Hadoop Administration Fundamentals Course Overview

Hadoop Administration Fundamentals Course Overview

The Hadoop Administration Fundamentals course is designed to equip learners with the essential skills and knowledge required to manage and maintain Hadoop clusters. By delving into the course, learners will gain an understanding of Hadoop's history, concepts, and ecosystem, as well as address common myths and challenges associated with Hadoop hardware and software. The course focuses on practical elements, such as planning and installing Hadoop, sizing clusters, and selecting appropriate hardware and network configurations, which are crucial for anyone looking to specialize in Hadoop admin online training.

Throughout various modules, participants will learn about HDFS operations, MapReduce operations, and how to monitor and optimize these systems. Advanced topics cover hardware and software monitoring, cluster expansion, backup, and security with Kerberos. This comprehensive Hadoop admin online training will ensure learners are well-prepared to handle real-world Hadoop administration tasks, thereby enhancing their capabilities to manage big data environments effectively.

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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  • Live Online Training (Duration : 24 Hours)
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  • Live Online Training (Duration : 24 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

You can request classroom training in any city on any date by Requesting More Information

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Course Prerequisites

To successfully undertake the Hadoop Administration Fundamentals course, the following minimum prerequisites are recommended:


  • Basic understanding of Linux or Unix-based operating systems, including common command-line operations and system navigation.
  • Familiarity with basic system administration concepts such as networking, hardware, and software management.
  • Fundamental knowledge of core IT concepts such as databases, servers, and networking.
  • Basic understanding of distributed computing concepts and principles.
  • Some exposure to scripting or programming could be beneficial but is not mandatory.

It is important to note that while these prerequisites are aimed at ensuring a smooth learning experience, the course is designed to be accessible and comprehensive, so a strong willingness to learn and dedication to the subject matter can compensate for a lack of experience in some areas.


Target Audience for Hadoop Administration Fundamentals

The Hadoop Administration Fundamentals course is designed for IT professionals aiming to manage and scale Hadoop clusters effectively.


  • Systems Administrators
  • Database Administrators
  • IT Managers
  • Data Engineers
  • Big Data Architects
  • Data Analytics Professionals
  • Infrastructure Engineers
  • Technical Operations Personnel
  • Cloud Systems Administrators
  • IT professionals involved in Hadoop deployment and maintenance
  • Network Administrators working with big data infrastructures
  • Professionals looking to learn about high availability and disaster recovery in Hadoop clusters
  • IT consultants specializing in Hadoop and big data solutions
  • Technical support engineers who manage Hadoop environments


Learning Objectives - What you will Learn in this Hadoop Administration Fundamentals?

Introduction to Course Outcomes:

The Hadoop Administration Fundamentals course equips students with the skills to manage and scale Hadoop clusters effectively, ensuring high availability and performance.

Learning Objectives and Outcomes:

  • Understand the history and concepts of Hadoop, including its ecosystem, distributions, and high-level architecture.
  • Distinguish Hadoop myths from facts and identify challenges associated with hardware and software in a Hadoop environment.
  • Learn to select appropriate Hadoop distributions, plan the size of clusters for scalability, and understand hardware and network considerations for optimal performance.
  • Gain knowledge of Hadoop Distributed File System (HDFS) operations, including scaling, replication, and health monitoring of nodes and daemons like NameNode and DataNode.
  • Master Hadoop installation procedures, directory structures, log management, and benchmarking techniques for performance tuning.
  • Comprehend the principles of MapReduce, contrasting it with other high-performance computing models, and learn how to monitor and optimize MapReduce jobs and configurations.
  • Acquire the ability to manage YARN architecture and its applications, ensuring efficient resource utilization and job scheduling.
  • Enhance skills in advanced Hadoop administration topics such as cluster monitoring, server management, backup and recovery, and business continuity planning.
  • Execute hardware and software monitoring, perform cluster configuration tweaks, and establish a hardware maintenance schedule.
  • Implement security measures in Hadoop clusters using Kerberos and stay informed about future Hadoop developments and trends.