 1. SLES 6. Appendix: Using Custom Hostnames 7. Appendix: Upgrading Ambari Server from 1. Preparing for the Upgrade 2.
Setting Up the Ambari Repository 3. Upgrading Ambari Server and Agents 4. Manage a Hadoop Cluster Ambari provides central management for starting, stopping, and reconfiguring Hadoop services across the entire cluster. Monitor a Hadoop Cluster Ambari provides a dashboard for monitoring health and status of the Hadoop cluster. Ambari leverages Ambari Metrics System for metrics collection. Ambari leverages Ambari Alert Framework for system alerting and will notify you when your attention is needed e.
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