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The Ultimate Hands-On Hadoop: Tame your Big Data!

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The Ultimate Hands-On Hadoop: Tame your Big Data!, available at $129.99, has an average rating of 4.54, with 109 lectures, based on 30267 reviews, and has 182671 subscribers.

You will learn about Design distributed systems that manage "big data" using Hadoop and related data engineering technologies. Use HDFS and MapReduce for storing and analyzing data at scale. Use Pig and Spark to create scripts to process data on a Hadoop cluster in more complex ways. Analyze relational data using Hive and MySQL Analyze non-relational data using HBase, Cassandra, and MongoDB Query data interactively with Drill, Phoenix, and Presto Choose an appropriate data storage technology for your application Understand how Hadoop clusters are managed by YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie. Publish data to your Hadoop cluster using Kafka, Sqoop, and Flume Consume streaming data using Spark Streaming, Flink, and Storm This course is ideal for individuals who are Software engineers and programmers who want to understand the larger Hadoop ecosystem, and use it to store, analyze, and vend "big data" at scale. or Project, program, or product managers who want to understand the lingo and high-level architecture of Hadoop. or Data analysts and database administrators who are curious about Hadoop and how it relates to their work. or System architects who need to understand the components available in the Hadoop ecosystem, and how they fit together. It is particularly useful for Software engineers and programmers who want to understand the larger Hadoop ecosystem, and use it to store, analyze, and vend "big data" at scale. or Project, program, or product managers who want to understand the lingo and high-level architecture of Hadoop. or Data analysts and database administrators who are curious about Hadoop and how it relates to their work. or System architects who need to understand the components available in the Hadoop ecosystem, and how they fit together.

Enroll now: The Ultimate Hands-On Hadoop: Tame your Big Data!

Summary

Title: The Ultimate Hands-On Hadoop: Tame your Big Data!

Price: $129.99

Average Rating: 4.54

Number of Lectures: 109

Number of Published Lectures: 104

Number of Curriculum Items: 109

Number of Published Curriculum Objects: 104

Original Price: $24.99

Quality Status: approved

Status: Live

What You Will Learn

  • Design distributed systems that manage "big data" using Hadoop and related data engineering technologies.
  • Use HDFS and MapReduce for storing and analyzing data at scale.
  • Use Pig and Spark to create scripts to process data on a Hadoop cluster in more complex ways.
  • Analyze relational data using Hive and MySQL
  • Analyze non-relational data using HBase, Cassandra, and MongoDB
  • Query data interactively with Drill, Phoenix, and Presto
  • Choose an appropriate data storage technology for your application
  • Understand how Hadoop clusters are managed by YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie.
  • Publish data to your Hadoop cluster using Kafka, Sqoop, and Flume
  • Consume streaming data using Spark Streaming, Flink, and Storm

Who Should Attend

  • Software engineers and programmers who want to understand the larger Hadoop ecosystem, and use it to store, analyze, and vend "big data" at scale.
  • Project, program, or product managers who want to understand the lingo and high-level architecture of Hadoop.
  • Data analysts and database administrators who are curious about Hadoop and how it relates to their work.
  • System architects who need to understand the components available in the Hadoop ecosystem, and how they fit together.

Target Audiences

  • Software engineers and programmers who want to understand the larger Hadoop ecosystem, and use it to store, analyze, and vend "big data" at scale.
  • Project, program, or product managers who want to understand the lingo and high-level architecture of Hadoop.
  • Data analysts and database administrators who are curious about Hadoop and how it relates to their work.
  • System architects who need to understand the components available in the Hadoop ecosystem, and how they fit together.

The world of Hadoopand “Big Data” can be intimidating – hundreds of different technologies with cryptic names form the Hadoop ecosystem. With this Hadoop tutorial, you’ll not only understand what those systems are and how they fit together – but you’ll go hands-on and learn how to use them to solve real business problems!

Learn and master the most popular data engineering technologies in this comprehensive course, taught by a former engineer and senior manager from Amazonand IMDb. We’ll go way beyond Hadoop itself, and dive into all sorts of distributed systems you may need to integrate with.

  • Install and work with a real Hadoop installation right on your desktop with Hortonworks (now part of Cloudera) and the AmbariUI

  • Manage big data on a cluster with HDFSand MapReduce

  • Write programs to analyze data on Hadoop with Pigand Spark

  • Store and query your data with Sqoop, Hive, MySQL, HBase, Cassandra, MongoDB, Drill, Phoenix, and Presto

  • Design real-world systems using the Hadoop ecosystem

  • Learn how your cluster is managed with YARN, Mesos, Zookeeper, Oozie, Zeppelin, and Hue

  • Handle streaming data in real time with Kafka, Flume, Spark Streaming, Flink, and Storm

Spark and Hadoop developers are hugely valued at companies with large amounts of data; these are very marketable skills to learn.

Almost every large company you might want to work at uses Hadoop in some way, including Amazon, Ebay, Facebook, Google, LinkedIn, IBM,  Spotify, Twitter, and Yahoo! And it’s not just technology companies that need Hadoop; even the New York Times uses Hadoop for processing images.

This course is comprehensive, covering over 25 different technologiesin over 14 hours of video lectures. It’s filled with hands-on activities and exercises, so you get some real experience in using Hadoop – it’s not just theory.

You’ll find a range of activities in this course for people at every level. If you’re a project manager who just wants to learn the buzzwords, there are web UI’s for many of the activities in the course that require no programming knowledge. If you’re comfortable with command lines, we’ll show you how to work with them too. And if you’re a programmer, I’ll challenge you with writing real scripts on a Hadoop system using Scala, Pig Latin, and Python.

You’ll walk away from this course with a real, deep understanding of Hadoop and its associated distributed systems, and you can apply Hadoop to real-world problems. Plus a valuable completion certificate is waiting for you at the end! 

Please note the focus on this course is on application development, not Hadoop administration. Although you will pick up some administration skills along the way.

Knowing how to wrangle “big data” is an incredibly valuable skill for today’s top tech employers. Don’t be left behind – enroll now!

  • “The Ultimate Hands-On Hadoop… was a crucial discovery for me. I supplemented your course with a bunch of literature and conferences until I managed to land an interview. I can proudly say that I landed a job as a Big Data Engineer around a year after I started your course. Thanks so much for all the great content you have generated and the crystal clear explanations. ” – Aldo Serrano

  • “I honestly wouldn’t be where I am now without this course. Frank makes the complex simple by helping you through the process every step of the way. Highly recommended and worth your time especially the Spark environment.   This course helped me achieve a far greater understanding of the environment and its capabilities.  Frank makes the complex simple by helping you through the process every step of the way. Highly recommended and worth your time especially the Spark environment.” – Tyler Buck

Course Curriculum

Chapter 1: Learn all the buzzwords! And install the Hortonworks Data Platform Sandbox.

Lecture 1: Udemy 101: Getting the Most From This Course

Lecture 2: Tips for Using This Course

Lecture 3: If you have trouble downloading Hortonworks Data Platform…

Lecture 4: Warning for Apple M1 users

Lecture 5: Installing Hadoop [Step by Step]

Lecture 6: The Hortonworks and Cloudera Merger, and how it affects this course.

Lecture 7: Hadoop Overview and History

Lecture 8: Overview of the Hadoop Ecosystem

Lecture 9: Important note

Chapter 2: Using Hadoop's Core: HDFS and MapReduce

Lecture 1: HDFS: What it is, and how it works

Lecture 2: Alternate MovieLens download location

Lecture 3: Installing the MovieLens Dataset

Lecture 4: [Activity] Install the MovieLens dataset into HDFS using the command line

Lecture 5: MapReduce: What it is, and how it works

Lecture 6: How MapReduce distributes processing

Lecture 7: MapReduce example: Break down movie ratings by rating score

Lecture 8: [Activity] Install Python, MRJob, and nano

Lecture 9: [Activity] Code up the ratings histogram MapReduce job and run it

Lecture 10: [Exercise] Rank movies by their popularity

Lecture 11: Note: Sorting will only work by partition.

Lecture 12: [Activity] Check your results against mine!

Chapter 3: Programming Hadoop with Pig

Lecture 1: Introducing Ambari

Lecture 2: Introducing Pig

Lecture 3: Example: Find the oldest movie with a 5-star rating using Pig

Lecture 4: [Activity] Find old 5-star movies with Pig

Lecture 5: More Pig Latin

Lecture 6: [Exercise] Find the most-rated one-star movie

Lecture 7: Pig Challenge: Compare Your Results to Mine!

Chapter 4: Programming Hadoop with Spark

Lecture 1: Why Spark?

Lecture 2: The Resilient Distributed Dataset (RDD)

Lecture 3: [Activity] Find the movie with the lowest average rating – with RDD's

Lecture 4: Datasets and Spark 2.0

Lecture 5: [Activity] Find the movie with the lowest average rating – with DataFrames

Lecture 6: [Activity] Movie recommendations with MLLib

Lecture 7: [Exercise] Filter the lowest-rated movies by number of ratings

Lecture 8: [Activity] Check your results against mine!

Chapter 5: Using relational data stores with Hadoop

Lecture 1: What is Hive?

Lecture 2: [Activity] Use Hive to find the most popular movie

Lecture 3: How Hive works

Lecture 4: [Exercise] Use Hive to find the movie with the highest average rating

Lecture 5: Compare your solution to mine.

Lecture 6: Integrating MySQL with Hadoop

Lecture 7: Cheat sheet for the following lecture

Lecture 8: [Activity] Install MySQL and import our movie data

Lecture 9: [Activity] Use Sqoop to import data from MySQL to HFDS/Hive

Lecture 10: [Activity] Use Sqoop to export data from Hadoop to MySQL

Chapter 6: Using non-relational data stores with Hadoop

Lecture 1: Why NoSQL?

Lecture 2: What is HBase

Lecture 3: [Activity] Import movie ratings into HBase

Lecture 4: [Activity] Use HBase with Pig to import data at scale.

Lecture 5: Cassandra overview

Lecture 6: If you have trouble installing Cassandra…

Lecture 7: [Activity] Installing Cassandra

Lecture 8: [Activity] Write Spark output into Cassandra

Lecture 9: MongoDB overview

Lecture 10: [Activity] Install MongoDB, and integrate Spark with MongoDB

Lecture 11: [Activity] Using the MongoDB shell

Lecture 12: Choosing a database technology

Lecture 13: [Exercise] Choose a database for a given problem

Chapter 7: Querying your Data Interactively

Lecture 1: Overview of Drill

Lecture 2: [Activity] Setting up Drill

Lecture 3: [Activity] Querying across multiple databases with Drill

Lecture 4: Overview of Phoenix

Lecture 5: [Activity] Install Phoenix and query HBase with it

Lecture 6: [Activity] Integrate Phoenix with Pig

Lecture 7: Overview of Presto

Lecture 8: [Activity] Install Presto, and query Hive with it.

Lecture 9: [Activity] Query both Cassandra and Hive using Presto.

Chapter 8: Managing your Cluster

Lecture 1: YARN explained

Lecture 2: Tez explained

Lecture 3: [Activity] Use Hive on Tez and measure the performance benefit

Lecture 4: Mesos explained

Lecture 5: ZooKeeper explained

Lecture 6: [Activity] Simulating a failing master with ZooKeeper

Lecture 7: Oozie explained

Lecture 8: [Activity] Set up a simple Oozie workflow

Lecture 9: Zeppelin overview

Lecture 10: [Activity] Use Zeppelin to analyze movie ratings, part 1

Lecture 11: [Activity] Use Zeppelin to analyze movie ratings, part 2

Lecture 12: Hue overview

Lecture 13: Other technologies worth mentioning

Chapter 9: Feeding Data to your Cluster

Lecture 1: Kafka explained

Lecture 2: [Activity] Setting up Kafka, and publishing some data.

Lecture 3: [Activity] Publishing web logs with Kafka

Lecture 4: Flume explained

Lecture 5: [Activity] Set up Flume and publish logs with it.

Lecture 6: [Activity] Set up Flume to monitor a directory and store its data in HDFS

Chapter 10: Analyzing Streams of Data

Lecture 1: Spark Streaming: Introduction

Lecture 2: [Activity] Analyze web logs published with Flume using Spark Streaming

Lecture 3: [Exercise] Monitor Flume-published logs for errors in real time

Instructors

Rating Distribution

  • 1 stars: 301 votes
  • 2 stars: 349 votes
  • 3 stars: 2302 votes
  • 4 stars: 10131 votes
  • 5 stars: 17187 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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