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Learn By Example: Hadoop, MapReduce for Big Data problems (Udemy.com)

A hands-on workout in Hadoop, MapReduce and the art of thinking "parallel"

Created by: Loony Corn

Last updated August 2018

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What you will learn

  • Develop advanced MapReduce applications to process BigData
  • Master the art of "thinking parallel" - how to break up a task into Map/Reduce transformations
  • Self-sufficiently set up their own mini-Hadoop cluster whether it's a single node, a physical cluster or in the cloud.
  • Use Hadoop + MapReduce to solve a wide variety of problems : from NLP to Inverted Indices to Recommendations
  • Understand HDFS, MapReduce and YARN and how they interact with each other
  • Understand the basics of performance tuning and managing your own cluster

How it compares

Against the other 150 rated Udemy courses in Hadoop on CourseDuck:

  • Rating4.5 out of 5higher than 68% of them
  • Reviews1,209#48 of 151 by number of reviews
  • Length13.7 hourslonger than 80% of them
  • Last updatedAugust 2018earlier than 81% of them

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Course Description

Taught by a 4 person team including 2 Stanford-educated, ex-Googlers  and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with Java and with billions of rows of data. 

This course is a zoom-in, zoom-out, hands-on workout involving Hadoop, MapReduce and the art of thinking parallel. 

Let’s parse that.

Zoom-in, Zoom-Out:  This course is both broad and deep. It covers the individual components of Hadoop in great detail, and also gives you a higher level picture of how they interact with each other. 

Hands-on workout involving Hadoop, MapReduce : This course will get you hands-on with Hadoop very early on.  You'll learn how to set up your own cluster using both VMs and the Cloud. All the major features of MapReduce are covered - including advanced topics like Total Sort and Secondary Sort. 

The art of thinking parallel: MapReduce completely changed the way people thought about processing Big Data. Breaking down any problem into parallelizable units is an art. The examples in this course will train you to "think parallel". 

What's Covered:

Lot's of cool stuff ..

  • Using MapReduce to 


    • Recommend friends in a Social Networking site: Generate Top 10 friend recommendations using a Collaborative filtering algorithm. 
    • Build an Inverted Index for Search Engines: Use MapReduce to parallelize the humongous task of building an inverted index for a search engine. 
    • Generate Bigrams from text: Generate bigrams and compute their frequency distribution in a corpus of text. 


  • Build your Hadoop cluster: 


    • Install Hadoop in Standalone, Pseudo-Distributed and Fully Distributed modes 
    • Set up a hadoop cluster using Linux VMs.
    • Set up a cloud Hadoop cluster on AWS with Cloudera Manager.
    • Understand HDFS, MapReduce and YARN and their interaction 


  • Customize your MapReduce Jobs: 


    • Chain multiple MR jobs together
    • Write your own Customized Partitioner
    • Total Sort : Globally sort a large amount of data by sampling input files
    • Secondary sorting 
    • Unit tests with MR Unit
    • Integrate with Python using the Hadoop Streaming API


.. and of course all the basics: 

  • MapReduce : Mapper, Reducer, Sort/Merge, Partitioning, Shuffle and Sort
  • HDFS & YARN: Namenode, Datanode, Resource manager, Node manager, the anatomy of a MapReduce application, YARN Scheduling, Configuring HDFS and YARN to performance tune your cluster. 

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Instructor Details

Loony Corn

Loonycorn is us, Janani Ravi and Vitthal Srinivasan. Between us, we have studied at Stanford, been admitted to IIM Ahmedabad and have spent years  working in tech, in the Bay Area, New York, Singapore and Bangalore.

Janani: 7 years at Google (New York, Singapore); Studied at Stanford; also worked at Flipkart and Microsoft

Vitthal: Also Google (Singapore) and studied at Stanford; Flipkart, Credit Suisse and INSEAD too

We think we might have hit upon a neat way of teaching complicated tech courses in a funny, practical, engaging way, which is why we are so excited to be here on Udemy!

We hope you will try our offerings, and think you'll like them :-)

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Reviews

4.5

1,209 ratings on Udemy

Select a bar to show only those reviews.Select the bar again to show every rating.

By Anonymized User on 10/12/2021

knowing about hadoop from basics is really good. This course seems to start from a very basic level where a layman can understand. Good explanation

By Arnab Chakraborty on 3/3/2021

This is the most detailed MR course I have come across anywhere. Coding along the course material will give anyone enough confidence to approach MR problems with great confidence. Kudos to the Loony Corn team.

By Anonymized User on 1/30/2020

Very well explained right from the scratch. If you're writing Hive queries not knowing how it works in the background this is a very good course to understand.

By Patrick Hagan on 5/25/2018

The visuals are very good and provide a very good explanation. Unfortunately, the speaker has a accent which makes hearing the lectures difficult. That can be seen when I turn on the closed captioning and the speaker's words do not translate well.

By w soud on 11/12/2017

What an amazing course this is! No assumptions are made of the skill levels of the students. Core concepts are reiterated again and again throughout. Code is explained line by line. Clear graphics are used to demonstrate difficult concepts. Important information is always written out to facilitate the learning process. I cannot remember a course where I can recall concepts the way I can with this course. This course is above and beyond, bar none. Thanks Loony Corn!!!

By Lucas de Sio Rosa on 8/25/2017

The contents of the course are very good, diving deep into the MapReduce inner workings and with code examples ranging from the simple to the complex. However, the presenter's diction is, unfortunately, subpar, which can make it difficult to understand what is being said. Also, I believe the pacing to be too slow. I feel that sometimes there's too much redundancy in what's being said, which makes the lessons longer than they need to be. Still, for anyone trying to go beyond basic "Hello World" tutorials on MapReduce, I still recommend this course as a very good way to better understand and visualize the parallel concepts and its implementations in Hadoop.

By Saleem AHMAD on 2/8/2017

I am loving the instructions so far. Installtion instructions were easy to follow so far, will leave complete rating later once the program is finished,

By Sriram Panyam on 1/7/2017

Course was pretty thorough and went through a fair bit of detail. Couple of things that could have made it better: 1. Reducing repetitions. A lot of the times concepts covered earlier were reviewed more than once. A simple link back to the appropriate section would have sufficed (eg on partitioning). 2. A few more examples on TotalOrderPartitioning could have helped. But other than that the course was great. Learnt a lot and hadoop and MR dont seem as daunting any more!

By Teena on 11/7/2016

Course is very well-structured and quite good for a beginner in Hadoop. I haven't come across an online Hadoop course that has explanations so clear and concise. I am giving 4 stars instead of 5 because the team takes time to respond to queries and that may not be good for a beginner especially when stuck at some step during an installation or the execution of a job. Also, the instructors use Mac and if you are a windows user, you might need some additional steps or google searches to accomplish the tasks that are part of the course.

By Andres Macedo on 6/14/2016

The material is great and really well explained. Coming from other object oriented prog language, I would love it to see the IDE setup and tips for using Eclipse or Intellij. the instructors are great at answering questions and providing additional resources.

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Quality Score

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Overall Score : 90 / 100