Big Data Hadoop Administration Online Training

Learning Objectives of Hadoop Administration

In this module, a student will understand all the features of Apache Hadoop and Big Data, Hadoop functionality to solve Big Data problems, Introduction to MapReduce framework, Hadoop Cluster Architecture, Role of a Hadoop Cluster Administrator, and Hadoop Data Loading techniques.

The covered topics in the training

A comprehensive introduction to Big Data
A typical Hadoop Cluster
Cases, where Big Data is, is utilized
Hadoop framework Introduction
Hadoop Architecture and MapReduce Framework
HDFS File system
Hadoop Administrator – Roles &Responsibilities, Current Job Market

Hadoop Architecture and Cluster setup:

Learning Objectives:

after the Hadoop Administration module, learners will understand the objective of Multiple Hadoop Server with its roles like DataNode and NameNode, as well as MapReduce data processing. They’ll also understand the comprehensive purpose of Hadoop 2.x Cluster, its setup and configuration along with how to Setting up Hadoop Clients using Hadoop 2.x. This will also help to understand the important Hadoop configuration files, their roles, and the required parameters.

Topics that are covered in Hadoop Administration Training

Role of the Hadoop server and their usage
Initial Configuration with Hadoop Installation
Understand the communication channels of DataNode and NameNode
Setup of Single Node Cluster
Details of NameNode Metadata
Multi-Node Cluster Setup
Deploying Hadoop in pseudo-distributed mode
Pass phrase less Access Setup
Rack Awareness with Anatomy of reading and writing
Data Processing
Replication Pipeline
Hadoop Clients’ installation
Scalability — the best practices.
Addition/Removal of nodes into the cluster/from the cluster.

Value Ads (as per the most advanced industry standards)

Running Hadoop Administration on the cloud
Installation and administration of Cloudera MGR and HDP
connectivity and administration to AWS
Cluster Monitoring and
Troubleshooting

Duration and Timings of the Hadoop Administration Training

Total Duration – 30 Hours
Training Type – Online Live Interactive Session
Faculty – Experienced

Key Features of Hadoop Administration Training

60 hours of blended online learning
Includes 4 projects that real industry-based
Includes 3 simulation exams for testing the Hadoop admin skills
Self-paced learning – Lifetime access
A dedicated session for mentoring from experts

Pre-requisites – Linux Knowledge [Basic Linux commands]

Linux Administration classes are also taken as a part of the course if people are not aware of Linux.
Ansible Administration

Hadoop Administration Course Content

Objective 1.1 – Big Data

What is Big Data?
Where Big Data is coming from?
What are Big Data use cases?
How Data is growing?
What are different varieties of Big Data?
What are the challenges in Big Data Storage & Access?

Objective 1.2 – Hadoop

Objective 2.1 – HDFS

Understanding File System
Understanding Hadoop Distributed File System (HDFS)
HDFS Replication
HDFS Components
- Name Node
- Data Node
- Secondary Name Node /Standby Namenode
- Journal nodes
- Zookeeper Failover controller
HDFS Features
HDFS Design Assumptions
Formatting Name Node
Communication between Nodes in a Cluster
How Metadata is maintained in Hadoop?
Types of Metadata
What is HDFS Block Report?
Check Pointing Mechanism
Metadata Memory Allocation
Anatomy of a File Writeinto& Read from HDFS
HDFS Block Replication Strategy
How to deal with Data Corruption?
HDFS Rebalancing &Space Reclamation
File Systems supported by Hadoop
Compression Formats supported by Hadoop
HDFS Federation
HDFS Balancer
- Based on Blockpool ID
- Based on Datanode
- Based on Intranode balancer
Disk Failures and Replacement
Health checks and utilization of the cluster
HDFS commands [Day to day operations]

Objective 2.2 – Map Reduce

Map Reduce Introduction
How Map Reduce works?
Communication between Job Tracker and Task Tracker
Anatomy of a Map Reduce Job Submission
JOB Submission and Troubleshooting.

Objective 3.1 – Hadoop 2.X

Hadoop 2.X Architecture
What is Edge/Gateway/Connecting Node?
What is Zookeeper?
Zookeeper Failover controllers
Different Types of Znodes
Difference between Hadoop 1.X and Hadoop 2.X
Understand the architecture of YARN
Understand the components of the YARN Resource Manager
Demonstrate the relationship between Node Managers and Application Master
Demonstrate the relationship between Resource Manager and Application Master
Explain the relationship between Containers and Application Masters
Job Flow in YARN

Process Definition

Different Shapes used in Flow & their purpose
Create Main Flow/Process flow
Create a Sub-flow/Screen flow
How to run the flow or creating work object
Create Tabbed/Tree navigation Screen Flow
Call a Sub-flow from another flow or from same flow
Design and Implement Screen flow
How to select Screen flow types

High Availability of Hadoop Components

Name node High Availability
- Using Shared Edits by using Journal nodes
- Using Zookeeper Quorum
Resource Manager HA
HiveServer2 HA
HMaster HA

Objective 3.2 –Cluster Planning

Understanding Hardware Components
- Master Hardware
- Slave Hardware
- CPU
- I/O
- Network
Plan your cluster growth
Managing Users & Groups
Cluster sharing across multiple use cases

Objective 4.1 – Install and Configure Cloudera

Understand the minimum hardware and software requirements
Understand the Cloudera Architecture
Understand how to install CDH using Cloudera Manager
Understand complete deployment layout
Understand how to configure and manage different services
Understand different configuration parameters

Lab:

Cloudera Cluster Installation

Objective 5.1 – Install and Configure Ambari& Hortonworks

Understand the minimum hardware and software requirements
Understand the Ambari Architecture
Understand how to install Ambari& Hortonworks
Understand complete deployment layout
Understand how to configure and manage different services
Understand different configuration parameters

Lab:

Hortonworks Cluster Installation

Objective 6.1 – MapR Distribution

Understand the minimum hardware and software requirements
Understand the MCS Architecture
Understand various services configured in MapR

Objective 7.1 – Monitor and Administering Hadoop Clusters

Monitor using the CM or Ambari UI
Back up and recover Hadoop data
Use Hadoop snapshots

Objective 7.2 – Hadoop Security

Understand security concepts
- Encryption at Rest
- TLS/SSL
- Sentry
Understanding & ConfiguringHadoop ACLs
Understanding & Configuring Kerberos
- Different types of Kerberos
  - MIT
  - AD Integration
- Working Mechanism

Objective 8 – Hadoop Ecosystem Tools [ Installations, Admin Responsibilities and Ecosystem workflow]

Objective 9 – Admin Roles and Responsibilities

Hadoop Cluster Backup
Hadoop Cluster Upgrade
OS & Hadoop Patching

Objective 10 – Performance Tuning

Hadoop Performance Turning from OS Level
Hadoop Performance Turning from HDFS Level (Storage Layer)
Hadoop Performance Turning from MR/YARN Level (Processing Layer)
Hadoop Performance Turning at ecosystems level

Objective 11 – Real Time Concepts and Issues.

Day to Day Admin Activities
Frequently Occurring Issues
Roles and Responsibilities
Interview Preparation
Resume Preparation
Real time issues discussion and project discussion.

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We provide the helpful Hadoop Administration tutorial for Beginners, Hadoop Administration training videos and Hadoop Administration interview questions & answers for both fresher and experienced candidates.

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About this course:

Method

Led Training

Type

Online

Schedules

Flexible Schedules

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