India

Hadoop Admin Intellipaat Online Training Course

This course covers Hadoop architecture and its components, installation process, monitoring and troubleshooting of the complex Hadoop issues.
1st Floor, 10th Cross,28th Main,Bangalore
9784286179

Course at a Glance

Mode of learning : Online - Self Paced

Domain / Subject : Engineering & Technology

Function : Information Technology(IT)

Duration : 26 Hours

Difficulty : Basic

Introduction

Hadoop Administration training for System Administrators is designed for technical operations personnel whose job is to install and maintain production Hadoop clusters in real world. We will cover Hadoop architecture and its components, installation process, monitoring and troubleshooting of the complex Hadoop issues. The Hadoop admin training is focused on practical hands-on exercises and encourages open discussions of how people are using Hadoop in enterprises dealing with large data sets.

Key Highlights !

1. 26hrs duration of videos which means we cover all the topics in very detail as compared to anyone in the industry
2. 24/7 Access to the training material and Videos
3. 3 months access to the enrolled courses
4. Intellipaat fully loaded Virtual Machine which contains all the softwares
5. Course is designed for clearing Cloudera certification
6. 200 Questions quiz simulator for interview preparation and Cloudera certification.
7. Project work at the end of the training to show how Hadoop is used in the Industry and explains each and every aspect of it from designing, architecture , data movement.

OBJECTIVE of this hadoop online certification Training for Big-data:

1. Understand Hadoop main components and Architecture

2. Be comfortable working with Hadoop Distributed File System

3. Understand MapReduce abstraction and how it works

4. Plan your Hadoop cluster

5. Deploy and administer Hadoop cluster

6. Optimize Hadoop cluster for the best performance based on specific job requirements

7. Monitor a Hadoop cluster and execute routine administration procedures

8. Deal with Hadoop component failures and recoveries

9. Get familiar with related Hadoop projects: Hbase, Hive and Pig

10. Know best practices of using Hadoop in enterprise world

Course Outline

1.Introduction to Hadoop

  • The amount of data processing in today’s life
  • What Hadoop is why it is important?
  • Hadoop comparison with traditional systems
  • Hadoop history
  • Hadoop main components and architecture

2.Hadoop Distributed File System (HDFS)

  • HDFS overview and design
  • HDFS architecture
  • HDFS file storage
  • Component failures and recoveries
  • Block placement
  • Balancing the Hadoop cluster

3.Planning your Hadoop cluster

  • Planning a Hadoop cluster and its capacity
  • Hadoop software and hardware configuration
  • HDFS Block replication and rack awareness
  • Network topology for Hadoop cluster

4.Hadoop Deployment

  • Different Hadoop deployment types
  • Hadoop distribution options
  • Hadoop competitors
  • Hadoop installation procedure
  • Distributed cluster architecture

Lab: Hadoop Installation

5.Working with HDFS

  • Ways of accessing data in HDFS
  • Common HDFS operations and commands
  • Different HDFS commands
  • Internals of a file read in HDFS
  • Data copying with ‘distcp’

Lab: Working with HDFS

6.Map-Reduce Abstraction

  • What MapReduce is and why it is popular
  • The Big Picture of the MapReduce
  • MapReduce process and terminology
  • MapReduce components failures and recoveries
  • Working with MapReduce

7.Hadoop Cluster Configuration

  • Hadoop configuration overview and important configuration file
  • Configuration parameters and values
  • HDFS parameters MapReduce parameters
  • Hadoop environment setup
  • ‘Include’ and ‘Exclude’ configuration files

Lab: MapReduce Performance Tuning

8.Hadoop Administration and Maintenance

  • Namenode/Datanode directory structures and files
  • File system image and Edit log
  • The Checkpoint Procedure
  • Namenode failure and recovery procedure
  • Safe Mode
  • Metadata and Data backup
  • Potential problems and solutions / what to look for
  • Adding and removing nodes

Lab: MapReduce File system Recovery

9.Hadoop Monitoring and Troubleshooting

  • Best practices of monitoring a Hadoop cluster
  • Using logs and stack traces for monitoring and troubleshooting
  • Using open-source tools to monitor Hadoop cluster

10.Job Scheduling

  • How to schedule Hadoop Jobs on the same cluster
  • Default Hadoop FIFO Schedule
  • Fair Scheduler and its configuration

Hadoop Multi Node Cluster Setup and Running Map Reduce Jobs on Amazon Ec2

  • Hadoop Multi Node Cluster Setup using Amazon ec2 – Creating 4 node cluster setup

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