Best MapReduce Courses 2026
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Best MapReduce Tutorials 2026
Taming Big Data with MapReduce and Hadoop – Hands On!
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Analyzing “big data” is a sought-after and very valuable skill – and this course will quickly teach you two fundamental technologies of big data: MapReduce and Hadoop. Have you ever wondered how Google manages to constantly crawl the entire Internet? You will learn these same techniques, using your own Windows system at home.
Learn and master the art of framing data analysis problems as MapReduce problems through more than 10 practical examples, then scale them to run on cloud computing services in this course. You will learn from a former engineer and senior manager at Amazon and IMDb.
Learn the concepts of MapReduce
Quickly run MapReduce jobs using Python and MRJob
Translate complex analysis problems into multi-step MapReduce tasks
Upgrade to Larger Data Sets Using Amazon’s Elastic MapReduce Service
Understand how Hadoop distributes MapReduce on compute clusters
Discover other Hadoop technologies, such as Hive, Pig and Spark
By the end of this course, you’ll be running code that analyzes gigabytes of information – in the cloud – in minutes.
We’re going to have fun along the way. You’ll warm up with some easy examples of using MapReduce to analyze movie rating data and book text. Once you have the basics under your belt, we’ll move on to more complex and interesting tasks. We’ll use a million movie ratings to find movies that look alike, and you might even discover new movies that you might like in the process! We’ll analyze a social graph of superheroes, and find out who is the most “popular” superhero – and develop a system to find “degrees of separation” between superheroes. Are all Marvel superheroes within a few degrees of being connected to The Incredible Hulk? You will find the answer.
This course is very practical; you will spend most of your time following up with the instructor as we write, analyze, and run real code together – both on your own system and in the cloud using Amazon’s Elastic MapReduce service. Over 5 hours of video content is included, with over 10 real life examples of increasing complexity that you can create, run and study on your own. Explore them at your own pace, on your own schedule. The course ends with an overview of other Hadoop-based technologies including Hive, Pig, and the very hot course will get you started with Hadoop early on. You will learn how to set up your own cluster using both VMs and the cloud. All major MapReduce features are covered, including advanced topics like total sort and secondary sort.
The Art of Parallel Thinking: MapReduce has completely changed the way people think about processing big data. Decomposing any problem into parallelizable units is an art. The examples in this course will teach you to “think in parallel”.
What is covered:
Recommend friends on a social networking site: Generate the 10 best friend recommendations using a collaborative filtering algorithm.
Create a reverse index for search engines: Use MapReduce to parallelize the colossal task of creating a reverse index for a search engine.
Generate bigrams from text: generate bigrams and calculate their frequency distribution in a text corpus.
Create your Hadoop cluster:
Install Hadoop in stand-alone, pseudo-distributed and fully distributed modes
Configure a hadoop cluster using Linux virtual machines.
Configure a Hadoop cloud cluster on AWS with