Course Overview

Key Features

  • 3 hours of High Quality e-learning
  • 5 Chapter-end Quizzes
  • 1 Project
  • Introduction to YARN and MapReduce
  • Advanced HDFS and MapReduce
  • Course Completion Certificate

Training Options

Self-Paced Learning

$ 299

  • Lifetime access to high-quality self-paced e-learning content curated by industry experts
  • 24x7 learner assistance and support

Corporate Training

Customized to your team's needs

  • Blended learning delivery model (self-paced eLearning and/or instructor-led options)
  • Flexible pricing options
  • Enterprise grade Learning Management System (LMS)
  • Enterprise dashboards for individuals and teams
  • 24x7 learner assistance and support

Course Curriculum

Course Content

  • Big Data and Hadoop Fundamentals

    Preview
    • Lesson 01 - Introduction to Big Data and Hadoop

      19:13Preview
      • 1.1 Introduction to Big Data and Hadoop
        00:16
      • 1.2 Objectives
        00:18
      • 1.3 Data Explosion
        01:03
      • 1.4 Types of Data
        00:36
      • 1.5 Need for Big Data
        00:59
      • 1.6 Big Data and Its Sources
        00:30
      • 1.7 Characteristics of Big Data
        01:32
      • 1.8 Characteristics of Big Data Technology
        01:36
      • 1.9 Knowledge Check
      • 1.10 Leveraging Multiple Data Sources
        00:35
      • 1.11 Traditional IT Analytics Approach
        00:25
      • 1.12 Traditional IT Analytics Approach (contd.)
        00:22
      • 1.13 Big Data Technology-Platform for Discovery and Exploration
        00:28
      • 1.14 Big Data Technology-Platform for Discovery and Exploration
        00:26
      • 1.15 Big Data Technology-Capabilities
        00:18
      • 1.16 Big Data-Use Cases
        00:34
      • 1.17 Handling Limitations of Big Data
        00:32
      • 1.18 Introduction to Hadoop
        00:49
      • 1.19 History and Milestones of Hadoop
        02:05
      • 1.20 Organizations Using Hadoop
        00:16
      • 1.21 VMware Player-Introduction
        00:13
      • 1.22 VMware Player-Hardware Requirements
        00:25
      • 1.23 Oracle VirtualBox to Open a VM - SL1 Backup
      • 1.24 Installing VM using Oracle VirtualBox
        02:05
      • 1.25 Opening a VM using Oracle VirtualBox
        01:57
      • 1.26 Quiz
      • 1.27 Summary
        00:46
      • 1.28 Conclusion
        00:07
    • Lesson 02 - Hadoop Architecture

      25:54Preview
      • 2.1 Hadoop Architecture
        00:10
      • 2.2 Objectives
        00:16
      • 2.3 Key Terms
        00:23
      • 2.4 Hadoop Cluster Using Commodity Hardware
        00:34
      • 2.5 Hadoop Configuration
      • 2.6 Hadoop Core Services
        00:51
      • 2.7 Apache Hadoop Core Components
        00:17
      • 2.8 Why HDFS
        01:30
      • 2.9 What is HDFS
        00:16
      • 2.10 HDFS Real-life Connect
        00:24
      • 2.11 Regular File System vs. HDFS
        00:36
      • 2.12 HDFS-Characteristics
        01:25
      • 2.13 HDFS-Key Features
        00:40
      • 2.14 HDFS Architecture
        00:46
      • 2.15 NameNode in HA mode
        01:10
      • 2.16 NameNode HA Architecture
        01:44
      • 2.17 HDFS Operation Principle
        02:15
      • 2.18 File System Namespace
        00:31
      • 2.19 NameNode Operation
        01:26
      • 2.20 Data Block Split
        00:45
      • 2.21 Benefits of Data Block Approach
        00:10
      • 2.22 HDFS-Block Replication Architecture
        00:37
      • 2.23 Replication Method
        00:38
      • 2.24 Data Replication Topology
        00:16
      • 2.25 Data Replication Representation
        00:49
      • 2.26 HDFS Access
        00:22
      • 2.27 Business Scenario
        00:20
      • 2.28 Create a New Directory in HDFS
        01:20
      • 2.29 Spot the Error
      • 2.30 Quiz
      • 2.31 Case Study
      • 2.32 Case study Demo
        04:49
      • 2.33 Summary
        00:29
      • 2.34 Conclusion
        00:05
    • Lesson 03 - Hadoop Deployment

      41:20Preview
      • 3.1 Hadoop Deployment
        00:14
      • 3.2 Objectives
        00:18
      • 3.3 Ubuntu Server Introduction
        00:33
      • 3.4 Installation of Ubuntu Server 13.04
      • 3.5 Business Scenario
        00:26
      • 3.6 Installing Ubuntu Server 14.04 Demo 01
        06:05
      • 3.7 Hadoop Installation Prerequisites
        00:17
      • 3.8 Hadoop Installation
        00:16
      • 3.9 Installing Hadoop Demo 02
        12:31
      • 3.10 Hadoop Multi-Node Installation Prerequisites
        00:19
      • 3.11 Steps for Hadoop Multi-Node Installation
      • 3.12 Single-Node Cluster vs. Multi-Node Cluster
        00:32
      • 3.13 Creating a Clone of Hadoop VM Demo 03
        00:59
      • 3.14 Performing Clustering of the Hadoop Environment Demo 04
        08:08
      • 3.15 Spot the Error
      • 3.16 Quiz
      • 3.17 Case Study
      • 3.18 Case study Demo
        10:02
      • 3.19 Summary
        00:34
      • 3.20 Conclusion
        00:06
    • Lesson 04 - Introduction to MapReduce

      52:39Preview
      • 4.1 Introduction to YARN and MapReduce
        00:13
      • 4.2 Objectives
        00:16
      • 4.3 Why YARN
        00:48
      • 4.4 What is YARN
        00:25
      • 4.5 YARN Real Life Connect
        00:53
      • 4.6 YARN Infrastructure
        00:44
      • 4.7 YARN Infrastructure (contd.)
        01:24
      • 4.8 Resource Manager
        01:48
      • 4.9 Other Resource Manager Components
        01:13
      • 4.10 Resource Manager in HA Mode
        01:12
      • 4.11 ApplicationMaster
        01:06
      • 4.12 NodeManager
        00:53
      • 4.13 Container
        00:56
      • 4.14 Applications Running on YARN
        00:43
      • 4.15 Application Startup in YARN
        02:48
      • 4.16 Application Startup in YARN (contd.)
        00:19
      • 4.17 Role of AppMaster in Application Startup
        00:40
      • 4.18 Why MapReduce
        00:51
      • 4.19 What is MapReduce
        00:18
      • 4.20 MapReduce Real-life Connect
        00:20
      • 4.21 MapReduce-Analogy
        00:44
      • 4.22 MapReduce-Analogy (contd.)
        00:35
      • 4.23 MapReduce-Example
        01:36
      • 4.24 Map Execution
      • 4.25 Map Execution-Distributed Two Node Environment
        00:37
      • 4.26 MapReduce Essentials
        00:58
      • 4.27 MapReduce Jobs
        01:00
      • 4.28 MapReduce and Associated Tasks
        00:31
      • 4.29 Hadoop Job Work Interaction
        00:38
      • 4.30 Characteristics of MapReduce
        00:36
      • 4.31 Real-time Uses of MapReduce
        00:31
      • 4.32 Prerequisites for Hadoop Installation in Ubuntu Desktop 14.04
        00:13
      • 4.33 Steps to Install Hadoop
        00:34
      • 4.34 Business Scenario
        00:37
      • 4.35 Set up Environment for MapReduce Development
        00:15
      • 4.36 Small Data and Big Data
      • 4.37 Uploading Small Data and Big Data
        00:16
      • 4.38 Installing Ubuntu Desktop OS Demo 1
        01:25
      • 4.39 Build MapReduce Program
        00:39
      • 4.40 Build a MapReduce Program Demo 2
        01:11
      • 4.41 Hadoop MapReduce Requirements
        00:45
      • 4.42 Steps of Hadoop MapReduce
        01:05
      • 4.43 MapReduce-Responsibilities
        00:35
      • 4.44 MapReduce Java Programming in Eclipse
        00:15
      • 4.45 Create a New Project
        00:45
      • 4.46 Checking Hadoop Environment for MapReduce
        00:22
      • 4.47 Build a MapReduce Application Demo 3
        08:18
      • 4.48 MapReduce v2.7
        00:05
      • 4.49 Spot the Error
      • 4.50 Quiz
      • 4.51 Case Study
      • 4.52 Case study Demo
        08:53
      • 4.53 Summary
        00:42
      • 4.54 Conclusion
        00:08
    • Lesson 05 - Advanced HDFS and MapReduce

      30:32Preview
      • 5.1 Introduction
        00:09
      • 5.2 Objectives
        00:16
      • 5.3 Advanced HDFS Introduction
        00:33
      • 5.4 HDFS Benchmarking
        00:28
      • 5.5 Setting Up HDFS Block Size
        00:59
      • 5.6 Decommissioning a DataNode
        00:30
      • 5.7 Business Scenario
        00:17
      • 5.8 HDFS Demo 01
        04:44
      • 5.9 Setting HDFS block size in Hadoop 2.7.1 Demo 02
        02:15
      • 5.10 Advanced MapReduce
        00:37
      • 5.11 Interfaces
        00:31
      • 5.12 Data Types in Hadoop
        00:34
      • 5.13 Data Types in Hadoop (contd.)
        00:08
      • 5.14 InputFormats in MapReduce
        00:57
      • 5.15 OutputFormats in MapReduce
        01:14
      • 5.16 Distributed Cache
        00:49
      • 5.17 Using Distributed Cache - Step 1
        00:05
      • 5.18 Using Distributed Cache - Step 2
        00:05
      • 5.19 Using Distributed Cache - Step 3
        00:05
      • 5.20 Joins in MapReduce
        01:00
      • 5.21 Reduce Side Join
        00:24
      • 5.22 Reduce Side Join (contd.)
        00:28
      • 5.23 Replicated Join
        00:19
      • 5.24 Replicated Join (contd.)
        00:32
      • 5.25 Composite Join
        00:26
      • 5.26 Composite Join (contd.)
        00:19
      • 5.27 Cartesian Product
        00:28
      • 5.28 Cartesian Product (contd.)
        00:20
      • 5.29 MapReduce program for Writable classes Demo 03
        03:10
      • 5.30 Spot the Error
      • 5.31 Quiz
      • 5.32 Case Study
      • 5.33 Case study Demo
        07:06
      • 5.34 Summary
        00:38
      • 5.35 Conclusion
        00:06

Exam & Certification

  • What qualifications do you need?

    There are no prerequisites for this course.

Why Online Bootcamp

  • Develop skills for real career growthCutting-edge curriculum designed in guidance with industry and academia to develop job-ready skills
  • Learn from experts active in their field, not out-of-touch trainersLeading practitioners who bring current best practices and case studies to sessions that fit into your work schedule.
  • Learn by working on real-world problemsCapstone projects involving real world data sets with virtual labs for hands-on learning
  • Structured guidance ensuring learning never stops24x7 Learning support from mentors and a community of like-minded peers to resolve any conceptual doubts
  • Disclaimer
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.