Resources Corporate Training Blog

Hadoop Administration Certification Training

Download Course View More

Hadoop Administration Certification Training

Apache Hadoop™ is an effective and dynamic data platform that simplifies and allows for the distributed processing of large data sets across clusters of computers and servers.Hadoop Administrator Training will give you the technical understanding required to manage a Hadoop cluster, either in a development or a production environment. This course introduces the fundamental concepts of Apache Hadoop™ and Hadoop Cluster. You will get the background to be able to configure, deploy and maintain a Hadoop cluster, and to confidently navigate the Hadoop ecosystem.

Why Should You Choose This Certification?

  • To use Apache Hadoop™ to build powerful applications to analyse Big Data.
  • About the Hadoop Distributed File System (HDFS).
  • How to setup, manage and monitor Hadoop cluster.
  • The basis of Apache Hive, how to install Hive, run HiveQL queries to create tables, load data etc.
  • About Apache Pig, Pig Latin scripting language.
Download Course

Hadoop Administration - Instructor Led Training

15 th  October
Sat&Sun (4 Weeks) Weekends Batches
Timings: 07:00 AM - 11:30AM(IST)
Sold Out
25 th  October
Sat&Sun (4 Weeks) Weekends Batches
Timings: 07:00 AM - 11:30AM(IST)
Filling Fast
1 st  November
Sat&Sun (4 Weeks) Weekends Batches
Timings: 07:00 AM - 11:30AM(IST)


  • Introduction to Big Data
  • Common big data domain scenarios
  • Limitations of traditional solutions
  • What is Hadoop?
  • Hadoop 1.0 ecosystem and its Core Components
  • Hadoop 2.x ecosystem and its Core Components
  • Application submission in YARN
  • Distributed File System
  • Hadoop Cluster Architecture
  • Replication rules
  • Hadoop Cluster Modes
  • Rack awareness theory
  • Hadoop cluster administrator responsibilities
  • Understand working of HDFS
  • NTP server
  • Initial configuration required before installing Hadoop
  • Deploying Hadoop in a pseudo-distributed mode
  • OS Tuning for Hadoop Performance
  • Pre-requisite for installing Hadoop
  • Hadoop Configuration Files
  • Stale Configuration
  • RPC and HTTP Server Properties
  • Properties of Namenode, Datanode and Secondary Namenode
  • Log Files in Hadoop
  • Deploying a multi-node Hadoop cluster
  • Commisioning and Decommissioning of Node
  • HDFS Balancer
  • Namenode Federation in Hadoop
  • High Availabilty in Hadoop
  • Trash Functionality
  • Checkpointing in Hadoop
  • Distcp
  • Disk balancer
  • Different Processing Frameworks
  • Different phases in Mapreduce
  • Spark and its Features
  • Application Workflow in YARN
  • YARN Metrics
  • YARN Capacity Scheduler and Fair Scheduler
  • Service Level Authorization (SLA)
  • Planning a Hadoop 2.x cluster
  • Cluster sizing
  • Hardware, Network and Software considerations
  • Popular Hadoop distributions
  • Workload and usage patterns
  • Industry recommendations
  • Monitoring Hadoop Clusters
  • Hadoop Security System Concepts
  • Securing a Hadoop Cluster With Kerberos
  • Common Misconfigurations
  • Overview on Kerberos
  • Checking log files to understand Hadoop clusters for troubleshooting
  • Visualize Cloudera Manager
  • Features of Cloudera Manager
  • Build Cloudera Hadoop cluster using CDH
  • Installation choices in Cloudera
  • Cloudera Manager Vocabulary
  • Cloudera terminologies
  • Different tabs in Cloudera Manager
  • What is HUE?
  • Hue Architecture
  • Hue Interface
  • Hue Features
  • Explain Hive
  • Hive Setup
  • Hive Configuration
  • Working with Hive
  • Setting Hive in local and remote metastore mode
  • Pig setup
  • Working with Pig
  • What is NoSQL Database
  • HBase data model
  • HBase Architecture
  • MemStore, WAL, BlockCache
  • HBase Hfile
  • Compactions
  • HBase Read and Write
  • HBase balancer and hbck
  • HBase setup
  • Working with HBase
  • Installing Zookeeper
  • Oozie overview
  • Oozie Features
  • Oozie workflow, coordinator and bundle
  • Start, End and Error Node
  • Action Node
  • Join and Fork
  • Decision Node
  • Oozie CLI
  • Install Oozie
  • Types of Data Ingestion
  • HDFS data loading commands
  • Purpose and features of Sqoop
  • Perform operations like, Sqoop Import, Export and Hive Import
  • Sqoop 2
  • Install Sqoop
  • Import data from RDBMS into HDFS
  • Flume features and architecture
  • Types of flow
  • Install Flume
  • Ingest Data From External Sources With Flume
  • Best Practices for Importing Data

About Hadoop Administration Training

Big Data and Hadoop Administrator course will equip you with all the skills you’ll need for your next Big Data admin assignment. You will learn to work with Hadoop’s Distributed File System, its processing and computation frameworks, core Hadoop distributions, and vendor-specific distributions such as Cloudera. You will learn the need for cluster management solutions and how to set up, secure, safeguard, and monitor clusters and their components such as Sqoop, Flume, Pig, Hive, and Impala with this Big Data Hadoop Admin course.

  • Understand the fundamentals and characteristics of Big Data and various scalability options available to help block size manage Big Data
  • Master the concepts of the Hadoop framework, including architecture, the Hadoop distributed file system, and deployment of Hadoop clusters using core or vendor-specific distributions
  • Use Cloudera manager for setup, deployment, maintenance, and monitoring of Hadoop clusters
  • Understand Hadoop Administration activities and computational frameworks for processing Big Data
  • Work with Hadoop clients, nodes for clients and web interfaces like HUE to work with Hadoop Cluster
  • Use cluster planning and tools for data ingestion into Hadoop clusters, and cluster monitoring activities
  • resource manager Hadoop components within Hadoop ecosystem like Hive, HBase, Spark, and Kafka
  • Understand security implementation to secure data and clusters
  • Systems administrators and IT managers
  • IT administrators and operators
  • IT Systems Engineers
  • Data Engineers and database administrators
  • Data Analytics Administrators
  • Cloud Systems Administrators
  • Web Engineers
  • Individuals who intend to design, deploy and maintain Hadoop cluster

The world is getting increasingly digital, and this means big data is here to stay. In fact, the importance of big data and data analytics is going to continue growing in the coming years. Choosing a career in the field of big data and analytics might just be the type of role that you have been trying to find to meet your career expectations.Professionals who are working in this field can expect an impressive salary, with the median salary for data scientists being $116,000. Even those who are at the entry level will find high salaries, with average earnings of $92,000.

Frequently Asked Question's

Through hands-on practice sessions and exercises, you can learn how to configure backup options, and diagnose and recover node failures in a Hadoop Cluster. Challenges in Big Data and cloud services can be readily addressed. Through a combination of technical theory and practical exercise sessions, software professionals new to Hadoop can quickly learn cluster administration. Our three-day Hadoop Cluster Administration training will give you a jumpstart in understanding and solving real world problems that you may come across while working on Hadoop Cluster.

There are no prerequisites for attending this course.

Your system must fulfill the following requirements:-

  • 64-bit Operating System
  • 8GB RAM

Please send us an email to, and we will answer any queries you may have!