Course Outline

Big Data Overview:

  • Definition of Big Data
  • Reasons for the Growing Popularity of Big Data
  • Case Studies in Big Data Applications
  • Characteristics of Big Data
  • Solutions and Tools for Managing Big Data

Hadoop & Its Components:

  • Overview of Hadoop and its Key Components
  • Hadoop Architecture and Data Handling Capabilities
  • Historical Background of Hadoop, Adoption by Companies, and Motivations for Usage
  • Detailed Explanation of the Hadoop Framework and Its Components
  • Introduction to HDFS and Data Operations in the Hadoop Distributed File System
  • Instructions for Setting Up a Hadoop Cluster in Various Modes (Stand-alone, Pseudo, Multi-Node)

This includes setting up a Hadoop cluster using VirtualBox, KVM, or VMware, network configurations, running Hadoop daemons, and testing the cluster.

  • Overview of the MapReduce Framework and Its Functionality
  • Executing MapReduce Jobs on a Hadoop Cluster
  • Understanding Replication, Mirroring, and Rack Awareness in Hadoop Clusters

Hadoop Cluster Planning:

  • Strategies for Planning a Hadoop Cluster
  • Hardware and Software Requirements for Hadoop Cluster Planning
  • Workload Analysis to Optimize Cluster Performance and Prevent Failures

What is MapR and Why Use MapR:

  • Overview of MapR and Its Architecture
  • Functionality of the MapR Control System, Volumes, Snapshots, and Mirrors
  • Cluster Planning Considerations for MapR
  • Comparison of MapR with Other Distributions and Apache Hadoop
  • Installation and Deployment of a MapR Cluster

Cluster Setup & Administration:

  • Management of Services, Nodes, Snapshots, Mirror Volumes, and Remote Clusters
  • Node Management Techniques
  • Integration of Hadoop Components with MapR Services
  • Accessing Data on the Cluster via NFS and Managing Services & Nodes
  • Data Management Using Volumes, User and Group Management, Role Assignment to Nodes, Node Commissioning and Decommissioning, Cluster Administration, Performance Monitoring, Metric Analysis, and MapR Security Configuration
  • Working with M7—Native Storage for MapR Tables
  • Cluster Configuration and Tuning for Optimal Performance

Cluster Upgrade and Integration with Other Setups:

  • Procedures for Upgrading the Software Version of MapR and Types of Upgrades
  • Configuring a MapR Cluster to Access an HDFS Cluster
  • Setting Up a MapR Cluster on Amazon Elastic MapReduce

All the topics include Demonstrations and Practical Sessions for Learners to Gain Hands-On Experience with the Technology.

Requirements

  • Fundamental understanding of the Linux file system for government use.
  • Basic proficiency in Java programming.
  • Knowledge of Apache Hadoop is recommended for government applications.
 28 Hours

Number of participants


Price per participant

Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.

Testimonials (1)

practical things of doing, also theory was served good by Ajay

Dominik Mazur - Capgemini Polska Sp. z o.o.
Course - Hadoop Administration on MapR

Upcoming Courses

Hadoop Administration on MapR

2026-03-02 09:30
28 hours
Fort Smith, AR
$ 5405 (Online)
$ 7805 (Classroom)

Hadoop Administration on MapR

2026-03-16 09:30
28 hours
Fort Wayne, IN - Regus – Power Center
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Hadoop Administration on MapR

2026-03-30 09:30
28 hours
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Hadoop Administration on MapR

2026-04-13 09:30
28 hours
Gulfport, MS
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