Big Data & Hadoop Training Course Content

Overview / Description: Hadoop developer training builds your development skills in big data domain. Hadoop is a free source, Java based programming framework that assists the processing and storage of highly large data sets in a distributed computing environment. Hadoop developer jobs is same as the software developer and their roles are also similar but the domain in which they work is different.

Prerequisites / Eligibility: There are no prerequisites for Hadoop knowledge. This course is designed for people proficient with Object Oriented Programming language (OOPS) and JAVA.

Detailed Course Content :

Chapter 01:Introduction

  • 1.1 Bigdata Introduction
  • 1.2 Distributed System
  • 1.3 BigData Use cases
  • 1.4 Various Solutions
  • 1.5 Overview of Hadoop Echo System

Chapter 02: ZooKeeper

  • 2.1 ZooKeeper -Race Condition
  • 2.2 ZooKeeper – Dead Lock
  • 2.3 Use Cases
  • 2.4 When not to Use

Chapter 03: HDFS

  • 3.1 Why HDFS and Why not existing File system
  • 3.2 HDFS – Name Node and Data Node
  • 3.3 Advanced HDFS concepts (HA, Federation)
  • 3.4 Data Locality (RAC awareness

Chapter 04: YARN

  • 4.1 YARN – Why not existing tools
  • 4.2 YARN – Evolution from MapReduce 1.0
  • 4.3 Resource Management – YARN Architecture
  • 4.4 Advanced Concept – Speculative Execution

Chapter 05: MapReduce Basics

  • 5.1 MapReduce-Understanding Sorting
  • 5.2 MapReduce-Overview
  • 5.3 Example 1- Word Frequency Problem without MapReduce
  • 5.4 Example2- Only Mapper – Image Resizing
  • 5.5 Example3- Word Frequency Problem
  • 5.6 Exampe4 – Temperature Problem
  • 5.7 Example5 – Multiple Reducer
  • 5.8 Example6 – Java MapReduce walk through

Chapter 06: MapReduce – Advanced

  • 6.1 Writing MapReduce Code Using Java
  • 6.2 Building MapReduce project using Ant
  • 6.3 Concept – Associative and Commutative
  • 6.4 Example1- Combiner
  • 6.5 Example2- Hadoop Streaming
  • 6.6 Example3 – Advanced Problem Solving – Anagrams
  • 6.7 Example4 -Advanced Problem Solving – Same DNA
  • 6.8 Example5 -Advanced Problem Solving – Similar DNA
  • 6.9 Example6-Joins – Voting
  • 6.10. Limitations of MapReduce

Chapter 07: Analyzing Data with Pig

  • 7.1 Pig – Introduction
  • 7.2 Pig – Modes
  • 7.3 Getting Started
  • 7.4 Example – NYSE (NewYork Stock Exchange)
  • 7.5 Concept – Lazy Evolution

Chapter 08: rocessing Data with Hive

  • 8.1 Hive Introduction
  • 8.2 Hive – Data Type
  • 8.3 Getting Started
  • 8.4 Loading Data in Hive Tables
  • 8.5 Example: Movelens Data Processing
  • 8.6 Advanced Concepts – Views
  • 8.7 Connecting Tableau and Hive Server2
  • 8.8 Connecting Microsoft Excel and Hive Server2
  • 8.9 Project: Sentiment Analysis of Twitter Data
  • 8.10. Advanced – Partitioned Tables
  • 8.11. Understanding HCatelog & Impala

Chapter 09: NoSQL and HBase

  • 9.1 NoSQL – Scaling Out /Up
  • 9.2 NoSQL – ACID properties and RDBMS
  • 9.3 CAP Theorem
  • 9.4 HBase Architecture – Region Servers
  • 9.5 HBase Data Model – Column Family Orientedness
  • 9.6 Getting Started – Creating tables and adding Data
  • 9.7 Example – Google Link Storage
  • 9.8 Bloom Filter – Concept
  • 9.9 Comparison of NoSQL Databases.

Chapter 10: importing Data with Sqoop, Flume and Oozie

  • 10.1 sqoop – Introduction
  • 10.2 Sqoop Import – MySQL to HDFS
  • 10.3 Exporting from MySQL to HDFS
  • 10.4 Unbound Dataset Processing or Stream processing
  • 10.5 Flume Overview –
  • 10.6 Source , Sink, Channel
  • 10.7 Example1: Data from Local Network service into HDFS
  • 10.8 Example2: Extracting Twitter Data
  • 10.9 Creating workflow with Oozie

Chapter 11: Fundamentals of Scala

  • 11.1 Scala – Quick Introduction
  • 11.2 Scala – Quick Introduction – Variables and Methods
  • 11.3 Getting Started: Interactive, Compilation, SBT
  • 11.4 Types, Variables & Values
  • 11.5 Functions
  • 11.6 Collections
  • 11.7 Classes
  • 11.8 Parameters

Chapter 12: Spark Basics

  • 12.1 Spark Introduction – Why Spark?
  • 12.2 Using the Spark Shell
  • 12.3 Example 1 – Performing Word Count
  • 12.4 Understanding Spark Cluster Modes on YARN
  • 12.5 RDDs (Resilient Distributed Datasets)
  • 12.6 General RDD Operations: Transformations & Actions
  • 12.7 RDD lineage
  • 12.8 RDD Persistence Overview
  • 12.9 Distributed Persistence
  • Member Testimonials

    Vikas Sharma

    Thanks a million. Appreciate taking ur time and effort.
    2017-06-30T12:38:32+00:00
    Thanks a million. Appreciate taking ur time and effort.

    Suresh Gadepalli

    "It gives me lot of confidence and interest to learn whenever I hear your training videos...I always feel that your effort towards the training is... Read More
    2017-06-30T11:37:22+00:00
    "It gives me lot of confidence and interest to learn whenever I hear your training videos...I always feel that your effort towards the training is 100% undoubtedly but it is me or we  that need to put our 100%. I would like to mention that the quality of audio/video sessions are really good. Your voice is very clear and understandable.No background score which is really appreciated. These positive factors are increasing the trainee's concentration towards the session. I was not able to put my complete effort because of  both project and personal commitments.However, I am moving ahead and gaining knowledge as much as possible from your training videos. I am really blessed to hear someone like you teaching us as if  we are preparing for some board exams. I appreciate all the efforts you are taking to help QA folks across the globe. I wish you all the best!"

    Testimonial 1

    Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nullam vitae imperdiet neque, nec elementum diam. Integer vel libero nunc. Vestibulum enim eros, tincidunt non dignissim... Read More
    2017-08-01T09:55:37+00:00
    Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nullam vitae imperdiet neque, nec elementum diam. Integer vel libero nunc. Vestibulum enim eros, tincidunt non dignissim eu, aliquam eu libero. Nulla scelerisque, mi ac laoreet facilisis, nisl nulla tristique mi, non laoreet est nisl sit amet velit.

    Testmonial 2

    Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nullam vitae imperdiet neque, nec elementum diam. Integer vel libero nunc. Vestibulum enim eros, tincidunt non dignissim... Read More
    2017-08-01T09:56:08+00:00
    Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nullam vitae imperdiet neque, nec elementum diam. Integer vel libero nunc. Vestibulum enim eros, tincidunt non dignissim eu, aliquam eu libero. Nulla scelerisque, mi ac laoreet facilisis, nisl nulla tristique mi, non laoreet est nisl sit amet velit.

    Suhasi Nair

    Karthik, u r really great in explaining, superb videos, have learnt some techniques n watching the chain to become an expert,thnx a lot
    2017-06-30T12:16:37+00:00
    Karthik, u r really great in explaining, superb videos, have learnt some techniques n watching the chain to become an expert,thnx a lot
  •  

Leave a Reply

Your email address will not be published. Required fields are marked *