Course Description

Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala. In this course, we'll see how the data parallel paradigm can be extended to the distributed case, using Spark throughout. We'll cover Spark's programming model in detail, being careful to understand how and when it differs from familiar programming models, like shared-memory parallel collections or sequential Scala collections. Through hands-on examples in Spark and Scala, we'll learn when important issues related to distribution like latency and network communication should be considered and how they can be addressed effectively for improved performance.Learning Outcomes. By the end of this course you will be able to:- read data from persistent storage and load it into Apache Spark,- manipulate data with Spark and Scala,- express algorithms for data alysis in a functiol style, - recognize how to avoid shuffles and recomputation in Spark,Recommended background: You should have at least one year programming experience. Proficiency with Java or C# is ideal, but experience with other languages such as C/C++, Python, Javascript or Ruby is also sufficient. You should have some familiarity using the command line. This course is intended to be taken after Parallel Programming: https://www.coursera.org/learn/parprog1.

Instructor Details

Prof. Heather Miller

Heather Miller is an assistant professor in Carnegie Mellon University's School of Computer Science. Previously, she was a research scientist at EPFL, and the co-founder and executive director of the Scala Center.



398 total reviews

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By Kuntal G on 1-Apr-17

Very Nice and effective course. One of the best course i have done on Spark online. Many Thanks to the course instructor Heather Miller for creating a very detail and updated course on Spark.

By Luiz C on 27-Jan-19

If you know the subject, may be easy. If you don't know the subject, too dense and abstract with not enough practical examples/exercises before the assignments (specially for week4). Would have been better to break the videos into smaller ones, include more practical concrete examples/exercises during the videos (as very well done by Pr. Obersky during the 1st Course of the Specialization). There could have been room to break week4 into material for 2 weeks. Still, inresting.

By Rodion G on 15-Apr-19

Course is good to have some practice in spark and scala. However it seems to be long forsaken by staff and some issues with assignments require doing archaeology in the forums. Also it is quite unpleasant to see that while specialization emphasizes functional programming, some auxiliary code in assignments is written in the worst manner of imperative programming... Why use scala then?

By Konrad C on 27-Jan-19

A lot things to learn and experiment.Challenging assignments.

By David F S on 15-Jan-19

Very informative. Well-organized presentation.

By Murat A on 20-Jan-19

It was very challenging, but also informative. Thanks a lot.

By Navjinder S V on 18-Dec-18

Great Course content with amazing and challenging assignments!

By Sreeraj R P on 7-Jan-19

Very good course for a great start in Spark. Require some initial knowledge and coding experience in Scala.

By Andrey M on 10-Jan-19

Thank you for the great introduction in to the Spark, What it is and What are the most commonly used APIs.

By sheng w on 10-Jan-19

Very useful course and great materials and assignments.

By Robert C M P on 12-Feb-19

Excellent videos, explanation, and resources!

Perfectly. Very competent teacher and good tasks. Requires knowledge of scala.