Big Data Hadoop Administration Online Training

Learning Objectives of Hadoop Administration

In this module, a student will understand all the features of Apache Hadoop and Big Data, Hadoop functionality to solve Big Data problems, Introduction to MapReduce framework, Hadoop Cluster Architecture, Role of a Hadoop Cluster Administrator, and Hadoop Data Loading techniques.

The covered topics in the training

  • A comprehensive introduction to Big Data
  • A typical Hadoop Cluster
  • Cases, where Big Data is, is utilized
  • Hadoop framework Introduction 
  • Hadoop Architecture and MapReduce Framework
  • HDFS File system
  • Hadoop Administrator – Roles &Responsibilities, Current Job Market

Hadoop Architecture and Cluster setup:

Learning Objectives:

 after the Hadoop Administration module, learners will understand the objective of Multiple Hadoop Server with its roles like DataNode and NameNode, as well as MapReduce data processing. They’ll also understand the comprehensive purpose of Hadoop 2.x Cluster, its setup and configuration along with how to Setting up Hadoop Clients using Hadoop 2.x. This will also help to understand the important Hadoop configuration files, their roles, and the required parameters.

Topics that are covered in Hadoop Administration Training

  • Role of the Hadoop server and their usage
  • Initial Configuration with Hadoop Installation
  • Understand the communication channels of DataNode and NameNode
  • Setup of Single Node Cluster
  • Details of NameNode Metadata
  • Multi-Node Cluster Setup
  • Deploying Hadoop in pseudo-distributed mode
  • Pass phrase less Access Setup 
  • Rack Awareness with Anatomy of reading and writing
  • Data Processing
  • Replication Pipeline
  • Hadoop Clients’ installation
  • Scalability — the best practices.
  • Addition/Removal of nodes into the cluster/from the cluster.

Value Ads (as per the most advanced industry standards)

  • Running Hadoop Administration on the cloud 
  • Installation and administration of Cloudera MGR and HDP
  • connectivity and administration to AWS
  • Cluster Monitoring and 
  • Troubleshooting

Duration and Timings of the Hadoop Administration Training

  • Total Duration – 30 Hours
  • Training Type – Online Live Interactive Session
  • Faculty – Experienced

Key Features of Hadoop Administration Training

  • 60 hours of blended online learning
  • Includes 4 projects that real industry-based 
  • Includes 3 simulation exams for testing the Hadoop admin skills
  • Self-paced learning – Lifetime access
  • A dedicated session for mentoring from experts

Pre-requisites – Linux Knowledge [Basic Linux commands]

  • Linux Administration classes are also taken as a part of the course if people are not aware of Linux.
  • Ansible Administration

Hadoop Administration Course Content

  • What is Big Data?
  • Where Big Data is coming from?
  • What are Big Data use cases?
  • How Data is growing?
  • What are different varieties of Big Data?
  • What are the challenges in Big Data Storage & Access?
  • Why Hadoop?
  • What is Hadoop?
  • What is Hadoop History?
  • What are Hadoop distributions?
  • What are Hadoop components?
  • Hadoop Architecture
  • Understanding File System
  • Understanding Hadoop Distributed File System (HDFS)
  • HDFS Replication
  • HDFS Components
    • Name Node
    • Data Node
    • Secondary Name Node /Standby Namenode
    • Journal nodes
    • Zookeeper Failover controller
  • HDFS Features
  • HDFS Design Assumptions
  • Formatting Name Node
  • Communication between Nodes in a Cluster
  • How Metadata is maintained in Hadoop?
  • Types of Metadata
  • What is HDFS Block Report?
  • Check Pointing Mechanism
  • Metadata Memory Allocation
  • Anatomy of a File Writeinto& Read from HDFS
  • HDFS Block Replication Strategy
  • How to deal with Data Corruption?
  • HDFS Rebalancing &Space Reclamation
  • File Systems supported by Hadoop
  • Compression Formats supported by Hadoop
  • HDFS Federation
  • HDFS Balancer
    • Based on Blockpool ID
    • Based on Datanode
    • Based on Intranode balancer
  • Disk Failures and Replacement
  • Health checks and utilization of the cluster
  • HDFS commands [Day to day operations]
  • Map Reduce Introduction
  • How Map Reduce works?
  • Communication between Job Tracker and Task Tracker
  • Anatomy of a Map Reduce Job Submission
  • JOB Submission and Troubleshooting.
  • Hadoop 2.X Architecture
  • What is Edge/Gateway/Connecting Node?
  • What is Zookeeper?
  • Zookeeper Failover controllers
  • Different Types of Znodes
  • Difference between Hadoop 1.X and Hadoop 2.X
  • Understand the architecture of YARN
  • Understand the components of the YARN Resource Manager
  • Demonstrate the relationship between Node Managers and Application Master
  • Demonstrate the relationship between Resource Manager and Application Master
  • Explain the relationship between Containers and Application Masters
  • Job Flow in YARN
  • Different Shapes used in Flow & their purpose
  • Create Main Flow/Process flow
  • Create a Sub-flow/Screen flow
  • How to run the flow or creating work object
  • Create Tabbed/Tree navigation Screen Flow
  • Call a Sub-flow from another flow or from same flow
  • Design and Implement Screen flow
  • How to select Screen flow types

High Availability of Hadoop Components

  • Name node High Availability
    • Using Shared Edits by using Journal nodes
    • Using Zookeeper Quorum
  • Resource Manager HA
  • HiveServer2 HA
  • HMaster HA
  • Understanding Hardware Components
    • Master Hardware
    • Slave Hardware
    • CPU
    • I/O
    • Network
  • Plan your cluster growth
  • Managing Users & Groups
  • Cluster sharing across multiple use cases
  • Understand the minimum hardware and software requirements
  • Understand the Cloudera Architecture
  • Understand how to install CDH using Cloudera Manager
  • Understand complete deployment layout
  • Understand how to configure and manage different services
  • Understand different configuration parameters


  • Cloudera Cluster Installation
  • Understand the minimum hardware and software requirements
  • Understand the Ambari Architecture
  • Understand how to install Ambari& Hortonworks
  • Understand complete deployment layout
  • Understand how to configure and manage different services
  • Understand different configuration parameters


  • Hortonworks Cluster Installation
  • Understand the minimum hardware and software requirements
  • Understand the MCS Architecture
  • Understand various services configured in MapR
  • Monitor using the CM or Ambari UI
  • Back up and recover Hadoop data
  • Use Hadoop snapshots
  • Understand security concepts
    • Encryption at Rest
    • TLS/SSL
    • Sentry
  • Understanding & ConfiguringHadoop ACLs
  • Understanding & Configuring Kerberos
    • Different types of Kerberos
      • MIT
      • AD Integration
    • Working Mechanism
  • Introduction to Sqoop
  • Introduction to Kafka
  • Introduction to Pig
  • Introduction to Hive
  • Introduction to HBase
  • Introduction to Oozie
  • Introduction to solr
  • Introduction to Impala
  • Introduction to Spark
  • Hadoop Cluster Backup
  • Hadoop Cluster Upgrade
  • OS & Hadoop Patching
  • Hadoop Performance Turning from OS Level
  • Hadoop Performance Turning from HDFS Level (Storage Layer)
  • Hadoop Performance Turning from MR/YARN Level (Processing Layer)
  • Hadoop Performance Turning at ecosystems level
  • Day to Day Admin Activities
  • Frequently Occurring Issues
  • Roles and Responsibilities
  • Interview Preparation
  • Resume Preparation
  • Real time issues discussion and project discussion.

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