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This course includes:

  • 6 hours on-demand video
  • 1 article
  • Full lifetime access
  • Access on mobile and TV
IT & Software Other IT & Software Big Data

Learn Big Data: The Hadoop Ecosystem Masterclass

Master the Hadoop ecosystem using HDFS, MapReduce, Yarn, Pig, Hive, Kafka, HBase, Spark, Knox, Ranger, Ambari, Zookeeper
Bestseller
Rating: 4.4 out of 54.4 (3,394 ratings)
19,451 students
Created by Edward Viaene
Last updated 8/2018
English
English [Auto], Portuguese [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Process Big Data using batch
  • Process Big Data using realtime data
  • Be familiar with the technologies in the Hadoop Stack
  • Be able to install and configure the Hortonworks Data Platform (HDP)
Curated for the Udemy for Business collection

Requirements

  • You will need to have a background in IT. The course is aimed at Software Engineers, System Administrators, DBAs who want to learn about Big Data
  • Knowing any programming language will enhance your course experience
  • The course contains demos you can try out on your own machine. To run the Hadoop cluster on your own machine, you will need to run a virtual server. 8 GB or more RAM is recommended.

Description

In this course you will learn Big Data using the Hadoop Ecosystem. Why Hadoop? It is one of the most sought after skills in the IT industry. The average salary in the US is $112,000 per year, up to an average of $160,000 in San Fransisco (source: Indeed).

The course is aimed at Software Engineers, Database Administrators, and System Administrators that want to learn about Big Data. Other IT professionals can also take this course, but might have to do some extra research to understand some of the concepts.

You will learn how to use the most popular software in the Big Data industry at moment, using batch processing as well as realtime processing. This course will give you enough background to be able to talk about real problems and solutions with experts in the industry. Updating your LinkedIn profile with these technologies will make recruiters want you to get interviews at the most prestigious companies in the world.

The course is very practical, with more than 6 hours of lectures. You want to try out everything yourself, adding multiple hours of learning. If you get stuck with the technology while trying, there is support available. I will answer your messages on the message boards and we have a Facebook group where you can post questions.

Who this course is for:

  • This course is for anyone that wants to know how Big Data works, and what technologies are involved
  • The main focus is on the Hadoop ecosystem. We don't cover any technologies not on the Hortonworks Data Platform Stack
  • The course compares MapR, Cloudera, and Hortonworks, but we only use the Hortonworks Data Platform (HDP) in the demos

Course content

17 sections • 98 lectures • 5h 58m total length

  • Preview03:01
  • Course Guide
    00:57

  • What is Big Data
    Preview02:16
  • Preview03:29
  • What is Data Science
    02:19
  • What is Hadoop
    04:13
  • Hadoop Distributions
    03:17
  • What is Big Data Quiz
    12 questions

  • Hadoop Installation
    04:40
  • Demo: Hortonworks Sandbox
    04:21
  • Demo: Hadoop Installation - Part 1
    04:58
  • Demo: Hadoop Installation - Part 2
    06:38
  • Introduction to HDFS
    03:28
  • DataNode Communications
    01:15
  • Demo: HDFS - Part 1
    05:45
  • Demo: HDFS - Part 2 - Using Ambari
    04:59
  • MapReduce WordCount Example
    04:17
  • Demo: MapReduce WordCount
    07:05
  • Lines that span blocks
    02:29
  • Introduction to Yarn
    04:20
  • Demo: Yarn and ResourceManager UI
    05:45
  • Ambari API and Blueprints
    03:35
  • Demo: Ambari API and Blueprints
    08:38
  • ETL Processing in Hadoop
    01:50
  • Introduction Quiz
    5 questions

  • Introduction to Pig
    02:36
  • Demo: Part 1 - Pig Installation
    02:08
  • Demo: Part 2 - Pig Commands
    06:21
  • Demo: Part 3 - More Pig Commands
    04:02

  • Introduction to Apache Spark
    03:42
  • Spark WordCount
    02:36
  • Demo: Spark installation and WordCount
    04:36
  • Preview03:52
  • Demo: RDD Transformations and Actions
    06:02
  • Overview of RDD Transformations and Actions
    03:36
  • Spark MLLib
    01:58

  • Introduction to Hive
    02:47
  • Hive Queries
    04:29
  • Demo: Hive Installation and Hive Queries
    07:33
  • Hive Partitioning, Buckets, UDFs, and SerDes
    04:32
  • The Stinger Initiative
    02:42
  • Hive in Spark
    01:43

  • Introduction to Realtime Processing
    02:53

  • Introduction to Kafka
    01:42
  • Kafka Topics
    04:10
  • Kafka Messages and Log Compaction
    04:04
  • Kafka Use Cases and Usage
    02:47
  • Demo: Kafka Installation and Usage
    06:31

  • Introduction to Storm
    02:49
  • A Storm Topology
    04:14
  • Demo: Storm installation and Example Topology
    09:33
  • Storm Message Processing and Reliability
    04:00
  • Trident
    02:42

  • Introduction to Spark Streaming
    01:57
  • Spark Streaming Architecture
    01:32
  • Spark Receivers and WordCount Streaming Example
    03:28
  • Demo: Spark Streaming with Kafka
    03:57
  • Spark Streaming State and Checkpointing
    02:09
  • Demo: Stateful Spark Streaming
    03:24
  • More Spark Streaming Features
    01:08

Instructor

Edward Viaene
DevOps, Cloud, Big Data Specialist
Edward Viaene
  • 4.3 Instructor Rating
  • 37,371 Reviews
  • 179,812 Students
  • 12 Courses

I've been a System Administrator and full stack developer for over 10 years, the typical profile for a DevOps engineer. I've been working in multiple organizations and startups. I've cofounded a startup that focusses on applying DevOps and Cloud. I have been training people in newer technologies, like Big Data. I've trained a lot of people working in FTSE 100 & S&P 100 companies. Today I mainly work together with companies to improve their software delivery processes, while coaching and teaching on platforms like Udemy.

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