Top 26 Apache Ambari Interview Questions You Must Prepare 02.Mar.2024

The shell is developed in Java and it actually based on Ambari REST client and the spring shell framework.

The following code will do help you to create an Ambari client:

from ambari_client.ambari_api import  AmbariClient

headers_dict={'X-Requested-By':'mycompany'} #Ambari needs X-Requested-By header

client = AmbariClient("localhost", 8080, "admin", "admin", version=1,http_header=headers_dict)

print client.version

print client.host_url


all_clusters = client.get_all_clusters()

print all_clusters.to_json_dict()

print all_clusters

The Apache Ambari is compatible with 64-bit version and the following are the operating systems that go well with Ambari implementation:

  1. Debian 7
  2. Ubuntu 12 and 14
  3. SLES (Suse Linux Enterprise Server) 11
  4. OEL (Oracle Enterprise Linux 6) and 7
  5. CentOS 6 and 7
  6. RHEL ( Redhat Enterprise Linux) 6 and 7

There are two ways to deploy the local repositories. It actually depends on your active Internet connection and based on that we can execute it.

  1. First of all mirror the packages to the local repository
  2. If the first method doesn’t work out good for you then download all the Repository Tarball and start building the Local repository

The other components of Ambari that are imported for Automation and Integration are actually divided into three pieces of information:

  1. Ambari Stacks
  2. Ambari Blueprints
  3. Ambari API

Actually, Ambari is built from scratch to make sure that it deals with Automation and Integration problems carefully.

The independent extensions that are contributed to the Ambari Codebase are as follows:

  1. Ambari SCOM Management Pack
  2. Apache Slider View

The types of Ambari Repositories are listed below:

  1. Ambari: This is for Ambari server, Ambari agent and other monitoring software packages
  2. HDP: This is used to host Hadoop Stack packages
  3. HDP-UTILS: All the utility packages for Ambari and HDP are available
  4. EPEL: It stands for “Extra Packages for Enterprise Linux. It has a set of additional packages for the Enterprise Linux

This process is only used when there is no active internet connection is not available.

So to set up a local repository, please follow the below steps:

  1. First and foremost, set up a host with Apache httpd
  2. Next is to download Tarball copy for every repository entire contents
  3. Once it is downloaded, one has to extract the contents

The following is the list of items that need to be checked before actually deploying the Hadoop instance:

  1. Check for existing installations
  2. Set up passwordless SSH
  3. Enable NTP on the clusters
  4. Check for DNS
  5. Disable the SELinux
  6. Disable iptables

With the help of Ambari, system administrators will be able to do the following easily, they are:

  1. Provision of Hadoop Cluster
  2. Manage a Hadoop cluster
  3. Monitor a Hadoop Cluster

The three layers that are supported by Ambari are below:

  1. Core Hadoop
  2. Essential Hadoop
  3. Hadoop Support

The Ambari has a defined life cycle commands and they are as follows:

  1. Start
  2. Stop
  3. Status
  4. Install
  5. Configure

It is one of the tools that is used in Ambari, it is mainly used for the following purpose:

  1. First and foremost it is used for health checking and alerts purpose
  2. The alert emails can be one of notifications type, service type, host address etc

The Yum is nothing but a package manager which actually fetches the software packages from the repository.

On RHEL/CentOS, typically “yum”,

ON SLES, typically “Zipper”.

The following tools are needed to build Ambari:

  1. If you are using Mac then you have to download Xcode from the apple store.
  2. JDK 7
  3. Apache Maven 3.3.9 or later
  4. Python 2.6 or later
  5. Node JS
  6. G++

The following are the commands that are used to do the following activities:

To start the Ambari server
ambari-server start

To check the Ambari server processes
ps -ef | grep Ambari

To stop the Ambari server
ambari-server stop

all_hosts = client.get_all_hosts()

print all_hosts

print all_hosts.to_json_dict()


The Ambari shell can provide an interactive and handy command line tool which actually supports the following:

  1. All the available functionality in Ambari Web-app
  2. All the context-aware command availability
  3. Tab completion
  4. Any required parameter support if needed

The latest version of Ambari that is available in the market is Ambari 2.5.@Within, this version they have added a feature called: Cross stack upgrade support.

The Apache Ambari is nothing but a project which is solely focused to make life simple while using Hadoop management system.

This software helps or provides comfort zone in terms of the following aspect:

  1. Provisioning
  2. Managing
  3. Monitoring Hadoop clusters
  4. Provides intuitive interface
  5. It is backed up RESTful API’s.
  6. Provides an easy to use Hadoop management web UI

Ambari Monitoring tools actually use two different open source projects for its monitoring purposes,

they are as follows:

  1. Ganglia
  2. Nagios

A local repository is nothing but a hosted space in the local environment. Usually, when the machines don't have an active internet connection or have restricted or very limited network access a local repository should be set up. With this setup, the user will be able to obtain Ambari and HDP software packages.

A repository is nothing but space where it hosts the software packages which can be used for download and plus install.

The Apache Ambari is a great gift for individuals who use Hadoop in their day to day work life.

With the use of Ambari, Hadoop users will get the core benefits:

  1. Installation process is simplified
  2. Configuration and overall management is simplified
  3. It has a centralized security setup process
  4. It gives out full visibility in terms of Cluster health
  5. It is extensively extendable and has an option to customize if needed.

It is one of the tools that is used in Ambari, it is mainly used for the following purpose:

  1. Monitoring
  2. Identifying trending patterns
  3. Metrics collection in the clusters
  4. It also supports detailed heatmaps