Courses

Hadoop Operation Training

By December 23, 2020 No Comments

Course Objectives

By the end of this course participants will acquire broad knowledge of Hadoop framework concepts and usability. The components, purpose and various modules of Hadoop will be outlined first. Practical examples and exercises will be used side by side with the presentation of the contents of the framework. The purpose of deploying Hadoop along with the main traits that differentiates it from traditional approaches will be pointed out. Particular focus will be given to advanced operations as well as the way of making value out of the orchestration of the various modules and applications that run on Hadoop. In the end of the course all the participants are expected to be ready to setup, create, deploy and manage operations running on Hadoop.

Contents

Hadoop Installation and Deployment

  • Components and architecture
  • Installation and configuration basics
  • Deployment types
  • Hosting in the cloud
  • Lab: Installation of Hadoop training environment

Hadoop Distributed File System (HDFS)

  • Overview
  • Architecture
  • File storage
  • Operations and commands

MapReduce

  • Terminology
  • Analysis of the algorithm
  • Examples
  • Design patterns
  • Lab: Implementation and execution of a MapReduce execution scenario

Scheduling, administration and monitoring

  • Scheduling approaches (FIFO, capacity, fair)
  • YARN resource manager
  • Resource manager high-availability
  • Authentication and security
  • Disaster recovery and backup practices
  • Lab: Hands-on experimentation with scheduling and resource planning configurations

Apache HBase

  • Architecture
  • Data model
  • Query language and API

Other applications running on Hadoop

  • Apache Phoenix
  • Apache Cassandra
  • Apache Hive
  • Apache Mahout 

Entry Requirements

Basic Java programming knowledge, database concepts and Linux operating system usage. 

Target Group

IT professionals 

Mode of Delivery

Instructor-led training. The course comprises lectures (accompanied with slides and source code), quizzes and practical hands-on exercises on actual development environment. Realistic working small-scale artifacts are expected to have been produced by the participants in the end of the course. 

Duration

3 days

Language

English

Participants

The suggested number of participants for this course is 8 

Time schedule

The time required always depends on the knowledge of the attending participants and the hours stated below can be used as an estimate.

Day Topics in the course Estimated Time (hours)
1 Components and architecture of Hadoop 0.5
Installation and configuration basics 0.5
Deployment types 0.5
Hosting in the cloud 0.5
Hadoop Distributed File System (HDFS) 1.5
Lab: Installation of Hadoop training environment 2.5
2 MapReduce 1.5
Lab: Implementation and execution of a MapReduce execution scenario 1
Scheduling approaches in Hadoop 1
YARN resource manager 1
Lab: Hands-on experimentation with scheduling and resource planning configurations 1.5
3 High-availability 0.5
Authentication and security 0.5
Disaster recovery and backup practices 0.5
Apache HBase 2.5
Other applications running on Hadoop 2