Hadoop Online Training


IQ Tech Online Training course delivers the most comprehensive suite of courses to address the Hadoop objectives of every data professional. Be it developers, administrators, or data analysts our Hadoop online training curriculum presents learning from each user’s perspective. Our curriculum developed by industry-experts presents the finer nuances of Hadoop and is updated regularly to match the new advancements in the topic. The course delivered through online medium, can be customized as per the learners schedule and requirements. Have a look at the course summary below for more details.

Course Summary

Course Name Hadoop Training
Course Contents Fundamentals of Hadoop
Course Duration 30 Hours with Flexible timings
Course Delivery Instructor Led-Live Online Training
Course Eligibility Any Graduate
Ideal For Freshers, aspirants seeking to learn the basic essentials of Hadoop
Next Batch Please visit the schedule section

Course Objectives

Highlights of Hadoop Course at IQ Tech

  • Covers core understanding about big data, Hadoop and its surrounding ecosystem of products.
  • Focuses on big data and details about the Hadoop core components
  • Presents several common examples of Hadoop use cases
  • Emphasizes on important topics such as enterprise data hub, large scale log analysis, and building recommendation engines
  • Dynamic curriculum with the inclusion of latest developments in the field
  • Ideal for all aspirants of big data and Hadoop Technology including business analysts and enterprise architects
  • Designed from a practical and industry perspective

Core Benefits of learning hadoop

Big data is the latest industry buzz word and every company is keen in investing on it. In big data, the most widely used system is Hadoop. Hadoop is an open source implementation of big data, which is widely accepted in the industry, and used for large-scale, extremely parallel, and distributed data processing. Hadoop’s fault tolerant capacity and multiple level configurability has a huge impact to the number of times the data is stored across. This makes it one of the most lucrative big-data technologies and is sought after by companies across industries.

Course Curriculum

Module 1: Big Data Introduction

Topics: Hadoop Introduction, Hadoop History?, Need for Hadoop, Different Types of Components in Hadoop?, Scope of Hadoop, Hdfs, Pig, Flume, Hive, Oozie, Hbase, Mapreduce, Sqoop

Module 2: Deep Drive In Hdfs

Topics: Hdfs Design, Introduction of Hdfs, Features of Hdfs, Hdfs Role in Hadoop, Anatomy of File Wright, Daemons of Hadoop and its Functionality, Network Topology, Anatomy of File Read, Basic Configuration for HDFS, Parallel Copying Using Distcp, Rack Awareness, Data Organization, How to Store the Data into Hdfs, Heartbeat Signal, Accessing Hdfs, How to Read the Data From Hdfs, CLI Commands

Module 3: Mapreduce Using Java

Topics: Mapreduce Architecture, The Introduction of Mapreduce, Understand Difference Between Block And Inputsplit, Data Flow in Mapreduce, Writing and Executing the Basic Mapreduce Program practicing Java, How Mapreduce Works, Joins, File Input or Output Formats in Mapreduce Jobs, Role of Record reader, Submission and Initialization of Mapreduce Job, Mapreduce Life Cycle, Partition Mapreduce Program, Side Data Distribution, Word Count Example, Job Scheduling, Counters

Module 4: Pig

Topics: Introduction to Pig Data Flow Engine, Introduction to Apache Pig, When Should Pig Use?, Mapreduce Vs. Pig in Detail, Word Count Example in Pig,Basic Pig Programming, Data Types In Pig, Execution Mechanisms, Modes of Execution in Pig, Operatorsn or Transformations in Pig, Pig Udf’s with Program, The Difference Between the Mapreduce and Pig

Module 5: SQOOP

Topics: Use of Sqoop, Introduction to Sqoop, Connect to Mysql Database, Export to Hbase Joins in Sqoop, Sqoop Commands, Export to Mysql

Module 6: Hive

Topics: Hive Meta Store, Introduction to Hive, Tables in Hive, Hive Architecture, Partition, Hive Data Types, Hive Udf’s and Uadf’s With Programs, Joins in Hive, Word Count Example

Module 7: Hbase

Topics: Introduction to Hbase, Fundamentals of Hbase, Basic Configurations of Hbase, What is Nosql?, Categories of Nosql Data Bases, How Hbase is Differed from Rdbms, Sql Vs. Nosql, Client-Side Buffering or Bulk Uploads, Hdfs Vs. Hbase, Hbase Operations, Hbase Architecture, Hbase Designing Tables, Hbase Data Model

Module 8: Mongodb

Topics: Where to Use?, What is Mongodb?, Inserting the Data into Mongodb?, Configuration on Windows, Reading the Mongodb Data

Module 9: Cluster Setup

Topics: Installing Java, Creating Cluster, Installing Hadoop, Monitoring the Cluster Health, Increasing Decreasing the Cluster Size, Starting and Stopping The Nodes, Downloading And Installing the Ubuntu12.X

Module 10: Zookeeper

Topics: Data Modal, Introduction Zookeeper, Operations

Module 11: Oozie

Topics: Use of Oozie, Introduction to Oozie, Where to Use?

Module 12: Flume

Topics: Uses of Flume, Introduction to Flume, Flume Architecture

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