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Avis et commentaires pour l'étudiant pour Big Data Analysis with Scala and Spark par École polytechnique fédérale de Lausanne

1,891 notes
388 Avis

À propos du cours

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:

Meilleurs avis


Jun 08, 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!


Apr 10, 2017

Great introduction to spark. Fun assignments. Since it was the first ever session, there were quite a few kinks with the assignments. But the discussion forums rescued me any time I was stuck.

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1 - 25 sur 375 Examens pour Big Data Analysis with Scala and Spark

By Luis

Jan 27, 2019

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.


Jun 10, 2019

Excellent explanations by Heather Miller. She really knows how to explain a topic, and also makes the lectures a lot of fun to listen !

By Valter F

May 29, 2019

I love the indepth aproach at the RDDs. I'd say DataFrames and DataSets required a bit more examples and testing material though.

By Kyle J

May 22, 2019

Pretty good, but one of the assignments was poorly set up. Some of the provided code was broken and it was very hard to debug.


May 17, 2019

Very engaging and tutor showed excellent delivery. thanks to Coursera.

By Joël V

May 17, 2019

The course presented the concepts in a clear and exemplified way. Tough, it was a bit too verbose.

The exercises were not too hard and thorough enough to cover the concepts presented in class.

I wished there were more exercises as Spark's API is huge and sometimes a bit tedious to use thus being hard to quickly get confident. I hope that the capstone project will help for that.

By Ronald C M

May 14, 2019

The best way to get to know Spark Fundamentals and Spark Core libraries

By Fábio A R

May 13, 2019

Excellent course, very handful for whoever is starting his studies in spark.

By 李帅鹏

May 02, 2019



Apr 16, 2019

Everything was excellent. This was one of the best courses I have attended so far

By Rodion G

Apr 15, 2019

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 Light0617

Apr 14, 2019


By Ngoc-Bien N

Apr 04, 2019

bon cours

By Kevin L

Apr 02, 2019

I loved this course - it was a great introduction to Spark. At the end, I wasn't (and am still not) clear on type-safe operations on Datasets, and now to write Tests to verify this.

These will be one of the targets of my upcoming research and study.

By Subodh C

Mar 30, 2019

Thanks Prof. Miller !

By Šejla Č

Mar 20, 2019

Brilliant lecturer and slides! The only problem is assignments not being clear on the expected outputs. Sometimes it takes more time to figure out what exactly is asked than to find the solution. A few more test cases or detailed examples would help.

By Varlamova E

Mar 10, 2019

It was amazing!!! Very useful course!

By Симкин И М

Mar 10, 2019

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

By Edgar D

Mar 10, 2019

Favorite so far out of the Scala Specialization Course. It was executed really well, and taught really well, too. Kinda wish they would add more exercises to help us get more experience with some of the concepts, but that's something you can always just do by yourself either way.

By Nag K

Feb 28, 2019

Course Assignments consumed more time than anticipated, as they required the knowledge from upcoming week's video lectures. Had it not been for someone mentioning about this in discussion forums, it would've consumed more time for me to complete the assignments

By Robert C M P

Feb 12, 2019

Excellent videos, explanation, and resources!

By Michaël M P

Feb 05, 2019

Talk about how to set Scala version in Eclipse

By Michael R

Feb 04, 2019

Great course, but week 4 leaves out some key Spark SQL concepts that you need to finish the last project, such as the use of when(). Also, the part about DataSets is gone through rather quickly and without nearly as much detail as RDD and DataFrames.

By Konrad C

Jan 27, 2019

A lot things to learn and experiment.

Challenging assignments.

By Msellek A

Jan 26, 2019

Great course ! Thanks for the effort