Database Operations Via Hadoop and MapReduce

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

What's Inside

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.

Folks working with data are used to running SQL queries which help analyze data with great ease. Once your data is in HDFS though, every operation needs to be expressed as a MapReduce job. This course will map constructs in SQL to corresponding design patterns for MapReduce jobs. For every one of your traditional SQL constructs such as Select, where, group by, having and join, we’ll work through the corresponding MapReduce jobs in Hadoop.


  • Mail us about anything - anything! - and we will always reply :-)

What are the requirements?

  • You'll need an IDE where you can write Java code or open the source code that's shared. IntelliJ and Eclipse are both great options.
  • You'll need some background in Object-Oriented Programming, preferably in Java. All the source code is in Java and we dive right in without going into Objects, Classes etc
  • A bit of exposure to Linux/Unix shells would be helpful, but it won't be a blocker

What am I going to get from this course?

  • Master the art of "thinking parallel" - how to break up a task into Map/Reduce transformations
  • Use Hadoop + MapReduce to implement a SQL query like operations

What is the target audience?

  • Yep! Analysts who want to leverage the power of HDFS where traditional databases don't cut it anymore
  • Yep! Engineers who want to develop complex distributed computing applications to process lot's of data
  • Yep! Data Scientists who want to add MapReduce to their bag of tricks for processing data

Get started now!



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312+ Students
8 Lectures
1+ Hours of Video
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Loonycorn

Loonycorn is comprised of a couple of individuals —Janani Ravi and Vitthal Srinivasan—who have honed their tech expertises at Google and Stanford. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

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