By the end of the module, the student will be able to understand the basics of big data, and will have the foundation of Hadoop daemons and Hadoop architecture.

• a.Understanding Big Data Basics
  b. Big Data Use Cases
  c. Introduction to Hadoop
  d. Understanding Hadoop Ecosystem
  e. Introduction to HDFS
• a. Introduction to Namenode
  b. Introduction to Datanode
• a. Introduction to Secondary Namenode
• a. Introduction to MapReduce
• a. Introduction to JobTracker
  b. Introduction to TaskTracker
• a. Summarizing Hadoop Architecture
  b. Roles and Responsibilities of a Hadoop Administrator

By the end of the module, the student will be able to create a multi-node Hadoop cluster. Preparing students to create Hadoop clusters, this module gives a deep understanding of how Linux works, how to setup virtual machines, and how to set up the password-less SSH.

• Linux internals
• i. Commands that are required
  ii. Linux basics
• Hadoop Cluster Installation Pre-requisites
• Pre-requisites of Hadoop Installation
• i. Software Downloads
  ii. Preparing your VM
  iii. Enabling VM with VMware
  iv. Understanding mandatory changes in the operating system
• Installation and Configuration
• i. Understanding Hadoop cluster installation modes
  ii. Understanding Hadoop Version 1 installation and configuration
  iii. Password-less SSH setup
• Hands-On Practice for creating a Hadoop cluster
• Helping individually in practicing Hadoop cluster installation

• By the end of the module, the student will be able to understand how to plan a production cluster of Hadoop. Students will understand the hardware and software requirements of a Hadoop cluster, performance tuning after cluster creation, and benchmarking.

By the end of the module, the student will be able to administrate a Hadoop cluster. Students will understand how to copy data from one Hadoop cluster to another Hadoop cluster, how to use different Hadoop schedulers to run jobs, how to perform backup and recovery of metadata, data, configurations, and application data, and how to recover cluster data.

By end of the module, the student will be able to understand how the next version of Hadoop and YARN works. An understanding of the new features of Hadoop Version 2 and Yarn framework will also be provided, and the knowledge to deploy a Hadoop 2 cluster in a pseudo-distributed and multi distributed mode.

• i. Hadoop 2.0 new features
  ii. YARN
• i. Understanding Resource Manager
  ii. Understanding Application Master
  iii. Understanding Node Manager
  iv. Understanding Hadoop 2 Job Execution Framework
• Hadoop 2 Multi-node cluster creation
• i. Pre-requisites of Hadoop Installation
  ii. Software Downloads
  iii. Preparing your VM
  iv. Enabling VM with VMware
  v. Understanding mandatory changes in the operating system
  vi. Installation and Configuration
  vii. Understanding Hadoop version 2 installation and configuration
  viii. Passwordless SSH setup

By the end of the module, the student will be able to learn how to achieve high availability, how to enable Federation in Namenode, and what the various improvements in Hadoop 2 are.

• Practice Hadoop 2 Multi-node Cluster Creation
• Helping individuals in practicing Hadoop 2 cluster installation
• a. Sample Yarn Job execution
  c. Understanding Issues of Hadoop 1
  d. Understanding improvements in Hadoop 2
  e. Namenode Federation
• Enable segregation of HDFS using multiple Namenodes
• Namenode – High Availability
• i. Achieving Namenode High-Availability using Quorum Journal Manager
  ii. Achieving Namenode High-Availability using Network File System
• Implementation of NN High Availability
• Helping individuals achieving Namenode High Availability

By end of the module, the student will be able to administrate the basics of Hadoop ecosystem components like Hive, Hbase, Sqoop, Flume, and Pig.

• Hadoop Ecosystem Introduction
• Understanding the integration of Hadoop ecosystem
• Touchbase with Hive
• What is Hive?
  ii. Architecture of Hive
  iii. Understanding Hive meta-store concepts
• HBase
• Understading HBase Basics
  ii. Understanding HBase storage Model
  iii. Understanding HBase Architecture
  iv. Cluster Installation and Configuration
• Pig
• What is Pig?
  ii. How Pig integrates with Hadoop cluster?
  iii. Demo of Pig Jobs using MapReduce
• Sqoop
• What is Sqoop?
  ii. How to import and export the data from Sqoop to RDBMS?
  iii. Example of Sqoop jobs using MySQL
• Flume
• What is F?
  ii. Sample Flume jobs

By the end of the module, the student will be able to build a multi-node Cloudera cluster using Cloudera Manager, will know how to achieve high availability, and how to add a new node into the cluster using Cloudera Manager.

• Understanding the internals of Cloudera Manager
  a. Understanding the automation of Hadoop installation using Cloudera Manager
  b. Understanding Cloudera Hadoop Distribution and Cloudera Manager
  c. Understanding the underlying directory structure of Cloudera Hadoop
  d. Cloudera Hadoop Cluster Installation – CDH