Hadoop Starter Kit

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The objective of this course is to walk you through step by step of all the core components in Hadoop but more importantly make Hadoop learning experience easy and fun. By enrolling in this course you can also get free access to our multi-node Hadoop training cluster so you can try out what you learn right away in a real multi-node distributed environment. WHAT YOU WILL LEARN IN THIS COURSE In the first section you will learn about what is big data with examples. We will discuss the factors to consider when considering whether a problem is big data problem or not. We will talk about the challenges with existing technologies when it comes to big data computation. We will breakdown the Big Data problem in terms of storage and computation and understand how Hadoop approaches the problem and provide a solution to the problem. In the HDFS, section you will learn about the need for another file system like HDFS. We will compare HDFS with traditional file systems and its benefits. We will also work with HDFS and discuss the architecture of HDFS. In the MapReduce section you will learn about the basics of MapReduce and phases involved in MapReduce. We will go over each phase in detail and understand what happens in each phase. Then we will write a MapReduce program in Java to calculate the maximum closing price for stock symbols from a stock dataset. In the next two sections, we will introduce you to Apache Pig & Hive. We will try to calculate the maximum closing price for stock symbols from a stock dataset using Pig and Hive.
  • Welcome & Let's Get Started
    • Course Introduction

      In this short video, we will give an overview of the course and walk through the each section of this course.

  • Introduction to Big Data
    • What Is Big Data?

      In this lesson, we will learn - What is Big Data and some examples of Big Data The problems that come with Big Data in terms of storage and computation What Hadoop can offer in terms of solutions to the Big Data problems Compare traditional solutions with Hadoop

    • Understanding Big Data Problem

      In this lesson, we will - Take a sample big data problem, Analyze the problem and understand the complexities in terms of storage and computation Finally, we will work on a solution together

  • HDFS
    • HDFS - Why Another Filesystem?

      In this lesson, we will learn - What is a file system and it's features Existing file systems Limitations of existing file systems in distributed computing How HDFS is different from local file system Basics of HDFS Benefits of HDFS

    • Working With HDFS

      In this lesson, we will see - Practical differences between HDFS and local file system Manipulate files and directories in HDFS Commands to check or update permissions, replications and file system check Physical blocks location and preview at hdfs-site.xml HDFS commands location in cluster - /hirw-starterkit/hdfs/commands

    • HDFS Architechture

      In this lesson, we will learn about - Data Node Name Node Information held by Name Node HDFS configuration files Topology - Node, Rack, Cluster

  • MapReduce
    • Introduction To MapReduce

      In this lesson we will learn MapReduce using a good illustrative example. You will not be bored with Word Count problem, we promise !!! This lesson covers the following - The basics of MapReduce Introduction to Phases of MapReduce phases Introduction to technical terms like Mapper, Reducer, InputSplit etc.

    • Dissecting MapReduce Components

      In this lesson we will - Dive deeper in to each phase of MapReduce Learn the difference between InputSplit vs Block Significance of Shuffle phase Partitioner, Combiner etc

    • Dissecting MapReduce Program (Part 1)

      In this lesson we will write a MapReduce program in Java to calculate the maximum closing of stock symbol from a stocks dataset. We will walk through every single line code and understand the programming concepts involved in writing MapReduce code. Location of code, jar, readme file in cluster - /hirw-starterkit/mapreduce/stocks

    • Dissecting MapReduce Program (Part 2)

      In this lesson we will write a MapReduce program in Java to calculate the maximum closing of stock symbol from a stocks dataset. We will walk through every single line code and understand the programming concepts involved in writing MapReduce code. Location of code, jar, readme file in cluster - /hirw-starterkit/mapreduce/stocks

  • Apache Pig
    • Introduction to Apache Pig

      This lesson will give you a very good introduction to Apache Pig. We will write Pig Latin instructions to calculate the maximum closing of stock symbol from a stocks dataset. Location of pig script, readme file in cluster - /hirw-starterkit/pig/stocks

  • Apache Hive
    • Introduction to Apache Hive

      This lesson will give you a very good introduction to Apache Hive. We will create Hive table and calculate the maximum closing of stock symbol from a stocks dataset with a simple query. Location of Hive script in cluster - /hirw-starterkit/pig/stocks

  • Hadoop Administrator In Real World (Upcoming Course)
    • Cloudera Manager - Introduction

      In this lecture we will learn about the benefits of Cloudera Manager, differences between Packages and Parcels and lifecycle of Parcels.

    • Cloudera Manager - Installation

      In this lecture we will see how to install a 3 node Hadoop cluster on AWS using Cloudera Manager

  • Our Hadoop Developer course
    • BONUS: Hadoop In Real World Course: Become an Expert Hadoop Developer
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