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

2,445 ratings
505 reviews

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:

Top reviews

Jun 7, 2017

The sessions where clearly explained and focused. Some of the exercises contained slightly confusing hints and information, but I'm sure those mistakes will be ironed out in future iterations. Thanks!

Nov 28, 2019

Excellent overview of Spark, including exercises that solidify what you learn during the lectures. The development environment setup tutorials were also very helpful, as I had not yet worked with sbt.

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326 - 350 of 488 Reviews for Big Data Analysis with Scala and Spark

By Light0617

Apr 14, 2019


By Saiteja t

Aug 1, 2018

Nice session

By Hengyu

Apr 6, 2018

very helpful

By Rafael M

Oct 18, 2017

Great Course

By Mihir S

Sep 27, 2017

Good Course.

By Angel V

Aug 21, 2017

very usefull

By Aleksey I

Jun 2, 2017

Good course.

By Roman I

Apr 5, 2020

good cource

By Kirill K

Oct 10, 2017

A good one.

By William H

Sep 6, 2017


By jose a m l

Jun 13, 2020


By Sanjeev R

Aug 26, 2019


By Ngoc-Bien N

Apr 4, 2019

bon cours


Jan 17, 2018


By Mohamed K

Oct 30, 2017

Perfect !

By Pengcheng L

Jun 5, 2017

Thanks :)

By Huajian M

Apr 4, 2017

So great!

By 李帅

May 1, 2019



Aug 7, 2017

Thanks !

By Estera K

Mar 20, 2017


By Satendra k

Apr 9, 2017


By Вьюн С А

Feb 27, 2020


By Kiệt Đ

Jul 1, 2017


By Bianca T

Apr 22, 2017

Taking into consideration that this was the first edition of the course, I can say that it has been a nice journey. I am glad about the fact that Heather managed to expose a bit of the Spark internals and not only talk about querying data and how easily this can be made by using Spark (as most of the Spark oriented courses consist of).

In addition to this, I could listen to Heather all day long - she's a great presenter and has wonderful teaching skills.

However, the homework has outlined some neglected aspects of the course:

- vague description or requirements

- not strongly related to the presented content (the lectures outlined partitioning mechanism, but the homework 2 did not require it...)

- not so meaningful feedback, except for some tests failing/passing - I would have expected something like you did ok, but your job took longer than expected; check out this and that

Overall, it's been a highly expected course and it was nice to get a broader outlook on Spark. I hope that there will be more courses (and more detailed) related to Spark ecosystem in the near future.

By Anton M

Jun 19, 2020

Really enjoyed most part of the course, it was a fun ride with Spark !

Explanations of lector was crystal clear and I liked all assignments (except last one)

There are some cons though:

-> Week 3 contains no assignment, I would prefer to have one really dedicated to "Partition and Shuffling" subject

-> Spark SQL explanations about untyped were too much shady. It somehow feels like this API goes totally orthogonal to everything functional we have had so far. It's like running in Java but using C with JNI... Well, after all, it's a drawback of API, not course itself, but still having bit of aftertaste of fighting with Scala type system trying to glue SQL... meh

-> there are many missed opportunities to have proper Coursera quiz during lectures