Chevron Left
Retour à Big Data Analysis with Scala and Spark

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

4.7
étoiles
2,383 évaluations
494 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: https://www.coursera.org/learn/parprog1....

Meilleurs avis

BP
28 nov. 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.

CC
7 juin 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!

Filtrer par :

76 - 100 sur 477 Avis pour Big Data Analysis with Scala and Spark

par Mohamed A T

6 août 2019

the theory is very clear and well explained.

the practical assignments are a little bit ambiguous but they are overall very good and challenging.

highly recommended!

par Andronik

15 juin 2017

Nice introduction into Spark with details about how Spark works internally. This course also talks about when to use RDD/Dataframe/Dataset and performance pitfalls.

par El G T

27 oct. 2019

really good material, well explained with many examples.

maybe more information or precisions should be added to the assignments but good material and explanations

par Seongsan K

9 mars 2018

It was really useful material. It would be really nice if there are more assignments to polish the materials we learn, but I am really satisfied with the course.

par Walter D

1 janv. 2018

Great course to get going with Apache Spark. Would recommend to someone who has java or scala experience already and wants to learn about distributed processing.

par Walter E Z

2 avr. 2017

Great introduction to Spark and it's data structures. The course is easy to follow, and lecturer is entertaining and really engaged.

Thanks, I really had fun !

par Zeb S

16 oct. 2019

I worked with PySpark professionally, and this helped add some depth to my knowledge of Spark as well as give me a chance to translate those skills to Scala.

par Antonio A

20 oct. 2017

Clear explanations, with emphasis done on the important/practical stuff. From zero to a general understanding on Spark and the available tools in 4 weeks.

par Shweta P

18 juil. 2020

I really liked the course. Learnt lot many things regarding Scala and Spark. The Assignments were really helpful to get hands-on knowlegde of Spark.

par Jeffrey S

9 avr. 2017

Lectures were clear and engaging and directly related to the homework. The assignments were very practical and very hard. Best course of the series!

par Grzegorz G

21 mars 2017

Some of the assignments are a bit challenging, due to grading system I suppose, but in the end general impression about this course is very positive

par Bulent B

7 août 2019

Amazing technology, explained wonderfully. Note: familiarity with scala (take Martin's course in coursera) would make your experience even better.

par Konstantin K

12 avr. 2017

good stuff, compared to the other similar course in PySpark this one gave me a lot more understanding of how things work in Spark on the low level

par Liqun Y

29 juin 2017

Very useful. Dr. Miller apparently did a very good job. I strongly suggest beginners to read the "Learning Spark" book and then take this class.

par Shane

10 mai 2018

Very well-organized courses about Spark ! Really learned some good practical tips. Hope there could be more explanations about the assignments.

par John V M

24 avr. 2017

Yet another excellent Scala class. Good lectures, good assignments. Clear and understandable, while presenting a whole bunch of new concepts.

par Bennie K

15 oct. 2017

Really clear and direct. Would love to see another course on the Advanced Spark topics such as Spark Streaming and Spark custom libraries

par Arman S

20 sept. 2020

The professor and her team has done a tremendous job in this course. A very hearty thank you to all of you. Please keep up the good work!

par Álvaro L L

11 juin 2017

A great introduction to Spark !!! An esential course to anyone interested in the field! Thank you very much Heather and the EPFL team !!

par Yacine G

23 déc. 2018

FANTASTIC!!! I don't even know which was better: the course material quality, the instructor's approach or the assignments. FANTASTIC!!!

par Buddhika L S

17 févr. 2018

This is a good course if you already know the Scala language and looking to improve your theoretical understanding of Spark programming.

par Neha B

19 mai 2017

It gave me very good understanding on Spark Architecture, functioning along with hands on over Scala. Good examples used during lessons.

par Oleg m

10 avr. 2017

First weeks were overcomplicated with k-means and stuff not related to Spark itself.

In general - GREAT JOB !!! Thx for such kind courses

par CLAUDIO A

9 juin 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 !

par Alvin H

4 avr. 2017

Awesome Course . Detail and Depth of RDD vs Dataframe vs Dataset.

Latency vs Network/IO vs Shuffling.

Learnt a lot .

Thank you Heather.