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Hadoop for Beginners

(21 Ratings) 1433 Students Enrolled
Created By Richardson V Last Updated Thu, 19-Mar-2020 English
  • Course Duration
    9 Hours
  • Mode of Training
    Self-Paced
  • Lessons
    46 Lessons
  • Placement Assistance
    Guaranteed
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What Will I Learn?
  • Understand the complex Architecture of Hadoop and its components
  • Understand the concept of MapReduce analyze big data sets
  • Learn how to install hadoop on your machine
  • Understand the Map Reduce concepts and formats
  • Learn about the Hadoop ecosystem

Requirements
  • Basic Knowledge of SQL and RDBMS
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Description

Hadoop is an open source distributed processing framework which helps to manage data processing and storage for big data applications running in clustered systems. The main objective of this course is to start from the basics of Hadoop, its architecture and map reduce concepts.  

Following modules are covered in this course namely:

  • Introduction to Hadoop
  • Hadoop setup
  • HDFS Architecture
  • Map Reduce 
  • Map Reduce types and Formats
  • Classic Map Reduce and YARN
  • Advanced Map Reduce Concepts
  • Introduction to Hadoop Ecosystem
Curriculum For This Course
46 Lessons 9 Hours
  • Big Data - Big value 00:05:47 Preview
  • Understanding Big Data 00:05:16 Preview
  • Hadoop and other Solutions 00:07:26
  • Distributed Architecture - A Brief Overview 00:02:55
  • Hadoop Releases 00:05:16
  • Setup Hadoop 00:28:57
  • Linux (Ubuntu) - Tips and Tricks 00:04:35
  • HDFS commands 00:10:33 Preview
  • Running a MapRed Program 00:07:48
  • HDFS Concepts 00:04:36 Preview
  • HDFS Architecture 00:06:35
  • HDFS Read and Write 00:04:55
  • HDFS Concepts II 00:04:04
  • Special Commands 00:06:35
  • MapReduce Introduction 00:06:06
  • Understanding MapReduce Part 1 00:05:13
  • Understanding MapReduce Part 2 00:05:19
  • Running First MapReduce Program 00:10:31
  • Combiner And Tool Runner 00:11:06
  • Recap Map, Reduce and Combiner Part 1 00:07:27
  • Recap Map, Reduce and Combiner Part 2 00:07:46
  • MapReduce Types and Formats 00:05:38
  • Experiments with Defaults 00:07:11
  • IO Format Classes 00:06:17
  • Experiments with File Output - Advanced Concept 00:03:38
  • Anatomy of MapReduce job run 00:04:22
  • Job Run- Classic MapReduce 00:07:54
  • Failure Scenarios - Classic Map Reduce 00:03:45
  • Job Run - YARN 00:09:45
  • Failure Scenario - YARN 00:05:18
  • Job Scheduling in MapReduce 00:05:07
  • Shuffle and Sort 00:04:33
  • Performance Tuning Features 00:07:10
  • Looking at Counters 00:06:22
  • Hands on - Counters 00:03:32
  • Sorting Ideas with Partitioner - Part 1 00:07:20
  • Sorting Ideas with Partitioner - Part 2 00:05:31
  • Map Side Join Operation 00:04:42
  • Reduce Side Join Operation 00:04:30
  • Side Distribution of Data 00:03:48
  • Hadoop Streaming and Hadoop Pipes 00:02:24
  • Introduction to Pig 00:09:24
  • Introduction to Hive 00:10:08
  • Introduction to Sqoop 00:08:44
  • Knowing Sqoop 00:04:05
  • Advanced Hadoop 03:31:53

Hadoop for Beginners