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Hadoop is a data platform that simplifies the big data distributing process. It deals with structured and unstructured data, which is why many organizations adopt Hadoop.

Hadoop technology is used by almost every industry to manage large volumes of data rapidly.

We provide the best Hadoop Developer Training in Chennai, where one can get in-depth knowledge in Introduction to Big Data and Hadoop, VMware Player – Introduction, Hadoop Architecture, Hadoop Deployment, Introduction to Map Reduce, Advanced HDFS and MapReduce, Pig, Hive, HBase, Commercial Distribution of Hadoop, Zookeeper sqoop and Flume, Ecosystem and its Components, Hadoop Administration, Troubleshooting and Security, Java Essential for Hadoop, Java Constructors and Essential classes & Exceptions in Java.

The Hadoop professionals in India earn an average ranging between ₹ 3.7 Lakhs to ₹ 10.5 Lakhs.

Lessons 1: Course Introduction

  • Welcome
  • Course Introduction
  • Course Objectives
  • Course Over view
  • Value to Professionals
  • Lessons Covered
  • Introduction to Big Data and Hadoop
  • Objectives
  • Data Explosion
  • Types of Data
  • Need for Big Data
  • Data – The Most Valuable Resource
  • Big Data and Its Sources
  • Three Characteristics of Big Data
  • Characteristics of Big Data Technology
  • Appeal of Big Data Technology
  • Leveraging Multiple Sources of Data
  • Traditional IT Analytics Approach
  • Big Data Technology – Platform for Discovery and Exploration
  • Big Data Technology – Capabilities
  • Big Data – Use Cases
  • Handling Limitations of Big Data/li>
  • Introduction to Hadoop
  • History and Milestones of Hadoop
  • Organisations Using Hadoop
  • Getting Started with Hadoop
  • Objectives
  • VMware Player – Introduction
  • VMware Player – Hardware Requirements
  • Steps to install VMware Player
  • Install VMware Player – All Steps
  • Steps to create a VM in VMware Player
  • Create a VM in a VMware Player – All Steps
  • Open a VM in VMware Player - All Steps
  • Oracle VirtualBox to Open a VM
  • Open a VM using VirtualBox -All Steps
  • Business Scenario
  • Demo
  • Hadoop Architecture
  • Objectives
  • Hadoop Cluster Using Commodity Hardware
  • Hadoop Configuration
  • Hadoop Core Services
  • Apache Hadoop Core Components
  • Hadoop Core Components – HDFS
  • Hadoop Core Components – MapReduce
  • Regular File System vs. HDFS
  • HDFS – Characteristics
  • HDFS – Key Features
  • HDFS Architecture
  • HDFS Operation Principle
  • HDFS
  • File System Namespace
  • NameNode Operation
  • Data Block Split
  • Benefits of Data Block Approach
  • HDFS – Block Replication Architecture
  • Replication Method
  • Data Replication Topology
  • Data Replication Representation
  • HDFS Access
  • Business Scenario
  • Demo
  • Hadoop Deployment
  • Objectives
  • Ubuntu Server – Intoduction and Installation with steps.
  • Hadoop Multi Node installation with steps
  • Introduction
  • Analogy
  • Map Execution
  • MapReduce Essentials
  • MapReduce Jobs
  • MapReduce Engine
  • MapReduce and Associated Tasks with HDFS
  • Characteristics and Real Time Uses of MapReduce
  • Hadoop MapReduce Requirement, Feetures, Processes and Steps
  • MapReduce Java Programming in Eclipse
  • Objectives
  • Introduction
  • HDFS Benchmarking
  • Setting up HDFS Block Size
  • Decommissioning a DataNode
  • Advanced MapReduce
  • Data Types in Hadoop
  • Using Distributed Cache
  • Reduce Side Join
  • Composite Join
  • Cartesian Product
  • Introduction
  • Components
  • How it works
  • Data Model
  • Nested Data Model
  • Pig Excecution and Interactive Modes
  • Salient Features
  • Steps to Install Pig Engine
  • Getting Datasets for Pig Development
  • Steps prerequisites to set the Environment for Pig Latin
  • Loading and Storing Methods
  • Script Interpretation
  • Filtering and transforming
  • Grouping and Sorting
  • Pig Commands
  • Objectives
  • Introduction
  • Characteristics
  • Metastore
  • Metastore Configuration
  • Driver
  • Query Compiler
  • Query Optimizer
  • Execution Engine
  • Client Components
  • Data Model
  • Hive File Formats
  • Hive Installation
  • Programming in Hive
  • Objectives
  • Introduction
  • Characteristics of HBase
  • Companies Using HBase
  • HBase Architecture
  • Storage Model of HBase
  • Row Distribution of Data between Region Servers
  • Data Storage in HBase
  • Data Model
  • Installation of HBase
  • Configuration of HBase
  • Objectives
  • Introduction
  • Cloudera
  • Starting the Cloudera VM
  • Logging into Hue
  • Logging into Cloudera Manager
  • Hortonworks Data Platform
  • MapR Data Platform
  • Pivotal HD
  • Objectives
  • Introduction to Zookeeper
  • Features of Zookeeper
  • Challenges Faced in Distributed Applications
  • Coordination
  • Goals of Zookeeper
  • Uses of Zookeeper
  • Zookeeper Data Model
  • Zookeeper Services
  • Client API Functions
  • Why Sqoop
  • Importing and Exporting Data to Hive
  • Importing and Exporting Data to HBase/li>
  • Apache Flume
  • Scalabiliy in Flume
  • Objectives
  • Apache Hadoop Ecosystem
  • Apache Oozie
  • Introduction to Mahout
  • Features of Mahout
  • Usage of Mahout
  • Apache Cassandra
  • Apache Spark
  • Hadoop Integration
  • Objectives
  • Typical Hadoop core Cluster
  • Load Balancer
  • Commands Used in Hadoop Programming
  • Different Configuration Files of Hadoop Cluster
  • Properties of Hadoop default.xml
  • Different Configuration Files of Hadoop Cluster
  • Port Numbers for individual Hadoop Services
  • Performance Monitoring
  • Performance Tuning
  • Parameters of Performance Tuning
  • Troubleshooting and Log Observation
  • Apache Ambari
  • Key Features of Apache Ambari
  • Hadoop Security – Kerberos
  • Kerberos Configuration
  • Data Confidentiality
  • Java Essential for Hadoop
  • Objectives
  • Java Definition
  • Java Virtual Machine
  • Working of Java
  • Running a Basic Java Program
  • Basic JAVA Syntax
  • Data Types in Java
  • Variables in Java
  • Naming Conventions of Variables
  • Type Casting
  • Operators
  • Mathematical Operators
  • Unary Operators
  • Relational Operators
  • Logical or Conditional Operators
  • Bitwise Opearators
  • Static Versus Non Static Variables
  • Flow Control
  • Variants of if Statement

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