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Learner Reviews & Feedback for Big Data Analysis with Scala and Spark by École Polytechnique Fédérale de Lausanne

4.6
stars
2,598 ratings

About the Course

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 analysis in a functional 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....

Top reviews

MP

Apr 9, 2017

Excellent material. Very good flow. Heather has an amazing way of walking through the flow and simplifying the concepts. Great assignments -- takes a bit longer than 3 hours.

MS

Jun 30, 2017

Great course with nice explanations of some Spark concepts. The third week was particularly useful for my understanding of Spark shuffling and partitioning. Thanks a lot!

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276 - 300 of 512 Reviews for Big Data Analysis with Scala and Spark

By Msellek A

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Jan 26, 2019

Great course ! Thanks for the effort

By Jose M N

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May 28, 2018

Great course. Thanks for everything.

By cnu m

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Sep 14, 2017

Very nice explanation with examples.

By Martin A

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May 4, 2017

Great course, good intro into Spark.

By Manuel M C

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Mar 24, 2017

Great course, keep up the good work.

By Neeraj V D

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Feb 27, 2018

limited content with dewp knowledge

By Abhay D

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Nov 4, 2018

Wonderful course. Helped me a lot.

By David M

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Sep 19, 2017

Concepts are very well explained..

By Liu D

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Jul 26, 2017

Great speeches with great exercise

By Fernando R

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Oct 29, 2017

it was a super interesting course

By Alejandro R C

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Aug 14, 2017

Everything was easy to understand

By Jinfu X

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Mar 13, 2017

Thanks! It's an excellent course.

By HẰNG N T M

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Jan 27, 2026

I feel satisfied for this course

By Fedor C

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Aug 31, 2017

Very interesting course! Thanks!

By Vasyl Y

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Jun 27, 2017

Cool course! Thanks for your job

By Kyle L

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Jun 11, 2017

very good course, really enjoyed

By Jong H S

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Aug 18, 2017

A wonderful and timely course.

By Zhu X

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Jul 6, 2017

Great course, I learned a lot.

By Salvo

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Apr 24, 2017

This course is very well done.

By Jay

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Sep 21, 2017

cool teacher and cool course!

By Atsuya K

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Oct 30, 2017

A good quick intro to Spark.

By Jakub T m G

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Jun 27, 2017

good introduction into Spark

By Benzakoun S

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May 8, 2017

excellent quality of content

By Akash D

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Jul 26, 2021

Wonderfully designed course